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piker
-----
trading gear for hackers
trading gear for hackers.
|gh_actions|
.. |gh_actions| image:: https://img.shields.io/endpoint.svg?url=https%3A%2F%2Factions-badge.atrox.dev%2Fpikers%2Fpiker%2Fbadge&style=popout-square
:target: https://actions-badge.atrox.dev/piker/pikers/goto
``piker`` is a broker agnostic, next-gen FOSS toolset and runtime for
real-time computational trading targeted at `hardcore Linux users
<comp_trader>`_ .
``piker`` is a broker agnostic, next-gen FOSS toolset for real-time
computational trading targeted at `hardcore Linux users <comp_trader>`_ .
we use much bleeding edge tech including (but not limited to):
we use as much bleeding edge tech as possible including (but not limited to):
- latest python for glue_
- uv_ for packaging and distribution
- trio_ & tractor_ for our distributed `structured concurrency`_ runtime
- Qt_ for pristine low latency UIs
- pyqtgraph_ (which we've extended) for real-time charting and graphics
- ``polars`` ``numpy`` and ``numba`` for redic `fast numerics`_
- `apache arrow and parquet`_ for time-series storage
- trio_ & tractor_ for our distributed, multi-core, real-time streaming
`structured concurrency`_ runtime B)
- Qt_ for pristine high performance UIs
- pyqtgraph_ for real-time charting
- ``polars`` ``numpy`` and ``numba`` for `fast numerics`_
- `apache arrow and parquet`_ for time series history management
persistence and sharing
- (prototyped) techtonicdb_ for L2 book storage
potential projects we might integrate with soon,
- (already prototyped in ) techtonicdb_ for L2 book storage
.. _comp_trader: https://jfaleiro.wordpress.com/2019/10/09/computational-trader/
.. _glue: https://numpy.org/doc/stable/user/c-info.python-as-glue.html#using-python-as-glue
.. _uv: https://docs.astral.sh/uv/
.. |travis| image:: https://img.shields.io/travis/pikers/piker/master.svg
:target: https://travis-ci.org/pikers/piker
.. _trio: https://github.com/python-trio/trio
.. _tractor: https://github.com/goodboy/tractor
.. _structured concurrency: https://trio.discourse.group/
.. _marketstore: https://github.com/alpacahq/marketstore
.. _techtonicdb: https://github.com/0b01/tectonicdb
.. _Qt: https://www.qt.io/
.. _pyqtgraph: https://github.com/pyqtgraph/pyqtgraph
.. _glue: https://numpy.org/doc/stable/user/c-info.python-as-glue.html#using-python-as-glue
.. _apache arrow and parquet: https://arrow.apache.org/faq/
.. _fast numerics: https://zerowithdot.com/python-numpy-and-pandas-performance/
.. _techtonicdb: https://github.com/0b01/tectonicdb
.. _comp_trader: https://jfaleiro.wordpress.com/2019/10/09/computational-trader/
focus and feats:
****************
fitting with these tenets, we're always open to new
framework/lib/service interop suggestions and ideas!
focus and features:
*******************
- 100% federated: your code, your hardware, your data feeds, your broker fills.
- zero web: low latency, native software that doesn't try to re-invent the OS
- maximal **privacy**: prevent brokers and mms from knowing your
planz; smack their spreads with dark volume.
- zero clutter: modal, context oriented UIs that echew minimalism, reduce
thought noise and encourage un-emotion.
- first class parallelism: built from the ground up on next-gen structured concurrency
primitives.
- traders first: broker/exchange/asset-class agnostic
- systems grounded: real-time financial signal processing that will
make any queuing or DSP eng juice their shorts.
- non-tina UX: sleek, powerful keyboard driven interaction with expected use in tiling wms
- data collaboration: every process and protocol is multi-host scalable.
- fight club ready: zero interest in adoption by suits; no corporate friendly license, ever.
- **100% federated**:
your code, your hardware, your data feeds, your broker fills.
fitting with these tenets, we're always open to new framework suggestions and ideas.
- **zero web**:
low latency as a prime objective, native UIs and modern IPC
protocols without trying to re-invent the "OS-as-an-app"..
- **maximal privacy**:
prevent brokers and mms from knowing your planz; smack their
spreads with dark volume from a VPN tunnel.
- **zero clutter**:
modal, context oriented UIs that echew minimalism, reduce thought
noise and encourage un-emotion.
- **first class parallelism**:
built from the ground up on a next-gen structured concurrency
supervision sys.
- **traders first**:
broker/exchange/venue/asset-class/money-sys agnostic
- **systems grounded**:
real-time financial signal processing (fsp) that will make any
queuing or DSP eng juice their shorts.
- **non-tina UX**:
sleek, powerful keyboard driven interaction with expected use in
tiling wms (or maybe even a DDE).
- **data collab at scale**:
every actor-process and protocol is multi-host aware.
- **fight club ready**:
zero interest in adoption by suits; no corporate friendly license,
ever.
building the hottest looking, fastest, most reliable, keyboard
friendly FOSS trading platform is the dream; join the cause.
building the best looking, most reliable, keyboard friendly trading
platform is the dream; join the cause.
a sane install with `uv`
************************
bc why install with `python` when you can faster with `rust` ::
sane install with `poetry`
**************************
TODO!
uv lock
rigorous install on ``nixos`` using ``poetry2nix``
**************************************************
TODO!
hacky install on nixos
**********************
``NixOS`` is our core devs' distro of choice for which we offer
`NixOS` is our core devs' distro of choice for which we offer
a stringently defined development shell envoirment that can be loaded with::
nix-shell default.nix
nix-shell develop.nix
this will setup the required python environment to run piker, make sure to
run::
pip install -r requirements.txt -e .
once after loading the shell
start a chart
*************
run a realtime OHLCV chart stand-alone::
install wild-west style via `pip`
*********************************
``piker`` is currently under heavy pre-alpha development and as such
should be cloned from this repo and hacked on directly.
piker -l info chart btcusdt.spot.binance xmrusdt.spot.kraken
for a development install::
this runs a chart UI (with 1m sampled OHLCV) and shows 2 spot markets from 2 diff cexes
overlayed on the same graph. Use of `piker` without first starting
a daemon (`pikerd` - see below) means there is an implicit spawning of the
multi-actor-runtime (implemented as a `tractor` app).
For additional subsystem feats available through our chart UI see the
various sub-readmes:
- order control using a mouse-n-keyboard UX B)
- cross venue market-pair (what most call "symbol") search, select, overlay Bo
- financial-signal-processing (`piker.fsp`) write-n-reload to sub-chart BO
- src-asset derivatives scan for anal, like the infamous "max pain" XO
git clone git@github.com:pikers/piker.git
cd piker
virtualenv env
source ./env/bin/activate
pip install -r requirements.txt -e .
spawn a daemon standalone
*************************
we call the root actor-process the ``pikerd``. it can be (and is
recommended normally to be) started separately from the ``piker
chart`` program::
check out our charts
********************
bet you weren't expecting this from the foss::
piker -l info -b kraken -b binance chart btcusdt.binance --pdb
this runs the main chart (currently with 1m sampled OHLC) in in debug
mode and you can practice paper trading using the following
micro-manual:
``order_mode`` (
edge triggered activation by any of the following keys,
``mouse-click`` on y-level to submit at that price
):
- ``f``/ ``ctl-f`` to stage buy
- ``d``/ ``ctl-d`` to stage sell
- ``a`` to stage alert
``search_mode`` (
``ctl-l`` or ``ctl-space`` to open,
``ctl-c`` or ``ctl-space`` to close
) :
- begin typing to have symbol search automatically lookup
symbols from all loaded backend (broker) providers
- arrow keys and mouse click to navigate selection
- vi-like ``ctl-[hjkl]`` for navigation
you can also configure your position allocation limits from the
sidepane.
run in distributed mode
***********************
start the service manager and data feed daemon in the background and
connect to it::
pikerd -l info --pdb
the daemon does nothing until a ``piker``-client (like ``piker
chart``) connects and requests some particular sub-system. for
a connecting chart ``pikerd`` will spawn and manage at least,
- a data-feed daemon: ``datad`` which does all the work of comms with
the backend provider (in this case the ``binance`` cex).
- a paper-trading engine instance, ``paperboi.binance``, (if no live
account has been configured) which allows for auto/manual order
control against the live quote stream.
connect your chart::
*using* an actor-service (aka micro-daemon) manager which dynamically
supervises various sub-subsystems-as-services throughout the ``piker``
runtime-stack.
piker -l info -b kraken -b binance chart xmrusdt.binance --pdb
now you can (implicitly) connect your chart::
piker chart btcusdt.spot.binance
since ``pikerd`` was started separately you can now enjoy a persistent
real-time data stream tied to the daemon-tree's lifetime. i.e. the next
time you spawn a chart it will obviously not only load much faster
(since the underlying ``datad.binance`` is left running with its
in-memory IPC data structures) but also the data-feed and any order
mgmt states should be persistent until you finally cancel ``pikerd``.
enjoy persistent real-time data feeds tied to daemon lifetime. the next
time you spawn a chart it will load much faster since the data feed has
been cached and is now always running live in the background until you
kill ``pikerd``.
if anyone asks you what this project is about
*********************************************
you don't talk about it; just use it.
you don't talk about it.
how do i get involved?
@ -165,15 +166,6 @@ enter the matrix.
how come there ain't that many docs
***********************************
i mean we want/need them but building the core right has been higher
prio then marketting (and likely will stay that way Bp).
soo, suck it up bc,
- no one is trying to sell you on anything
- learning the code base is prolly way more valuable
- the UI/UXs are intended to be "intuitive" for any hacker..
we obviously need tonz help so if you want to start somewhere and
can't necessarily write "advanced" concurrent python/rust code, this
helping document literally anything might be the place for you!
suck it up, learn the code; no one is trying to sell you on anything.
also, we need lotsa help so if you want to start somewhere and can't
necessarily write serious code, this might be the place for you!

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@ -2,15 +2,13 @@
# ---- CEXY ----
################
[binance]
accounts.paper = 'paper'
accounts.usdtm = 'futes'
futes.use_testnet = false
futes.use_testnet = true
futes.api_key = ''
futes.api_secret = ''
accounts.spot = 'spot'
spot.use_testnet = false
spot.use_testnet = true
spot.api_key = ''
spot.api_secret = ''

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@ -1,134 +0,0 @@
with (import <nixpkgs> {});
let
glibStorePath = lib.getLib glib;
zlibStorePath = lib.getLib zlib;
zstdStorePath = lib.getLib zstd;
dbusStorePath = lib.getLib dbus;
libGLStorePath = lib.getLib libGL;
freetypeStorePath = lib.getLib freetype;
qt6baseStorePath = lib.getLib qt6.qtbase;
fontconfigStorePath = lib.getLib fontconfig;
libxkbcommonStorePath = lib.getLib libxkbcommon;
xcbutilcursorStorePath = lib.getLib xcb-util-cursor;
qtpyStorePath = lib.getLib python312Packages.qtpy;
pyqt6StorePath = lib.getLib python312Packages.pyqt6;
pyqt6SipStorePath = lib.getLib python312Packages.pyqt6-sip;
rapidfuzzStorePath = lib.getLib python312Packages.rapidfuzz;
qdarkstyleStorePath = lib.getLib python312Packages.qdarkstyle;
xorgLibX11StorePath = lib.getLib xorg.libX11;
xorgLibxcbStorePath = lib.getLib xorg.libxcb;
xorgxcbutilwmStorePath = lib.getLib xorg.xcbutilwm;
xorgxcbutilimageStorePath = lib.getLib xorg.xcbutilimage;
xorgxcbutilerrorsStorePath = lib.getLib xorg.xcbutilerrors;
xorgxcbutilkeysymsStorePath = lib.getLib xorg.xcbutilkeysyms;
xorgxcbutilrenderutilStorePath = lib.getLib xorg.xcbutilrenderutil;
in
stdenv.mkDerivation {
name = "piker-qt6-uv";
buildInputs = [
# System requirements.
glib
zlib
dbus
zstd
libGL
freetype
qt6.qtbase
libgcc.lib
fontconfig
libxkbcommon
# Xorg requirements
xcb-util-cursor
xorg.libxcb
xorg.libX11
xorg.xcbutilwm
xorg.xcbutilimage
xorg.xcbutilerrors
xorg.xcbutilkeysyms
xorg.xcbutilrenderutil
# Python requirements.
python312Full
python312Packages.uv
python312Packages.qdarkstyle
python312Packages.rapidfuzz
python312Packages.pyqt6
python312Packages.qtpy
];
src = null;
shellHook = ''
set -e
# Set the Qt plugin path
# export QT_DEBUG_PLUGINS=1
QTBASE_PATH="${qt6baseStorePath}/lib"
QT_PLUGIN_PATH="$QTBASE_PATH/qt-6/plugins"
QT_QPA_PLATFORM_PLUGIN_PATH="$QT_PLUGIN_PATH/platforms"
LIB_GCC_PATH="${libgcc.lib}/lib"
GLIB_PATH="${glibStorePath}/lib"
ZSTD_PATH="${zstdStorePath}/lib"
ZLIB_PATH="${zlibStorePath}/lib"
DBUS_PATH="${dbusStorePath}/lib"
LIBGL_PATH="${libGLStorePath}/lib"
FREETYPE_PATH="${freetypeStorePath}/lib"
FONTCONFIG_PATH="${fontconfigStorePath}/lib"
LIB_XKB_COMMON_PATH="${libxkbcommonStorePath}/lib"
XCB_UTIL_CURSOR_PATH="${xcbutilcursorStorePath}/lib"
XORG_LIB_X11_PATH="${xorgLibX11StorePath}/lib"
XORG_LIB_XCB_PATH="${xorgLibxcbStorePath}/lib"
XORG_XCB_UTIL_IMAGE_PATH="${xorgxcbutilimageStorePath}/lib"
XORG_XCB_UTIL_WM_PATH="${xorgxcbutilwmStorePath}/lib"
XORG_XCB_UTIL_RENDER_UTIL_PATH="${xorgxcbutilrenderutilStorePath}/lib"
XORG_XCB_UTIL_KEYSYMS_PATH="${xorgxcbutilkeysymsStorePath}/lib"
XORG_XCB_UTIL_ERRORS_PATH="${xorgxcbutilerrorsStorePath}/lib"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$QTBASE_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$QT_PLUGIN_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$QT_QPA_PLATFORM_PLUGIN_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIB_GCC_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$DBUS_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$GLIB_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$ZLIB_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$ZSTD_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIBGL_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$FONTCONFIG_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$FREETYPE_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$LIB_XKB_COMMON_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XCB_UTIL_CURSOR_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_LIB_X11_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_LIB_XCB_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_XCB_UTIL_IMAGE_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_XCB_UTIL_WM_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_XCB_UTIL_RENDER_UTIL_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_XCB_UTIL_KEYSYMS_PATH"
LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$XORG_XCB_UTIL_ERRORS_PATH"
export LD_LIBRARY_PATH
RPDFUZZ_PATH="${rapidfuzzStorePath}/lib/python3.12/site-packages"
QDRKSTYLE_PATH="${qdarkstyleStorePath}/lib/python3.12/site-packages"
QTPY_PATH="${qtpyStorePath}/lib/python3.12/site-packages"
PYQT6_PATH="${pyqt6StorePath}/lib/python3.12/site-packages"
PYQT6_SIP_PATH="${pyqt6SipStorePath}/lib/python3.12/site-packages"
PATCH="$PATCH:$RPDFUZZ_PATH"
PATCH="$PATCH:$QDRKSTYLE_PATH"
PATCH="$PATCH:$QTPY_PATH"
PATCH="$PATCH:$PYQT6_PATH"
PATCH="$PATCH:$PYQT6_SIP_PATH"
export PATCH
# Install deps
uv lock
'';
}

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@ -1,34 +1,28 @@
with (import <nixpkgs> {});
with python310Packages;
stdenv.mkDerivation {
name = "poetry-env";
name = "pip-env";
buildInputs = [
# System requirements.
readline
# TODO: hacky non-poetry install stuff we need to get rid of!!
poetry
# virtualenv
# setuptools
# pip
# Python requirements (enough to get a virtualenv going).
python311Full
virtualenv
setuptools
pip
# obviously, and see below for hacked linking
python311Packages.pyqt5
python311Packages.pyqt5_sip
# python311Packages.qtpy
pyqt5
# Python requirements (enough to get a virtualenv going).
python310Full
# numerics deps
python311Packages.levenshtein
python311Packages.fastparquet
python311Packages.polars
python310Packages.python-Levenshtein
python310Packages.fastparquet
python310Packages.polars
];
# environment.sessionVariables = {
# LD_LIBRARY_PATH = "${pkgs.stdenv.cc.cc.lib}/lib";
# };
src = null;
shellHook = ''
# Allow the use of wheels.
@ -36,12 +30,13 @@ stdenv.mkDerivation {
# Augment the dynamic linker path
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:${R}/lib/R/lib:${readline}/lib
export QT_QPA_PLATFORM_PLUGIN_PATH="${qt5.qtbase.bin}/lib/qt-${qt5.qtbase.version}/plugins";
if [ ! -d ".venv" ]; then
poetry install --with uis
if [ ! -d "venv" ]; then
virtualenv venv
fi
poetry shell
source venv/bin/activate
'';
}

View File

@ -19,9 +19,8 @@ services:
# other image tags available:
# https://github.com/waytrade/ib-gateway-docker#supported-tags
# image: waytrade/ib-gateway:1012.2i
image: ghcr.io/gnzsnz/ib-gateway:latest
# image: waytrade/ib-gateway:981.3j
image: waytrade/ib-gateway:1012.2i
restart: 'no' # restart on boot whenev there's a crash or user clicsk
network_mode: 'host'

View File

@ -117,57 +117,9 @@ SecondFactorDevice=
# If you use the IBKR Mobile app for second factor authentication,
# and you fail to complete the process before the time limit imposed
# by IBKR, this setting tells IBC whether to automatically restart
# the login sequence, giving you another opportunity to complete
# second factor authentication.
#
# Permitted values are 'yes' and 'no'.
#
# If this setting is not present or has no value, then the value
# of the deprecated ExitAfterSecondFactorAuthenticationTimeout is
# used instead. If this also has no value, then this setting defaults
# to 'no'.
#
# NB: you must be using IBC v3.14.0 or later to use this setting:
# earlier versions ignore it.
ReloginAfterSecondFactorAuthenticationTimeout=
# This setting is only relevant if
# ReloginAfterSecondFactorAuthenticationTimeout is set to 'yes',
# or if ExitAfterSecondFactorAuthenticationTimeout is set to 'yes'.
#
# It controls how long (in seconds) IBC waits for login to complete
# after the user acknowledges the second factor authentication
# alert at the IBKR Mobile app. If login has not completed after
# this time, IBC terminates.
# The default value is 60.
SecondFactorAuthenticationExitInterval=
# This setting specifies the timeout for second factor authentication
# imposed by IB. The value is in seconds. You should not change this
# setting unless you have reason to believe that IB has changed the
# timeout. The default value is 180.
SecondFactorAuthenticationTimeout=180
# DEPRECATED SETTING
# ------------------
#
# ExitAfterSecondFactorAuthenticationTimeout - THIS SETTING WILL BE
# REMOVED IN A FUTURE RELEASE. For IBC version 3.14.0 and later, see
# the notes for ReloginAfterSecondFactorAuthenticationTimeout above.
#
# For IBC versions earlier than 3.14.0: If you use the IBKR Mobile
# app for second factor authentication, and you fail to complete the
# process before the time limit imposed by IBKR, you can use this
# setting to tell IBC to exit: arrangements can then be made to
# automatically restart IBC in order to initiate the login sequence
# afresh. Otherwise, manual intervention at TWS's
# by IBKR, you can use this setting to tell IBC to exit: arrangements
# can then be made to automatically restart IBC in order to initiate
# the login sequence afresh. Otherwise, manual intervention at TWS's
# Second Factor Authentication dialog is needed to complete the
# login.
#
@ -180,18 +132,29 @@ SecondFactorAuthenticationTimeout=180
ExitAfterSecondFactorAuthenticationTimeout=no
# This setting is only relevant if
# ExitAfterSecondFactorAuthenticationTimeout is set to 'yes'.
#
# It controls how long (in seconds) IBC waits for login to complete
# after the user acknowledges the second factor authentication
# alert at the IBKR Mobile app. If login has not completed after
# this time, IBC terminates.
# The default value is 40.
SecondFactorAuthenticationExitInterval=
# Trading Mode
# ------------
#
# This indicates whether the live account or the paper trading
# account corresponding to the supplied credentials is to be used.
# The allowed values are 'live' (the default) and 'paper'.
#
# If this is set to 'live', then the credentials for the live
# account must be supplied. If it is set to 'paper', then either
# the live or the paper-trading credentials may be supplied.
# TWS 955 introduced a new Trading Mode combo box on its login
# dialog. This indicates whether the live account or the paper
# trading account corresponding to the supplied credentials is
# to be used. The allowed values are 'live' (the default) and
# 'paper'. For earlier versions of TWS this setting has no
# effect.
TradingMode=paper
TradingMode=
# Paper-trading Account Warning
@ -225,7 +188,7 @@ AcceptNonBrokerageAccountWarning=yes
#
# The default value is 60.
LoginDialogDisplayTimeout=60
LoginDialogDisplayTimeout=20
@ -254,15 +217,7 @@ LoginDialogDisplayTimeout=60
# but they are acceptable.
#
# The default is the current working directory when IBC is
# started, unless the TWS_SETTINGS_PATH setting in the relevant
# start script is set.
#
# If both this setting and TWS_SETTINGS_PATH are set, then this
# setting takes priority. Note that if they have different values,
# auto-restart will not work.
#
# NB: this setting is now DEPRECATED. You should use the
# TWS_SETTINGS_PATH setting in the relevant start script.
# started.
IbDir=/root/Jts
@ -331,30 +286,13 @@ ExistingSessionDetectedAction=primary
#
# If OverrideTwsApiPort is set to an integer, IBC changes the
# 'Socket port' in TWS's API configuration to that number shortly
# after startup (but note that for the FIX Gateway, this setting is
# actually stored in jts.ini rather than the Gateway's settings
# file). Leaving the setting blank will make no change to
# after startup. Leaving the setting blank will make no change to
# the current setting. This setting is only intended for use in
# certain specialized situations where the port number needs to
# be set dynamically at run-time, and for the FIX Gateway: most
# non-FIX users will never need it, so don't use it unless you know
# you need it.
OverrideTwsApiPort=4000
# Override TWS Master Client ID
# -----------------------------
#
# If OverrideTwsMasterClientID is set to an integer, IBC changes the
# 'Master Client ID' value in TWS's API configuration to that
# value shortly after startup. Leaving the setting blank will make
# no change to the current setting. This setting is only intended
# for use in certain specialized situations where the value needs to
# be set dynamically at run-time: most users will never need it,
# so don't use it unless you know you need it.
OverrideTwsMasterClientID=
; OverrideTwsApiPort=4002
# Read-only Login
@ -364,13 +302,11 @@ OverrideTwsMasterClientID=
# account security programme, the user will not be asked to perform
# the second factor authentication action, and login to TWS will
# occur automatically in read-only mode: in this mode, placing or
# managing orders is not allowed.
#
# If set to 'no', and the user is enrolled in IB's account security
# programme, the second factor authentication process is handled
# according to the Second Factor Authentication Settings described
# elsewhere in this file.
#
# managing orders is not allowed. If set to 'no', and the user is
# enrolled in IB's account security programme, the user must perform
# the relevant second factor authentication action to complete the
# login.
# If the user is not enrolled in IB's account security programme,
# this setting is ignored. The default is 'no'.
@ -390,44 +326,7 @@ ReadOnlyLogin=no
# set the relevant checkbox (this only needs to be done once) and
# not provide a value for this setting.
ReadOnlyApi=
# API Precautions
# ---------------
#
# These settings relate to the corresponding 'Precautions' checkboxes in the
# API section of the Global Configuration dialog.
#
# For all of these, the accepted values are:
# - 'yes' sets the checkbox
# - 'no' clears the checkbox
# - if not set, the existing TWS/Gateway configuration is unchanged
#
# NB: thess settings are really only supplied for the benefit of new TWS
# or Gateway instances that are being automatically installed and
# started without user intervention, or where user settings are not preserved
# between sessions (eg some Docker containers). Where a user is involved, they
# should use the Global Configuration to set the relevant checkboxes and not
# provide values for these settings.
BypassOrderPrecautions=
BypassBondWarning=
BypassNegativeYieldToWorstConfirmation=
BypassCalledBondWarning=
BypassSameActionPairTradeWarning=
BypassPriceBasedVolatilityRiskWarning=
BypassUSStocksMarketDataInSharesWarning=
BypassRedirectOrderWarning=
BypassNoOverfillProtectionPrecaution=
ReadOnlyApi=no
# Market data size for US stocks - lots or shares
@ -482,145 +381,54 @@ AcceptBidAskLastSizeDisplayUpdateNotification=accept
SendMarketDataInLotsForUSstocks=
# Trusted API Client IPs
# ----------------------
#
# NB: THIS SETTING IS ONLY RELEVANT FOR THE GATEWAY, AND ONLY WHEN FIX=yes.
# In all other cases it is ignored.
#
# This is a list of IP addresses separated by commas. API clients with IP
# addresses in this list are able to connect to the API without Gateway
# generating the 'Incoming connection' popup.
#
# Note that 127.0.0.1 is always permitted to connect, so do not include it
# in this setting.
TrustedTwsApiClientIPs=
# Reset Order ID Sequence
# -----------------------
#
# The setting resets the order id sequence for orders submitted via the API, so
# that the next invocation of the `NextValidId` API callback will return the
# value 1. The reset occurs when TWS starts.
#
# Note that order ids are reset for all API clients, except those that have
# outstanding (ie incomplete) orders: their order id sequence carries on as
# before.
#
# Valid values are 'yes', 'true', 'false' and 'no'. The default is 'no'.
ResetOrderIdsAtStart=
# This setting specifies IBC's action when TWS displays the dialog asking for
# confirmation of a request to reset the API order id sequence.
#
# Note that the Gateway never displays this dialog, so this setting is ignored
# for a Gateway session.
#
# Valid values consist of two strings separated by a solidus '/'. The first
# value specifies the action to take when the order id reset request resulted
# from setting ResetOrderIdsAtStart=yes. The second specifies the action to
# take when the order id reset request is a result of the user clicking the
# 'Reset API order ID sequence' button in the API configuration. Each value
# must be one of the following:
#
# 'confirm'
# order ids will be reset
#
# 'reject'
# order ids will not be reset
#
# 'ignore'
# IBC will ignore the dialog. The user must take action.
#
# The default setting is ignore/ignore
# Examples:
#
# 'confirm/reject' - confirm order id reset only if ResetOrderIdsAtStart=yes
# and reject any user-initiated requests
#
# 'ignore/confirm' - user must decide what to do if ResetOrderIdsAtStart=yes
# and confirm user-initiated requests
#
# 'reject/ignore' - reject order id reset if ResetOrderIdsAtStart=yes but
# allow user to handle user-initiated requests
ConfirmOrderIdReset=
# =============================================================================
# 4. TWS Auto-Logoff and Auto-Restart
# 4. TWS Auto-Closedown
# =============================================================================
#
# TWS and Gateway insist on being restarted every day. Two alternative
# automatic options are offered:
# IMPORTANT NOTE: Starting with TWS 974, this setting no longer
# works properly, because IB have changed the way TWS handles its
# autologoff mechanism.
#
# - Auto-Logoff: at a specified time, TWS shuts down tidily, without
# restarting.
# You should now configure the TWS autologoff time to something
# convenient for you, and restart IBC each day.
#
# - Auto-Restart: at a specified time, TWS shuts down and then restarts
# without the user having to re-autheticate.
#
# The normal way to configure the time at which this happens is via the Lock
# and Exit section of the Configuration dialog. Once this time has been
# configured in this way, the setting persists until the user changes it again.
#
# However, there are situations where there is no user available to do this
# configuration, or where there is no persistent storage (for example some
# Docker images). In such cases, the auto-restart or auto-logoff time can be
# set whenever IBC starts with the settings below.
#
# The value, if specified, must be a time in HH:MM AM/PM format, for example
# 08:00 AM or 10:00 PM. Note that there must be a single space between the
# two parts of this value; also that midnight is "12:00 AM" and midday is
# "12:00 PM".
#
# If no value is specified for either setting, the currently configured
# settings will apply. If a value is supplied for one setting, the other
# setting is cleared. If values are supplied for both settings, only the
# auto-restart time is set, and the auto-logoff time is cleared.
#
# Note that for a normal TWS/Gateway installation with persistent storage
# (for example on a desktop computer) the value will be persisted as if the
# user had set it via the configuration dialog.
#
# If you choose to auto-restart, you should take note of the considerations
# described at the link below. Note that where this information mentions
# 'manual authentication', restarting IBC will do the job (IBKR does not
# recognise the existence of IBC in its docuemntation).
#
# https://www.interactivebrokers.com/en/software/tws/twsguide.htm#usersguidebook/configuretws/auto_restart_info.htm
#
# If you use the "RESTART" command via the IBC command server, and IBC is
# running any version of the Gateway (or a version of TWS earlier than 1018),
# note that this will set the Auto-Restart time in Gateway/TWS's configuration
# dialog to the time at which the restart actually happens (which may be up to
# a minute after the RESTART command is issued). To prevent future auto-
# restarts at this time, you must make sure you have set AutoLogoffTime or
# AutoRestartTime to your desired value before running IBC. NB: this does not
# apply to TWS from version 1018 onwards.
# Alternatively, discontinue use of IBC and use the auto-relogin
# mechanism within TWS 974 and later versions (note that the
# auto-relogin mechanism provided by IB is not available if you
# use IBC).
AutoLogoffTime=
# Set to yes or no (lower case).
#
# yes means allow TWS to shut down automatically at its
# specified shutdown time, which is set via the TWS
# configuration menu.
#
# no means TWS never shuts down automatically.
#
# NB: IB recommends that you do not keep TWS running
# continuously. If you set this setting to 'no', you may
# experience incorrect TWS operation.
#
# NB: the default for this setting is 'no'. Since this will
# only work properly with TWS versions earlier than 974, you
# should explicitly set this to 'yes' for version 974 and later.
IbAutoClosedown=yes
AutoRestartTime=
# =============================================================================
# 5. TWS Tidy Closedown Time
# =============================================================================
#
# Specifies a time at which TWS will close down tidily, with no restart.
# NB: starting with TWS 974 this is no longer a useful option
# because both TWS and Gateway now have the same auto-logoff
# mechanism, and IBC can no longer avoid this.
#
# There is little reason to use this setting. It is similar to AutoLogoffTime,
# but can include a day-of-the-week, whereas AutoLogoffTime and AutoRestartTime
# apply every day. So for example you could use ClosedownAt in conjunction with
# AutoRestartTime to shut down TWS on Friday evenings after the markets
# close, without it running on Saturday as well.
# Note that giving this setting a value does not change TWS's
# auto-logoff in any way: any setting will be additional to the
# TWS auto-logoff.
#
# To tell IBC to tidily close TWS at a specified time every
# day, set this value to <hh:mm>, for example:
@ -679,7 +487,7 @@ AcceptIncomingConnectionAction=reject
# no means the dialog remains on display and must be
# handled by the user.
AllowBlindTrading=no
AllowBlindTrading=yes
# Save Settings on a Schedule
@ -722,26 +530,6 @@ AllowBlindTrading=no
SaveTwsSettingsAt=
# Confirm Crypto Currency Orders Automatically
# --------------------------------------------
#
# When you place an order for a cryptocurrency contract, a dialog is displayed
# asking you to confirm that you want to place the order, and notifying you
# that you are placing an order to trade cryptocurrency with Paxos, a New York
# limited trust company, and not at Interactive Brokers.
#
# transmit means that the order will be placed automatically, and the
# dialog will then be closed
#
# cancel means that the order will not be placed, and the dialog will
# then be closed
#
# manual means that IBC will take no action and the user must deal
# with the dialog
ConfirmCryptoCurrencyOrders=transmit
# =============================================================================
# 7. Settings Specific to Indian Versions of TWS
@ -778,17 +566,13 @@ DismissNSEComplianceNotice=yes
#
# The port number that IBC listens on for commands
# such as "STOP". DO NOT set this to the port number
# used for TWS API connections.
#
# The convention is to use 7462 for this port,
# but it must be set to a different value from any other
# IBC instance that might run at the same time.
#
# The default value is 0, which tells IBC not to start
# the command server
# used for TWS API connections. There is no good reason
# to change this setting unless the port is used by
# some other application (typically another instance of
# IBC). The default value is 0, which tells IBC not to
# start the command server
#CommandServerPort=7462
CommandServerPort=0
# Permitted Command Sources
@ -799,19 +583,19 @@ CommandServerPort=0
# IBC. Commands can always be sent from the
# same host as IBC is running on.
ControlFrom=
ControlFrom=127.0.0.1
# Address for Receiving Commands
# ------------------------------
#
# Specifies the IP address on which the Command Server
# is to listen. For a multi-homed host, this can be used
# is so listen. For a multi-homed host, this can be used
# to specify that connection requests are only to be
# accepted on the specified address. The default is to
# accept connection requests on all local addresses.
BindAddress=
BindAddress=127.0.0.1
# Command Prompt
@ -837,7 +621,7 @@ CommandPrompt=
# information is sent. The default is that such information
# is not sent.
SuppressInfoMessages=yes
SuppressInfoMessages=no
@ -867,10 +651,10 @@ SuppressInfoMessages=yes
# The LogStructureScope setting indicates which windows are
# eligible for structure logging:
#
# - (default value) if set to 'known', only windows that
# IBC recognizes are eligible - these are windows that
# IBC has some interest in monitoring, usually to take
# some action on the user's behalf;
# - if set to 'known', only windows that IBC recognizes
# are eligible - these are windows that IBC has some
# interest in monitoring, usually to take some action
# on the user's behalf;
#
# - if set to 'unknown', only windows that IBC does not
# recognize are eligible. Most windows displayed by
@ -883,8 +667,9 @@ SuppressInfoMessages=yes
# - if set to 'all', then every window displayed by TWS
# is eligible.
#
# The default value is 'known'.
LogStructureScope=known
LogStructureScope=all
# When to Log Window Structure
@ -897,15 +682,13 @@ LogStructureScope=known
# structure of an eligible window the first time it
# is encountered;
#
# - if set to 'openclose', the structure is logged every
# time an eligible window is opened or closed;
#
# - if set to 'activate', the structure is logged every
# time an eligible window is made active;
#
# - (default value) if set to 'never' or 'no' or 'false',
# structure information is never logged.
# - if set to 'never' or 'no' or 'false', structure
# information is never logged.
#
# The default value is 'never'.
LogStructureWhen=never
@ -925,3 +708,4 @@ LogStructureWhen=never
#LogComponents=

View File

@ -1,138 +0,0 @@
{
"nodes": {
"flake-utils": {
"inputs": {
"systems": "systems"
},
"locked": {
"lastModified": 1689068808,
"narHash": "sha256-6ixXo3wt24N/melDWjq70UuHQLxGV8jZvooRanIHXw0=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "919d646de7be200f3bf08cb76ae1f09402b6f9b4",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"type": "github"
}
},
"flake-utils_2": {
"inputs": {
"systems": "systems_2"
},
"locked": {
"lastModified": 1689068808,
"narHash": "sha256-6ixXo3wt24N/melDWjq70UuHQLxGV8jZvooRanIHXw0=",
"owner": "numtide",
"repo": "flake-utils",
"rev": "919d646de7be200f3bf08cb76ae1f09402b6f9b4",
"type": "github"
},
"original": {
"owner": "numtide",
"repo": "flake-utils",
"type": "github"
}
},
"nix-github-actions": {
"inputs": {
"nixpkgs": [
"poetry2nix",
"nixpkgs"
]
},
"locked": {
"lastModified": 1688870561,
"narHash": "sha256-4UYkifnPEw1nAzqqPOTL2MvWtm3sNGw1UTYTalkTcGY=",
"owner": "nix-community",
"repo": "nix-github-actions",
"rev": "165b1650b753316aa7f1787f3005a8d2da0f5301",
"type": "github"
},
"original": {
"owner": "nix-community",
"repo": "nix-github-actions",
"type": "github"
}
},
"nixpkgs": {
"locked": {
"lastModified": 1692174805,
"narHash": "sha256-xmNPFDi/AUMIxwgOH/IVom55Dks34u1g7sFKKebxUm0=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "caac0eb6bdcad0b32cb2522e03e4002c8975c62e",
"type": "github"
},
"original": {
"owner": "NixOS",
"ref": "nixos-unstable",
"repo": "nixpkgs",
"type": "github"
}
},
"poetry2nix": {
"inputs": {
"flake-utils": "flake-utils_2",
"nix-github-actions": "nix-github-actions",
"nixpkgs": [
"nixpkgs"
]
},
"locked": {
"lastModified": 1692048894,
"narHash": "sha256-cDw03rso2V4CDc3Mll0cHN+ztzysAvdI8pJ7ybbz714=",
"ref": "refs/heads/pyqt6",
"rev": "b059ad4c3051f45d6c912e17747aae37a9ec1544",
"revCount": 2276,
"type": "git",
"url": "file:///home/lord_fomo/repos/poetry2nix"
},
"original": {
"type": "git",
"url": "file:///home/lord_fomo/repos/poetry2nix"
}
},
"root": {
"inputs": {
"flake-utils": "flake-utils",
"nixpkgs": "nixpkgs",
"poetry2nix": "poetry2nix"
}
},
"systems": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"type": "github"
}
},
"systems_2": {
"locked": {
"lastModified": 1681028828,
"narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
"owner": "nix-systems",
"repo": "default",
"rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
"type": "github"
},
"original": {
"owner": "nix-systems",
"repo": "default",
"type": "github"
}
}
},
"root": "root",
"version": 7
}

180
flake.nix
View File

@ -1,180 +0,0 @@
# NOTE: to convert to a poetry2nix env like this here are the
# steps:
# - install poetry in your system nix config
# - convert the repo to use poetry using `poetry init`:
# https://python-poetry.org/docs/basic-usage/#initialising-a-pre-existing-project
# - then manually ensuring all deps are converted over:
# - add this file to the repo and commit it
# -
# GROKin tips:
# - CLI eps are (ostensibly) added via an `entry_points.txt`:
# - https://packaging.python.org/en/latest/specifications/entry-points/#file-format
# - https://github.com/nix-community/poetry2nix/blob/master/editable.nix#L49
{
description = "piker: trading gear for hackers (pkged with poetry2nix)";
inputs.flake-utils.url = "github:numtide/flake-utils";
inputs.nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
# see https://github.com/nix-community/poetry2nix/tree/master#api
inputs.poetry2nix = {
# url = "github:nix-community/poetry2nix";
# url = "github:K900/poetry2nix/qt5-explicit-deps";
url = "/home/lord_fomo/repos/poetry2nix";
inputs.nixpkgs.follows = "nixpkgs";
};
outputs = {
self,
nixpkgs,
flake-utils,
poetry2nix,
}:
# TODO: build cross-OS and use the `${system}` var thingy..
flake-utils.lib.eachDefaultSystem (system:
let
# use PWD as sources
projectDir = ./.;
pyproject = ./pyproject.toml;
poetrylock = ./poetry.lock;
# TODO: port to 3.11 and support both versions?
python = "python3.10";
# for more functions and examples.
# inherit
# (poetry2nix.legacyPackages.${system})
# mkPoetryApplication;
# pkgs = nixpkgs.legacyPackages.${system};
pkgs = nixpkgs.legacyPackages.x86_64-linux;
lib = pkgs.lib;
p2npkgs = poetry2nix.legacyPackages.x86_64-linux;
# define all pkg overrides per dep, see edgecases.md:
# https://github.com/nix-community/poetry2nix/blob/master/docs/edgecases.md
# TODO: add these into the json file:
# https://github.com/nix-community/poetry2nix/blob/master/overrides/build-systems.json
pypkgs-build-requirements = {
asyncvnc = [ "setuptools" ];
eventkit = [ "setuptools" ];
ib-insync = [ "setuptools" "flake8" ];
msgspec = [ "setuptools"];
pdbp = [ "setuptools" ];
pyqt6-sip = [ "setuptools" ];
tabcompleter = [ "setuptools" ];
tractor = [ "setuptools" ];
tricycle = [ "setuptools" ];
trio-typing = [ "setuptools" ];
trio-util = [ "setuptools" ];
xonsh = [ "setuptools" ];
};
# auto-generate override entries
p2n-overrides = p2npkgs.defaultPoetryOverrides.extend (self: super:
builtins.mapAttrs (package: build-requirements:
(builtins.getAttr package super).overridePythonAttrs (old: {
buildInputs = (
old.buildInputs or [ ]
) ++ (
builtins.map (
pkg: if builtins.isString pkg then builtins.getAttr pkg super else pkg
) build-requirements
);
})
) pypkgs-build-requirements
);
# override some ahead-of-time compiled extensions
# to be built with their wheels.
ahot_overrides = p2n-overrides.extend(
final: prev: {
# llvmlite = prev.llvmlite.override {
# preferWheel = false;
# };
# TODO: get this workin with p2n and nixpkgs..
# pyqt6 = prev.pyqt6.override {
# preferWheel = true;
# };
# NOTE: this DOESN'T work atm but after a fix
# to poetry2nix, it will and actually this line
# won't be needed - thanks @k900:
# https://github.com/nix-community/poetry2nix/pull/1257
pyqt5 = prev.pyqt5.override {
# withWebkit = false;
preferWheel = true;
};
# see PR from @k900:
# https://github.com/nix-community/poetry2nix/pull/1257
# pyqt5-qt5 = prev.pyqt5-qt5.override {
# withWebkit = false;
# preferWheel = true;
# };
# TODO: patch in an override for polars to build
# from src! See the details likely needed from
# the cryptography entry:
# https://github.com/nix-community/poetry2nix/blob/master/overrides/default.nix#L426-L435
polars = prev.polars.override {
preferWheel = true;
};
}
);
# WHY!? -> output-attrs that `nix develop` scans for:
# https://nixos.org/manual/nix/stable/command-ref/new-cli/nix3-develop.html#flake-output-attributes
in
rec {
packages = {
# piker = poetry2nix.legacyPackages.x86_64-linux.mkPoetryEditablePackage {
# editablePackageSources = { piker = ./piker; };
piker = p2npkgs.mkPoetryApplication {
projectDir = projectDir;
# SEE ABOVE for auto-genned input set, override
# buncha deps with extras.. like `setuptools` mostly.
# TODO: maybe propose a patch to p2n to show that you
# can even do this in the edgecases docs?
overrides = ahot_overrides;
# XXX: won't work on llvmlite..
# preferWheels = true;
};
};
# devShells.default = pkgs.mkShell {
# projectDir = projectDir;
# python = "python3.10";
# overrides = ahot_overrides;
# inputsFrom = [ self.packages.x86_64-linux.piker ];
# packages = packages;
# # packages = [ poetry2nix.packages.${system}.poetry ];
# };
# TODO: grok the difference here..
# - avoid re-cloning git repos on every develop entry..
# - ideally allow hacking on the src code of some deps
# (tractor, pyqtgraph, tomlkit, etc.) WITHOUT having to
# re-install them every time a change is made.
# - boot a usable xonsh inside the poetry virtualenv when
# defined via a custom entry point?
devShells.default = p2npkgs.mkPoetryEnv {
# env = p2npkgs.mkPoetryEnv {
projectDir = projectDir;
python = pkgs.python310;
overrides = ahot_overrides;
editablePackageSources = packages;
# piker = "./";
# tractor = "../tractor/";
# }; # wut?
};
}
); # end of .outputs scope
}

View File

@ -1,16 +0,0 @@
.accounting
-----------
A subsystem for transaction processing, storage and historical
measurement.
.pnl
----
BEP, the break even price: the price at which liquidating
a remaining position results in a zero PnL since the position was
"opened" in the destination asset.
PPU: price-per-unit: the "average cost" (in cumulative mean terms)
of the "entry" transactions which "make a position larger"; taking
a profit relative to this price means that you will "make more
profit then made prior" since the position was opened.

View File

@ -21,21 +21,17 @@ for tendiez.
'''
from ..log import get_logger
from .calc import (
iter_by_dt,
)
from ._ledger import (
iter_by_dt,
Transaction,
TransactionLedger,
open_trade_ledger,
)
from ._pos import (
Account,
load_account,
load_account_from_ledger,
load_pps_from_ledger,
open_pps,
open_account,
Position,
PpTable,
)
from ._mktinfo import (
Asset,
@ -51,25 +47,22 @@ from ._allocate import (
Allocator,
)
log = get_logger(__name__)
__all__ = [
'Account',
'Allocator',
'Asset',
'MktPair',
'Position',
'PpTable',
'Symbol',
'Transaction',
'TransactionLedger',
'dec_digits',
'digits_to_dec',
'iter_by_dt',
'load_account',
'load_account_from_ledger',
'load_pps_from_ledger',
'mk_allocator',
'open_account',
'open_pps',
'open_trade_ledger',
'unpack_fqme',
@ -89,7 +82,7 @@ def get_likely_pair(
'''
try:
src_name_start: str = bs_mktid.rindex(src)
src_name_start = bs_mktid.rindex(src)
except (
ValueError, # substr not found
):
@ -100,8 +93,25 @@ def get_likely_pair(
# log.warning(
# f'No src fiat {src} found in {bs_mktid}?'
# )
return None
return
likely_dst: str = bs_mktid[:src_name_start]
likely_dst = bs_mktid[:src_name_start]
if likely_dst == dst:
return bs_mktid
if __name__ == '__main__':
import sys
from pprint import pformat
args = sys.argv
assert len(args) > 1, 'Specifiy account(s) from `brokers.toml`'
args = args[1:]
for acctid in args:
broker, name = acctid.split('.')
trans, updated_pps = load_pps_from_ledger(broker, name)
print(
f'Processing transactions into pps for {broker}:{acctid}\n'
f'{pformat(trans)}\n\n'
f'{pformat(updated_pps)}'
)

View File

@ -25,7 +25,7 @@ from bidict import bidict
from ._pos import Position
from . import MktPair
from piker.types import Struct
from ..data.types import Struct
_size_units = bidict({
@ -118,9 +118,9 @@ class Allocator(Struct):
ld: int = mkt.size_tick_digits
size_unit = self.size_unit
live_size = live_pp.cumsize
live_size = live_pp.size
abs_live_size = abs(live_size)
abs_startup_size = abs(startup_pp.cumsize)
abs_startup_size = abs(startup_pp.size)
u_per_slot, currency_per_slot = self.step_sizes()
@ -213,6 +213,8 @@ class Allocator(Struct):
slots_used = self.slots_used(
Position(
mkt=mkt,
size=order_size,
ppu=price,
bs_mktid=mkt.bs_mktid,
)
)
@ -239,7 +241,7 @@ class Allocator(Struct):
Calc and return the number of slots used by this ``Position``.
'''
abs_pp_size = abs(pp.cumsize)
abs_pp_size = abs(pp.size)
if self.size_unit == 'currency':
# live_currency_size = size or (abs_pp_size * pp.ppu)

View File

@ -21,77 +21,65 @@ Trade and transaction ledger processing.
from __future__ import annotations
from collections import UserDict
from contextlib import contextmanager as cm
from functools import partial
from pathlib import Path
from pprint import pformat
from types import ModuleType
from typing import (
Any,
Callable,
Generator,
Literal,
TYPE_CHECKING,
Iterator,
Union,
Generator
)
from pendulum import (
datetime,
DateTime,
from_timestamp,
parse,
)
import tomli_w # for fast ledger writing
from piker.types import Struct
from piker import config
from .. import config
from ..data.types import Struct
from ..log import get_logger
from .calc import (
iter_by_dt,
)
if TYPE_CHECKING:
from ..data._symcache import (
SymbologyCache,
from ._mktinfo import (
Symbol, # legacy
MktPair,
Asset,
)
log = get_logger(__name__)
TxnType = Literal[
'clear',
'transfer',
# TODO: see https://github.com/pikers/piker/issues/510
# 'split',
# 'rename',
# 'resize',
# 'removal',
]
class Transaction(Struct, frozen=True):
# NOTE: this is a unified acronym also used in our `MktPair`
# and can stand for any of a
# "fully qualified <blank> endpoint":
# - "market" in the case of financial trades
# (btcusdt.spot.binance).
# - "merkel (tree)" aka a blockchain system "wallet tranfers"
# (btc.blockchain)
# - "money" for tradtitional (digital databases)
# *bank accounts* (usd.swift, eur.sepa)
# TODO: unify this with the `MktPair`,
# once we have that as a required field,
# we don't really need the fqme any more..
fqme: str
tid: str | int # unique transaction id
tid: Union[str, int] # unique transaction id
size: float
price: float
cost: float # commisions or other additional costs
dt: DateTime
# the "event type" in terms of "market events" see above and
# https://github.com/pikers/piker/issues/510
etype: TxnType = 'clear'
dt: datetime
# TODO: we can drop this right since we
# can instead expect the backend to provide this
# via the `MktPair`?
expiry: DateTime | None = None
expiry: datetime | None = None
# TODO: drop the Symbol type, construct using
# t.sys (the transaction system)
# the underlying "transaction system", normally one of a ``MktPair``
# (a description of a tradable double auction) or a ledger-recorded
# ("ledger" in any sense as long as you can record transfers) of any
# sort) ``Asset``.
sym: MktPair | Asset | Symbol | None = None
@property
def sys(self) -> Symbol:
return self.sym
# (optional) key-id defined by the broker-service backend which
# ensures the instrument-symbol market key for this record is unique
@ -100,16 +88,15 @@ class Transaction(Struct, frozen=True):
# service.
bs_mktid: str | int | None = None
def to_dict(
self,
**kwargs,
) -> dict:
dct: dict[str, Any] = super().to_dict(**kwargs)
def to_dict(self) -> dict:
dct = super().to_dict()
# TODO: switch to sys!
dct.pop('sym')
# ensure we use a pendulum formatted
# ISO style str here!@
dct['dt'] = str(self.dt)
return dct
@ -121,45 +108,17 @@ class TransactionLedger(UserDict):
outside.
'''
# NOTE: see `open_trade_ledger()` for defaults, this should
# never be constructed manually!
def __init__(
self,
ledger_dict: dict,
file_path: Path,
account: str,
mod: ModuleType, # broker mod
tx_sort: Callable,
symcache: SymbologyCache,
) -> None:
self.account: str = account
self.file_path: Path = file_path
self.mod: ModuleType = mod
self.tx_sort: Callable = tx_sort
self._symcache: SymbologyCache = symcache
# any added txns we keep in that form for meta-data
# gathering purposes
self._txns: dict[str, Transaction] = {}
self.file_path = file_path
self.tx_sort = tx_sort
super().__init__(ledger_dict)
def __repr__(self) -> str:
return (
f'TransactionLedger: {len(self)}\n'
f'{pformat(list(self.data))}'
)
@property
def symcache(self) -> SymbologyCache:
'''
Read-only ref to backend's ``SymbologyCache``.
'''
return self._symcache
def update_from_t(
self,
t: Transaction,
@ -170,14 +129,14 @@ class TransactionLedger(UserDict):
'''
self.data[t.tid] = t.to_dict()
self._txns[t.tid] = t
def iter_txns(
def iter_trans(
self,
symcache: SymbologyCache | None = None,
mkt_by_fqme: dict[str, MktPair],
broker: str = 'paper',
) -> Generator[
Transaction,
tuple[str, Transaction],
None,
None,
]:
@ -186,125 +145,129 @@ class TransactionLedger(UserDict):
form via generator.
'''
symcache = symcache or self._symcache
if broker != 'paper':
raise NotImplementedError('Per broker support not dun yet!')
if self.account == 'paper':
from piker.clearing import _paper_engine
norm_trade: Callable = partial(
_paper_engine.norm_trade,
brokermod=self.mod,
# TODO: lookup some standard normalizer
# func in the backend?
# from ..brokers import get_brokermod
# mod = get_brokermod(broker)
# trans_dict = mod.norm_trade_records(self.data)
# NOTE: instead i propose the normalizer is
# a one shot routine (that can be lru cached)
# and instead call it for each entry incrementally:
# normer = mod.norm_trade_record(txdict)
# TODO: use tx_sort here yah?
for txdict in self.tx_sort(self.data.values()):
# for tid, txdict in self.data.items():
# special field handling for datetimes
# to ensure pendulum is used!
tid: str = txdict['tid']
fqme: str = txdict.get('fqme') or txdict['fqsn']
dt: DateTime = parse(txdict['dt'])
expiry: str | None = txdict.get('expiry')
if not (mkt := mkt_by_fqme.get(fqme)):
# we can't build a trans if we don't have
# the ``.sys: MktPair`` info, so skip.
continue
tx = Transaction(
fqme=fqme,
tid=txdict['tid'],
dt=dt,
price=txdict['price'],
size=txdict['size'],
cost=txdict.get('cost', 0),
bs_mktid=txdict['bs_mktid'],
# TODO: change to .sys!
sym=mkt,
expiry=parse(expiry) if expiry else None,
)
yield tid, tx
else:
norm_trade: Callable = self.mod.norm_trade
# datetime-sort and pack into txs
for tid, txdict in self.tx_sort(self.data.items()):
txn: Transaction = norm_trade(
tid,
txdict,
pairs=symcache.pairs,
symcache=symcache,
)
yield txn
def to_txns(
def to_trans(
self,
symcache: SymbologyCache | None = None,
**kwargs,
) -> dict[str, Transaction]:
'''
Return entire output from ``.iter_txns()`` in a ``dict``.
Return entire output from ``.iter_trans()`` in a ``dict``.
'''
txns: dict[str, Transaction] = {}
for t in self.iter_txns(symcache=symcache):
return dict(self.iter_trans(**kwargs))
if not t:
log.warning(f'{self.mod.name}:{self.account} TXN is -> {t}')
continue
def write_config(
self,
txns[t.tid] = t
return txns
def write_config(self) -> None:
) -> None:
'''
Render the self.data ledger dict to its TOML file form.
ALWAYS order datetime sorted!
Render the self.data ledger dict to it's TOML file form.
'''
is_paper: bool = self.account == 'paper'
symcache: SymbologyCache = self._symcache
cpy = self.data.copy()
towrite: dict[str, Any] = {}
for tid, txdict in self.tx_sort(self.data.copy()):
# write blank-str expiry for non-expiring assets
for tid, trans in cpy.items():
# drop key for non-expiring assets
txdict = towrite[tid] = self.data[tid]
if (
'expiry' in txdict
and txdict['expiry'] is None
):
txdict['expiry'] = ''
txdict.pop('expiry')
# (maybe) re-write old acro-key
if (
is_paper
# if symcache is empty/not supported (yet), don't
# bother xD
and symcache.mktmaps
):
fqme: str = txdict.pop('fqsn', None) or txdict['fqme']
bs_mktid: str | None = txdict.get('bs_mktid')
if (
fqme not in symcache.mktmaps
or (
# also try to see if this is maybe a paper
# engine ledger in which case the bs_mktid
# should be the fqme as well!
bs_mktid
and fqme != bs_mktid
)
):
# always take any (paper) bs_mktid if defined and
# in the backend's cache key set.
if bs_mktid in symcache.mktmaps:
fqme: str = bs_mktid
else:
best_fqme: str = list(symcache.search(fqme))[0]
log.warning(
f'Could not find FQME: {fqme} in qualified set?\n'
f'Qualifying and expanding {fqme} -> {best_fqme}'
)
fqme = best_fqme
if (
bs_mktid
and bs_mktid != fqme
):
# in paper account case always make sure both the
# fqme and bs_mktid are fully qualified..
txdict['bs_mktid'] = fqme
# in paper ledgers always write the latest
# symbology key field: an FQME.
# re-write old acro-key
fqme = txdict.get('fqsn')
if fqme:
txdict['fqme'] = fqme
towrite[tid] = txdict
with self.file_path.open(mode='wb') as fp:
tomli_w.dump(towrite, fp)
def iter_by_dt(
records: dict[str, dict[str, Any]] | list[dict],
# NOTE: parsers are looked up in the insert order
# so if you know that the record stats show some field
# is more common then others, stick it at the top B)
parsers: dict[tuple[str], Callable] = {
'dt': None, # parity case
'datetime': parse, # datetime-str
'time': from_timestamp, # float epoch
},
key: Callable | None = None,
) -> Iterator[tuple[str, dict]]:
'''
Iterate entries of a ``records: dict`` table sorted by entry recorded
datetime presumably set at the ``'dt'`` field in each entry.
'''
def dyn_parse_to_dt(txdict: dict[str, Any]) -> DateTime:
k, v, parser = next(
(k, txdict[k], parsers[k]) for k in parsers if k in txdict
)
return parser(v) if parser else v
if isinstance(records, dict):
records = records.values()
for entry in sorted(
records,
key=key or dyn_parse_to_dt,
):
yield entry
def load_ledger(
brokername: str,
acctid: str,
# for testing or manual load from file
dirpath: Path | None = None,
) -> tuple[dict, Path]:
'''
Load a ledger (TOML) file from user's config directory:
@ -319,11 +282,7 @@ def load_ledger(
except ModuleNotFoundError:
import tomli as tomllib
ldir: Path = (
dirpath
or
config._config_dir / 'accounting' / 'ledgers'
)
ldir: Path = config._config_dir / 'accounting' / 'ledgers'
if not ldir.is_dir():
ldir.mkdir()
@ -349,15 +308,8 @@ def open_trade_ledger(
broker: str,
account: str,
allow_from_sync_code: bool = False,
symcache: SymbologyCache | None = None,
# default is to sort by detected datetime-ish field
tx_sort: Callable = iter_by_dt,
rewrite: bool = False,
# for testing or manual load from file
_fp: Path | None = None,
) -> Generator[TransactionLedger, None, None]:
'''
@ -369,52 +321,18 @@ def open_trade_ledger(
name as defined in the user's ``brokers.toml`` config.
'''
from ..brokers import get_brokermod
mod: ModuleType = get_brokermod(broker)
ledger_dict, fpath = load_ledger(
broker,
account,
dirpath=_fp,
)
ledger_dict, fpath = load_ledger(broker, account)
cpy = ledger_dict.copy()
# XXX NOTE: if not provided presume we are being called from
# sync code and need to maybe run `trio` to generate..
if symcache is None:
# XXX: be mega pendantic and ensure the caller knows what
# they're doing!
if not allow_from_sync_code:
raise RuntimeError(
'You MUST set `allow_from_sync_code=True` when '
'calling `open_trade_ledger()` from sync code! '
'If you are calling from async code you MUST '
'instead pass a `symcache: SymbologyCache`!'
)
from ..data._symcache import (
get_symcache,
)
symcache: SymbologyCache = get_symcache(broker)
assert symcache
ledger = TransactionLedger(
ledger_dict=cpy,
file_path=fpath,
account=account,
mod=mod,
symcache=symcache,
tx_sort=getattr(mod, 'tx_sort', tx_sort),
tx_sort=tx_sort,
)
try:
yield ledger
finally:
if (
ledger.data != ledger_dict
or rewrite
):
if ledger.data != ledger_dict:
# TODO: show diff output?
# https://stackoverflow.com/questions/12956957/print-diff-of-python-dictionaries
log.info(f'Updating ledger for {fpath}:\n')

View File

@ -36,7 +36,7 @@ from typing import (
Literal,
)
from piker.types import Struct
from ..data.types import Struct
# TODO: make these literals..
@ -130,29 +130,8 @@ class Asset(Struct, frozen=True):
# should not be explicitly required in our generic API.
info: dict | None = None
# `None` is not toml-compat so drop info
# if no extra data added..
def to_dict(
self,
**kwargs,
) -> dict:
dct = super().to_dict(**kwargs)
if (info := dct.pop('info', None)):
dct['info'] = info
assert dct['tx_tick']
return dct
@classmethod
def from_msg(
cls,
msg: dict[str, Any],
) -> Asset:
return cls(
tx_tick=Decimal(str(msg.pop('tx_tick'))),
info=msg.pop('info', None),
**msg,
)
# TODO?
# _to_dict_skip = {'info'}
def __str__(self) -> str:
return self.name
@ -309,40 +288,12 @@ class MktPair(Struct, frozen=True):
# strike price, call or put, swap type, exercise model, etc.
contract_info: list[str] | None = None
# TODO: rename to sectype since all of these can
# be considered "securities"?
_atype: str = ''
# allow explicit disable of the src part of the market
# pair name -> useful for legacy markets like qqq.nasdaq.ib
_fqme_without_src: bool = False
# NOTE: when cast to `str` return fqme
def __str__(self) -> str:
return self.fqme
def to_dict(
self,
**kwargs,
) -> dict:
d = super().to_dict(**kwargs)
d['src'] = self.src.to_dict(**kwargs)
if not isinstance(self.dst, str):
d['dst'] = self.dst.to_dict(**kwargs)
else:
d['dst'] = str(self.dst)
d['price_tick'] = str(self.price_tick)
d['size_tick'] = str(self.size_tick)
if self.contract_info is None:
d.pop('contract_info')
# d.pop('_fqme_without_src')
return d
@classmethod
def from_msg(
cls,
@ -353,32 +304,36 @@ class MktPair(Struct, frozen=True):
Constructor for a received msg-dict normally received over IPC.
'''
if not isinstance(
dst_asset_msg := msg.pop('dst'),
str,
):
dst: Asset = Asset.from_msg(dst_asset_msg) # .copy()
dst_asset_msg = msg.pop('dst')
src_asset_msg = msg.pop('src')
if isinstance(dst_asset_msg, str):
src: str = str(src_asset_msg)
assert isinstance(src, str)
return cls.from_fqme(
dst_asset_msg,
src=src,
**msg,
)
else:
dst: str = dst_asset_msg
# NOTE: we call `.copy()` here to ensure
# type casting!
dst = Asset(**dst_asset_msg).copy()
if not isinstance(src_asset_msg, str):
src = Asset(**src_asset_msg).copy()
else:
src = str(src_asset_msg)
src_asset_msg: dict = msg.pop('src')
src: Asset = Asset.from_msg(src_asset_msg) # .copy()
# XXX NOTE: ``msgspec`` can encode `Decimal` but it doesn't
# decide to it by default since we aren't spec-cing these
# msgs as structs proper to get them to decode implictily
# (yet) as per,
# - https://github.com/pikers/piker/pull/354
# - https://github.com/goodboy/tractor/pull/311
# SO we have to ensure we do a struct type
# case (which `.copy()` does) to ensure we get the right
# type!
return cls(
dst=dst,
src=src,
price_tick=Decimal(msg.pop('price_tick')),
size_tick=Decimal(msg.pop('size_tick')),
**msg,
# XXX NOTE: ``msgspec`` can encode `Decimal`
# but it doesn't decide to it by default since
# we aren't spec-cing these msgs as structs, SO
# we have to ensure we do a struct type case (which `.copy()`
# does) to ensure we get the right type!
).copy()
@property
@ -406,20 +361,7 @@ class MktPair(Struct, frozen=True):
):
_fqme = f'{fqme}.{broker}'
broker, mkt_ep_key, venue, expiry = unpack_fqme(_fqme)
kven: str = kwargs.pop('venue', venue)
if venue:
assert venue == kven
else:
venue = kven
exp: str = kwargs.pop('expiry', expiry)
if expiry:
assert exp == expiry
else:
expiry = exp
broker, mkt_ep_key, venue, suffix = unpack_fqme(_fqme)
dst: Asset = Asset.guess_from_mkt_ep_key(
mkt_ep_key,
atype=kwargs.get('_atype'),
@ -431,15 +373,14 @@ class MktPair(Struct, frozen=True):
# which we expect to be filled in by some
# backend client with access to that data-info.
return cls(
dst=dst,
# XXX: not resolved to ``Asset`` :(
#src=src,
dst=dst,
broker=broker,
venue=venue,
# XXX NOTE: we presume this token
# if the expiry for now!
expiry=expiry,
expiry=suffix,
price_tick=price_tick,
size_tick=size_tick,
@ -545,7 +486,7 @@ class MktPair(Struct, frozen=True):
'''
key: str = (
self.pair(delim_char=delim_char)
if not (without_src or self._fqme_without_src)
if not without_src
else str(self.dst)
)
@ -614,7 +555,7 @@ class MktPair(Struct, frozen=True):
if isinstance(self.dst, Asset):
return str(self.dst.atype)
return 'UNKNOWN'
return 'unknown'
@property
def price_tick_digits(self) -> int:

File diff suppressed because it is too large Load Diff

View File

@ -1,698 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Calculation routines for balance and position tracking such that
you know when you're losing money (if possible) XD
'''
from __future__ import annotations
from collections.abc import ValuesView
from contextlib import contextmanager as cm
from math import copysign
from typing import (
Any,
Callable,
Iterator,
TYPE_CHECKING,
)
import polars as pl
from pendulum import (
DateTime,
from_timestamp,
parse,
)
if TYPE_CHECKING:
from ._ledger import (
Transaction,
TransactionLedger,
)
def ppu(
clears: Iterator[Transaction],
# include transaction cost in breakeven price
# and presume the worst case of the same cost
# to exit this transaction (even though in reality
# it will be dynamic based on exit stratetgy).
cost_scalar: float = 2,
# return the ledger of clears as a (now dt sorted) dict with
# new position fields inserted alongside each entry.
as_ledger: bool = False,
) -> float | list[(str, dict)]:
'''
Compute the "price-per-unit" price for the given non-zero sized
rolling position.
The recurrence relation which computes this (exponential) mean
per new clear which **increases** the accumulative postiion size
is:
ppu[-1] = (
ppu[-2] * accum_size[-2]
+
ppu[-1] * size
) / accum_size[-1]
where `cost_basis` for the current step is simply the price
* size of the most recent clearing transaction.
-----
TODO: get the BEP computed and working similarly!
-----
the equivalent "break even price" or bep at each new clear
event step conversely only changes when an "position exiting
clear" which **decreases** the cumulative dst asset size:
bep[-1] = ppu[-1] - (cum_pnl[-1] / cumsize[-1])
'''
asize_h: list[float] = [] # historical accumulative size
ppu_h: list[float] = [] # historical price-per-unit
# ledger: dict[str, dict] = {}
ledger: list[dict] = []
t: Transaction
for t in clears:
clear_size: float = t.size
clear_price: str | float = t.price
is_clear: bool = not isinstance(clear_price, str)
last_accum_size = asize_h[-1] if asize_h else 0
accum_size: float = last_accum_size + clear_size
accum_sign = copysign(1, accum_size)
sign_change: bool = False
# on transfers we normally write some non-valid
# price since withdrawal to another account/wallet
# has nothing to do with inter-asset-market prices.
# TODO: this should be better handled via a `type: 'tx'`
# field as per existing issue surrounding all this:
# https://github.com/pikers/piker/issues/510
if isinstance(clear_price, str):
# TODO: we can't necessarily have this commit to
# the overall pos size since we also need to
# include other positions contributions to this
# balance or we might end up with a -ve balance for
# the position..
continue
# test if the pp somehow went "passed" a net zero size state
# resulting in a change of the "sign" of the size (+ve for
# long, -ve for short).
sign_change = (
copysign(1, last_accum_size) + accum_sign == 0
and last_accum_size != 0
)
# since we passed the net-zero-size state the new size
# after sum should be the remaining size the new
# "direction" (aka, long vs. short) for this clear.
if sign_change:
clear_size: float = accum_size
abs_diff: float = abs(accum_size)
asize_h.append(0)
ppu_h.append(0)
else:
# old size minus the new size gives us size diff with
# +ve -> increase in pp size
# -ve -> decrease in pp size
abs_diff = abs(accum_size) - abs(last_accum_size)
# XXX: LIFO breakeven price update. only an increaze in size
# of the position contributes the breakeven price,
# a decrease does not (i.e. the position is being made
# smaller).
# abs_clear_size = abs(clear_size)
abs_new_size: float | int = abs(accum_size)
if (
abs_diff > 0
and is_clear
):
cost_basis = (
# cost basis for this clear
clear_price * abs(clear_size)
+
# transaction cost
accum_sign * cost_scalar * t.cost
)
if asize_h:
size_last: float = abs(asize_h[-1])
cb_last: float = ppu_h[-1] * size_last
ppu: float = (cost_basis + cb_last) / abs_new_size
else:
ppu: float = cost_basis / abs_new_size
else:
# TODO: for PPU we should probably handle txs out
# (aka withdrawals) similarly by simply not having
# them contrib to the running PPU calc and only
# when the next entry clear comes in (which will
# then have a higher weighting on the PPU).
# on "exit" clears from a given direction,
# only the size changes not the price-per-unit
# need to be updated since the ppu remains constant
# and gets weighted by the new size.
ppu: float = ppu_h[-1] if ppu_h else 0 # set to previous value
# extend with new rolling metric for this step
ppu_h.append(ppu)
asize_h.append(accum_size)
# ledger[t.tid] = {
# 'txn': t,
# ledger[t.tid] = t.to_dict() | {
ledger.append((
t.tid,
t.to_dict() | {
'ppu': ppu,
'cumsize': accum_size,
'sign_change': sign_change,
# TODO: cum_pnl, bep
}
))
final_ppu = ppu_h[-1] if ppu_h else 0
# TODO: once we have etypes in all ledger entries..
# handle any split info entered (for now) manually by user
# if self.split_ratio is not None:
# final_ppu /= self.split_ratio
if as_ledger:
return ledger
else:
return final_ppu
def iter_by_dt(
records: (
dict[str, dict[str, Any]]
| ValuesView[dict] # eg. `Position._events.values()`
| list[dict]
| list[Transaction] # XXX preferred!
),
# NOTE: parsers are looked up in the insert order
# so if you know that the record stats show some field
# is more common then others, stick it at the top B)
parsers: dict[str, Callable | None] = {
'dt': parse, # parity case
'datetime': parse, # datetime-str
'time': from_timestamp, # float epoch
},
key: Callable | None = None,
) -> Iterator[tuple[str, dict]]:
'''
Iterate entries of a transaction table sorted by entry recorded
datetime presumably set at the ``'dt'`` field in each entry.
'''
if isinstance(records, dict):
records: list[tuple[str, dict]] = list(records.items())
def dyn_parse_to_dt(
tx: tuple[str, dict[str, Any]] | Transaction,
) -> DateTime:
# handle `.items()` inputs
if isinstance(tx, tuple):
tx = tx[1]
# dict or tx object?
isdict: bool = isinstance(tx, dict)
# get best parser for this record..
for k in parsers:
if (
isdict and k in tx
or getattr(tx, k, None)
):
v = tx[k] if isdict else tx.dt
assert v is not None, f'No valid value for `{k}`!?'
# only call parser on the value if not None from
# the `parsers` table above (when NOT using
# `.get()`), otherwise pass through the value and
# sort on it directly
if (
not isinstance(v, DateTime)
and (parser := parsers.get(k))
):
return parser(v)
else:
return v
else:
# XXX: should never get here..
breakpoint()
entry: tuple[str, dict] | Transaction
for entry in sorted(
records,
key=key or dyn_parse_to_dt,
):
# NOTE the type sig above; either pairs or txns B)
yield entry
# TODO: probably just move this into the test suite or
# keep it here for use from as such?
# def ensure_state(self) -> None:
# '''
# Audit either the `.cumsize` and `.ppu` local instance vars against
# the clears table calculations and return the calc-ed values if
# they differ and log warnings to console.
# '''
# # clears: list[dict] = self._clears
# # self.first_clear_dt = min(clears, key=lambda e: e['dt'])['dt']
# last_clear: dict = clears[-1]
# csize: float = self.calc_size()
# accum: float = last_clear['accum_size']
# if not self.expired():
# if (
# csize != accum
# and csize != round(accum * (self.split_ratio or 1))
# ):
# raise ValueError(f'Size mismatch: {csize}')
# else:
# assert csize == 0, 'Contract is expired but non-zero size?'
# if self.cumsize != csize:
# log.warning(
# 'Position state mismatch:\n'
# f'{self.cumsize} => {csize}'
# )
# self.cumsize = csize
# cppu: float = self.calc_ppu()
# ppu: float = last_clear['ppu']
# if (
# cppu != ppu
# and self.split_ratio is not None
# # handle any split info entered (for now) manually by user
# and cppu != (ppu / self.split_ratio)
# ):
# raise ValueError(f'PPU mismatch: {cppu}')
# if self.ppu != cppu:
# log.warning(
# 'Position state mismatch:\n'
# f'{self.ppu} => {cppu}'
# )
# self.ppu = cppu
@cm
def open_ledger_dfs(
brokername: str,
acctname: str,
ledger: TransactionLedger | None = None,
**kwargs,
) -> tuple[
dict[str, pl.DataFrame],
TransactionLedger,
]:
'''
Open a ledger of trade records (presumably from some broker
backend), normalize the records into `Transactions` via the
backend's declared endpoint, cast to a `polars.DataFrame` which
can update the ledger on exit.
'''
from piker.toolz import open_crash_handler
with open_crash_handler():
if not ledger:
import time
from ._ledger import open_trade_ledger
now = time.time()
with open_trade_ledger(
brokername,
acctname,
rewrite=True,
allow_from_sync_code=True,
# proxied through from caller
**kwargs,
) as ledger:
if not ledger:
raise ValueError(f'No ledger for {acctname}@{brokername} exists?')
print(f'LEDGER LOAD TIME: {time.time() - now}')
yield ledger_to_dfs(ledger), ledger
def ledger_to_dfs(
ledger: TransactionLedger,
) -> dict[str, pl.DataFrame]:
txns: dict[str, Transaction] = ledger.to_txns()
# ldf = pl.DataFrame(
# list(txn.to_dict() for txn in txns.values()),
ldf = pl.from_dicts(
list(txn.to_dict() for txn in txns.values()),
# only for ordering the cols
schema=[
('fqme', str),
('tid', str),
('bs_mktid', str),
('expiry', str),
('etype', str),
('dt', str),
('size', pl.Float64),
('price', pl.Float64),
('cost', pl.Float64),
],
).sort( # chronological order
'dt'
).with_columns([
pl.col('dt').str.to_datetime(),
# pl.col('expiry').str.to_datetime(),
# pl.col('expiry').dt.date(),
])
# filter out to the columns matching values filter passed
# as input.
# if filter_by_ids:
# for col, vals in filter_by_ids.items():
# str_vals = set(map(str, vals))
# pred: pl.Expr = pl.col(col).eq(str_vals.pop())
# for val in str_vals:
# pred |= pl.col(col).eq(val)
# fdf = df.filter(pred)
# TODO: originally i had tried just using a plain ol' groupby
# + agg here but the issue was re-inserting to the src frame.
# however, learning more about `polars` seems like maybe we can
# use `.over()`?
# https://pola-rs.github.io/polars/py-polars/html/reference/expressions/api/polars.Expr.over.html#polars.Expr.over
# => CURRENTLY we break up into a frame per mkt / fqme
dfs: dict[str, pl.DataFrame] = ldf.partition_by(
'bs_mktid',
as_dict=True,
)
# TODO: not sure if this is even possible but..
# - it'd be more ideal to use `ppt = df.groupby('fqme').agg([`
# - ppu and bep calcs!
for key in dfs:
# covert to lazy form (since apparently we might need it
# eventually ...)
df: pl.DataFrame = dfs[key]
ldf: pl.LazyFrame = df.lazy()
df = dfs[key] = ldf.with_columns([
pl.cumsum('size').alias('cumsize'),
# amount of source asset "sent" (via buy txns in
# the market) to acquire the dst asset, PER txn.
# when this value is -ve (i.e. a sell operation) then
# the amount sent is actually "returned".
(
(pl.col('price') * pl.col('size'))
+
(pl.col('cost')) # * pl.col('size').sign())
).alias('dst_bot'),
]).with_columns([
# rolling balance in src asset units
(pl.col('dst_bot').cumsum() * -1).alias('src_balance'),
# "position operation type" in terms of increasing the
# amount in the dst asset (entering) or decreasing the
# amount in the dst asset (exiting).
pl.when(
pl.col('size').sign() == pl.col('cumsize').sign()
).then(
pl.lit('enter') # see above, but is just price * size per txn
).otherwise(
pl.when(pl.col('cumsize') == 0)
.then(pl.lit('exit_to_zero'))
.otherwise(pl.lit('exit'))
).alias('descr'),
(pl.col('cumsize').sign() == pl.col('size').sign())
.alias('is_enter'),
]).with_columns([
# pl.lit(0, dtype=pl.Utf8).alias('virt_cost'),
pl.lit(0, dtype=pl.Float64).alias('applied_cost'),
pl.lit(0, dtype=pl.Float64).alias('pos_ppu'),
pl.lit(0, dtype=pl.Float64).alias('per_txn_pnl'),
pl.lit(0, dtype=pl.Float64).alias('cum_pos_pnl'),
pl.lit(0, dtype=pl.Float64).alias('pos_bep'),
pl.lit(0, dtype=pl.Float64).alias('cum_ledger_pnl'),
pl.lit(None, dtype=pl.Float64).alias('ledger_bep'),
# TODO: instead of the iterative loop below i guess we
# could try using embedded lists to track which txns
# are part of which ppu / bep calcs? Not sure this will
# look any better nor be any more performant though xD
# pl.lit([[0]], dtype=pl.List(pl.Float64)).alias('list'),
# choose fields to emit for accounting puposes
]).select([
pl.exclude([
'tid',
# 'dt',
'expiry',
'bs_mktid',
'etype',
# 'is_enter',
]),
]).collect()
# compute recurrence relations for ppu and bep
last_ppu: float = 0
last_cumsize: float = 0
last_ledger_pnl: float = 0
last_pos_pnl: float = 0
virt_costs: list[float, float] = [0., 0.]
# imperatively compute the PPU (price per unit) and BEP
# (break even price) iteratively over the ledger, oriented
# around each position state: a state of split balances in
# > 1 asset.
for i, row in enumerate(df.iter_rows(named=True)):
cumsize: float = row['cumsize']
is_enter: bool = row['is_enter']
price: float = row['price']
size: float = row['size']
# the profit is ALWAYS decreased, aka made a "loss"
# by the constant fee charged by the txn provider!
# see below in final PnL calculation and row element
# set.
txn_cost: float = row['cost']
pnl: float = 0
# ALWAYS reset per-position cum PnL
if last_cumsize == 0:
last_pos_pnl: float = 0
# a "position size INCREASING" or ENTER transaction
# which "makes larger", in src asset unit terms, the
# trade's side-size of the destination asset:
# - "buying" (more) units of the dst asset
# - "selling" (more short) units of the dst asset
if is_enter:
# Naively include transaction cost in breakeven
# price and presume the worst case of the
# exact-same-cost-to-exit this transaction's worth
# of size even though in reality it will be dynamic
# based on exit strategy, price, liquidity, etc..
virt_cost: float = txn_cost
# cpu: float = cost / size
# cummean of the cost-per-unit used for modelling
# a projected future exit cost which we immediately
# include in the costs incorporated to BEP on enters
last_cum_costs_size, last_cpu = virt_costs
cum_costs_size: float = last_cum_costs_size + abs(size)
cumcpu = (
(last_cpu * last_cum_costs_size)
+
txn_cost
) / cum_costs_size
virt_costs = [cum_costs_size, cumcpu]
txn_cost = txn_cost + virt_cost
# df[i, 'virt_cost'] = f'{-virt_cost} FROM {cumcpu}@{cum_costs_size}'
# a cumulative mean of the price-per-unit acquired
# in the destination asset:
# https://en.wikipedia.org/wiki/Moving_average#Cumulative_average
# You could also think of this measure more
# generally as an exponential mean with `alpha
# = 1/N` where `N` is the current number of txns
# included in the "position" defining set:
# https://en.wikipedia.org/wiki/Exponential_smoothing
ppu: float = (
(
(last_ppu * last_cumsize)
+
(price * size)
) /
cumsize
)
# a "position size DECREASING" or EXIT transaction
# which "makes smaller" the trade's side-size of the
# destination asset:
# - selling previously bought units of the dst asset
# (aka 'closing' a long position).
# - buying previously borrowed and sold (short) units
# of the dst asset (aka 'covering'/'closing' a short
# position).
else:
# only changes on position size increasing txns
ppu: float = last_ppu
# UNWIND IMPLIED COSTS FROM ENTRIES
# => Reverse the virtual/modelled (2x predicted) txn
# cost that was included in the least-recently
# entered txn that is still part of the current CSi
# set.
# => we look up the cost-per-unit cumsum and apply
# if over the current txn size (by multiplication)
# and then reverse that previusly applied cost on
# the txn_cost for this record.
#
# NOTE: current "model" is just to previously assumed 2x
# the txn cost for a matching enter-txn's
# cost-per-unit; we then immediately reverse this
# prediction and apply the real cost received here.
last_cum_costs_size, last_cpu = virt_costs
prev_virt_cost: float = last_cpu * abs(size)
txn_cost: float = txn_cost - prev_virt_cost # +ve thus a "reversal"
cum_costs_size: float = last_cum_costs_size - abs(size)
virt_costs = [cum_costs_size, last_cpu]
# df[i, 'virt_cost'] = (
# f'{-prev_virt_cost} FROM {last_cpu}@{cum_costs_size}'
# )
# the per-txn profit or loss (PnL) given we are
# (partially) "closing"/"exiting" the position via
# this txn.
pnl: float = (last_ppu - price) * size
# always subtract txn cost from total txn pnl
txn_pnl: float = pnl - txn_cost
# cumulative PnLs per txn
last_ledger_pnl = (
last_ledger_pnl + txn_pnl
)
last_pos_pnl = df[i, 'cum_pos_pnl'] = (
last_pos_pnl + txn_pnl
)
if cumsize == 0:
last_ppu = ppu = 0
# compute the BEP: "break even price", a value that
# determines at what price the remaining cumsize can be
# liquidated such that the net-PnL on the current
# position will result in ZERO gain or loss from open
# to close including all txn costs B)
if (
abs(cumsize) > 0 # non-exit-to-zero position txn
):
cumsize_sign: float = copysign(1, cumsize)
ledger_bep: float = (
(
(ppu * cumsize)
-
(last_ledger_pnl * cumsize_sign)
) / cumsize
)
# NOTE: when we "enter more" dst asset units (aka
# increase position state) AFTER having exited some
# units (aka decreasing the pos size some) the bep
# needs to be RECOMPUTED based on new ppu such that
# liquidation of the cumsize at the bep price
# results in a zero-pnl for the existing position
# (since the last one).
# for position lifetime BEP we never can have
# a valid value once the position is "closed"
# / full exitted Bo
pos_bep: float = (
(
(ppu * cumsize)
-
(last_pos_pnl * cumsize_sign)
) / cumsize
)
# inject DF row with all values
df[i, 'pos_ppu'] = ppu
df[i, 'per_txn_pnl'] = txn_pnl
df[i, 'applied_cost'] = -txn_cost
df[i, 'cum_pos_pnl'] = last_pos_pnl
df[i, 'pos_bep'] = pos_bep
df[i, 'cum_ledger_pnl'] = last_ledger_pnl
df[i, 'ledger_bep'] = ledger_bep
# keep backrefs to suffice reccurence relation
last_ppu: float = ppu
last_cumsize: float = cumsize
# TODO?: pass back the current `Position` object loaded from
# the account as well? Would provide incentive to do all
# this ledger loading inside a new async open_account().
# bs_mktid: str = df[0]['bs_mktid']
# pos: Position = acnt.pps[bs_mktid]
return dfs

View File

@ -19,7 +19,6 @@ CLI front end for trades ledger and position tracking management.
'''
from __future__ import annotations
from pprint import pformat
from rich.console import Console
@ -38,11 +37,13 @@ from ..calc import humanize
from ..brokers._daemon import broker_init
from ._ledger import (
load_ledger,
TransactionLedger,
# open_trade_ledger,
# TransactionLedger,
)
from .calc import (
open_ledger_dfs,
from ._pos import (
PpTable,
load_pps_from_ledger,
# load_account,
)
@ -239,73 +240,54 @@ def sync(
def disect(
# "fully_qualified_account_name"
fqan: str,
fqme: str, # for ib
# TODO: in tractor we should really have
# a debug_mode ctx for wrapping any kind of code no?
bs_mktid: str, # for ib
pdb: bool = False,
bs_mktid: str = typer.Option(
None,
"-bid",
),
loglevel: str = typer.Option(
'error',
"-l",
),
):
from piker.log import get_console_log
from piker.toolz import open_crash_handler
get_console_log(loglevel)
pair: tuple[str, str]
if not (pair := unpack_fqan(fqan)):
raise ValueError('{fqan} malformed!?')
brokername, account = pair
# ledger dfs groupby-partitioned by fqme
dfs: dict[str, pl.DataFrame]
# actual ledger instance
ldgr: TransactionLedger
pl.Config.set_tbl_cols(-1)
pl.Config.set_tbl_rows(-1)
with (
open_crash_handler(),
open_ledger_dfs(
# ledger: TransactionLedger
records: dict[str, dict]
table: PpTable
records, table = load_pps_from_ledger(
brokername,
account,
) as (dfs, ldgr),
):
# look up specific frame for fqme-selected asset
if (df := dfs.get(fqme)) is None:
mktids2fqmes: dict[str, list[str]] = {}
for bs_mktid in dfs:
df: pl.DataFrame = dfs[bs_mktid]
fqmes: pl.Series[str] = df['fqme']
uniques: list[str] = fqmes.unique()
mktids2fqmes[bs_mktid] = set(uniques)
if fqme in uniques:
break
print(
f'No specific ledger for fqme={fqme} could be found in\n'
f'{pformat(mktids2fqmes)}?\n'
f'Maybe the `{brokername}` backend uses something '
'else for its `bs_mktid` then the `fqme`?\n'
'Scanning for matches in unique fqmes per frame..\n'
filter_by_ids={bs_mktid},
)
df = pl.DataFrame(
list(records.values()),
# schema=[
# ('tid', str),
# ('fqme', str),
# ('dt', str),
# ('size', pl.Float64),
# ('price', pl.Float64),
# ('cost', pl.Float64),
# ('expiry', str),
# ('bs_mktid', str),
# ],
).select([
pl.col('fqme'),
pl.col('dt').str.to_datetime(),
# pl.col('expiry').dt.datetime(),
pl.col('size'),
pl.col('price'),
])
# :pray:
assert not df.is_empty()
# muck around in pdbp REPL
breakpoint()
# TODO: we REALLY need a better console REPL for this
# kinda thing..
# - `xonsh` is an obvious option (and it looks amazin) but
# we need to figure out how to embed it better then just:
# from xonsh.main import main
# main(argv=[])
# which will not actually inject the `df` to globals?
# tractor.pause_from_sync()
# with open_trade_ledger(
# brokername,
# account,
# ) as ledger:
# for tid, rec in ledger.items():
# bs_mktid: str = rec['bs_mktid']

View File

@ -50,7 +50,7 @@ __brokers__: list[str] = [
'binance',
'ib',
'kraken',
'kucoin',
'kucoin'
# broken but used to work
# 'questrade',
@ -71,7 +71,7 @@ def get_brokermod(brokername: str) -> ModuleType:
Return the imported broker module by name.
'''
module: ModuleType = import_module('.' + brokername, 'piker.brokers')
module = import_module('.' + brokername, 'piker.brokers')
# we only allow monkeying because it's for internal keying
module.name = module.__name__.split('.')[-1]
return module
@ -106,6 +106,6 @@ async def open_cached_client(
) as (cache_hit, client):
if cache_hit:
log.runtime(f'Reusing existing {client}')
log.info(f'Reusing existing {client}')
yield client

View File

@ -179,6 +179,9 @@ def broker_init(
subpath: str = f'{modpath}.{submodname}'
enabled.append(subpath)
# TODO XXX: DO WE NEED THIS?
# enabled.append('piker.data.feed')
return (
brokermod,
start_actor_kwargs, # to `ActorNursery.start_actor()`

View File

@ -18,11 +18,10 @@
Handy cross-broker utils.
"""
from __future__ import annotations
from functools import partial
import json
import httpx
import asks
import logging
from ..log import (
@ -51,7 +50,6 @@ class SymbolNotFound(BrokerError):
"Symbol not found by broker search"
# TODO: these should probably be moved to `.tsp/.data`?
class NoData(BrokerError):
'''
Symbol data not permitted or no data
@ -61,15 +59,14 @@ class NoData(BrokerError):
def __init__(
self,
*args,
info: dict|None = None,
frame_size: int = 1000,
) -> None:
super().__init__(*args)
self.info: dict|None = info
# when raised, machinery can check if the backend
# set a "frame size" for doing datetime calcs.
# self.frame_size: int = 1000
self.frame_size: int = 1000
class DataUnavailable(BrokerError):
@ -91,18 +88,16 @@ class DataThrottle(BrokerError):
def resproc(
resp: httpx.Response,
resp: asks.response_objects.Response,
log: logging.Logger,
return_json: bool = True,
log_resp: bool = False,
) -> httpx.Response:
'''
Process response and return its json content.
) -> asks.response_objects.Response:
"""Process response and return its json content.
Raise the appropriate error on non-200 OK responses.
'''
"""
if not resp.status_code == 200:
raise BrokerError(resp.body)
try:

View File

@ -32,19 +32,12 @@ from .feed import (
)
from .broker import (
open_trade_dialog,
get_cost,
)
from .venues import (
SpotPair,
FutesPair,
)
__all__ = [
'get_client',
'get_mkt_info',
'get_cost',
'SpotPair',
'FutesPair',
'open_trade_dialog',
'open_history_client',
'open_symbol_search',

View File

@ -25,7 +25,6 @@ from __future__ import annotations
from collections import ChainMap
from contextlib import (
asynccontextmanager as acm,
AsyncExitStack,
)
from datetime import datetime
from pprint import pformat
@ -42,7 +41,8 @@ import trio
from pendulum import (
now,
)
import httpx
import asks
from fuzzywuzzy import process as fuzzy
import numpy as np
from piker import config
@ -52,13 +52,9 @@ from piker.clearing._messages import (
from piker.accounting import (
Asset,
digits_to_dec,
MktPair,
)
from piker.types import Struct
from piker.data import (
def_iohlcv_fields,
match_from_pairs,
)
from piker.data.types import Struct
from piker.data import def_iohlcv_fields
from piker.brokers import (
resproc,
SymbolNotFound,
@ -68,6 +64,7 @@ from .venues import (
PAIRTYPES,
Pair,
MarketType,
_spot_url,
_futes_url,
_testnet_futes_url,
@ -77,18 +74,16 @@ from .venues import (
log = get_logger('piker.brokers.binance')
def get_config() -> dict[str, Any]:
def get_config() -> dict:
conf: dict
path: Path
conf, path = config.load(
conf_name='brokers',
touch_if_dne=True,
)
section: dict = conf.get('binance')
conf, path = config.load()
section = conf.get('binance')
if not section:
log.warning(
f'No config section found for binance in {path}'
)
log.warning(f'No config section found for binance in {path}')
return {}
return section
@ -144,7 +139,7 @@ def binance_timestamp(
class Client:
'''
Async ReST API client using `trio` + `httpx` B)
Async ReST API client using ``trio`` + ``asks`` B)
Supports all of the spot, margin and futures endpoints depending
on method.
@ -153,17 +148,10 @@ class Client:
def __init__(
self,
venue_sessions: dict[
str, # venue key
tuple[httpx.AsyncClient, str] # session, eps path
],
conf: dict[str, Any],
# TODO: change this to `Client.[mkt_]venue: MarketType`?
mkt_mode: MarketType = 'spot',
) -> None:
self.conf = conf
# build out pair info tables for each market type
# and wrap in a chain-map view for search / query.
self._spot_pairs: dict[str, Pair] = {} # spot info table
@ -190,13 +178,44 @@ class Client:
# market symbols for use by search. See `.exch_info()`.
self._pairs: ChainMap[str, Pair] = ChainMap()
# spot EPs sesh
self._sesh = asks.Session(connections=4)
self._sesh.base_location: str = _spot_url
# spot testnet
self._test_sesh: asks.Session = asks.Session(connections=4)
self._test_sesh.base_location: str = _testnet_spot_url
# margin and extended spot endpoints session.
self._sapi_sesh = asks.Session(connections=4)
self._sapi_sesh.base_location: str = _spot_url
# futes EPs sesh
self._fapi_sesh = asks.Session(connections=4)
self._fapi_sesh.base_location: str = _futes_url
# futes testnet
self._test_fapi_sesh: asks.Session = asks.Session(connections=4)
self._test_fapi_sesh.base_location: str = _testnet_futes_url
# global client "venue selection" mode.
# set this when you want to switch venues and not have to
# specify the venue for the next request.
self.mkt_mode: MarketType = mkt_mode
# per-mkt-venue API client table
self.venue_sesh = venue_sessions
# per 8
self.venue_sesh: dict[
str, # venue key
tuple[asks.Session, str] # session, eps path
] = {
'spot': (self._sesh, '/api/v3/'),
'spot_testnet': (self._test_sesh, '/fapi/v1/'),
'margin': (self._sapi_sesh, '/sapi/v1/'),
'usdtm_futes': (self._fapi_sesh, '/fapi/v1/'),
'usdtm_futes_testnet': (self._test_fapi_sesh, '/fapi/v1/'),
# 'futes_coin': self._dapi, # TODO
}
# lookup for going from `.mkt_mode: str` to the config
# subsection `key: str`
@ -211,6 +230,40 @@ class Client:
'futes': ['usdtm_futes'],
}
# for creating API keys see,
# https://www.binance.com/en/support/faq/how-to-create-api-keys-on-binance-360002502072
self.conf: dict = get_config()
for key, subconf in self.conf.items():
if api_key := subconf.get('api_key', ''):
venue_keys: list[str] = self.confkey2venuekeys[key]
venue_key: str
sesh: asks.Session
for venue_key in venue_keys:
sesh, _ = self.venue_sesh[venue_key]
api_key_header: dict = {
# taken from official:
# https://github.com/binance/binance-futures-connector-python/blob/main/binance/api.py#L47
"Content-Type": "application/json;charset=utf-8",
# TODO: prolly should just always query and copy
# in the real latest ver?
"User-Agent": "binance-connector/6.1.6smbz6",
"X-MBX-APIKEY": api_key,
}
sesh.headers.update(api_key_header)
# if `.use_tesnet = true` in the config then
# also add headers for the testnet session which
# will be used for all order control
if subconf.get('use_testnet', False):
testnet_sesh, _ = self.venue_sesh[
venue_key + '_testnet'
]
testnet_sesh.headers.update(api_key_header)
def _mk_sig(
self,
data: dict,
@ -229,6 +282,7 @@ class Client:
'to define the creds for auth-ed endpoints!?'
)
# XXX: Info on security and authentification
# https://binance-docs.github.io/apidocs/#endpoint-security-type
if not (api_secret := subconf.get('api_secret')):
@ -268,9 +322,8 @@ class Client:
- /fapi/v3/ USD-M FUTURES, or
- /api/v3/ SPOT/MARGIN
account/market endpoint request depending on either passed in
`venue: str` or the current setting `.mkt_mode: str` setting,
default `'spot'`.
account/market endpoint request depending on either passed in `venue: str`
or the current setting `.mkt_mode: str` setting, default `'spot'`.
Docs per venue API:
@ -299,6 +352,9 @@ class Client:
venue=venue_key,
)
sesh: asks.Session
path: str
# Check if we're configured to route order requests to the
# venue equivalent's testnet.
use_testnet: bool = False
@ -323,12 +379,11 @@ class Client:
# ctl machinery B)
venue_key += '_testnet'
client: httpx.AsyncClient
path: str
client, path = self.venue_sesh[venue_key]
meth: Callable = getattr(client, method)
sesh, path = self.venue_sesh[venue_key]
meth: Callable = getattr(sesh, method)
resp = await meth(
url=path + endpoint,
path=path + endpoint,
params=params,
timeout=float('inf'),
)
@ -341,6 +396,7 @@ class Client:
) -> None:
# lookup internal mkt-specific pair table to update
pair_table: dict[str, Pair] = self._venue2pairs[venue]
asset_table: dict[str, Asset] = self._venue2assets[venue]
# make API request(s)
resp = await self._api(
@ -352,7 +408,6 @@ class Client:
venue=venue,
allow_testnet=False, # XXX: never use testnet for symbol lookups
)
mkt_pairs = resp['symbols']
if not mkt_pairs:
raise SymbolNotFound(f'No market pairs found!?:\n{resp}')
@ -370,60 +425,28 @@ class Client:
item['filters'] = filters
pair_type: Type = PAIRTYPES[venue]
try:
pair: Pair = pair_type(**item)
except Exception as e:
e.add_note(
"\nDon't panic, prolly stupid binance changed their symbology schema again..\n"
'Check out their API docs here:\n\n'
'https://binance-docs.github.io/apidocs/spot/en/#exchange-information'
)
raise
pair_table[pair.symbol.upper()] = pair
# update an additional top-level-cross-venue-table
# `._pairs: ChainMap` for search B0
pairs_view_subtable[pair.bs_fqme] = pair
# XXX WOW: TURNS OUT THIS ISN'T TRUE !?
# > (populate `Asset` table for spot mkts only since it
# > should be a superset of any other venues such as
# > futes or margin)
if venue == 'spot':
dst_sectype: str = 'crypto_currency'
elif venue in {'usdtm_futes'}:
dst_sectype: str = 'future'
if pair.contractType == 'PERPETUAL':
dst_sectype: str = 'perpetual_future'
spot_asset_table: dict[str, Asset] = self._venue2assets['spot']
ven_asset_table: dict[str, Asset] = self._venue2assets[venue]
if (
(name := pair.quoteAsset) not in spot_asset_table
):
spot_asset_table[pair.bs_src_asset] = Asset(
if (name := pair.quoteAsset) not in asset_table:
asset_table[name] = Asset(
name=name,
atype='crypto_currency',
tx_tick=digits_to_dec(pair.quoteAssetPrecision),
)
if (
(name := pair.baseAsset) not in ven_asset_table
):
if venue != 'spot':
assert dst_sectype != 'crypto_currency'
ven_asset_table[pair.bs_dst_asset] = Asset(
if (name := pair.baseAsset) not in asset_table:
asset_table[name] = Asset(
name=name,
atype=dst_sectype,
atype='crypto_currency',
tx_tick=digits_to_dec(pair.baseAssetPrecision),
)
# log.warning(
# f'Assets not YET found in spot set: `{pformat(dne)}`!?'
# )
# NOTE: make merged view of all market-type pairs but
# use market specific `Pair.bs_fqme` for keys!
# this allows searching for market pairs with different
@ -435,29 +458,16 @@ class Client:
if venue == 'spot':
return
# TODO: maybe use this assets response for non-spot venues?
# -> issue is we do the exch_info queries conc, so we can't
# guarantee order for inter-table lookups..
# if venue ep delivers an explicit set of assets copy just
# ensure they are also already listed in the spot equivs.
# assets: list[dict] = resp.get('assets', ())
# for entry in assets:
# name: str = entry['asset']
# spot_asset_table: dict[str, Asset] = self._venue2assets['spot']
# if name not in spot_asset_table:
# log.warning(
# f'COULDNT FIND ASSET {name}\n{entry}\n'
# f'ADDING AS FUTES ONLY!?'
# )
# asset_table: dict[str, Asset] = self._venue2assets[venue]
# asset_table[name] = spot_asset_table.get(name)
assets: list[dict] = resp.get('assets', ())
for entry in assets:
name: str = entry['asset']
asset_table[name] = self._venue2assets['spot'].get(name)
async def exch_info(
self,
sym: str | None = None,
venue: MarketType | None = None,
expiry: str | None = None,
) -> dict[str, Pair] | Pair:
'''
@ -473,20 +483,9 @@ class Client:
'''
pair_table: dict[str, Pair] = self._venue2pairs[
venue
or
self.mkt_mode
venue or self.mkt_mode
]
if (
expiry
and 'perp' not in expiry.lower()
):
sym: str = f'{sym}_{expiry}'
if (
sym
and (cached_pair := pair_table.get(sym))
):
if cached_pair := pair_table.get(sym):
return cached_pair
venues: list[str] = ['spot', 'usdtm_futes']
@ -494,52 +493,14 @@ class Client:
venues: list[str] = [venue]
# batch per-venue download of all exchange infos
async with trio.open_nursery() as tn:
async with trio.open_nursery() as rn:
for ven in venues:
tn.start_soon(
rn.start_soon(
self._cache_pairs,
ven,
)
if sym:
return pair_table[sym]
else:
return self._pairs
async def get_assets(
self,
venue: str | None = None,
) -> dict[str, Asset]:
if (
venue
and venue != 'spot'
):
venues = [venue]
else:
venues = ['usdtm_futes']
ass_table: dict[str, Asset] = self._venue2assets['spot']
# merge in futes contracts with a sectype suffix
for venue in venues:
ass_table |= self._venue2assets[venue]
return ass_table
async def get_mkt_pairs(self) -> dict[str, Pair]:
'''
Flatten the multi-venue (chain) map of market pairs
to a fqme indexed table for data layer caching.
'''
flat: dict[str, Pair] = {}
for venmap in self._pairs.maps:
for bs_fqme, pair in venmap.items():
flat[pair.bs_fqme] = pair
return flat
return pair_table[sym] if sym else self._pairs
# TODO: unused except by `brokers.core.search_symbols()`?
async def search_symbols(
@ -549,32 +510,20 @@ class Client:
) -> dict[str, Any]:
fq_pairs: dict[str, Pair] = await self.exch_info()
fq_pairs: dict = await self.exch_info()
# TODO: cache this list like we were in
# `open_symbol_search()`?
# keys: list[str] = list(fq_pairs)
return match_from_pairs(
pairs=fq_pairs,
query=pattern.upper(),
matches = fuzzy.extractBests(
pattern,
fq_pairs,
score_cutoff=50,
)
def pair2venuekey(
self,
pair: Pair,
) -> str:
return {
'USDTM': 'usdtm_futes',
'SPOT': 'spot',
# 'COINM': 'coin_futes',
# ^-TODO-^ bc someone might want it..?
}[pair.venue]
# repack in dict form
return {item[0]['symbol']: item[0]
for item in matches}
async def bars(
self,
mkt: MktPair,
symbol: str,
start_dt: datetime | None = None,
end_dt: datetime | None = None,
@ -604,20 +553,16 @@ class Client:
start_time = binance_timestamp(start_dt)
end_time = binance_timestamp(end_dt)
bs_pair: Pair = self._pairs[mkt.bs_fqme.upper()]
# https://binance-docs.github.io/apidocs/spot/en/#kline-candlestick-data
bars = await self._api(
'klines',
params={
# NOTE: always query using their native symbology!
'symbol': mkt.bs_mktid.upper(),
'symbol': symbol.upper(),
'interval': '1m',
'startTime': start_time,
'endTime': end_time,
'limit': limit
},
venue=self.pair2venuekey(bs_pair),
allow_testnet=False,
)
new_bars: list[tuple] = []
@ -934,148 +879,17 @@ class Client:
await self.close_listen_key(key)
_venue_urls: dict[str, str] = {
'spot': (
_spot_url,
'/api/v3/',
),
'spot_testnet': (
_testnet_spot_url,
'/fapi/v1/'
),
# margin and extended spot endpoints session.
# TODO: did this ever get implemented fully?
# 'margin': (
# _spot_url,
# '/sapi/v1/'
# ),
'usdtm_futes': (
_futes_url,
'/fapi/v1/',
),
'usdtm_futes_testnet': (
_testnet_futes_url,
'/fapi/v1/',
),
# TODO: for anyone who actually needs it ;P
# 'coin_futes': ()
}
def init_api_keys(
client: Client,
conf: dict[str, Any],
) -> None:
'''
Set up per-venue API keys each http client according to the user's
`brokers.conf`.
For ex, to use spot-testnet and live usdt futures APIs:
```toml
[binance]
# spot test net
spot.use_testnet = true
spot.api_key = '<spot_api_key_from_binance_account>'
spot.api_secret = '<spot_api_key_password>'
# futes live
futes.use_testnet = false
accounts.usdtm = 'futes'
futes.api_key = '<futes_api_key_from_binance>'
futes.api_secret = '<futes_api_key_password>''
# if uncommented will use the built-in paper engine and not
# connect to `binance` API servers for order ctl.
# accounts.paper = 'paper'
```
'''
for key, subconf in conf.items():
if api_key := subconf.get('api_key', ''):
venue_keys: list[str] = client.confkey2venuekeys[key]
venue_key: str
client: httpx.AsyncClient
for venue_key in venue_keys:
client, _ = client.venue_sesh[venue_key]
api_key_header: dict = {
# taken from official:
# https://github.com/binance/binance-futures-connector-python/blob/main/binance/api.py#L47
"Content-Type": "application/json;charset=utf-8",
# TODO: prolly should just always query and copy
# in the real latest ver?
"User-Agent": "binance-connector/6.1.6smbz6",
"X-MBX-APIKEY": api_key,
}
client.headers.update(api_key_header)
# if `.use_tesnet = true` in the config then
# also add headers for the testnet session which
# will be used for all order control
if subconf.get('use_testnet', False):
testnet_sesh, _ = client.venue_sesh[
venue_key + '_testnet'
]
testnet_sesh.headers.update(api_key_header)
@acm
async def get_client(
mkt_mode: MarketType = 'spot',
) -> Client:
'''
Construct an single `piker` client which composes multiple underlying venue
specific API clients both for live and test networks.
async def get_client() -> Client:
'''
venue_sessions: dict[
str, # venue key
tuple[httpx.AsyncClient, str] # session, eps path
] = {}
async with AsyncExitStack() as client_stack:
for name, (base_url, path) in _venue_urls.items():
api: httpx.AsyncClient = await client_stack.enter_async_context(
httpx.AsyncClient(
base_url=base_url,
# headers={},
# TODO: is there a way to numerate this?
# https://www.python-httpx.org/advanced/clients/#why-use-a-client
# connections=4
)
)
venue_sessions[name] = (
api,
path,
)
conf: dict[str, Any] = get_config()
# for creating API keys see,
# https://www.binance.com/en/support/faq/how-to-create-api-keys-on-binance-360002502072
client = Client(
venue_sessions=venue_sessions,
conf=conf,
mkt_mode=mkt_mode,
)
init_api_keys(
client=client,
conf=conf,
)
fq_pairs: dict[str, Pair] = await client.exch_info()
assert fq_pairs
client = Client()
await client.exch_info()
log.info(
f'Loaded multi-venue `Client` in mkt_mode={client.mkt_mode!r}\n\n'
f'Symbology Summary:\n'
f'------ - ------\n'
f'{client} in {client.mkt_mode} mode: caching exchange infos..\n'
'Cached multi-market pairs:\n'
f'spot: {len(client._spot_pairs)}\n'
f'usdtm_futes: {len(client._ufutes_pairs)}\n'
'------ - ------\n'
f'total: {len(client._pairs)}\n'
f'Total: {len(client._pairs)}\n'
)
yield client

View File

@ -36,6 +36,7 @@ import trio
from piker.accounting import (
Asset,
# MktPair,
)
from piker.brokers._util import (
get_logger,
@ -48,9 +49,7 @@ from piker.brokers import (
open_cached_client,
BrokerError,
)
from piker.clearing import (
OrderDialogs,
)
from piker.clearing import OrderDialogs
from piker.clearing._messages import (
BrokerdOrder,
BrokerdOrderAck,
@ -72,33 +71,6 @@ from .api import Client
log = get_logger('piker.brokers.binance')
# Fee schedule template, mostly for paper engine fees modelling.
# https://www.binance.com/en/support/faq/what-are-market-makers-and-takers-360007720071
def get_cost(
price: float,
size: float,
is_taker: bool = False,
) -> float:
# https://www.binance.com/en/fee/trading
cb: float = price * size
match is_taker:
case True:
return cb * 0.001000
case False if cb < 1e6:
return cb * 0.001000
case False if 1e6 >= cb < 5e6:
return cb * 0.000900
# NOTE: there's more but are you really going
# to have a cb bigger then this per trade?
case False if cb >= 5e6:
return cb * 0.000800
async def handle_order_requests(
ems_order_stream: tractor.MsgStream,
client: Client,
@ -260,24 +232,16 @@ async def open_trade_dialog(
account_name: str = 'usdtm'
use_testnet: bool = False
# TODO: if/when we add .accounting support we need to
# do a open_symcache() call.. though maybe we can hide
# this in a new async version of open_account()?
async with open_cached_client('binance') as client:
subconf: dict|None = client.conf.get(venue_name)
subconf: dict = client.conf[venue_name]
use_testnet = subconf.get('use_testnet', False)
# XXX: if no futes.api_key or spot.api_key has been set we
# always fall back to the paper engine!
if (
not subconf
or
not subconf.get('api_key')
):
if not subconf.get('api_key'):
await ctx.started('paper')
return
use_testnet: bool = subconf.get('use_testnet', False)
async with (
open_cached_client('binance') as client,
):
@ -357,7 +321,7 @@ async def open_trade_dialog(
if balance > 0:
balances[spot_asset] = (balance, last_update_t)
# await tractor.pause()
# await tractor.breakpoint()
# @position response:
# {'positions': [{'entryPrice': '0.0',
@ -436,7 +400,7 @@ async def open_trade_dialog(
# and comparison with binance's own position calcs.
# - load pps and accounts using accounting apis, write
# the ledger and account files
# - table: Account
# - table: PpTable
# - ledger: TransactionLedger
async with (

View File

@ -24,11 +24,8 @@ from contextlib import (
aclosing,
)
from datetime import datetime
from functools import (
partial,
)
from functools import partial
import itertools
from pprint import pformat
from typing import (
Any,
AsyncGenerator,
@ -42,12 +39,12 @@ from trio_typing import TaskStatus
from pendulum import (
from_timestamp,
)
from fuzzywuzzy import process as fuzzy
import numpy as np
import tractor
from piker.brokers import (
open_cached_client,
NoData,
)
from piker._cacheables import (
async_lifo_cache,
@ -57,8 +54,9 @@ from piker.accounting import (
DerivTypes,
MktPair,
unpack_fqme,
digits_to_dec,
)
from piker.types import Struct
from piker.data.types import Struct
from piker.data.validate import FeedInit
from piker.data._web_bs import (
open_autorecon_ws,
@ -110,7 +108,6 @@ class AggTrade(Struct, frozen=True):
async def stream_messages(
ws: NoBsWs,
) -> AsyncGenerator[NoBsWs, dict]:
# TODO: match syntax here!
@ -221,8 +218,6 @@ def make_sub(pairs: list[str], sub_name: str, uid: int) -> dict[str, str]:
}
# TODO, why aren't frame resp `log.info()`s showing in upstream
# code?!
@acm
async def open_history_client(
mkt: MktPair,
@ -255,30 +250,24 @@ async def open_history_client(
else:
client.mkt_mode = 'spot'
array: np.ndarray = await client.bars(
mkt=mkt,
# NOTE: always query using their native symbology!
mktid: str = mkt.bs_mktid
array = await client.bars(
mktid,
start_dt=start_dt,
end_dt=end_dt,
)
if array.size == 0:
raise NoData(
f'No frame for {start_dt} -> {end_dt}\n'
)
times = array['time']
if not times.any():
raise ValueError(
'Bad frame with null-times?\n\n'
f'{times}'
)
if end_dt is None:
inow: int = round(time.time())
if (
end_dt is None
):
inow = round(time.time())
if (inow - times[-1]) > 60:
await tractor.pause()
await tractor.breakpoint()
start_dt = from_timestamp(times[0])
end_dt = from_timestamp(times[-1])
return array, start_dt, end_dt
yield get_ohlc, {'erlangs': 3, 'rate': 3}
@ -288,113 +277,69 @@ async def open_history_client(
async def get_mkt_info(
fqme: str,
) -> tuple[MktPair, Pair] | None:
) -> tuple[MktPair, Pair]:
# uppercase since kraken bs_mktid is always upper
if 'binance' not in fqme.lower():
if 'binance' not in fqme:
fqme += '.binance'
mkt_mode: str = ''
bs_fqme, _, broker = fqme.rpartition('.')
broker, mkt_ep, venue, expiry = unpack_fqme(fqme)
# NOTE: we always upper case all tokens to be consistent with
# binance's symbology style for pairs, like `BTCUSDT`, but in
# theory we could also just keep things lower case; as long as
# we're consistent and the symcache matches whatever this func
# returns, always!
expiry: str = expiry.upper()
venue: str = venue.upper()
venue_lower: str = venue.lower()
# XXX TODO: we should change the usdtm_futes name to just
# usdm_futes (dropping the tether part) since it turns out that
# there are indeed USD-tokens OTHER THEN tether being used as
# the margin assets.. it's going to require a wholesale
# (variable/key) rename as well as file name adjustments to any
# existing tsdb set..
if 'usd' in venue_lower:
mkt_mode: str = 'usdtm_futes'
# NO IDEA what these contracts (some kinda DEX-ish futes?) are
# but we're masking them for now..
elif (
'defi' in venue_lower
# TODO: handle coinm futes which have a margin asset that
# is some crypto token!
# https://binance-docs.github.io/apidocs/delivery/en/#exchange-information
or 'btc' in venue_lower
):
return None
else:
# NOTE: see the `FutesPair.bs_fqme: str` implementation
# to understand the reverse market info lookup below.
mkt_mode = venue_lower or 'spot'
mkt_mode = venue = venue.lower() or 'spot'
_atype: str = ''
if (
venue
and 'spot' not in venue_lower
and 'spot' not in venue.lower()
# XXX: catch all in case user doesn't know which
# venue they want (usdtm vs. coinm) and we can choose
# a default (via config?) once we support coin-m APIs.
or 'perp' in venue_lower
or 'perp' in bs_fqme.lower()
):
if not mkt_mode:
mkt_mode: str = f'{venue_lower}_futes'
mkt_mode: str = f'{venue.lower()}_futes'
if 'perp' in expiry:
_atype = 'perpetual_future'
else:
_atype = 'future'
async with open_cached_client(
'binance',
) as client:
assets: dict[str, Asset] = await client.get_assets()
pair_str: str = mkt_ep.upper()
# switch venue-mode depending on input pattern parsing
# since we want to use a particular endpoint (set) for
# pair info lookup!
# switch mode depending on input pattern parsing
client.mkt_mode = mkt_mode
pair: Pair = await client.exch_info(
pair_str,
venue=mkt_mode, # explicit
expiry=expiry,
)
pair_str: str = mkt_ep.upper()
pair: Pair = await client.exch_info(pair_str)
if 'futes' in mkt_mode:
assert isinstance(pair, FutesPair)
dst: Asset | None = assets.get(pair.bs_dst_asset)
if (
not dst
# TODO: a known asset DNE list?
# and pair.baseAsset == 'DEFI'
):
log.warning(
f'UNKNOWN {venue} asset {pair.baseAsset} from,\n'
f'{pformat(pair.to_dict())}'
)
# XXX UNKNOWN missing "asset", though no idea why?
# maybe it's only avail in the margin venue(s): /dapi/ ?
return None
mkt = MktPair(
dst=dst,
src=assets[pair.bs_src_asset],
dst=Asset(
name=pair.baseAsset,
atype='crypto',
tx_tick=digits_to_dec(pair.baseAssetPrecision),
),
src=Asset(
name=pair.quoteAsset,
atype='crypto',
tx_tick=digits_to_dec(pair.quoteAssetPrecision),
),
price_tick=pair.price_tick,
size_tick=pair.size_tick,
bs_mktid=pair.symbol,
expiry=expiry,
venue=venue,
broker='binance',
# NOTE: sectype is always taken from dst, see
# `MktPair.type_key` and `Client._cache_pairs()`
# _atype=sectype,
_atype=_atype,
)
return mkt, pair
both = mkt, pair
return both
@acm
@ -465,8 +410,6 @@ async def stream_quotes(
):
init_msgs: list[FeedInit] = []
for sym in symbols:
mkt: MktPair
pair: Pair
mkt, pair = await get_mkt_info(sym)
# build out init msgs according to latest spec
@ -515,6 +458,7 @@ async def stream_quotes(
# start streaming
async for typ, quote in msg_gen:
# period = time.time() - last
# hz = 1/period if period else float('inf')
# if hz > 60:
@ -528,11 +472,10 @@ async def open_symbol_search(
ctx: tractor.Context,
) -> Client:
# NOTE: symbology tables are loaded as part of client
# startup in ``.api.get_client()`` and in this case
# are stored as `Client._pairs`.
async with open_cached_client('binance') as client:
# load all symbols locally for fast search
fqpairs_cache = await client.exch_info()
# TODO: maybe we should deliver the cache
# so that client's can always do a local-lookup-first
# style try and then update async as (new) match results
@ -543,15 +486,14 @@ async def open_symbol_search(
pattern: str
async for pattern in stream:
# NOTE: pattern fuzzy-matching is done within
# the methd impl.
pairs: dict[str, Pair] = await client.search_symbols(
matches = fuzzy.extractBests(
pattern,
fqpairs_cache,
score_cutoff=50,
)
# repack in fqme-keyed table
byfqme: dict[str, Pair] = {}
for pair in pairs.values():
byfqme[pair.bs_fqme] = pair
await stream.send(byfqme)
# repack in dict form
await stream.send({
item[0].bs_fqme: item[0]
for item in matches
})

View File

@ -1,5 +1,8 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# Copyright (C)
# Guillermo Rodriguez (aka ze jefe)
# Tyler Goodlet
# (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
@ -26,7 +29,7 @@ from decimal import Decimal
from msgspec import field
from piker.types import Struct
from piker.data.types import Struct
# API endpoint paths by venue / sub-API
@ -62,7 +65,7 @@ MarketType = Literal[
'spot',
# 'margin',
'usdtm_futes',
# 'coinm_futes',
# 'coin_futes',
]
@ -84,7 +87,6 @@ def get_api_eps(venue: MarketType) -> tuple[str, str]:
class Pair(Struct, frozen=True, kw_only=True):
symbol: str
status: str
orderTypes: list[str]
@ -118,10 +120,6 @@ class Pair(Struct, frozen=True, kw_only=True):
def bs_fqme(self) -> str:
return self.symbol
@property
def bs_mktid(self) -> str:
return f'{self.symbol}.{self.venue}'
class SpotPair(Pair, frozen=True):
@ -137,31 +135,15 @@ class SpotPair(Pair, frozen=True):
quoteOrderQtyMarketAllowed: bool
isSpotTradingAllowed: bool
isMarginTradingAllowed: bool
otoAllowed: bool
defaultSelfTradePreventionMode: str
allowedSelfTradePreventionModes: list[str]
permissions: list[str]
permissionSets: list[list[str]]
# NOTE: see `.data._symcache.SymbologyCache.load()` for why
ns_path: str = 'piker.brokers.binance:SpotPair'
@property
def venue(self) -> str:
return 'SPOT'
@property
def bs_fqme(self) -> str:
return f'{self.symbol}.SPOT'
@property
def bs_src_asset(self) -> str:
return f'{self.quoteAsset}'
@property
def bs_dst_asset(self) -> str:
return f'{self.baseAsset}'
class FutesPair(Pair):
@ -181,14 +163,12 @@ class FutesPair(Pair):
quoteAsset: str # 'USDT',
quotePrecision: int # 8,
requiredMarginPercent: float # '5.0000',
settlePlan: int # 0,
timeInForce: list[str] # ['GTC', 'IOC', 'FOK', 'GTX'],
triggerProtect: float # '0.0500',
underlyingSubType: list[str] # ['PoW'],
underlyingType: str # 'COIN'
# NOTE: see `.data._symcache.SymbologyCache.load()` for why
ns_path: str = 'piker.brokers.binance:FutesPair'
# NOTE: for compat with spot pairs and `MktPair.src: Asset`
# processing..
@property
@ -196,101 +176,32 @@ class FutesPair(Pair):
return self.quotePrecision
@property
def expiry(self) -> str:
symbol: str = self.symbol
contype: str = self.contractType
match contype:
case (
'CURRENT_QUARTER'
| 'CURRENT_QUARTER DELIVERING'
| 'NEXT_QUARTER' # su madre binance..
):
pair, _, expiry = symbol.partition('_')
assert pair == self.pair # sanity
return f'{expiry}'
case 'PERPETUAL':
return 'PERP'
case '':
subtype: list[str] = self.underlyingSubType
if not subtype:
if self.status == 'PENDING_TRADING':
return 'PENDING'
match subtype:
case ['DEFI']:
return 'PERP'
# wow, just wow you binance guys suck..
if self.status == 'PENDING_TRADING':
return 'PENDING'
# XXX: yeah no clue then..
raise ValueError(
f'Bad .expiry token match: {contype} for {symbol}'
)
@property
def venue(self) -> str:
def bs_fqme(self) -> str:
symbol: str = self.symbol
ctype: str = self.contractType
margin: str = self.marginAsset
match ctype:
case 'PERPETUAL':
return f'{margin}M'
return f'{symbol}.{margin}M.PERP'
case (
'CURRENT_QUARTER'
| 'CURRENT_QUARTER DELIVERING'
| 'NEXT_QUARTER' # su madre binance..
):
_, _, expiry = symbol.partition('_')
return f'{margin}M'
case 'CURRENT_QUARTER':
pair, _, expiry = symbol.partition('_')
return f'{pair}.{margin}M.{expiry}'
case '':
subtype: list[str] = self.underlyingSubType
if not subtype:
if self.status == 'PENDING_TRADING':
return f'{margin}M'
return f'{symbol}.{margin}M.PENDING'
match subtype:
case (
['DEFI']
| ['USDC']
):
return f'{subtype[0]}'
match subtype[0]:
case 'DEFI':
return f'{symbol}.{subtype}.PERP'
# XXX: yeah no clue then..
raise ValueError(
f'Bad .venue token match: {ctype}'
)
return f'{symbol}.WTF.PWNED.BBQ'
@property
def bs_fqme(self) -> str:
symbol: str = self.symbol
ctype: str = self.contractType
venue: str = self.venue
pair: str = self.pair
match ctype:
case (
'CURRENT_QUARTER'
| 'NEXT_QUARTER' # su madre binance..
):
pair, _, expiry = symbol.partition('_')
assert pair == self.pair
return f'{pair}.{venue}.{self.expiry}'
@property
def bs_src_asset(self) -> str:
return f'{self.quoteAsset}'
@property
def bs_dst_asset(self) -> str:
return f'{self.baseAsset}.{self.venue}'
PAIRTYPES: dict[MarketType, Pair] = {

View File

@ -454,18 +454,8 @@ def mkt_info(
@cli.command()
@click.argument('pattern', required=True)
# TODO: move this to top level click/typer context for all subs
@click.option(
'--pdb',
is_flag=True,
help='Enable tractor debug mode',
)
@click.pass_obj
def search(
config: dict,
pattern: str,
pdb: bool,
):
def search(config, pattern):
'''
Search for symbols from broker backend(s).
@ -478,12 +468,9 @@ def search(
async with maybe_open_pikerd(
loglevel=config['loglevel'],
debug_mode=pdb,
):
return await func()
from piker.toolz import open_crash_handler
with open_crash_handler():
quotes = trio.run(
main,
partial(
@ -506,11 +493,9 @@ def search(
@click.option('--delete', '-d', flag_value=True, help='Delete section')
@click.pass_obj
def brokercfg(config, section, value, delete):
'''
If invoked with no arguments, open an editor to edit broker
configs file or get / update an individual section.
'''
"""If invoked with no arguments, open an editor to edit broker configs file
or get / update an individual section.
"""
from .. import config
if section:

View File

@ -95,15 +95,15 @@ async def option_chain(
return await client.option_chains(contracts)
# async def contracts(
# brokermod: ModuleType,
# symbol: str,
# ) -> Dict[str, Dict[str, Dict[str, Any]]]:
# """Return option contracts (all expiries) for ``symbol``.
# """
# async with brokermod.get_client() as client:
# # return await client.get_all_contracts([symbol])
async def contracts(
brokermod: ModuleType,
symbol: str,
) -> Dict[str, Dict[str, Dict[str, Any]]]:
"""Return option contracts (all expiries) for ``symbol``.
"""
async with brokermod.get_client() as client:
# return await client.get_all_contracts([symbol])
return await client.get_all_contracts([symbol])
async def bars(
@ -117,6 +117,21 @@ async def bars(
return await client.bars(symbol, **kwargs)
async def mkt_info(
brokermod: ModuleType,
fqme: str,
**kwargs,
) -> MktPair:
'''
Return MktPair info from broker including src and dst assets.
'''
return await brokermod.get_mkt_info(
fqme.replace(brokermod.name, '')
)
async def search_w_brokerd(name: str, pattern: str) -> dict:
async with open_cached_client(name) as client:
@ -145,11 +160,7 @@ async def symbol_search(
async with maybe_spawn_brokerd(
mod.name,
infect_asyncio=getattr(
mod,
'_infect_asyncio',
False,
),
infect_asyncio=getattr(mod, '_infect_asyncio', False),
) as portal:
results.append((
@ -167,20 +178,3 @@ async def symbol_search(
n.start_soon(search_backend, mod.name)
return results
async def mkt_info(
brokermod: ModuleType,
fqme: str,
**kwargs,
) -> MktPair:
'''
Return MktPair info from broker including src and dst assets.
'''
async with open_cached_client(brokermod.name) as client:
assert client
return await brokermod.get_mkt_info(
fqme.replace(brokermod.name, '')
)

View File

@ -34,7 +34,7 @@ from typing import (
import pendulum
import trio
from trio_typing import TaskStatus
from rapidfuzz import process as fuzzy
from fuzzywuzzy import process as fuzzy
import numpy as np
from tractor.trionics import (
broadcast_receiver,
@ -52,11 +52,8 @@ from cryptofeed.defines import (
)
from cryptofeed.symbols import Symbol
from piker.data import (
def_iohlcv_fields,
match_from_pairs,
Struct,
)
from piker.data.types import Struct
from piker.data import def_iohlcv_fields
from piker.data._web_bs import (
open_jsonrpc_session
)
@ -82,7 +79,7 @@ _testnet_ws_url = 'wss://test.deribit.com/ws/api/v2'
class JSONRPCResult(Struct):
jsonrpc: str = '2.0'
id: int
result: Optional[list[dict]] = None
result: Optional[dict] = None
error: Optional[dict] = None
usIn: int
usOut: int
@ -292,29 +289,24 @@ class Client:
currency: str = 'btc', # BTC, ETH, SOL, USDC
kind: str = 'option',
expired: bool = False
) -> dict[str, Any]:
"""Get symbol info for the exchange.
) -> dict[str, dict]:
'''
Get symbol infos.
'''
"""
if self._pairs:
return self._pairs
# will retrieve all symbols by default
params: dict[str, str] = {
params = {
'currency': currency.upper(),
'kind': kind,
'expired': str(expired).lower()
}
resp: JSONRPCResult = await self.json_rpc(
'public/get_instruments',
params,
)
# convert to symbol-keyed table
results: list[dict] | None = resp.result
instruments: dict[str, dict] = {
resp = await self.json_rpc('public/get_instruments', params)
results = resp.result
instruments = {
item['instrument_name'].lower(): item
for item in results
}
@ -327,7 +319,6 @@ class Client:
async def cache_symbols(
self,
) -> dict:
if not self._pairs:
self._pairs = await self.symbol_info()
@ -338,23 +329,17 @@ class Client:
pattern: str,
limit: int = 30,
) -> dict[str, Any]:
'''
Fuzzy search symbology set for pairs matching `pattern`.
data = await self.symbol_info()
'''
pairs: dict[str, Any] = await self.symbol_info()
matches: dict[str, Pair] = match_from_pairs(
pairs=pairs,
query=pattern.upper(),
matches = fuzzy.extractBests(
pattern,
data,
score_cutoff=35,
limit=limit
)
# repack in name-keyed table
return {
pair['instrument_name'].lower(): pair
for pair in matches.values()
}
# repack in dict form
return {item[0]['instrument_name'].lower(): item[0]
for item in matches}
async def bars(
self,

View File

@ -26,7 +26,7 @@ import time
import trio
from trio_typing import TaskStatus
import pendulum
from rapidfuzz import process as fuzzy
from fuzzywuzzy import process as fuzzy
import numpy as np
import tractor

View File

@ -30,33 +30,23 @@ from .api import (
)
from .feed import (
open_history_client,
open_symbol_search,
stream_quotes,
)
from .broker import (
open_trade_dialog,
)
from .ledger import (
norm_trade,
norm_trade_records,
tx_sort,
)
from .symbols import (
get_mkt_info,
open_symbol_search,
_search_conf,
)
__all__ = [
'get_client',
'get_mkt_info',
'norm_trade',
'norm_trade_records',
'open_trade_dialog',
'open_history_client',
'open_symbol_search',
'stream_quotes',
'_search_conf',
'tx_sort',
]
_brokerd_mods: list[str] = [
@ -66,7 +56,6 @@ _brokerd_mods: list[str] = [
_datad_mods: list[str] = [
'feed',
'symbols',
]
@ -86,8 +75,3 @@ _spawn_kwargs = {
# know if ``brokerd`` should be spawned with
# ``tractor``'s aio mode.
_infect_asyncio: bool = True
# XXX NOTE: for now we disable symcache with this backend since
# there is no clearly simple nor practical way to download "all
# symbology info" for all supported venues..
_no_symcache: bool = True

View File

@ -159,11 +159,7 @@ def load_flex_trades(
for acctid in trades_by_account:
trades_by_id = trades_by_account[acctid]
with open_trade_ledger(
'ib',
acctid,
allow_from_sync_code=True,
) as ledger_dict:
with open_trade_ledger('ib', acctid) as ledger_dict:
tid_delta = set(trades_by_id) - set(ledger_dict)
log.info(
'New trades detected\n'

View File

@ -88,25 +88,16 @@ async def data_reset_hack(
api_port: str = str(ib_client.client.port)
vnc_host: str
vnc_port: int
vnc_sockaddr: tuple[str] | None = client.conf.get('vnc_addrs')
no_setup_msg:str = (
f'No data reset hack test setup for {vnc_sockaddr}!\n'
'See config setup tips @\n'
'https://github.com/pikers/piker/tree/master/piker/brokers/ib'
)
if not vnc_sockaddr:
log.warning(
no_setup_msg
+
'REQUIRES A `vnc_addrs: array` ENTRY'
)
vnc_host, vnc_port = vnc_sockaddr.get(
vnc_host, vnc_port = client.conf['vnc_addrs'].get(
api_port,
('localhost', 3003)
)
no_setup_msg:str = (
f'No data reset hack test setup for {vnc_host}!\n'
'See setup @\n'
'https://github.com/pikers/piker/tree/master/piker/brokers/ib'
)
global _reset_tech
match _reset_tech:

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@ -21,40 +21,33 @@ from __future__ import annotations
import asyncio
from contextlib import (
asynccontextmanager as acm,
nullcontext,
)
from decimal import Decimal
from dataclasses import asdict
from datetime import datetime
from functools import partial
from pprint import pformat
from math import isnan
import time
from typing import (
Any,
Callable,
TYPE_CHECKING,
Awaitable,
)
from async_generator import aclosing
from fuzzywuzzy import process as fuzzy
import ib_insync as ibis
import numpy as np
from pendulum import (
now,
from_timestamp,
# DateTime,
Duration,
duration as mk_duration,
)
import pendulum
import tractor
import trio
from trio_typing import TaskStatus
from piker.accounting import (
MktPair,
)
from piker.data.validate import FeedInit
from piker.brokers._util import (
from .._util import (
NoData,
DataUnavailable,
SymbolNotFound,
)
from .api import (
# _adhoc_futes_set,
@ -70,10 +63,14 @@ from .api import (
RequestError,
)
from ._util import data_reset_hack
from .symbols import get_mkt_info
if TYPE_CHECKING:
from trio._core._run import Task
from piker._cacheables import (
async_lifo_cache,
)
from piker.accounting import (
Asset,
MktPair,
)
from piker.data.validate import FeedInit
# XXX NOTE: See available types table docs:
@ -143,21 +140,32 @@ async def open_history_client(
# memory.
# IB's internal symbology does not expect the "source asset" in
# the "symbol name", what we call the "market pair name". This is
# the "symbol name", what we call the "market name". This is
# common in most legacy market brokers since it's presumed that
# given a certain stock exchange, listed assets are traded
# "from" a particular source fiat, normally something like USD
# on the given venue-provider, eg. nasdaq, nyse, etc.
# "from" a particular source fiat, normally something like USD.
if (
mkt.src
and mkt.src.atype == 'fiat'
):
fqme_kwargs: dict[str, Any] = {}
if mkt.dst.atype != 'fiat':
if mkt.dst.atype == 'forex':
# XXX: for now we do need the src token kept in since
fqme_kwargs = {
'without_src': True, # default is True
'without_src': False, # default is True
'delim_char': '', # bc they would normally use a frickin `.` smh
}
fqme: str = mkt.get_bs_fqme(**(fqme_kwargs))
else:
fqme = mkt.bs_fqme
async with open_data_client() as proxy:
max_timeout: float = 2.
mean: float = 0
count: int = 0
@ -165,13 +173,12 @@ async def open_history_client(
head_dt: None | datetime = None
if (
# fx cons seem to not provide this endpoint?
# TODO: guard against all contract types which don't
# support it?
'idealpro' not in fqme
):
head_dt: datetime | None = await proxy.maybe_get_head_time(
fqme=fqme
)
try:
head_dt = await proxy.get_head_time(fqme=fqme)
except RequestError:
head_dt = None
async def get_hist(
timeframe: float,
@ -179,15 +186,8 @@ async def open_history_client(
start_dt: datetime | None = None,
) -> tuple[np.ndarray, str]:
nonlocal max_timeout, mean, count
if (
start_dt
and start_dt.timestamp() == 0
):
await tractor.pause()
query_start = time.time()
out, timedout = await get_bars(
proxy,
@ -208,48 +208,24 @@ async def open_history_client(
f'mean: {mean}'
)
if (
out is None
):
# could be trying to retreive bars over weekend
if out is None:
log.error(f"Can't grab bars starting at {end_dt}!?!?")
raise NoData(
f'{end_dt}',
# frame_size=2000,
)
if (
end_dt
and head_dt
and end_dt <= head_dt
):
raise DataUnavailable(
f'First timestamp is {head_dt}\n'
f'But {end_dt} was requested..'
)
raise DataUnavailable(f'First timestamp is {head_dt}')
else:
raise NoData(
info={
'fqme': fqme,
'head_dt': head_dt,
'start_dt': start_dt,
'end_dt': end_dt,
'timedout': timedout,
},
)
# also see return type for `get_bars()`
bars: ibis.objects.BarDataList
bars_array: np.ndarray
first_dt: datetime
last_dt: datetime
(
bars,
bars_array,
first_dt,
last_dt,
) = out
# TODO: audit the sampling period here as well?
# timestep should always be at least as large as the
# period step.
# tdiff: np.ndarray = np.diff(bars_array['time'])
# if (tdiff < timeframe).any():
# await tractor.pause()
bars, bars_array, first_dt, last_dt = out
# volume cleaning since there's -ve entries,
# wood luv to know what crookery that is..
@ -263,18 +239,7 @@ async def open_history_client(
# quite sure why.. needs some tinkering and probably
# a lookthrough of the ``ib_insync`` machinery, for eg. maybe
# we have to do the batch queries on the `asyncio` side?
yield (
get_hist,
{
'erlangs': 1, # max conc reqs
'rate': 3, # max req rate
'frame_types': { # expected frame sizes
1: mk_duration(seconds=2e3),
60: mk_duration(days=2),
}
},
)
yield get_hist, {'erlangs': 1, 'rate': 3}
_pacing: str = (
@ -360,7 +325,7 @@ async def wait_on_data_reset(
return False
_data_resetter_task: Task | None = None
_data_resetter_task: trio.Task | None = None
_failed_resets: int = 0
@ -386,15 +351,7 @@ async def get_bars(
task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
) -> tuple[
tuple[ # result tuple
ibis.objects.BarDataList,
np.ndarray,
datetime,
datetime,
] | None,
bool, # timed out hint
]:
) -> (dict, np.ndarray):
'''
Retrieve historical data from a ``trio``-side task using
a ``MethoProxy``.
@ -419,11 +376,7 @@ async def get_bars(
while _failed_resets < max_failed_resets:
try:
(
bars,
bars_array,
dt_duration,
) = await proxy.bars(
out = await proxy.bars(
fqme=fqme,
end_dt=end_dt,
sample_period_s=timeframe,
@ -434,58 +387,44 @@ async def get_bars(
# current impl) to detect a cancel case.
# timeout=timeout,
)
# usually either a request during a venue closure
# or into a large (weekend) closure gap.
if not bars:
# no data returned?
log.warning(
'History frame is blank?\n'
f'start_dt: {start_dt}\n'
f'end_dt: {end_dt}\n'
f'duration: {dt_duration}\n'
)
# NOTE: REQUIRED to pass back value..
result = None
return None
if out is None:
raise NoData(f'{end_dt}')
bars, bars_array, dt_duration = out
# not enough bars signal, likely due to venue
# operational gaps.
if end_dt:
dur_s: float = len(bars) * timeframe
bars_dur = Duration(seconds=dur_s)
dt_dur_s: float = dt_duration.in_seconds()
if dur_s < dt_dur_s:
log.warning(
'History frame is shorter then expected?\n'
f'start_dt: {start_dt}\n'
f'end_dt: {end_dt}\n'
f'duration: {dt_dur_s}\n'
f'frame duration seconds: {dur_s}\n'
f'dur diff: {dt_duration - bars_dur}\n'
too_little: bool = False
if (
end_dt
and (
not bars
or (too_little :=
start_dt
and (len(bars) * timeframe)
< dt_duration.in_seconds()
)
# NOTE: we used to try to get a minimal
# set of bars by recursing but this ran
# into possible infinite query loops
# when logic in the `Client.bars()` dt
# diffing went bad. So instead for now
# we just return the
# shorter-then-expected history with
# a warning.
# TODO: in the future it prolly makes
# the most send to do venue operating
# hours lookup and
# timestamp-in-operating-range set
# checking to know for sure if we can
# safely and quickly ignore non-uniform history
# frame timestamp gaps..
# end_dt -= dt_duration
# continue
# await tractor.pause()
)
):
if (
end_dt
or too_little
):
log.warning(
f'History is blank for {dt_duration} from {end_dt}'
)
end_dt -= dt_duration
continue
first_dt = from_timestamp(
raise NoData(f'{end_dt}')
if bars_array is None:
raise SymbolNotFound(fqme)
first_dt = pendulum.from_timestamp(
bars[0].date.timestamp())
last_dt = from_timestamp(
last_dt = pendulum.from_timestamp(
bars[-1].date.timestamp())
time = bars_array['time']
@ -498,22 +437,15 @@ async def get_bars(
if data_cs:
data_cs.cancel()
# NOTE: setting this is critical!
result = (
bars, # ib native
bars_array, # numpy
first_dt,
last_dt,
)
result = (bars, bars_array, first_dt, last_dt)
# signal data reset loop parent task
result_ready.set()
# NOTE: this isn't getting collected anywhere!
return result
except RequestError as err:
msg: str = err.message
msg = err.message
if 'No market data permissions for' in msg:
# TODO: signalling for no permissions searches
@ -535,7 +467,7 @@ async def get_bars(
if end_dt is not None:
end_dt = end_dt.subtract(days=1)
elif end_dt is None:
end_dt = now().subtract(days=1)
end_dt = pendulum.now().subtract(days=1)
log.warning(
f'NO DATA found ending @ {end_dt}\n'
@ -551,29 +483,21 @@ async def get_bars(
nodatas_count += 1
continue
elif (
'API historical data query cancelled'
in
err.message
):
elif 'API historical data query cancelled' in err.message:
log.warning(
'Query cancelled by IB (:eyeroll:):\n'
f'{err.message}'
)
continue
elif (
'Trading TWS session is connected from a different IP'
in
err.message
in err.message
):
log.warning("ignoring ip address warning")
continue
# XXX: more or less same as above timeout case
elif (
_pacing in msg
):
elif _pacing in msg:
log.warning(
'History throttle rate reached!\n'
'Resetting farms with `ctrl-alt-f` hack\n'
@ -625,10 +549,9 @@ async def get_bars(
# don't double invoke the reset hack if another
# requester task already has it covered.
continue
else:
_data_resetter_task = trio.lowlevel.current_task()
unset_resetter: bool = True
unset_resetter = True
# spawn new data reset task
data_cs, reset_done = await nurse.start(
@ -641,16 +564,31 @@ async def get_bars(
# sync wait on reset to complete
await reset_done.wait()
_data_resetter_task = (
None
if unset_resetter
else _data_resetter_task
)
_data_resetter_task = None if unset_resetter else _data_resetter_task
assert result
return (
result,
data_cs is not None,
)
return result, data_cs is not None
# re-mapping to piker asset type names
# https://github.com/erdewit/ib_insync/blob/master/ib_insync/contract.py#L113
_asset_type_map = {
'STK': 'stock',
'OPT': 'option',
'FUT': 'future',
'CONTFUT': 'continuous_future',
'CASH': 'forex',
'IND': 'index',
'CFD': 'cfd',
'BOND': 'bond',
'CMDTY': 'commodity',
'FOP': 'futures_option',
'FUND': 'mutual_fund',
'WAR': 'warrant',
'IOPT': 'warran',
'BAG': 'bag',
'CRYPTO': 'crypto', # bc it's diff then fiat?
# 'NEWS': 'news',
}
_quote_streams: dict[str, trio.abc.ReceiveStream] = {}
@ -671,8 +609,8 @@ async def _setup_quote_stream(
# making them mostly useless and explains why the scanner
# is always slow XD
# '293', # Trade count for day
# '294', # Trade rate / minute
# '295', # Vlm rate / minute
'294', # Trade rate / minute
'295', # Vlm rate / minute
),
contract: Contract | None = None,
@ -856,6 +794,96 @@ def normalize(
return data
@async_lifo_cache()
async def get_mkt_info(
fqme: str,
proxy: MethodProxy | None = None,
) -> tuple[MktPair, ibis.ContractDetails]:
# XXX: we don't need to split off any fqme broker part?
# bs_fqme, _, broker = fqme.partition('.')
proxy: MethodProxy
if proxy is not None:
client_ctx = nullcontext(proxy)
else:
client_ctx = open_data_client
async with client_ctx as proxy:
try:
(
con, # Contract
details, # ContractDetails
) = await proxy.get_sym_details(symbol=fqme)
except ConnectionError:
log.exception(f'Proxy is ded {proxy._aio_ns}')
raise
# TODO: more consistent field translation
atype = _asset_type_map[con.secType]
if atype == 'commodity':
venue: str = 'cmdty'
else:
venue = con.primaryExchange or con.exchange
price_tick: Decimal = Decimal(str(details.minTick))
if atype == 'stock':
# XXX: GRRRR they don't support fractional share sizes for
# stocks from the API?!
# if con.secType == 'STK':
size_tick = Decimal('1')
else:
size_tick: Decimal = Decimal(str(details.minSize).rstrip('0'))
# |-> TODO: there is also the Contract.sizeIncrement, bt wtf is it?
# NOTE: this is duplicate from the .broker.norm_trade_records()
# routine, we should factor all this parsing somewhere..
expiry_str = str(con.lastTradeDateOrContractMonth)
# if expiry:
# expiry_str: str = str(pendulum.parse(
# str(expiry).strip(' ')
# ))
# TODO: currently we can't pass the fiat src asset because
# then we'll get a `MNQUSD` request for history data..
# we need to figure out how we're going to handle this (later?)
# but likely we want all backends to eventually handle
# ``dst/src.venue.`` style !?
src: str | Asset = ''
if atype == 'forex':
src = Asset(
name=str(con.currency),
atype='fiat',
tx_tick=Decimal('0.01'), # right?
)
mkt = MktPair(
dst=Asset(
name=con.symbol.lower(),
atype=atype,
tx_tick=size_tick,
),
src=src,
price_tick=price_tick,
size_tick=size_tick,
bs_mktid=str(con.conId),
venue=str(venue),
expiry=expiry_str,
broker='ib',
# TODO: options contract info as str?
# contract_info=<optionsdetails>
)
return mkt, details
async def stream_quotes(
send_chan: trio.abc.SendChannel,
@ -883,10 +911,7 @@ async def stream_quotes(
proxy: MethodProxy
mkt: MktPair
details: ibis.ContractDetails
async with (
open_data_client() as proxy,
# trio.open_nursery() as tn,
):
async with open_data_client() as proxy:
mkt, details = await get_mkt_info(
sym,
proxy=proxy, # passed to avoid implicit client load
@ -895,7 +920,7 @@ async def stream_quotes(
init_msg = FeedInit(mkt_info=mkt)
if mkt.dst.atype in {
'fiat',
'forex',
'index',
'commodity',
}:
@ -906,50 +931,27 @@ async def stream_quotes(
init_msgs.append(init_msg)
con: Contract = details.contract
first_ticker: Ticker | None = None
with trio.move_on_after(1):
first_ticker: Ticker = await proxy.get_quote(
contract=con,
raise_on_timeout=False,
)
if first_ticker:
first_ticker: Ticker = await proxy.get_quote(contract=con)
first_quote: dict = normalize(first_ticker)
# TODO: we need a stack-oriented log levels filters for
# this!
# log.info(message, filter={'stack': 'live_feed'}) ?
log.runtime(
'Rxed init quote:\n\n'
f'{pformat(first_quote)}\n'
)
log.warning(f'FIRST QUOTE: {first_quote}')
# NOTE: it might be outside regular trading hours for
# assets with "standard venue operating hours" so we
# only "pretend the feed is live" when the dst asset
# type is NOT within the NON-NORMAL-venue set: aka not
# commodities, forex or crypto currencies which CAN
# always return a NaN on a snap quote request during
# normal venue hours. In the case of a closed venue
# (equitiies, futes, bonds etc.) we at least try to
# grab the OHLC history.
# TODO: we should instead spawn a task that waits on a feed to start
# and let it wait indefinitely..instead of this hard coded stuff.
with trio.move_on_after(1):
first_ticker = await proxy.get_quote(contract=con)
# it might be outside regular trading hours so see if we can at
# least grab history.
if (
first_ticker
and
isnan(first_ticker.last)
# SO, if the last quote price value is NaN we ONLY
# "pretend to do" `feed_is_live.set()` if it's a known
# dst asset venue with a lot of closed operating hours.
isnan(first_ticker.last) # last quote price value is nan
and mkt.dst.atype not in {
'commodity',
'fiat',
'forex',
'crypto',
}
):
task_status.started((
init_msgs,
first_quote,
))
task_status.started((init_msgs, first_quote))
# it's not really live but this will unblock
# the brokerd feed task to tell the ui to update?
@ -959,28 +961,6 @@ async def stream_quotes(
await trio.sleep_forever()
return # we never expect feed to come up?
# TODO: we should instead spawn a task that waits on a feed
# to start and let it wait indefinitely..instead of this
# hard coded stuff.
# async def wait_for_first_quote():
# with trio.CancelScope() as cs:
# XXX: MUST acquire a ticker + first quote before starting
# the live quotes loop!
# with trio.move_on_after(1):
first_ticker = await proxy.get_quote(
contract=con,
raise_on_timeout=True,
)
first_quote: dict = normalize(first_ticker)
# TODO: we need a stack-oriented log levels filters for
# this!
# log.info(message, filter={'stack': 'live_feed'}) ?
log.runtime(
'Rxed init quote:\n'
f'{pformat(first_quote)}'
)
cs: trio.CancelScope | None = None
startup: bool = True
while (
@ -1001,11 +981,8 @@ async def stream_quotes(
# only on first entry at feed boot up
if startup:
startup: bool = False
task_status.started((
init_msgs,
first_quote,
))
startup = False
task_status.started((init_msgs, first_quote))
# start a stream restarter task which monitors the
# data feed event.
@ -1029,7 +1006,7 @@ async def stream_quotes(
# generally speaking these feeds don't
# include vlm data.
atype: str = mkt.dst.atype
atype = mkt.dst.atype
log.info(
f'No-vlm {mkt.fqme}@{atype}, skipping quote poll'
)
@ -1065,8 +1042,7 @@ async def stream_quotes(
quote = normalize(ticker)
log.debug(f"First ticker received {quote}")
# tell data-layer spawner-caller that live
# quotes are now streaming.
# tell caller quotes are now coming in live
feed_is_live.set()
# last = time.time()
@ -1078,3 +1054,141 @@ async def stream_quotes(
# ugh, clear ticks since we've consumed them
ticker.ticks = []
# last = time.time()
@tractor.context
async def open_symbol_search(
ctx: tractor.Context,
) -> None:
# TODO: load user defined symbol set locally for fast search?
await ctx.started({})
async with (
open_client_proxies() as (proxies, _),
open_data_client() as data_proxy,
):
async with ctx.open_stream() as stream:
# select a non-history client for symbol search to lighten
# the load in the main data node.
proxy = data_proxy
for name, proxy in proxies.items():
if proxy is data_proxy:
continue
break
ib_client = proxy._aio_ns.ib
log.info(f'Using {ib_client} for symbol search')
last = time.time()
async for pattern in stream:
log.info(f'received {pattern}')
now = time.time()
# this causes tractor hang...
# assert 0
assert pattern, 'IB can not accept blank search pattern'
# throttle search requests to no faster then 1Hz
diff = now - last
if diff < 1.0:
log.debug('throttle sleeping')
await trio.sleep(diff)
try:
pattern = stream.receive_nowait()
except trio.WouldBlock:
pass
if (
not pattern
or pattern.isspace()
# XXX: not sure if this is a bad assumption but it
# seems to make search snappier?
or len(pattern) < 1
):
log.warning('empty pattern received, skipping..')
# TODO: *BUG* if nothing is returned here the client
# side will cache a null set result and not showing
# anything to the use on re-searches when this query
# timed out. We probably need a special "timeout" msg
# or something...
# XXX: this unblocks the far end search task which may
# hold up a multi-search nursery block
await stream.send({})
continue
log.info(f'searching for {pattern}')
last = time.time()
# async batch search using api stocks endpoint and module
# defined adhoc symbol set.
stock_results = []
async def stash_results(target: Awaitable[list]):
try:
results = await target
except tractor.trionics.Lagged:
print("IB SYM-SEARCH OVERRUN?!?")
return
stock_results.extend(results)
for i in range(10):
with trio.move_on_after(3) as cs:
async with trio.open_nursery() as sn:
sn.start_soon(
stash_results,
proxy.search_symbols(
pattern=pattern,
upto=5,
),
)
# trigger async request
await trio.sleep(0)
if cs.cancelled_caught:
log.warning(
f'Search timeout? {proxy._aio_ns.ib.client}'
)
continue
else:
break
# # match against our ad-hoc set immediately
# adhoc_matches = fuzzy.extractBests(
# pattern,
# list(_adhoc_futes_set),
# score_cutoff=90,
# )
# log.info(f'fuzzy matched adhocs: {adhoc_matches}')
# adhoc_match_results = {}
# if adhoc_matches:
# # TODO: do we need to pull contract details?
# adhoc_match_results = {i[0]: {} for i in
# adhoc_matches}
log.debug(f'fuzzy matching stocks {stock_results}')
stock_matches = fuzzy.extractBests(
pattern,
stock_results,
score_cutoff=50,
)
# matches = adhoc_match_results | {
matches = {
item[0]: {} for item in stock_matches
}
# TODO: we used to deliver contract details
# {item[2]: item[0] for item in stock_matches}
log.debug(f"sending matches: {matches.keys()}")
await stream.send(matches)

View File

@ -18,328 +18,135 @@
Trade transaction accounting and normalization.
'''
from __future__ import annotations
from bisect import insort
from dataclasses import asdict
from decimal import Decimal
from functools import partial
from pprint import pformat
from typing import (
Any,
Callable,
TYPE_CHECKING,
)
from bidict import bidict
from pendulum import (
DateTime,
parse,
from_timestamp,
)
from ib_insync import (
Contract,
Commodity,
Fill,
Execution,
CommissionReport,
)
import pendulum
from piker.types import Struct
from piker.data import (
SymbologyCache,
)
from piker.accounting import (
Asset,
dec_digits,
digits_to_dec,
Transaction,
MktPair,
iter_by_dt,
)
from ._flex_reports import parse_flex_dt
from ._util import log
if TYPE_CHECKING:
from .api import (
Client,
MethodProxy,
)
def norm_trade_records(
ledger: dict[str, Any],
tx_sort: Callable = partial(
iter_by_dt,
parsers={
'dateTime': parse_flex_dt,
'datetime': parse,
) -> dict[str, Transaction]:
'''
Normalize a flex report or API retrieved executions
ledger into our standard record format.
# XXX: for some some fucking 2022 and
# back options records.. f@#$ me..
'date': parse,
}
)
'''
records: list[Transaction] = []
for tid, record in ledger.items():
conid = record.get('conId') or record['conid']
comms = record.get('commission')
if comms is None:
comms = -1*record['ibCommission']
def norm_trade(
tid: str,
record: dict[str, Any],
# this is the dict that was returned from
# `Client.get_mkt_pairs()` and when running offline ledger
# processing from `.accounting`, this will be the table loaded
# into `SymbologyCache.pairs`.
pairs: dict[str, Struct],
symcache: SymbologyCache | None = None,
) -> Transaction | None:
conid: int = str(record.get('conId') or record['conid'])
bs_mktid: str = str(conid)
# NOTE: sometimes weird records (like BTTX?)
# have no field for this?
comms: float = -1 * (
record.get('commission')
or record.get('ibCommission')
or 0
)
if not comms:
log.warning(
'No commissions found for record?\n'
f'{pformat(record)}\n'
)
price: float = (
record.get('price')
or record.get('tradePrice')
)
if price is None:
log.warning(
'No `price` field found in record?\n'
'Skipping normalization..\n'
f'{pformat(record)}\n'
)
return None
price = record.get('price') or record['tradePrice']
# the api doesn't do the -/+ on the quantity for you but flex
# records do.. are you fucking serious ib...!?
size: float|int = (
record.get('quantity')
or record['shares']
) * {
size = record.get('quantity') or record['shares'] * {
'BOT': 1,
'SLD': -1,
}[record['side']]
symbol: str = record['symbol']
exch: str = (
record.get('listingExchange')
or record.get('primaryExchange')
or record['exchange']
)
exch = record['exchange']
lexch = record.get('listingExchange')
# NOTE: remove null values since `tomlkit` can't serialize
# them to file.
if dnc := record.pop('deltaNeutralContract', None):
dnc = record.pop('deltaNeutralContract', False)
if dnc is not None:
record['deltaNeutralContract'] = dnc
suffix = lexch or exch
symbol = record['symbol']
# likely an opts contract record from a flex report..
# TODO: no idea how to parse ^ the strike part from flex..
# (00010000 any, or 00007500 tsla, ..)
# we probably must do the contract lookup for this?
if (
' ' in symbol
or '--' in exch
):
if ' ' in symbol or '--' in exch:
underlying, _, tail = symbol.partition(' ')
exch: str = 'opt'
expiry: str = tail[:6]
suffix = exch = 'opt'
expiry = tail[:6]
# otype = tail[6]
# strike = tail[7:]
log.warning(
f'Skipping option contract -> NO SUPPORT YET!\n'
f'{symbol}\n'
)
return None
print(f'skipping opts contract {symbol}')
continue
# timestamping is way different in API records
dtstr: str = record.get('datetime')
date: str = record.get('date')
flex_dtstr: str = record.get('dateTime')
dtstr = record.get('datetime')
date = record.get('date')
flex_dtstr = record.get('dateTime')
if dtstr or date:
dt: DateTime = parse(dtstr or date)
dt = pendulum.parse(dtstr or date)
elif flex_dtstr:
# probably a flex record with a wonky non-std timestamp..
dt: DateTime = parse_flex_dt(record['dateTime'])
dt = parse_flex_dt(record['dateTime'])
# special handling of symbol extraction from
# flex records using some ad-hoc schema parsing.
asset_type: str = (
record.get('assetCategory')
or record.get('secType')
or 'STK'
)
asset_type: str = record.get(
'assetCategory'
) or record.get('secType', 'STK')
if (expiry := (
# TODO: XXX: WOA this is kinda hacky.. probably
# should figure out the correct future pair key more
# explicitly and consistently?
if asset_type == 'FUT':
# (flex) ledger entries don't have any simple 3-char key?
symbol = record['symbol'][:3]
asset_type: str = 'future'
elif asset_type == 'STK':
asset_type: str = 'stock'
# try to build out piker fqme from record.
expiry = (
record.get('lastTradeDateOrContractMonth')
or record.get('expiry')
)
):
expiry: str = str(expiry).strip(' ')
# NOTE: we directly use the (simple and usually short)
# date-string expiry token when packing the `MktPair`
# since we want the fqme to contain *that* token.
# It might make sense later to instead parse and then
# render different output str format(s) for this same
# purpose depending on asset-type-market down the road.
# Eg. for derivs we use the short token only for fqme
# but use the isoformat('T') for transactions and
# account file position entries?
# dt_str: str = pendulum.parse(expiry).isoformat('T')
# XXX: pretty much all legacy market assets have a fiat
# currency (denomination) determined by their venue.
currency: str = record['currency']
src = Asset(
name=currency.lower(),
atype='fiat',
tx_tick=Decimal('0.01'),
)
if expiry:
expiry = str(expiry).strip(' ')
suffix = f'{exch}.{expiry}'
expiry = pendulum.parse(expiry)
match asset_type:
case 'FUT':
# XXX (flex) ledger entries don't necessarily have any
# simple 3-char key.. sometimes the .symbol is some
# weird internal key that we probably don't want in the
# .fqme => we should probably just wrap `Contract` to
# this like we do other crypto$ backends XD
# NOTE: at least older FLEX records should have
# this field.. no idea about API entries..
local_symbol: str | None = record.get('localSymbol')
underlying_key: str = record.get('underlyingSymbol')
descr: str | None = record.get('description')
if (
not (
local_symbol
and symbol in local_symbol
)
and (
descr
and symbol not in descr
)
):
con_key, exp_str = descr.split(' ')
symbol: str = underlying_key or con_key
dst = Asset(
name=symbol.lower(),
atype='future',
tx_tick=Decimal('1'),
)
case 'STK':
dst = Asset(
name=symbol.lower(),
atype='stock',
tx_tick=Decimal('1'),
)
case 'CASH':
if currency not in symbol:
# likely a dict-casted `Forex` contract which
# has .symbol as the dst and .currency as the
# src.
name: str = symbol.lower()
else:
# likely a flex-report record which puts
# EUR.USD as the symbol field and just USD in
# the currency field.
name: str = symbol.lower().replace(f'.{src.name}', '')
dst = Asset(
name=name,
atype='fiat',
tx_tick=Decimal('0.01'),
)
case 'OPT':
dst = Asset(
name=symbol.lower(),
atype='option',
tx_tick=Decimal('1'),
# TODO: we should probably always cast to the
# `Contract` instance then dict-serialize that for
# the `.info` field!
# info=asdict(Option()),
)
case 'CMDTY':
from .symbols import _adhoc_symbol_map
con_kwargs, _ = _adhoc_symbol_map[symbol.upper()]
dst = Asset(
name=symbol.lower(),
atype='commodity',
tx_tick=Decimal('1'),
info=asdict(Commodity(**con_kwargs)),
)
# try to build out piker fqme from record.
# src: str = record['currency']
price_tick: Decimal = digits_to_dec(dec_digits(price))
# NOTE: can't serlialize `tomlkit.String` so cast to native
atype: str = str(dst.atype)
# if not (mkt := symcache.mktmaps.get(bs_mktid)):
mkt = MktPair(
bs_mktid=bs_mktid,
dst=dst,
pair = MktPair.from_fqme(
fqme=f'{symbol}.{suffix}.ib',
bs_mktid=str(conid),
_atype=str(asset_type), # XXX: can't serlialize `tomlkit.String`
price_tick=price_tick,
# NOTE: for "legacy" assets, volume is normally discreet, not
# a float, but we keep a digit in case the suitz decide
# to get crazy and change it; we'll be kinda ready
# schema-wise..
size_tick=Decimal('1'),
src=src, # XXX: normally always a fiat
_atype=atype,
venue=exch,
expiry=expiry,
broker='ib',
_fqme_without_src=(atype != 'fiat'),
size_tick='1',
)
fqme: str = mkt.fqme
# XXX: if passed in, we fill out the symcache ad-hoc in order
# to make downstream accounting work..
if symcache is not None:
orig_mkt: MktPair | None = symcache.mktmaps.get(bs_mktid)
if (
orig_mkt
and orig_mkt.fqme != mkt.fqme
):
log.warning(
# print(
f'Contracts with common `conId`: {bs_mktid} mismatch..\n'
f'{orig_mkt.fqme} -> {mkt.fqme}\n'
# 'with DIFF:\n'
# f'{mkt - orig_mkt}'
)
symcache.mktmaps[bs_mktid] = mkt
symcache.mktmaps[fqme] = mkt
symcache.assets[src.name] = src
symcache.assets[dst.name] = dst
fqme = pair.fqme
# NOTE: for flex records the normal fields for defining an fqme
# sometimes won't be available so we rely on two approaches for
@ -351,8 +158,11 @@ def norm_trade(
# should already have entries if the pps are still open, in
# which case, we can pull the fqme from that table (see
# `trades_dialogue()` above).
return Transaction(
insort(
records,
Transaction(
fqme=fqme,
sym=pair,
tid=tid,
size=size,
price=price,
@ -360,40 +170,7 @@ def norm_trade(
dt=dt,
expiry=expiry,
bs_mktid=str(conid),
)
def norm_trade_records(
ledger: dict[str, Any],
symcache: SymbologyCache | None = None,
) -> dict[str, Transaction]:
'''
Normalize (xml) flex-report or (recent) API trade records into
our ledger format with parsing for `MktPair` and `Asset`
extraction to fill in the `Transaction.sys: MktPair` field.
'''
records: list[Transaction] = []
for tid, record in ledger.items():
txn = norm_trade(
tid,
record,
# NOTE: currently no symcache support
pairs={},
symcache=symcache,
)
if txn is None:
continue
# inject txns sorted by datetime
insort(
records,
txn,
),
key=lambda t: t.dt
)
@ -402,49 +179,50 @@ def norm_trade_records(
def api_trades_to_ledger_entries(
accounts: bidict[str, str],
fills: list[Fill],
) -> dict[str, dict]:
# TODO: maybe we should just be passing through the
# ``ib_insync.order.Trade`` instance directly here
# instead of pre-casting to dicts?
trade_entries: list[dict],
) -> dict:
'''
Convert API execution objects entry objects into
flattened-``dict`` form, pretty much straight up without
modification except add a `pydatetime` field from the parsed
timestamp so that on write
Convert API execution objects entry objects into ``dict`` form,
pretty much straight up without modification except add
a `pydatetime` field from the parsed timestamp.
'''
trades_by_account: dict[str, dict] = {}
for fill in fills:
trades_by_account = {}
for t in trade_entries:
# NOTE: example of schema we pull from the API client.
# {
# 'commissionReport': CommissionReport(...
# 'contract': {...
# 'execution': Execution(...
# 'time': 1654801166.0
# }
# NOTE: for the schema, see the defn for `Fill` which is
# a `NamedTuple` subtype
fdict: dict = fill._asdict()
# flatten all (sub-)objects and convert to dicts.
# with values packed into one top level entry.
val: CommissionReport | Execution | Contract
txn_dict: dict[str, Any] = {}
for attr_name, val in fdict.items():
match attr_name:
# value is a `@dataclass` subtype
# flatten all sub-dicts and values into one top level entry.
entry = {}
for section, val in t.items():
match section:
case 'contract' | 'execution' | 'commissionReport':
txn_dict.update(asdict(val))
# sub-dict cases
entry.update(val)
case 'time':
# ib has wack ns timestamps, or is that us?
continue
# TODO: we can remove this case right since there's
# only 4 fields on a `Fill`?
case _:
txn_dict[attr_name] = val
entry[section] = val
tid = str(txn_dict['execId'])
dt = from_timestamp(txn_dict['time'])
txn_dict['datetime'] = str(dt)
acctid = accounts[txn_dict['acctNumber']]
# NOTE: only inserted (then later popped) for sorting below!
txn_dict['pydatetime'] = dt
tid = str(entry['execId'])
dt = pendulum.from_timestamp(entry['time'])
# TODO: why isn't this showing seconds in the str?
entry['pydatetime'] = dt
entry['datetime'] = str(dt)
acctid = accounts[entry['acctNumber']]
if not tid:
# this is likely some kind of internal adjustment
@ -455,18 +233,13 @@ def api_trades_to_ledger_entries(
# the user from the accounts window in TWS where they can
# manually set the avg price and size:
# https://api.ibkr.com/lib/cstools/faq/web1/index.html#/tag/DTWS_ADJ_AVG_COST
log.warning(
'Skipping ID-less ledger txn_dict:\n'
f'{pformat(txn_dict)}'
)
log.warning(f'Skipping ID-less ledger entry:\n{pformat(entry)}')
continue
trades_by_account.setdefault(
acctid, {}
)[tid] = txn_dict
)[tid] = entry
# TODO: maybe we should just bisect.insort() into a list of
# tuples and then return a dict of that?
# sort entries in output by python based datetime
for acctid in trades_by_account:
trades_by_account[acctid] = dict(sorted(
@ -475,55 +248,3 @@ def api_trades_to_ledger_entries(
))
return trades_by_account
async def update_ledger_from_api_trades(
fills: list[Fill],
client: Client | MethodProxy,
accounts_def_inv: bidict[str, str],
# NOTE: provided for ad-hoc insertions "as transactions are
# processed" -> see `norm_trade()` signature requirements.
symcache: SymbologyCache | None = None,
) -> tuple[
dict[str, Transaction],
dict[str, dict],
]:
# XXX; ERRGGG..
# pack in the "primary/listing exchange" value from a
# contract lookup since it seems this isn't available by
# default from the `.fills()` method endpoint...
fill: Fill
for fill in fills:
con: Contract = fill.contract
conid: str = con.conId
pexch: str | None = con.primaryExchange
if not pexch:
cons = await client.get_con(conid=conid)
if cons:
con = cons[0]
pexch = con.primaryExchange or con.exchange
else:
# for futes it seems like the primary is always empty?
pexch: str = con.exchange
# pack in the ``Contract.secType``
# entry['asset_type'] = condict['secType']
entries: dict[str, dict] = api_trades_to_ledger_entries(
accounts_def_inv,
fills,
)
# normalize recent session's trades to the `Transaction` type
trans_by_acct: dict[str, dict[str, Transaction]] = {}
for acctid, trades_by_id in entries.items():
# normalize to transaction form
trans_by_acct[acctid] = norm_trade_records(
trades_by_id,
symcache=symcache,
)
return trans_by_acct, entries

View File

@ -1,615 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Symbology search and normalization.
'''
from __future__ import annotations
from contextlib import (
nullcontext,
)
from decimal import Decimal
import time
from typing import (
Awaitable,
TYPE_CHECKING,
)
from rapidfuzz import process as fuzzy
import ib_insync as ibis
import tractor
import trio
from piker.accounting import (
Asset,
MktPair,
unpack_fqme,
)
from piker._cacheables import (
async_lifo_cache,
)
from ._util import (
log,
)
if TYPE_CHECKING:
from .api import (
MethodProxy,
Client,
)
_futes_venues = (
'GLOBEX',
'NYMEX',
'CME',
'CMECRYPTO',
'COMEX',
# 'CMDTY', # special name case..
'CBOT', # (treasury) yield futures
)
_adhoc_cmdty_set = {
# metals
# https://misc.interactivebrokers.com/cstools/contract_info/v3.10/index.php?action=Conid%20Info&wlId=IB&conid=69067924
'xauusd.cmdty', # london gold spot ^
'xagusd.cmdty', # silver spot
}
# NOTE: if you aren't seeing one of these symbol's futues contracts
# show up, it's likely the `.<venue>` part is wrong!
_adhoc_futes_set = {
# equities
'nq.cme',
'mnq.cme', # micro
'es.cme',
'mes.cme', # micro
# cypto$
'brr.cme',
'mbt.cme', # micro
'ethusdrr.cme',
# agriculture
'he.comex', # lean hogs
'le.comex', # live cattle (geezers)
'gf.comex', # feeder cattle (younguns)
# raw
'lb.comex', # random len lumber
'gc.comex',
'mgc.comex', # micro
# oil & gas
'cl.nymex',
'ni.comex', # silver futes
'qi.comex', # mini-silver futes
# treasury yields
# etfs by duration:
# SHY -> IEI -> IEF -> TLT
'zt.cbot', # 2y
'z3n.cbot', # 3y
'zf.cbot', # 5y
'zn.cbot', # 10y
'zb.cbot', # 30y
# (micros of above)
'2yy.cbot',
'5yy.cbot',
'10y.cbot',
'30y.cbot',
}
# taken from list here:
# https://www.interactivebrokers.com/en/trading/products-spot-currencies.php
_adhoc_fiat_set = set((
'USD, AED, AUD, CAD,'
'CHF, CNH, CZK, DKK,'
'EUR, GBP, HKD, HUF,'
'ILS, JPY, MXN, NOK,'
'NZD, PLN, RUB, SAR,'
'SEK, SGD, TRY, ZAR'
).split(' ,')
)
# manually discovered tick discrepancies,
# onl god knows how or why they'd cuck these up..
_adhoc_mkt_infos: dict[int | str, dict] = {
'vtgn.nasdaq': {'price_tick': Decimal('0.01')},
}
# map of symbols to contract ids
_adhoc_symbol_map = {
# https://misc.interactivebrokers.com/cstools/contract_info/v3.10/index.php?action=Conid%20Info&wlId=IB&conid=69067924
# NOTE: some cmdtys/metals don't have trade data like gold/usd:
# https://groups.io/g/twsapi/message/44174
'XAUUSD': ({'conId': 69067924}, {'whatToShow': 'MIDPOINT'}),
}
for qsn in _adhoc_futes_set:
sym, venue = qsn.split('.')
assert venue.upper() in _futes_venues, f'{venue}'
_adhoc_symbol_map[sym.upper()] = (
{'exchange': venue},
{},
)
# exchanges we don't support at the moment due to not knowing
# how to do symbol-contract lookup correctly likely due
# to not having the data feeds subscribed.
_exch_skip_list = {
'ASX', # aussie stocks
'MEXI', # mexican stocks
# no idea
'NSE',
'VALUE',
'FUNDSERV',
'SWB2',
'PSE',
'PHLX',
}
# optional search config the backend can register for
# it's symbol search handling (in this case we avoid
# accepting patterns before the kb has settled more then
# a quarter second).
_search_conf = {
'pause_period': 6 / 16,
}
@tractor.context
async def open_symbol_search(ctx: tractor.Context) -> None:
'''
Symbology search brokerd-endpoint.
'''
from .api import open_client_proxies
from .feed import open_data_client
# TODO: load user defined symbol set locally for fast search?
await ctx.started({})
async with (
open_client_proxies() as (proxies, _),
open_data_client() as data_proxy,
):
async with ctx.open_stream() as stream:
# select a non-history client for symbol search to lighten
# the load in the main data node.
proxy = data_proxy
for name, proxy in proxies.items():
if proxy is data_proxy:
continue
break
ib_client = proxy._aio_ns.ib
log.info(
f'Using API client for symbol-search\n'
f'{ib_client}\n'
)
last = time.time()
async for pattern in stream:
log.info(f'received {pattern}')
now: float = time.time()
# this causes tractor hang...
# assert 0
assert pattern, 'IB can not accept blank search pattern'
# throttle search requests to no faster then 1Hz
diff = now - last
if diff < 1.0:
log.debug('throttle sleeping')
await trio.sleep(diff)
try:
pattern = stream.receive_nowait()
except trio.WouldBlock:
pass
if (
not pattern
or pattern.isspace()
# XXX: not sure if this is a bad assumption but it
# seems to make search snappier?
or len(pattern) < 1
):
log.warning('empty pattern received, skipping..')
# TODO: *BUG* if nothing is returned here the client
# side will cache a null set result and not showing
# anything to the use on re-searches when this query
# timed out. We probably need a special "timeout" msg
# or something...
# XXX: this unblocks the far end search task which may
# hold up a multi-search nursery block
await stream.send({})
continue
log.info(f'searching for {pattern}')
last = time.time()
# async batch search using api stocks endpoint and module
# defined adhoc symbol set.
stock_results = []
async def extend_results(
target: Awaitable[list]
) -> None:
try:
results = await target
except tractor.trionics.Lagged:
print("IB SYM-SEARCH OVERRUN?!?")
return
stock_results.extend(results)
for _ in range(10):
with trio.move_on_after(3) as cs:
async with trio.open_nursery() as sn:
sn.start_soon(
extend_results,
proxy.search_symbols(
pattern=pattern,
upto=5,
),
)
# trigger async request
await trio.sleep(0)
if cs.cancelled_caught:
log.warning(
f'Search timeout? {proxy._aio_ns.ib.client}'
)
continue
elif stock_results:
break
# else:
# await tractor.pause()
# # match against our ad-hoc set immediately
# adhoc_matches = fuzzy.extract(
# pattern,
# list(_adhoc_futes_set),
# score_cutoff=90,
# )
# log.info(f'fuzzy matched adhocs: {adhoc_matches}')
# adhoc_match_results = {}
# if adhoc_matches:
# # TODO: do we need to pull contract details?
# adhoc_match_results = {i[0]: {} for i in
# adhoc_matches}
log.debug(f'fuzzy matching stocks {stock_results}')
stock_matches = fuzzy.extract(
pattern,
stock_results,
score_cutoff=50,
)
# matches = adhoc_match_results | {
matches = {
item[0]: {} for item in stock_matches
}
# TODO: we used to deliver contract details
# {item[2]: item[0] for item in stock_matches}
log.debug(f"sending matches: {matches.keys()}")
await stream.send(matches)
# re-mapping to piker asset type names
# https://github.com/erdewit/ib_insync/blob/master/ib_insync/contract.py#L113
_asset_type_map = {
'STK': 'stock',
'OPT': 'option',
'FUT': 'future',
'CONTFUT': 'continuous_future',
'CASH': 'fiat',
'IND': 'index',
'CFD': 'cfd',
'BOND': 'bond',
'CMDTY': 'commodity',
'FOP': 'futures_option',
'FUND': 'mutual_fund',
'WAR': 'warrant',
'IOPT': 'warran',
'BAG': 'bag',
'CRYPTO': 'crypto', # bc it's diff then fiat?
# 'NEWS': 'news',
}
def parse_patt2fqme(
# client: Client,
pattern: str,
) -> tuple[str, str, str, str]:
# TODO: we can't use this currently because
# ``wrapper.starTicker()`` currently cashes ticker instances
# which means getting a singel quote will potentially look up
# a quote for a ticker that it already streaming and thus run
# into state clobbering (eg. list: Ticker.ticks). It probably
# makes sense to try this once we get the pub-sub working on
# individual symbols...
# XXX UPDATE: we can probably do the tick/trades scraping
# inside our eventkit handler instead to bypass this entirely?
currency = ''
# fqme parsing stage
# ------------------
if '.ib' in pattern:
_, symbol, venue, expiry = unpack_fqme(pattern)
else:
symbol = pattern
expiry = ''
# # another hack for forex pairs lul.
# if (
# '.idealpro' in symbol
# # or '/' in symbol
# ):
# exch: str = 'IDEALPRO'
# symbol = symbol.removesuffix('.idealpro')
# if '/' in symbol:
# symbol, currency = symbol.split('/')
# else:
# TODO: yes, a cache..
# try:
# # give the cache a go
# return client._contracts[symbol]
# except KeyError:
# log.debug(f'Looking up contract for {symbol}')
expiry: str = ''
if symbol.count('.') > 1:
symbol, _, expiry = symbol.rpartition('.')
# use heuristics to figure out contract "type"
symbol, venue = symbol.upper().rsplit('.', maxsplit=1)
return symbol, currency, venue, expiry
def con2fqme(
con: ibis.Contract,
_cache: dict[int, (str, bool)] = {}
) -> tuple[str, bool]:
'''
Convert contracts to fqme-style strings to be used both in
symbol-search matching and as feed tokens passed to the front
end data deed layer.
Previously seen contracts are cached by id.
'''
# should be real volume for this contract by default
calc_price: bool = False
if con.conId:
try:
# TODO: LOL so apparently IB just changes the contract
# ID (int) on a whim.. so we probably need to use an
# FQME style key after all...
return _cache[con.conId]
except KeyError:
pass
suffix: str = con.primaryExchange or con.exchange
symbol: str = con.symbol
expiry: str = con.lastTradeDateOrContractMonth or ''
match con:
case ibis.Option():
# TODO: option symbol parsing and sane display:
symbol = con.localSymbol.replace(' ', '')
case (
ibis.Commodity()
# search API endpoint returns std con box..
| ibis.Contract(secType='CMDTY')
):
# commodities and forex don't have an exchange name and
# no real volume so we have to calculate the price
suffix = con.secType
# no real volume on this tract
calc_price = True
case ibis.Forex() | ibis.Contract(secType='CASH'):
dst, src = con.localSymbol.split('.')
symbol = ''.join([dst, src])
suffix = con.exchange or 'idealpro'
# no real volume on forex feeds..
calc_price = True
if not suffix:
entry = _adhoc_symbol_map.get(
con.symbol or con.localSymbol
)
if entry:
meta, kwargs = entry
cid = meta.get('conId')
if cid:
assert con.conId == meta['conId']
suffix = meta['exchange']
# append a `.<suffix>` to the returned symbol
# key for derivatives that normally is the expiry
# date key.
if expiry:
suffix += f'.{expiry}'
fqme_key = symbol.lower()
if suffix:
fqme_key = '.'.join((fqme_key, suffix)).lower()
_cache[con.conId] = fqme_key, calc_price
return fqme_key, calc_price
@async_lifo_cache()
async def get_mkt_info(
fqme: str,
proxy: MethodProxy | None = None,
) -> tuple[MktPair, ibis.ContractDetails]:
if '.ib' not in fqme:
fqme += '.ib'
broker, pair, venue, expiry = unpack_fqme(fqme)
proxy: MethodProxy
if proxy is not None:
client_ctx = nullcontext(proxy)
else:
from .feed import (
open_data_client,
)
client_ctx = open_data_client
async with client_ctx as proxy:
try:
(
con, # Contract
details, # ContractDetails
) = await proxy.get_sym_details(fqme=fqme)
except ConnectionError:
log.exception(f'Proxy is ded {proxy._aio_ns}')
raise
# TODO: more consistent field translation
atype = _asset_type_map[con.secType]
if atype == 'commodity':
venue: str = 'cmdty'
else:
venue = con.primaryExchange or con.exchange
price_tick: Decimal = Decimal(str(details.minTick))
ib_min_tick_gt_2: Decimal = Decimal('0.01')
if (
price_tick < ib_min_tick_gt_2
):
# TODO: we need to add some kinda dynamic rounding sys
# to our MktPair i guess?
# not sure where the logic should sit, but likely inside
# the `.clearing._ems` i suppose...
log.warning(
'IB seems to disallow a min price tick < 0.01 '
'when the price is > 2.0..?\n'
f'Decreasing min tick precision for {fqme} to 0.01'
)
# price_tick = ib_min_tick
# await tractor.pause()
if atype == 'stock':
# XXX: GRRRR they don't support fractional share sizes for
# stocks from the API?!
# if con.secType == 'STK':
size_tick = Decimal('1')
else:
size_tick: Decimal = Decimal(
str(details.minSize).rstrip('0')
)
# |-> TODO: there is also the Contract.sizeIncrement, bt wtf is it?
# NOTE: this is duplicate from the .broker.norm_trade_records()
# routine, we should factor all this parsing somewhere..
expiry_str = str(con.lastTradeDateOrContractMonth)
# if expiry:
# expiry_str: str = str(pendulum.parse(
# str(expiry).strip(' ')
# ))
# TODO: currently we can't pass the fiat src asset because
# then we'll get a `MNQUSD` request for history data..
# we need to figure out how we're going to handle this (later?)
# but likely we want all backends to eventually handle
# ``dst/src.venue.`` style !?
src = Asset(
name=str(con.currency).lower(),
atype='fiat',
tx_tick=Decimal('0.01'), # right?
)
dst = Asset(
name=con.symbol.lower(),
atype=atype,
tx_tick=size_tick,
)
mkt = MktPair(
src=src,
dst=dst,
price_tick=price_tick,
size_tick=size_tick,
bs_mktid=str(con.conId),
venue=str(venue),
expiry=expiry_str,
broker='ib',
# TODO: options contract info as str?
# contract_info=<optionsdetails>
_fqme_without_src=(atype != 'fiat'),
)
# just.. wow.
if entry := _adhoc_mkt_infos.get(mkt.bs_fqme):
log.warning(f'Frickin {mkt.fqme} has an adhoc {entry}..')
new = mkt.to_dict()
new['price_tick'] = entry['price_tick']
new['src'] = src
new['dst'] = dst
mkt = MktPair(**new)
# if possible register the bs_mktid to the just-built
# mkt so that it can be retreived by order mode tasks later.
# TODO NOTE: this is going to be problematic if/when we split
# out the datatd vs. brokerd actors since the mktmap lookup
# table will now be inaccessible..
if proxy is not None:
client: Client = proxy._aio_ns
client._contracts[mkt.bs_fqme] = con
client._cons2mkts[con] = mkt
return mkt, details

View File

@ -19,36 +19,23 @@ Kraken backend.
Sub-modules within break into the core functionalities:
- .api: for the core API machinery which generally
a ``asks``/``trio-websocket`` implemented ``Client``.
- .broker: part for orders / trading endpoints.
- .feed: for real-time and historical data query endpoints.
- .ledger: for transaction processing as it pertains to accounting.
- .symbols: for market (name) search and symbology meta-defs.
- ``broker.py`` part for orders / trading endpoints
- ``feed.py`` for real-time data feed endpoints
- ``api.py`` for the core API machinery which is ``trio``-ized
wrapping around ``ib_insync``.
'''
from .symbols import (
Pair, # for symcache
open_symbol_search,
# required by `.accounting`, `.data`
get_mkt_info,
)
# required by `.brokers`
from .api import (
get_client,
)
from .feed import (
# required by `.data`
stream_quotes,
get_mkt_info,
open_history_client,
open_symbol_search,
stream_quotes,
)
from .broker import (
# required by `.clearing`
open_trade_dialog,
)
from .ledger import (
# required by `.accounting`
norm_trade,
norm_trade_records,
)
@ -56,20 +43,17 @@ from .ledger import (
__all__ = [
'get_client',
'get_mkt_info',
'Pair',
'open_trade_dialog',
'open_history_client',
'open_symbol_search',
'stream_quotes',
'norm_trade_records',
'norm_trade',
]
# tractor RPC enable arg
__enable_modules__: list[str] = [
'api',
'broker',
'feed',
'symbols',
'broker',
]

View File

@ -15,11 +15,12 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Core (web) API client
Kraken web API wrapping.
'''
from contextlib import asynccontextmanager as acm
from datetime import datetime
from decimal import Decimal
import itertools
from typing import (
Any,
@ -27,8 +28,10 @@ from typing import (
)
import time
import httpx
from bidict import bidict
import pendulum
import asks
from fuzzywuzzy import process as fuzzy
import numpy as np
import urllib.parse
import hashlib
@ -37,14 +40,11 @@ import base64
import trio
from piker import config
from piker.data import (
def_iohlcv_fields,
match_from_pairs,
)
from piker.data.types import Struct
from piker.data import def_iohlcv_fields
from piker.accounting._mktinfo import (
Asset,
digits_to_dec,
dec_digits,
)
from piker.brokers._util import (
resproc,
@ -54,17 +54,11 @@ from piker.brokers._util import (
)
from piker.accounting import Transaction
from piker.log import get_logger
from .symbols import Pair
log = get_logger('piker.brokers.kraken')
# <uri>/<version>/
_url = 'https://api.kraken.com/0'
_headers: dict[str, str] = {
'User-Agent': 'krakenex/2.1.0 (+https://github.com/veox/python3-krakenex)'
}
# TODO: this is the only backend providing this right?
# in which case we should drop it from the defaults and
# instead make a custom fields descr in this module!
@ -75,18 +69,12 @@ _symbol_info_translation: dict[str, str] = {
def get_config() -> dict[str, Any]:
'''
Load our section from `piker/brokers.toml`.
'''
conf, path = config.load(
conf_name='brokers',
touch_if_dne=True,
)
if (section := conf.get('kraken')) is None:
log.warning(
f'No config section found for kraken in {path}'
)
conf, path = config.load()
section = conf.get('kraken')
if section is None:
log.warning(f'No config section found for kraken in {path}')
return {}
return section
@ -117,51 +105,96 @@ class InvalidKey(ValueError):
'''
# https://www.kraken.com/features/api#get-tradable-pairs
class Pair(Struct):
altname: str # alternate pair name
wsname: str # WebSocket pair name (if available)
aclass_base: str # asset class of base component
base: str # asset id of base component
aclass_quote: str # asset class of quote component
quote: str # asset id of quote component
lot: str # volume lot size
cost_decimals: int
costmin: float
pair_decimals: int # scaling decimal places for pair
lot_decimals: int # scaling decimal places for volume
# amount to multiply lot volume by to get currency volume
lot_multiplier: float
# array of leverage amounts available when buying
leverage_buy: list[int]
# array of leverage amounts available when selling
leverage_sell: list[int]
# fee schedule array in [volume, percent fee] tuples
fees: list[tuple[int, float]]
# maker fee schedule array in [volume, percent fee] tuples (if on
# maker/taker)
fees_maker: list[tuple[int, float]]
fee_volume_currency: str # volume discount currency
margin_call: str # margin call level
margin_stop: str # stop-out/liquidation margin level
ordermin: float # minimum order volume for pair
tick_size: float # min price step size
status: str
short_position_limit: float = 0
long_position_limit: float = float('inf')
@property
def price_tick(self) -> Decimal:
return digits_to_dec(self.pair_decimals)
@property
def size_tick(self) -> Decimal:
return digits_to_dec(self.lot_decimals)
@property
def bs_fqme(self) -> str:
return f'{self.symbol}.SPOT'
class Client:
# assets and mkt pairs are key-ed by kraken's ReST response
# symbol-bs_mktids (we call them "X-keys" like fricking
# "XXMRZEUR"). these keys used directly since ledger endpoints
# return transaction sets keyed with the same set!
_Assets: dict[str, Asset] = {}
_AssetPairs: dict[str, Pair] = {}
# symbol mapping from all names to the altname
_ntable: dict[str, str] = {}
# offer lookup tables for all .altname and .wsname
# to the equivalent .xname so that various symbol-schemas
# can be mapped to `Pair`s in the tables above.
_altnames: dict[str, str] = {}
_wsnames: dict[str, str] = {}
# 2-way map of symbol names to their "alt names" ffs XD
_altnames: bidict[str, str] = bidict()
# key-ed by `Pair.bs_fqme: str`, and thus used for search
# allowing for lookup using piker's own FQME symbology sys.
_pairs: dict[str, Pair] = {}
_assets: dict[str, Asset] = {}
def __init__(
self,
config: dict[str, str],
httpx_client: httpx.AsyncClient,
name: str = '',
api_key: str = '',
secret: str = ''
) -> None:
self._sesh: httpx.AsyncClient = httpx_client
self._sesh = asks.Session(connections=4)
self._sesh.base_location = _url
self._sesh.headers.update({
'User-Agent':
'krakenex/2.1.0 (+https://github.com/veox/python3-krakenex)'
})
self._name = name
self._api_key = api_key
self._secret = secret
self.conf: dict[str, str] = config
self.assets: dict[str, Asset] = {}
@property
def pairs(self) -> dict[str, Pair]:
if self._pairs is None:
raise RuntimeError(
"Client didn't run `.get_mkt_pairs()` on startup?!"
"Make sure to run `cache_symbols()` on startup!"
)
# retreive and cache all symbols
return self._pairs
@ -170,9 +203,10 @@ class Client:
method: str,
data: dict,
) -> dict[str, Any]:
resp: httpx.Response = await self._sesh.post(
url=f'/public/{method}',
resp = await self._sesh.post(
path=f'/public/{method}',
json=data,
timeout=float('inf')
)
return resproc(resp, log)
@ -183,18 +217,18 @@ class Client:
uri_path: str
) -> dict[str, Any]:
headers = {
'Content-Type': 'application/x-www-form-urlencoded',
'API-Key': self._api_key,
'API-Sign': get_kraken_signature(
uri_path,
data,
self._secret,
),
'Content-Type':
'application/x-www-form-urlencoded',
'API-Key':
self._api_key,
'API-Sign':
get_kraken_signature(uri_path, data, self._secret)
}
resp: httpx.Response = await self._sesh.post(
url=f'/private/{method}',
resp = await self._sesh.post(
path=f'/private/{method}',
data=data,
headers=headers,
timeout=float('inf')
)
return resproc(resp, log)
@ -220,29 +254,17 @@ class Client:
'Balance',
{},
)
by_bsmktid: dict[str, dict] = resp['result']
by_bsmktid = resp['result']
balances: dict = {}
for xname, bal in by_bsmktid.items():
asset: Asset = self._Assets[xname]
# TODO: we need to pull out the "asset" decimals
# data and return a `decimal.Decimal` instead here!
# using the underlying Asset
return {
self._altnames[sym].lower(): float(bal)
for sym, bal in by_bsmktid.items()
}
# TODO: which KEY should we use? it's used to index
# the `Account.pps: dict` ..
key: str = asset.name.lower()
# TODO: should we just return a `Decimal` here
# or is the rounded version ok?
balances[key] = round(
float(bal),
ndigits=dec_digits(asset.tx_tick)
)
return balances
async def get_assets(
self,
reload: bool = False,
) -> dict[str, Asset]:
async def get_assets(self) -> dict[str, Asset]:
'''
Load and cache all asset infos and pack into
our native ``Asset`` struct.
@ -260,37 +282,21 @@ class Client:
}
'''
if (
not self._assets
or reload
):
resp = await self._public('Assets', {})
assets: dict[str, dict] = resp['result']
assets = resp['result']
for bs_mktid, info in assets.items():
altname: str = info['altname']
altname = self._altnames[bs_mktid] = info['altname']
aclass: str = info['aclass']
asset = Asset(
name=altname,
self.assets[bs_mktid] = Asset(
name=altname.lower(),
atype=f'crypto_{aclass}',
tx_tick=digits_to_dec(info['decimals']),
info=info,
)
# NOTE: yes we keep 2 sets since kraken insists on
# keeping 3 frickin sets bc apparently they have
# no sane data engineers whol all like different
# keys for their fricking symbology sets..
self._Assets[bs_mktid] = asset
self._assets[altname.lower()] = asset
self._assets[altname] = asset
# we return the "most native" set merged with our preferred
# naming (which i guess is the "altname" one) since that's
# what the symcache loader will be storing, and we need the
# keys that are easiest to match against in any trade
# records.
return self._Assets | self._assets
return self.assets
async def get_trades(
self,
@ -371,25 +377,23 @@ class Client:
# 'amount': '0.00300726', 'fee': '0.00001000', 'time':
# 1658347714, 'status': 'Success'}]}
if xfers:
import tractor
await tractor.pp()
trans: dict[str, Transaction] = {}
for entry in xfers:
# look up the normalized name and asset info
asset_key: str = entry['asset']
asset: Asset = self._Assets[asset_key]
asset_key: str = asset.name.lower()
asset_key = entry['asset']
asset = self.assets[asset_key]
asset_key = self._altnames[asset_key].lower()
# XXX: this is in the asset units (likely) so it isn't
# quite the same as a commisions cost necessarily..)
# TODO: also round this based on `Pair` cost precision info?
cost = float(entry['fee'])
# fqme: str = asset_key + '.kraken'
fqme = asset_key + '.kraken'
tx = Transaction(
fqme=asset_key, # this must map to an entry in .assets!
fqme=fqme,
sym=asset,
tid=entry['txid'],
dt=pendulum.from_timestamp(entry['time']),
bs_mktid=f'{asset_key}{src_asset}',
@ -404,11 +408,6 @@ class Client:
# XXX: see note above
cost=cost,
# not a trade but a withdrawal or deposit on the
# asset (chain) system.
etype='transfer',
)
trans[tx.tid] = tx
@ -459,7 +458,7 @@ class Client:
# txid is a transaction id given by kraken
return await self.endpoint('CancelOrder', {"txid": reqid})
async def asset_pairs(
async def pair_info(
self,
pair_patt: str | None = None,
@ -471,76 +470,64 @@ class Client:
https://docs.kraken.com/rest/#tag/Market-Data/operation/getTradableAssetPairs
'''
if not self._AssetPairs:
# get all pairs by default, or filter
# to whatever pattern is provided as input.
req_pairs: dict[str, str] | None = None
pairs: dict[str, str] | None = None
if pair_patt is not None:
req_pairs = {'pair': pair_patt}
pairs = {'pair': pair_patt}
resp = await self._public(
'AssetPairs',
req_pairs,
pairs,
)
err = resp['error']
if err:
raise SymbolNotFound(pair_patt)
# NOTE: we try to key pairs by our custom defined
# `.bs_fqme` field since we want to offer search over
# this pattern set, callers should fill out lookup
# tables for kraken's bs_mktid keys to map to these
# keys!
# XXX: FURTHER kraken's data eng team decided to offer
# 3 frickin market-pair-symbol key sets depending on
# which frickin API is being used.
# Example for the trading pair 'LTC<EUR'
# - the "X-key" from rest eps 'XLTCZEUR'
# - the "websocket key" from ws msgs is 'LTC/EUR'
# - the "altname key" also delivered in pair info is 'LTCEUR'
for xkey, data in resp['result'].items():
pairs: dict[str, Pair] = {
# NOTE: always cache in pairs tables for faster lookup
pair = Pair(xname=xkey, **data)
# register the above `Pair` structs for all
# key-sets/monikers: a set of 4 (frickin) tables
# acting as a combined surjection of all possible
# (and stupid) kraken names to their `Pair` obj.
self._AssetPairs[xkey] = pair
self._pairs[pair.bs_fqme] = pair
self._altnames[pair.altname] = pair
self._wsnames[pair.wsname] = pair
key: Pair(**data)
for key, data in resp['result'].items()
}
# always cache so we can possibly do faster lookup
self._pairs.update(pairs)
if pair_patt is not None:
return next(iter(self._pairs.items()))[1]
return next(iter(pairs.items()))[1]
return self._AssetPairs
return pairs
async def get_mkt_pairs(
self,
reload: bool = False,
) -> dict:
async def cache_symbols(self) -> dict:
'''
Load all market pair info build and cache it for downstream
use.
Load all market pair info build and cache it for downstream use.
Multiple pair info lookup tables (like ``._altnames:
dict[str, str]``) are created for looking up the
piker-native `Pair`-struct from any input of the three
(yes, it's that idiotic..) available symbol/pair-key-sets
that kraken frickin offers depending on the API including
the .altname, .wsname and the weird ass default set they
return in ReST responses .xname..
A ``._ntable: dict[str, str]`` is available for mapping the
websocket pair name-keys and their http endpoint API (smh)
equivalents to the "alternative name" which is generally the one
we actually want to use XD
'''
if (
not self._pairs
or reload
):
await self.asset_pairs()
if not self._pairs:
pairs = await self.pair_info()
assert self._pairs == pairs
return self._AssetPairs
# table of all ws and rest keys to their alt-name values.
ntable: dict[str, str] = {}
for rest_key in list(pairs.keys()):
pair: Pair = pairs[rest_key]
altname = pair.altname
wsname = pair.wsname
ntable[altname] = ntable[rest_key] = ntable[wsname] = altname
# register the pair under all monikers, a giant flat
# surjection of all possible names to each info obj.
self._pairs[altname] = self._pairs[wsname] = pair
self._ntable.update(ntable)
return self._pairs
async def search_symbols(
self,
@ -556,20 +543,16 @@ class Client:
'''
if not len(self._pairs):
await self.get_mkt_pairs()
assert self._pairs, '`Client.get_mkt_pairs()` was never called!?'
await self.cache_symbols()
assert self._pairs, '`Client.cache_symbols()` was never called!?'
matches: dict[str, Pair] = match_from_pairs(
pairs=self._pairs,
query=pattern.upper(),
matches = fuzzy.extractBests(
pattern,
self._pairs,
score_cutoff=50,
)
# repack in .altname-keyed output table
return {
pair.altname: pair
for pair in matches.values()
}
# repack in dict form
return {item[0].altname: item[0] for item in matches}
async def bars(
self,
@ -649,10 +632,10 @@ class Client:
raise BrokerError(errmsg)
@classmethod
def to_bs_fqme(
def normalize_symbol(
cls,
pair_str: str
) -> str:
ticker: str
) -> tuple[str, Pair]:
'''
Normalize symbol names to to a 3x3 pair from the global
definition map which we build out from the data retreived from
@ -660,7 +643,7 @@ class Client:
'''
try:
return cls._altnames[pair_str.upper()].bs_fqme
return cls._ntable[ticker]
except KeyError as ke:
raise SymbolNotFound(f'kraken has no {ke.args[0]}')
@ -668,36 +651,21 @@ class Client:
@acm
async def get_client() -> Client:
conf: dict[str, Any] = get_config()
async with httpx.AsyncClient(
base_url=_url,
headers=_headers,
# TODO: is there a way to numerate this?
# https://www.python-httpx.org/advanced/clients/#why-use-a-client
# connections=4
) as trio_client:
conf = get_config()
if conf:
client = Client(
conf,
httpx_client=trio_client,
# TODO: don't break these up and just do internal
# conf lookups instead..
name=conf['key_descr'],
api_key=conf['api_key'],
secret=conf['secret']
)
else:
client = Client(
conf={},
httpx_client=trio_client,
)
client = Client({})
# at startup, load all symbols, and asset info in
# batch requests.
async with trio.open_nursery() as nurse:
nurse.start_soon(client.get_assets)
await client.get_mkt_pairs()
await client.cache_symbols()
yield client

View File

@ -24,6 +24,7 @@ from contextlib import (
)
from functools import partial
from itertools import count
import math
from pprint import pformat
import time
from typing import (
@ -34,16 +35,21 @@ from typing import (
)
from bidict import bidict
import pendulum
import trio
import tractor
from piker.accounting import (
Position,
Account,
PpTable,
Transaction,
TransactionLedger,
open_trade_ledger,
open_account,
open_pps,
get_likely_pair,
)
from piker.accounting._mktinfo import (
MktPair,
)
from piker.clearing import(
OrderDialogs,
@ -59,24 +65,18 @@ from piker.clearing._messages import (
BrokerdPosition,
BrokerdStatus,
)
from piker.brokers import (
open_cached_client,
)
from piker.data import open_symcache
from .api import (
log,
Client,
BrokerError,
get_client,
)
from .feed import (
get_mkt_info,
open_autorecon_ws,
NoBsWs,
stream_messages,
)
from .ledger import (
norm_trade_records,
verify_balances,
)
MsgUnion = Union[
BrokerdCancel,
@ -371,8 +371,7 @@ async def subscribe(
def trades2pps(
acnt: Account,
ledger: TransactionLedger,
table: PpTable,
acctid: str,
new_trans: dict[str, Transaction] = {},
@ -380,14 +379,13 @@ def trades2pps(
) -> list[BrokerdPosition]:
if new_trans:
updated = acnt.update_from_ledger(
updated = table.update_from_trans(
new_trans,
symcache=ledger.symcache,
)
log.info(f'Updated pps:\n{pformat(updated)}')
pp_entries, closed_pp_objs = acnt.dump_active()
pp_objs: dict[Union[str, int], Position] = acnt.pps
pp_entries, closed_pp_objs = table.dump_active()
pp_objs: dict[Union[str, int], Position] = table.pps
pps: dict[int, Position]
position_msgs: list[dict] = []
@ -401,13 +399,13 @@ def trades2pps(
# backend suffix prefixed but when
# reading accounts from ledgers we
# don't need it and/or it's prefixed
# in the section acnt.. we should
# in the section table.. we should
# just strip this from the message
# right since `.broker` is already
# included?
account='kraken.' + acctid,
symbol=p.mkt.fqme,
size=p.cumsize,
size=p.size,
avg_price=p.ppu,
currency='',
)
@ -418,7 +416,7 @@ def trades2pps(
# as little as possible. we need to either do
# these writes in another actor, or try out `trio`'s
# async file IO api?
acnt.write_config()
table.write_config()
return position_msgs
@ -429,12 +427,7 @@ async def open_trade_dialog(
) -> AsyncIterator[dict[str, Any]]:
async with (
# TODO: maybe bind these together and deliver
# a tuple from `.open_cached_client()`?
open_cached_client('kraken') as client,
open_symcache('kraken') as symcache,
):
async with get_client() as client:
# make ems flip to paper mode when no creds setup in
# `brokers.toml` B0
if not client._api_key:
@ -464,8 +457,8 @@ async def open_trade_dialog(
# - delete the *ABSOLUTE LAST* entry from account's corresponding
# trade ledgers file (NOTE this MUST be the last record
# delivered from the api ledger),
# - open you ``account.kraken.spot.toml`` and find that
# same tid and delete it from the pos's clears table,
# - open you ``pps.toml`` and find that same tid and delete it
# from the pp's clears table,
# - set this flag to `True`
#
# You should see an update come in after the order mode
@ -476,85 +469,172 @@ async def open_trade_dialog(
# update things correctly.
simulate_pp_update: bool = False
acnt: Account
table: PpTable
ledger: TransactionLedger
with (
open_account(
open_pps(
'kraken',
acctid,
write_on_exit=True,
) as acnt,
) as table,
open_trade_ledger(
'kraken',
acctid,
symcache=symcache,
) as ledger,
):
# TODO: loading ledger entries should all be done
# within a newly implemented `async with open_account()
# as acnt` where `Account.ledger: TransactionLedger`
# can be used to explicitily update and write the
# offline TOML files!
# ------ - ------
# MOL the init sequence is:
# - get `Account` (with presumed pre-loaded ledger done
# beind the scenes as part of ctx enter).
# - pull new trades from API, update the ledger with
# normalized to `Transaction` entries of those
# records, presumably (and implicitly) update the
# acnt state including expiries, positions,
# transfers..), and finally of course existing
# per-asset balances.
# - validate all pos and balances ensuring there's
# no seemingly noticeable discrepancies?
# transaction-ify the ledger entries
ledger_trans = await norm_trade_records(ledger)
# LOAD and transaction-ify the EXISTING LEDGER
ledger_trans: dict[str, Transaction] = await norm_trade_records(
ledger,
client,
api_name_set='xname',
)
if not acnt.pps:
acnt.update_from_ledger(
ledger_trans,
symcache=ledger.symcache,
)
acnt.write_config()
if not table.pps:
# NOTE: we can't use this since it first needs
# broker: str input support!
# table.update_from_trans(ledger.to_trans())
table.update_from_trans(ledger_trans)
table.write_config()
# TODO: eventually probably only load
# as far back as it seems is not deliverd in the
# most recent 50 trades and assume that by ordering we
# already have those records in the ledger?
tids2trades: dict[str, dict] = await client.get_trades()
# already have those records in the ledger.
tids2trades = await client.get_trades()
ledger.update(tids2trades)
if tids2trades:
ledger.write_config()
api_trans: dict[str, Transaction] = await norm_trade_records(
tids2trades,
client,
api_name_set='xname',
)
api_trans = await norm_trade_records(tids2trades)
# retrieve kraken reported balances
# and do diff with ledger to determine
# what amount of trades-transactions need
# to be reloaded.
balances: dict[str, float] = await client.get_balances()
balances = await client.get_balances()
verify_balances(
acnt,
for dst, size in balances.items():
# we don't care about tracking positions
# in the user's source fiat currency.
if (
dst == src_fiat
or not any(
dst in bs_mktid for bs_mktid in table.pps
)
):
log.warning(
f'Skipping balance `{dst}`:{size} for position calcs!'
)
continue
def has_pp(
dst: str,
size: float,
) -> Position | None:
src2dst: dict[str, str] = {}
for bs_mktid in table.pps:
likely_pair = get_likely_pair(
src_fiat,
balances,
client,
ledger,
ledger_trans,
api_trans,
dst,
bs_mktid,
)
if likely_pair:
src2dst[src_fiat] = dst
for src, dst in src2dst.items():
pair = f'{dst}{src_fiat}'
pp = table.pps.get(pair)
if (
pp
and math.isclose(pp.size, size)
):
return pp
elif (
size == 0
and pp.size
):
log.warning(
f'`kraken` account says you have a ZERO '
f'balance for {bs_mktid}:{pair}\n'
f'but piker seems to think `{pp.size}`\n'
'This is likely a discrepancy in piker '
'accounting if the above number is'
"large,' though it's likely to due lack"
"f tracking xfers fees.."
)
return pp
return None # signal no entry
pos = has_pp(dst, size)
if not pos:
# we have a balance for which there is no pp
# entry? so we have to likely update from the
# ledger.
updated = table.update_from_trans(ledger_trans)
log.info(f'Updated pps from ledger:\n{pformat(updated)}')
pos = has_pp(dst, size)
if (
not pos
and not simulate_pp_update
):
# try reloading from API
table.update_from_trans(api_trans)
pos = has_pp(dst, size)
if not pos:
# get transfers to make sense of abs balances.
# NOTE: we do this after ledger and API
# loading since we might not have an entry
# in the ``pps.toml`` for the necessary pair
# yet and thus this likely pair grabber will
# likely fail.
for bs_mktid in table.pps:
likely_pair = get_likely_pair(
src_fiat,
dst,
bs_mktid,
)
if likely_pair:
break
else:
raise ValueError(
'Could not find a position pair in '
'ledger for likely widthdrawal '
f'candidate: {dst}'
)
# XXX NOTE: only for simulate-testing a "new fill" since
if likely_pair:
# this was likely pp that had a withdrawal
# from the dst asset out of the account.
xfer_trans = await client.get_xfers(
dst,
# TODO: not all src assets are
# 3 chars long...
src_asset=likely_pair[3:],
)
if xfer_trans:
updated = table.update_from_trans(
xfer_trans,
cost_scalar=1,
)
log.info(
f'Updated {dst} from transfers:\n'
f'{pformat(updated)}'
)
if has_pp(dst, size):
raise ValueError(
'Could not reproduce balance:\n'
f'dst: {dst}, {size}\n'
)
# only for simulate-testing a "new fill" since
# otherwise we have to actually conduct a live clear.
if simulate_pp_update:
tid = list(tids2trades)[0]
@ -563,27 +643,25 @@ async def open_trade_dialog(
reqids2txids[0] = last_trade_dict['ordertxid']
ppmsgs: list[BrokerdPosition] = trades2pps(
acnt,
ledger,
table,
acctid,
)
# sync with EMS delivering pps and accounts
await ctx.started((ppmsgs, [acc_name]))
# TODO: ideally this blocks the this task
# as little as possible. we need to either do
# these writes in another actor, or try out `trio`'s
# async file IO api?
acnt.write_config()
table.write_config()
# Get websocket token for authenticated data stream
# Assert that a token was actually received.
resp = await client.endpoint('GetWebSocketsToken', {})
if err := resp.get('error'):
err = resp.get('error')
if err:
raise BrokerError(err)
# resp token for ws init
token: str = resp['result']['token']
token = resp['result']['token']
ws: NoBsWs
async with (
@ -612,35 +690,32 @@ async def open_trade_dialog(
# enter relay loop
await handle_order_updates(
client=client,
ws=ws,
ws_stream=stream,
ems_stream=ems_stream,
apiflows=apiflows,
ids=ids,
reqids2txids=reqids2txids,
acnt=acnt,
ledger=ledger,
acctid=acctid,
acc_name=acc_name,
token=token,
ws,
stream,
ems_stream,
apiflows,
ids,
reqids2txids,
table,
api_trans,
acctid,
acc_name,
token,
)
async def handle_order_updates(
client: Client, # only for pairs table needed in ledger proc
ws: NoBsWs,
ws_stream: AsyncIterator,
ems_stream: tractor.MsgStream,
apiflows: OrderDialogs,
ids: bidict[str, int],
reqids2txids: bidict[int, str],
acnt: Account,
table: PpTable,
# transaction records which will be updated
# on new trade clearing events (aka order "fills")
ledger: TransactionLedger,
# ledger_trans: dict[str, Transaction],
ledger_trans: dict[str, Transaction],
acctid: str,
acc_name: str,
token: str,
@ -658,7 +733,7 @@ async def handle_order_updates(
# TODO: turns out you get the fill events from the
# `openOrders` before you get this, so it might be better
# to do all fill/status/pos updates in that sub and just use
# to do all fill/status/pp updates in that sub and just use
# this one for ledger syncs?
# For eg. we could take the "last 50 trades" and do a diff
@ -700,8 +775,7 @@ async def handle_order_updates(
# if tid not in ledger_trans
}
for tid, trade in trades.items():
# assert tid not in ledger_trans
assert tid not in ledger
assert tid not in ledger_trans
txid = trade['ordertxid']
reqid = trade.get('userref')
@ -744,22 +818,12 @@ async def handle_order_updates(
)
await ems_stream.send(status_msg)
new_trans = await norm_trade_records(
trades,
client,
api_name_set='wsname',
new_trans = await norm_trade_records(trades)
ppmsgs = trades2pps(
table,
acctid,
new_trans,
)
ppmsgs: list[BrokerdPosition] = trades2pps(
acnt=acnt,
ledger=ledger,
acctid=acctid,
new_trans=new_trans,
)
# ppmsgs = trades2pps(
# acnt,
# acctid,
# new_trans,
# )
for pp_msg in ppmsgs:
await ems_stream.send(pp_msg)
@ -1119,3 +1183,36 @@ async def handle_order_updates(
})
case _:
log.warning(f'Unhandled trades update msg: {msg}')
async def norm_trade_records(
ledger: dict[str, Any],
) -> dict[str, Transaction]:
records: dict[str, Transaction] = {}
for tid, record in ledger.items():
size = float(record.get('vol')) * {
'buy': 1,
'sell': -1,
}[record['type']]
# we normalize to kraken's `altname` always..
bs_mktid: str = Client.normalize_symbol(record['pair'])
fqme = f'{bs_mktid.lower()}.kraken'
mkt: MktPair = (await get_mkt_info(fqme))[0]
records[tid] = Transaction(
fqme=fqme,
sym=mkt,
tid=tid,
size=size,
price=float(record['price']),
cost=float(record['fee']),
dt=pendulum.from_timestamp(float(record['time'])),
bs_mktid=bs_mktid,
)
return records

View File

@ -30,29 +30,38 @@ from typing import (
)
import time
from fuzzywuzzy import process as fuzzy
import numpy as np
import pendulum
from trio_typing import TaskStatus
import tractor
import trio
from piker.accounting._mktinfo import (
Asset,
MktPair,
unpack_fqme,
)
from piker.brokers import (
open_cached_client,
SymbolNotFound,
)
from piker._cacheables import (
async_lifo_cache,
)
from piker.brokers._util import (
BrokerError,
DataThrottle,
DataUnavailable,
)
from piker.types import Struct
from piker.data.types import Struct
from piker.data.validate import FeedInit
from piker.data._web_bs import open_autorecon_ws, NoBsWs
from .api import (
log,
Client,
Pair,
)
from .symbols import get_mkt_info
class OHLC(Struct, frozen=True):
@ -258,6 +267,62 @@ async def open_history_client(
yield get_ohlc, {'erlangs': 1, 'rate': 1}
@async_lifo_cache()
async def get_mkt_info(
fqme: str,
) -> tuple[MktPair, Pair]:
'''
Query for and return a `MktPair` and backend-native `Pair` (or
wtv else) info.
If more then one fqme is provided return a ``dict`` of native
key-strs to `MktPair`s.
'''
venue: str = 'spot'
expiry: str = ''
if '.kraken' in fqme:
broker, pair, venue, expiry = unpack_fqme(fqme)
venue: str = venue or 'spot'
if venue != 'spot':
raise SymbolNotFound(
'kraken only supports spot markets right now!\n'
f'{fqme}\n'
)
async with open_cached_client('kraken') as client:
# uppercase since kraken bs_mktid is always upper
bs_fqme, _, broker = fqme.partition('.')
pair_str: str = bs_fqme.upper()
bs_mktid: str = Client.normalize_symbol(pair_str)
pair: Pair = await client.pair_info(pair_str)
assets = client.assets
dst_asset: Asset = assets[pair.base]
src_asset: Asset = assets[pair.quote]
mkt = MktPair(
dst=dst_asset,
src=src_asset,
price_tick=pair.price_tick,
size_tick=pair.size_tick,
bs_mktid=bs_mktid,
expiry=expiry,
venue=venue or 'spot',
# TODO: futes
# _atype=_atype,
broker='kraken',
)
return mkt, pair
async def stream_quotes(
send_chan: trio.abc.SendChannel,
@ -413,3 +478,30 @@ async def stream_quotes(
log.warning(f'Unknown WSS message: {typ}, {quote}')
await send_chan.send({topic: quote})
@tractor.context
async def open_symbol_search(
ctx: tractor.Context,
) -> Client:
async with open_cached_client('kraken') as client:
# load all symbols locally for fast search
cache = await client.cache_symbols()
await ctx.started(cache)
async with ctx.open_stream() as stream:
async for pattern in stream:
matches = fuzzy.extractBests(
pattern,
cache,
score_cutoff=50,
)
# repack in dict form
await stream.send({
pair[0].altname: pair[0]
for pair in matches
})

View File

@ -1,269 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Trade transaction accounting and normalization.
'''
import math
from pprint import pformat
from typing import (
Any,
)
import pendulum
from piker.accounting import (
Transaction,
Position,
Account,
get_likely_pair,
TransactionLedger,
# MktPair,
)
from piker.types import Struct
from piker.data import (
SymbologyCache,
)
from .api import (
log,
Client,
Pair,
)
# from .feed import get_mkt_info
def norm_trade(
tid: str,
record: dict[str, Any],
# this is the dict that was returned from
# `Client.get_mkt_pairs()` and when running offline ledger
# processing from `.accounting`, this will be the table loaded
# into `SymbologyCache.pairs`.
pairs: dict[str, Struct],
symcache: SymbologyCache | None = None,
) -> Transaction:
size: float = float(record.get('vol')) * {
'buy': 1,
'sell': -1,
}[record['type']]
# NOTE: this value may be either the websocket OR the rest schema
# so we need to detect the key format and then choose the
# correct symbol lookup table to evetually get a ``Pair``..
# See internals of `Client.asset_pairs()` for deats!
src_pair_key: str = record['pair']
# XXX: kraken's data engineering is soo bad they require THREE
# different pair schemas (more or less seemingly tied to
# transport-APIs)..LITERALLY they return different market id
# pairs in the ledger endpoints vs. the websocket event subs..
# lookup pair using appropriately provided tabled depending
# on API-key-schema..
pair: Pair = pairs[src_pair_key]
fqme: str = pair.bs_fqme.lower() + '.kraken'
return Transaction(
fqme=fqme,
tid=tid,
size=size,
price=float(record['price']),
cost=float(record['fee']),
dt=pendulum.from_timestamp(float(record['time'])),
bs_mktid=pair.bs_mktid,
)
async def norm_trade_records(
ledger: dict[str, Any],
client: Client,
api_name_set: str = 'xname',
) -> dict[str, Transaction]:
'''
Loop through an input ``dict`` of trade records
and convert them to ``Transactions``.
'''
records: dict[str, Transaction] = {}
for tid, record in ledger.items():
# manual_fqme: str = f'{bs_mktid.lower()}.kraken'
# mkt: MktPair = (await get_mkt_info(manual_fqme))[0]
# fqme: str = mkt.fqme
# assert fqme == manual_fqme
pairs: dict[str, Pair] = {
'xname': client._AssetPairs,
'wsname': client._wsnames,
'altname': client._altnames,
}[api_name_set]
records[tid] = norm_trade(
tid,
record,
pairs=pairs,
)
return records
def has_pp(
acnt: Account,
src_fiat: str,
dst: str,
size: float,
) -> Position | None:
src2dst: dict[str, str] = {}
for bs_mktid in acnt.pps:
likely_pair = get_likely_pair(
src_fiat,
dst,
bs_mktid,
)
if likely_pair:
src2dst[src_fiat] = dst
for src, dst in src2dst.items():
pair: str = f'{dst}{src_fiat}'
pos: Position = acnt.pps.get(pair)
if (
pos
and math.isclose(pos.size, size)
):
return pos
elif (
size == 0
and pos.size
):
log.warning(
f'`kraken` account says you have a ZERO '
f'balance for {bs_mktid}:{pair}\n'
f'but piker seems to think `{pos.size}`\n'
'This is likely a discrepancy in piker '
'accounting if the above number is'
"large,' though it's likely to due lack"
"f tracking xfers fees.."
)
return pos
return None # indicate no entry found
# TODO: factor most of this "account updating from txns" into the
# the `Account` impl so has to provide for hiding the mostly
# cross-provider updates from txn sets
async def verify_balances(
acnt: Account,
src_fiat: str,
balances: dict[str, float],
client: Client,
ledger: TransactionLedger,
ledger_trans: dict[str, Transaction], # from toml
api_trans: dict[str, Transaction], # from API
simulate_pp_update: bool = False,
) -> None:
for dst, size in balances.items():
# we don't care about tracking positions
# in the user's source fiat currency.
if (
dst == src_fiat
or not any(
dst in bs_mktid for bs_mktid in acnt.pps
)
):
log.warning(
f'Skipping balance `{dst}`:{size} for position calcs!'
)
continue
# we have a balance for which there is no pos entry
# - we have to likely update from the ledger?
if not has_pp(acnt, src_fiat, dst, size):
updated = acnt.update_from_ledger(
ledger_trans,
symcache=ledger.symcache,
)
log.info(f'Updated pps from ledger:\n{pformat(updated)}')
# FIRST try reloading from API records
if (
not has_pp(acnt, src_fiat, dst, size)
and not simulate_pp_update
):
acnt.update_from_ledger(
api_trans,
symcache=ledger.symcache,
)
# get transfers to make sense of abs
# balances.
# NOTE: we do this after ledger and API
# loading since we might not have an
# entry in the
# ``account.kraken.spot.toml`` for the
# necessary pair yet and thus this
# likely pair grabber will likely fail.
if not has_pp(acnt, src_fiat, dst, size):
for bs_mktid in acnt.pps:
likely_pair: str | None = get_likely_pair(
src_fiat,
dst,
bs_mktid,
)
if likely_pair:
break
else:
raise ValueError(
'Could not find a position pair in '
'ledger for likely widthdrawal '
f'candidate: {dst}'
)
# this was likely pos that had a withdrawal
# from the dst asset out of the account.
if likely_pair:
xfer_trans = await client.get_xfers(
dst,
# TODO: not all src assets are
# 3 chars long...
src_asset=likely_pair[3:],
)
if xfer_trans:
updated = acnt.update_from_ledger(
xfer_trans,
cost_scalar=1,
symcache=ledger.symcache,
)
log.info(
f'Updated {dst} from transfers:\n'
f'{pformat(updated)}'
)
if has_pp(acnt, src_fiat, dst, size):
raise ValueError(
'Could not reproduce balance:\n'
f'dst: {dst}, {size}\n'
)

View File

@ -1,206 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Symbology defs and search.
'''
from decimal import Decimal
import tractor
from rapidfuzz import process as fuzzy
from piker._cacheables import (
async_lifo_cache,
)
from piker.accounting._mktinfo import (
digits_to_dec,
)
from piker.brokers import (
open_cached_client,
SymbolNotFound,
)
from piker.types import Struct
from piker.accounting._mktinfo import (
Asset,
MktPair,
unpack_fqme,
)
# https://www.kraken.com/features/api#get-tradable-pairs
class Pair(Struct):
xname: str # idiotic bs_mktid equiv i guess?
altname: str # alternate pair name
wsname: str # WebSocket pair name (if available)
aclass_base: str # asset class of base component
base: str # asset id of base component
aclass_quote: str # asset class of quote component
quote: str # asset id of quote component
lot: str # volume lot size
cost_decimals: int
costmin: float
pair_decimals: int # scaling decimal places for pair
lot_decimals: int # scaling decimal places for volume
# amount to multiply lot volume by to get currency volume
lot_multiplier: float
# array of leverage amounts available when buying
leverage_buy: list[int]
# array of leverage amounts available when selling
leverage_sell: list[int]
# fee schedule array in [volume, percent fee] tuples
fees: list[tuple[int, float]]
# maker fee schedule array in [volume, percent fee] tuples (if on
# maker/taker)
fees_maker: list[tuple[int, float]]
fee_volume_currency: str # volume discount currency
margin_call: str # margin call level
margin_stop: str # stop-out/liquidation margin level
ordermin: float # minimum order volume for pair
tick_size: float # min price step size
status: str
short_position_limit: float = 0
long_position_limit: float = float('inf')
# TODO: should we make this a literal NamespacePath ref?
ns_path: str = 'piker.brokers.kraken:Pair'
@property
def bs_mktid(self) -> str:
'''
Kraken seems to index it's market symbol sets in
transaction ledgers using the key returned from rest
queries.. so use that since apparently they can't
make up their minds on a better key set XD
'''
return self.xname
@property
def price_tick(self) -> Decimal:
return digits_to_dec(self.pair_decimals)
@property
def size_tick(self) -> Decimal:
return digits_to_dec(self.lot_decimals)
@property
def bs_dst_asset(self) -> str:
dst, _ = self.wsname.split('/')
return dst
@property
def bs_src_asset(self) -> str:
_, src = self.wsname.split('/')
return src
@property
def bs_fqme(self) -> str:
'''
Basically the `.altname` but with special '.' handling and
`.SPOT` suffix appending (for future multi-venue support).
'''
dst, src = self.wsname.split('/')
# XXX: omg for stupid shite like ETH2.S/ETH..
dst = dst.replace('.', '-')
return f'{dst}{src}.SPOT'
@tractor.context
async def open_symbol_search(ctx: tractor.Context) -> None:
async with open_cached_client('kraken') as client:
# load all symbols locally for fast search
cache = await client.get_mkt_pairs()
await ctx.started(cache)
async with ctx.open_stream() as stream:
async for pattern in stream:
await stream.send(
await client.search_symbols(pattern)
)
@async_lifo_cache()
async def get_mkt_info(
fqme: str,
) -> tuple[MktPair, Pair]:
'''
Query for and return a `MktPair` and backend-native `Pair` (or
wtv else) info.
If more then one fqme is provided return a ``dict`` of native
key-strs to `MktPair`s.
'''
venue: str = 'spot'
expiry: str = ''
if '.kraken' not in fqme:
fqme += '.kraken'
broker, pair, venue, expiry = unpack_fqme(fqme)
venue: str = venue or 'spot'
if venue.lower() != 'spot':
raise SymbolNotFound(
'kraken only supports spot markets right now!\n'
f'{fqme}\n'
)
async with open_cached_client('kraken') as client:
# uppercase since kraken bs_mktid is always upper
# bs_fqme, _, broker = fqme.partition('.')
# pair_str: str = bs_fqme.upper()
pair_str: str = f'{pair}.{venue}'
pair: Pair | None = client._pairs.get(pair_str.upper())
if not pair:
bs_fqme: str = client.to_bs_fqme(pair_str)
pair: Pair = client._pairs[bs_fqme]
if not (assets := client._assets):
assets: dict[str, Asset] = await client.get_assets()
dst_asset: Asset = assets[pair.bs_dst_asset]
src_asset: Asset = assets[pair.bs_src_asset]
mkt = MktPair(
dst=dst_asset,
src=src_asset,
price_tick=pair.price_tick,
size_tick=pair.size_tick,
bs_mktid=pair.bs_mktid,
expiry=expiry,
venue=venue or 'spot',
# TODO: futes
# _atype=_atype,
broker='kraken',
)
return mkt, pair

View File

@ -16,9 +16,10 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Kucoin cex API backend.
Kucoin broker backend
'''
from contextlib import (
asynccontextmanager as acm,
aclosing,
@ -40,8 +41,9 @@ from typing import (
import wsproto
from uuid import uuid4
from fuzzywuzzy import process as fuzzy
from trio_typing import TaskStatus
import httpx
import asks
from bidict import bidict
import numpy as np
import pendulum
@ -62,11 +64,8 @@ from piker._cacheables import (
)
from piker.log import get_logger
from piker.data.validate import FeedInit
from piker.types import Struct # NOTE, this is already a `tractor.msg.Struct`
from piker.data import (
def_iohlcv_fields,
match_from_pairs,
)
from piker.data.types import Struct
from piker.data import def_iohlcv_fields
from piker.data._web_bs import (
open_autorecon_ws,
NoBsWs,
@ -75,8 +74,6 @@ from ._util import DataUnavailable
log = get_logger(__name__)
_no_symcache: bool = True
class KucoinMktPair(Struct, frozen=True):
'''
@ -89,27 +86,18 @@ class KucoinMktPair(Struct, frozen=True):
@property
def price_tick(self) -> Decimal:
return Decimal(str(self.quoteIncrement))
return Decimal(str(self.baseIncrement))
baseMaxSize: float
baseMinSize: float
@property
def size_tick(self) -> Decimal:
return Decimal(str(self.quoteMinSize))
callauctionFirstStageStartTime: None|float
callauctionIsEnabled: bool
callauctionPriceCeiling: float|None
callauctionPriceFloor: float|None
callauctionSecondStageStartTime: float|None
callauctionThirdStageStartTime: float|None
return Decimal(str(self.baseMinSize))
enableTrading: bool
feeCategory: int
feeCurrency: str
isMarginEnabled: bool
makerFeeCoefficient: float
market: str
minFunds: float
name: str
@ -119,10 +107,7 @@ class KucoinMktPair(Struct, frozen=True):
quoteIncrement: float
quoteMaxSize: float
quoteMinSize: float
st: bool
symbol: str # our bs_mktid, kucoin's internal id
takerFeeCoefficient: float
tradingStartTime: float|None
class AccountTrade(Struct, frozen=True):
@ -222,12 +207,7 @@ def get_config() -> BrokerConfig | None:
class Client:
def __init__(
self,
httpx_client: httpx.AsyncClient,
) -> None:
self._http: httpx.AsyncClient = httpx_client
def __init__(self) -> None:
self._config: BrokerConfig | None = get_config()
self._pairs: dict[str, KucoinMktPair] = {}
self._fqmes2mktids: bidict[str, str] = bidict()
@ -242,24 +222,18 @@ class Client:
) -> dict[str, str | bytes]:
'''
Generate authenticated request headers:
Generate authenticated request headers
https://docs.kucoin.com/#authentication
https://www.kucoin.com/docs/basic-info/connection-method/authentication/creating-a-request
https://www.kucoin.com/docs/basic-info/connection-method/authentication/signing-a-message
'''
if not self._config:
raise ValueError(
'No config found when trying to send authenticated request'
)
'No config found when trying to send authenticated request')
str_to_sign = (
str(int(time.time() * 1000))
+
action
+
f'/api/{api}/{endpoint.lstrip("/")}'
+ action + f'/api/{api}/{endpoint.lstrip("/")}'
)
signature = base64.b64encode(
@ -270,7 +244,6 @@ class Client:
).digest()
)
# TODO: can we cache this between calls?
passphrase = base64.b64encode(
hmac.new(
self._config.key_secret.encode('utf-8'),
@ -292,10 +265,8 @@ class Client:
self,
action: Literal['POST', 'GET'],
endpoint: str,
api: str = 'v2',
headers: dict = {},
) -> Any:
'''
Generic request wrapper for Kucoin API
@ -308,19 +279,14 @@ class Client:
api,
)
req_meth: Callable = getattr(
self._http,
action.lower(),
)
res = await req_meth(
url=f'/{api}/{endpoint}',
headers=headers,
)
json: dict = res.json()
if (data := json.get('data')) is not None:
return data
api_url = f'https://api.kucoin.com/api/{api}/{endpoint}'
res = await asks.request(action, api_url, headers=headers)
json = res.json()
if 'data' in json:
return json['data']
else:
api_url: str = self._http.base_url
log.error(
f'Error making request to {api_url} ->\n'
f'{pformat(res)}'
@ -378,8 +344,8 @@ class Client:
currencies: dict[str, Currency] = {}
entries: list[dict] = await self._request(
'GET',
endpoint='currencies',
api='v1',
endpoint='currencies',
)
for entry in entries:
curr = Currency(**entry).copy()
@ -395,29 +361,20 @@ class Client:
dict[str, KucoinMktPair],
bidict[str, KucoinMktPair],
]:
entries = await self._request(
'GET',
endpoint='symbols',
)
entries = await self._request('GET', 'symbols')
log.info(f' {len(entries)} Kucoin market pairs fetched')
pairs: dict[str, KucoinMktPair] = {}
fqmes2mktids: bidict[str, str] = bidict()
for item in entries:
try:
pair = pairs[item['name']] = KucoinMktPair(**item)
except TypeError as te:
raise TypeError(
'`KucoinMktPair` and reponse fields do not match ??\n'
f'{KucoinMktPair.fields_diff(item)}\n'
) from te
fqmes2mktids[
item['name'].lower().replace('-', '')
] = pair.name
return pairs, fqmes2mktids
async def get_mkt_pairs(
async def cache_pairs(
self,
update: bool = False,
@ -445,27 +402,16 @@ class Client:
) -> dict[str, KucoinMktPair]:
'''
Use fuzzy search engine to match against pairs, deliver
matching ones.
Use fuzzy search to match against all market names.
'''
if not len(self._pairs):
await self.get_mkt_pairs()
assert self._pairs, '`Client.get_mkt_pairs()` was never called!?'
data = await self.cache_pairs()
matches: dict[str, KucoinMktPair] = match_from_pairs(
pairs=self._pairs,
# query=pattern.upper(),
query=pattern.upper(),
score_cutoff=35,
limit=limit,
matches = fuzzy.extractBests(
pattern, data, score_cutoff=35, limit=limit
)
# repack in dict form
return {
pair.name: pair
for pair in matches.values()
}
return {item[0].name: item[0] for item in matches}
async def last_trades(self, sym: str) -> list[AccountTrade]:
trades = await self._request(
@ -605,18 +551,10 @@ def fqme_to_kucoin_sym(
@acm
async def get_client() -> AsyncGenerator[Client, None]:
'''
Load an API `Client` preconfigured from user settings
client = Client()
'''
async with (
httpx.AsyncClient(
base_url='https://api.kucoin.com/api',
) as trio_client,
):
client = Client(httpx_client=trio_client)
async with trio.open_nursery() as tn:
tn.start_soon(client.get_mkt_pairs)
async with trio.open_nursery() as n:
n.start_soon(client.cache_pairs)
await client.get_currencies()
yield client
@ -628,7 +566,7 @@ async def open_symbol_search(
) -> None:
async with open_cached_client('kucoin') as client:
# load all symbols locally for fast search
await client.get_mkt_pairs()
await client.cache_pairs()
await ctx.started()
async with ctx.open_stream() as stream:
@ -655,7 +593,7 @@ async def open_ping_task(
await trio.sleep((ping_interval - 1000) / 1000)
await ws.send_msg({'id': connect_id, 'type': 'ping'})
log.warning('Starting ping task for kucoin ws connection')
log.info('Starting ping task for kucoin ws connection')
n.start_soon(ping_server)
yield
@ -667,21 +605,16 @@ async def open_ping_task(
async def get_mkt_info(
fqme: str,
) -> tuple[
MktPair,
KucoinMktPair,
]:
) -> tuple[MktPair, KucoinMktPair]:
'''
Query for and return both a `piker.accounting.MktPair` and
`KucoinMktPair` from provided `fqme: str`
(fully-qualified-market-endpoint).
Query for and return a `MktPair` and `KucoinMktPair`.
'''
async with open_cached_client('kucoin') as client:
# split off any fqme broker part
bs_fqme, _, broker = fqme.partition('.')
pairs: dict[str, KucoinMktPair] = await client.get_mkt_pairs()
pairs: dict[str, KucoinMktPair] = await client.cache_pairs()
try:
# likely search result key which is already in native mkt symbol form
@ -749,8 +682,6 @@ async def stream_quotes(
log.info(f'Starting up quote stream(s) for {symbols}')
for sym_str in symbols:
mkt: MktPair
pair: KucoinMktPair
mkt, pair = await get_mkt_info(sym_str)
init_msgs.append(
FeedInit(mkt_info=mkt)
@ -758,11 +689,7 @@ async def stream_quotes(
ws: NoBsWs
token, ping_interval = await client._get_ws_token()
log.info('API reported ping_interval: {ping_interval}\n')
connect_id: str = str(uuid4())
typ: str
quote: dict
connect_id = str(uuid4())
async with (
open_autorecon_ws(
(
@ -776,37 +703,20 @@ async def stream_quotes(
),
) as ws,
open_ping_task(ws, ping_interval, connect_id),
aclosing(
iter_normed_quotes(
ws, sym_str
)
) as iter_quotes,
aclosing(stream_messages(ws, sym_str)) as msg_gen,
):
typ, quote = await anext(iter_quotes)
typ, quote = await anext(msg_gen)
while typ != 'trade':
# take care to not unblock here until we get a real
# trade quote?
# ^TODO, remove this right?
# -[ ] what often blocks chart boot/new-feed switching
# since we'ere waiting for a live quote instead of just
# loading history afap..
# |_ XXX, not sure if we require a bit of rework to core
# feed init logic or if backends justg gotta be
# changed up.. feel like there was some causality
# dilema prolly only seen with IB too..
# while typ != 'trade':
# typ, quote = await anext(iter_quotes)
# trade quote
typ, quote = await anext(msg_gen)
task_status.started((init_msgs, quote))
feed_is_live.set()
# XXX NOTE, DO NOT include the `.<backend>` suffix!
# OW the sampling loop will not broadcast correctly..
# since `bus._subscribers.setdefault(bs_fqme, set())`
# is used inside `.data.open_feed_bus()` !!!
topic: str = mkt.bs_fqme
async for typ, quote in iter_quotes:
await send_chan.send({topic: quote})
async for typ, msg in msg_gen:
await send_chan.send({sym_str: msg})
@acm
@ -861,7 +771,7 @@ async def subscribe(
)
async def iter_normed_quotes(
async def stream_messages(
ws: NoBsWs,
sym: str,
@ -892,9 +802,6 @@ async def iter_normed_quotes(
yield 'trade', {
'symbol': sym,
# TODO, is 'last' even used elsewhere/a-good
# semantic? can't we just read the ticks with our
# .data.ticktools.frame_ticks()`/
'last': trade_data.price,
'brokerd_ts': last_trade_ts,
'ticks': [
@ -987,7 +894,7 @@ async def open_history_client(
if end_dt is None:
inow = round(time.time())
log.debug(
print(
f'difference in time between load and processing'
f'{inow - times[-1]}'
)

View File

@ -1,49 +0,0 @@
piker.clearing
______________
trade execution-n-control subsys for both live and paper trading as
well as algo-trading manual override/interaction across any backend
broker and data provider.
avail UIs
*********
order ctl
---------
the `piker.clearing` subsys is exposed mainly though
the `piker chart` GUI as a "chart trader" style UX and
is automatically enabled whenever a chart is opened.
.. ^TODO, more prose here!
the "manual" order control features are exposed via the
`piker.ui.order_mode` API and can pretty much always be
used (at least) in simulated-trading mode, aka "paper"-mode, and
the micro-manual is as follows:
``order_mode`` (
edge triggered activation by any of the following keys,
``mouse-click`` on y-level to submit at that price
):
- ``f``/ ``ctl-f`` to stage buy
- ``d``/ ``ctl-d`` to stage sell
- ``a`` to stage alert
``search_mode`` (
``ctl-l`` or ``ctl-space`` to open,
``ctl-c`` or ``ctl-space`` to close
) :
- begin typing to have symbol search automatically lookup
symbols from all loaded backend (broker) providers
- arrow keys and mouse click to navigate selection
- vi-like ``ctl-[hjkl]`` for navigation
position (pp) mgmt
------------------
you can also configure your position allocation limits from the
sidepane.
.. ^TODO, explain and provide tut once more refined!

View File

@ -27,28 +27,13 @@ from ._ems import (
open_brokerd_dialog,
)
from ._util import OrderDialogs
from ._messages import(
Order,
Status,
Cancel,
# TODO: deprecate these and replace end-2-end with
# client-side-dialog set above B)
# https://github.com/pikers/piker/issues/514
BrokerdPosition
)
__all__ = [
'FeeModel',
'open_ems',
'OrderClient',
'open_brokerd_dialog',
'OrderDialogs',
'Order',
'Status',
'Cancel',
'BrokerdPosition'
]

View File

@ -30,7 +30,7 @@ from tractor.trionics import broadcast_receiver
from ._util import (
log, # sub-sys logger
)
from piker.types import Struct
from ..data.types import Struct
from ..service import maybe_open_emsd
from ._messages import (
Order,

View File

@ -27,7 +27,7 @@ from contextlib import asynccontextmanager as acm
from decimal import Decimal
from math import isnan
from pprint import pformat
from time import time_ns
import time
from types import ModuleType
from typing import (
AsyncIterator,
@ -51,13 +51,12 @@ from ..accounting._mktinfo import (
unpack_fqme,
dec_digits,
)
from piker.types import Struct
from ..ui._notify import notify_from_ems_status_msg
from ..data import iterticks
from ..data.types import Struct
from ._messages import (
Order,
Status,
Error,
BrokerdCancel,
BrokerdOrder,
# BrokerdOrderAck,
@ -256,7 +255,7 @@ async def clear_dark_triggers(
action=action,
oid=oid,
account=account,
time_ns=time_ns(),
time_ns=time.time_ns(),
symbol=bfqme,
price=submit_price,
size=size,
@ -269,7 +268,7 @@ async def clear_dark_triggers(
# fallthrough logic
status = Status(
oid=oid, # ems dialog id
time_ns=time_ns(),
time_ns=time.time_ns(),
resp=resp,
req=cmd,
brokerd_msg=brokerd_msg,
@ -827,8 +826,8 @@ async def translate_and_relay_brokerd_events(
# keep pps per account up to date locally in ``emsd`` mem
# sym, broker = pos_msg.symbol, pos_msg.broker
# NOTE: translate to a FQME!
relay.positions.setdefault(
# NOTE: translate to a FQSN!
(broker, pos_msg.account),
{}
)[pos_msg.symbol] = pos_msg
@ -884,7 +883,7 @@ async def translate_and_relay_brokerd_events(
BrokerdCancel(
oid=oid,
reqid=reqid,
time_ns=time_ns(),
time_ns=time.time_ns(),
account=status_msg.req.account,
)
)
@ -899,6 +898,15 @@ async def translate_and_relay_brokerd_events(
continue
# BrokerdError
case {
'name': 'error',
'oid': oid, # ems order-dialog id
'reqid': reqid, # brokerd generated order-request id
}:
status_msg = book._active.get(oid)
msg = BrokerdError(**brokerd_msg)
log.error(fmsg) # XXX make one when it's blank?
# TODO: figure out how this will interact with EMS clients
# for ex. on an error do we react with a dark orders
# management response, like cancelling all dark orders?
@ -906,69 +914,23 @@ async def translate_and_relay_brokerd_events(
# some unexpected failure - something we need to think more
# about. In most default situations, with composed orders
# (ex. brackets), most brokers seem to use a oca policy.
case {
'name': 'error',
'oid': oid, # ems order-dialog id
'reqid': reqid, # brokerd generated order-request id
}:
if (
not oid
# try to lookup any order dialog by
# brokerd-side id..
and not (
oid := book._ems2brokerd_ids.inverse.get(reqid)
)
):
log.warning(
f'Rxed unusable error-msg:\n'
f'{brokerd_msg}'
)
continue
msg = BrokerdError(**brokerd_msg)
# NOTE: retreive the last client-side response
# OR create an error when we have no last msg /dialog
# on record
status_msg: Status
if not (status_msg := book._active.get(oid)):
status_msg = Error(
time_ns=time_ns(),
oid=oid,
reqid=reqid,
brokerd_msg=msg,
)
else:
# only modify last status if we have an active
# ongoing dialog..
# only relay to client side if we have an active
# ongoing dialog
if status_msg:
status_msg.resp = 'error'
status_msg.brokerd_msg = msg
book._active[oid] = status_msg
log.error(
'Translating brokerd error to status:\n'
f'{fmsg}'
f'{status_msg.to_dict()}'
)
if req := status_msg.req:
fqme: str = req.symbol
else:
bdmsg: Struct = status_msg.brokerd_msg
fqme: str = (
bdmsg.symbol # might be None
or
bdmsg.broker_details['flow']
# NOTE: what happens in empty case in the
# broadcast below? it's a problem?
.get('symbol', '')
)
await router.client_broadcast(
fqme,
status_msg.req.symbol,
status_msg,
)
else:
log.error(f'Error for unknown order flow:\n{msg}')
continue
# BrokerdStatus
case {
'name': 'status',
@ -1108,7 +1070,7 @@ async def translate_and_relay_brokerd_events(
status_msg.req = order
assert status_msg.src # source tag?
oid: str = str(status_msg.reqid)
oid = str(status_msg.reqid)
# attempt to avoid collisions
status_msg.reqid = oid
@ -1125,28 +1087,38 @@ async def translate_and_relay_brokerd_events(
status_msg,
)
# don't fall through
continue
# brokerd error
case {
'name': 'status',
'status': 'error',
}:
log.error(f'Broker error:\n{fmsg}')
# XXX: we presume the brokerd cancels its own order
continue
# TOO FAST ``BrokerdStatus`` that arrives
# before the ``BrokerdAck``.
# NOTE XXX: sometimes there is a race with the backend (like
# `ib` where the pending status will be relayed *before*
# the ack msg, in which case we just ignore the faster
case {
# XXX: sometimes there is a race with the backend (like
# `ib` where the pending stauts will be related before
# the ack, in which case we just ignore the faster
# pending msg and wait for our expected ack to arrive
# later (i.e. the first block below should enter).
case {
'name': 'status',
'status': status,
'reqid': reqid,
}:
msg = (
f'Unhandled broker status for dialog {reqid}:\n'
f'{pformat(brokerd_msg)}'
)
if (
oid := book._ems2brokerd_ids.inverse.get(reqid)
):
oid = book._ems2brokerd_ids.inverse.get(reqid)
msg = f'Unhandled broker status for dialog {reqid}:\n'
if oid:
status_msg = book._active.get(oid)
# status msg may not have been set yet or popped?
# NOTE: have seen a key error here on kraken
# clearable limits..
if status_msg := book._active.get(oid):
if status_msg:
msg += (
f'last status msg: {pformat(status_msg)}\n\n'
f'this msg:{fmsg}\n'
@ -1242,7 +1214,7 @@ async def process_client_order_cmds(
BrokerdCancel(
oid=oid,
reqid=reqid,
time_ns=time_ns(),
time_ns=time.time_ns(),
account=order.account,
)
)
@ -1317,7 +1289,7 @@ async def process_client_order_cmds(
msg = BrokerdOrder(
oid=oid, # no ib support for oids...
time_ns=time_ns(),
time_ns=time.time_ns(),
# if this is None, creates a new order
# otherwise will modify any existing one
@ -1335,7 +1307,7 @@ async def process_client_order_cmds(
oid=oid,
reqid=reqid,
resp='pending',
time_ns=time_ns(),
time_ns=time.time_ns(),
brokerd_msg=msg,
req=req,
)
@ -1452,7 +1424,7 @@ async def process_client_order_cmds(
status = Status(
resp=resp,
oid=oid,
time_ns=time_ns(),
time_ns=time.time_ns(),
req=req,
src='dark',
)

View File

@ -18,14 +18,39 @@
Clearing sub-system message and protocols.
"""
from __future__ import annotations
# from collections import (
# ChainMap,
# deque,
# )
from typing import (
Literal,
)
from msgspec import field
from piker.types import Struct
from ..data.types import Struct
# TODO: a composite for tracking msg flow on 2-legged
# dialogs.
# class Dialog(ChainMap):
# '''
# Msg collection abstraction to easily track the state changes of
# a msg flow in one high level, query-able and immutable construct.
# The main use case is to query data from a (long-running)
# msg-transaction-sequence
# '''
# def update(
# self,
# msg,
# ) -> None:
# self.maps.insert(0, msg.to_dict())
# def flatten(self) -> dict:
# return dict(self)
# TODO: ``msgspec`` stuff worth paying attention to:
@ -138,18 +163,6 @@ class Status(Struct):
brokerd_msg: dict = {}
class Error(Status):
resp: str = 'error'
# TODO: allow re-wrapping from existing (last) status?
@classmethod
def from_status(
cls,
msg: Status,
) -> Error:
...
# ---------------
# emsd -> brokerd
# ---------------
@ -213,7 +226,6 @@ class BrokerdOrderAck(Struct):
# emsd id originally sent in matching request msg
oid: str
# TODO: do we need this?
account: str = ''
name: str = 'ack'
@ -226,14 +238,13 @@ class BrokerdStatus(Struct):
'open',
'canceled',
'pending',
# 'error', # NOTE: use `BrokerdError`
'error',
'closed',
]
name: str = 'status'
oid: str = ''
# TODO: do we need this?
account: str | None = None,
name: str = 'status'
filled: float = 0.0
reason: str = ''
remaining: float = 0.0
@ -276,22 +287,20 @@ class BrokerdError(Struct):
This is still a TODO thing since we're not sure how to employ it yet.
'''
oid: str
reason: str
# TODO: drop this right?
symbol: str | None = None
oid: str | None = None
# if no brokerd order request was actually submitted (eg. we errored
# at the ``pikerd`` layer) then there will be ``reqid`` allocated.
reqid: str | None = None
reqid: int | str | None = None
name: str = 'error'
broker_details: dict = {}
# TODO: yeah, so we REALLY need to completely deprecate
# this and use the `.accounting.Position` msg-type instead..
class BrokerdPosition(Struct):
'''
Position update event from brokerd.

View File

@ -26,12 +26,10 @@ from contextlib import asynccontextmanager as acm
from datetime import datetime
from operator import itemgetter
import itertools
from pprint import pformat
import time
from typing import (
Callable,
)
from types import ModuleType
import uuid
from bidict import bidict
@ -39,26 +37,22 @@ import pendulum
import trio
import tractor
from piker.brokers import get_brokermod
from piker.service import find_service
from piker.accounting import (
Account,
from ..brokers import get_brokermod
from .. import data
from ..data.types import Struct
from ..accounting._mktinfo import (
MktPair,
)
from ..accounting import (
Position,
PpTable,
Transaction,
TransactionLedger,
open_account,
open_trade_ledger,
unpack_fqme,
open_pps,
)
from piker.data import (
Feed,
SymbologyCache,
iterticks,
open_feed,
open_symcache,
)
from piker.types import Struct
from ..data import iterticks
from ..accounting import unpack_fqme
from ._util import (
log, # sub-sys logger
get_console_log,
@ -83,10 +77,11 @@ class PaperBoi(Struct):
'''
broker: str
ems_trades_stream: tractor.MsgStream
acnt: Account
ppt: PpTable
ledger: TransactionLedger
fees: Callable
# map of paper "live" orders which be used
# to simulate fills based on paper engine settings
@ -268,42 +263,29 @@ class PaperBoi(Struct):
# we don't actually have any unique backend symbol ourselves
# other then this thing, our fqme address.
bs_mktid: str = fqme
if fees := self.fees:
cost: float = fees(price, size)
else:
cost: float = 0
t = Transaction(
fqme=fqme,
sym=self._mkts[fqme],
tid=oid,
size=size,
price=price,
cost=cost,
cost=0, # TODO: cost model
dt=pendulum.from_timestamp(fill_time_s),
bs_mktid=bs_mktid,
)
# update in-mem ledger and pos table
self.ledger.update_from_t(t)
self.acnt.update_from_ledger(
{oid: t},
symcache=self.ledger._symcache,
# XXX when a backend has no symcache support yet we can
# simply pass in the gmi() retreived table created
# during init :o
_mktmap_table=self._mkts,
)
self.ppt.update_from_trans({oid: t})
# transmit pp msg to ems
pp: Position = self.acnt.pps[bs_mktid]
pp = self.ppt.pps[bs_mktid]
pp_msg = BrokerdPosition(
broker=self.broker,
account='paper',
symbol=fqme,
size=pp.cumsize,
size=pp.size,
avg_price=pp.ppu,
# TODO: we need to look up the asset currency from
@ -314,7 +296,7 @@ class PaperBoi(Struct):
# write all updates to filesys immediately
# (adds latency but that works for simulation anyway)
self.ledger.write_config()
self.acnt.write_config()
self.ppt.write_config()
await self.ems_trades_stream.send(pp_msg)
@ -343,7 +325,6 @@ async def simulate_fills(
# this stream may eventually contain multiple symbols
async for quotes in quote_stream:
for sym, quote in quotes.items():
# print(sym)
for tick in iterticks(
quote,
# dark order price filter(s)
@ -559,76 +540,53 @@ async def open_trade_dialog(
# enable piker.clearing console log for *this* subactor
get_console_log(loglevel)
symcache: SymbologyCache
async with open_symcache(get_brokermod(broker)) as symcache:
acnt: Account
ppt: PpTable
ledger: TransactionLedger
with (
# TODO: probably do the symcache and ledger loading
# implicitly behind this? Deliver an account, and ledger
# pair or make the ledger an attr of the account?
open_account(
open_pps(
broker,
'paper',
write_on_exit=True,
) as acnt,
) as ppt,
open_trade_ledger(
broker,
'paper',
symcache=symcache,
) as ledger
):
# NOTE: WE MUST retreive market(pair) info from each
# backend broker since ledger entries (in their
# provider-native format) often don't contain necessary
# market info per trade record entry..
# FURTHER, if no fqme was passed in, we presume we're
# running in "ledger-sync-only mode" and thus we load
# mkt info for each symbol found in the ledger to
# an acnt table manually.
# NOTE: retreive market(pair) info from the backend broker
# since ledger entries (in their backend native format) often
# don't contain necessary market info per trade record entry..
# - if no fqme was passed in, we presume we're running in
# "ledger-sync-only mode" and thus we load mkt info for
# each symbol found in the ledger to a ppt table manually.
# TODO: how to process ledger info from backends?
# - should we be rolling our own actor-cached version of these
# client API refs or using portal IPC to send requests to the
# existing brokerd daemon?
# - alternatively we can possibly expect and use
# a `.broker.ledger.norm_trade()` ep?
brokermod: ModuleType = get_brokermod(broker)
gmi: Callable = getattr(brokermod, 'get_mkt_info', None)
# a `.broker.norm_trade_records()` ep?
brokermod = get_brokermod(broker)
gmi = getattr(brokermod, 'get_mkt_info', None)
# update all transactions with mkt info before
# loading any pps
mkt_by_fqme: dict[str, MktPair] = {}
if (
fqme
and fqme not in symcache.mktmaps
):
log.warning(
f'Symcache for {broker} has no `{fqme}` entry?\n'
'Manually requesting mkt map data via `.get_mkt_info()`..'
)
if fqme:
bs_fqme, _, broker = fqme.rpartition('.')
mkt, pair = await gmi(bs_fqme)
mkt, _ = await brokermod.get_mkt_info(bs_fqme)
mkt_by_fqme[mkt.fqme] = mkt
# for each sym in the ledger load its `MktPair` info
# for each sym in the ledger load it's `MktPair` info
for tid, txdict in ledger.data.items():
l_fqme: str = txdict.get('fqme') or txdict['fqsn']
if (
gmi
and l_fqme not in symcache.mktmaps
and l_fqme not in mkt_by_fqme
):
log.warning(
f'Symcache for {broker} has no `{l_fqme}` entry?\n'
'Manually requesting mkt map data via `.get_mkt_info()`..'
)
mkt, pair = await gmi(
mkt, pair = await brokermod.get_mkt_info(
l_fqme.rstrip(f'.{broker}'),
)
mkt_by_fqme[l_fqme] = mkt
@ -645,26 +603,17 @@ async def open_trade_dialog(
# update pos table from ledger history and provide a ``MktPair``
# lookup for internal position accounting calcs.
acnt.update_from_ledger(
ledger,
# NOTE: if the symcache fails on fqme lookup
# (either sycache not yet supported or not filled
# in) use manually constructed table from calling
# the `.get_mkt_info()` provider EP above.
_mktmap_table=mkt_by_fqme,
)
ppt.update_from_trans(ledger.to_trans(mkt_by_fqme=mkt_by_fqme))
pp_msgs: list[BrokerdPosition] = []
pos: Position
token: str # f'{symbol}.{self.broker}'
for token, pos in acnt.pps.items():
for token, pos in ppt.pps.items():
pp_msgs.append(BrokerdPosition(
broker=broker,
account='paper',
symbol=pos.mkt.fqme,
size=pos.cumsize,
size=pos.size,
avg_price=pos.ppu,
))
@ -675,7 +624,7 @@ async def open_trade_dialog(
# write new positions state in case ledger was
# newer then that tracked in pps.toml
acnt.write_config()
ppt.write_config()
# exit early since no fqme was passed,
# normally this case is just to load
@ -688,28 +637,15 @@ async def open_trade_dialog(
await trio.sleep_forever()
return
feed: Feed
async with (
open_feed(
data.open_feed(
[fqme],
loglevel=loglevel,
) as feed,
):
# sanity check all the mkt infos
for fqme, flume in feed.flumes.items():
mkt: MktPair = symcache.mktmaps.get(fqme) or mkt_by_fqme[fqme]
if mkt != flume.mkt:
diff: tuple = mkt - flume.mkt
log.warning(
'MktPair sig mismatch?\n'
f'{pformat(diff)}'
)
get_cost: Callable = getattr(
brokermod,
'get_cost',
None,
)
assert mkt_by_fqme[fqme] == flume.mkt
async with (
ctx.open_stream() as ems_stream,
@ -718,9 +654,8 @@ async def open_trade_dialog(
client = PaperBoi(
broker=broker,
ems_trades_stream=ems_stream,
acnt=acnt,
ppt=ppt,
ledger=ledger,
fees=get_cost,
_buys=_buys,
_sells=_sells,
@ -761,7 +696,7 @@ async def open_paperboi(
service_name = f'paperboi.{broker}'
async with (
find_service(service_name) as portal,
tractor.find_actor(service_name) as portal,
tractor.open_nursery() as an,
):
# NOTE: only spawn if no paperboi already is up since we likely
@ -784,59 +719,7 @@ async def open_paperboi(
) as (ctx, first):
yield ctx, first
# ALWAYS tear down connection AND any newly spawned
# paperboi actor on exit!
# tear down connection and any spawned actor on exit
await ctx.cancel()
if we_spawned:
await portal.cancel_actor()
def norm_trade(
tid: str,
txdict: dict,
pairs: dict[str, Struct],
symcache: SymbologyCache | None = None,
brokermod: ModuleType | None = None,
) -> Transaction:
from pendulum import (
DateTime,
parse,
)
# special field handling for datetimes
# to ensure pendulum is used!
dt: DateTime = parse(txdict['dt'])
expiry: str | None = txdict.get('expiry')
fqme: str = txdict.get('fqme') or txdict.pop('fqsn')
price: float = txdict['price']
size: float = txdict['size']
cost: float = txdict.get('cost', 0)
if (
brokermod
and (get_cost := getattr(
brokermod,
'get_cost',
False,
))
):
cost = get_cost(
price,
size,
is_taker=True,
)
return Transaction(
fqme=fqme,
tid=txdict['tid'],
dt=dt,
price=price,
size=size,
cost=cost,
bs_mktid=txdict['bs_mktid'],
expiry=parse(expiry) if expiry else None,
etype='clear',
)

View File

@ -25,7 +25,7 @@ from ..log import (
get_logger,
get_console_log,
)
from piker.types import Struct
from piker.data.types import Struct
subsys: str = 'piker.clearing'
log = get_logger(subsys)
@ -36,6 +36,9 @@ get_console_log = partial(
)
# TODO: use this in other backends like kraken which currently has
# a less formalized version more or less:
# `apiflows[reqid].maps.append(status_msg.to_dict())`
class OrderDialogs(Struct):
'''
Order control dialog (and thus transaction) tracking via

View File

@ -1,33 +1,30 @@
# piker: trading gear for hackers
# Copyright (C) 2018-present Tyler Goodlet
# (in stewardship for pikers, everywhere.)
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of pikers)
# This program is free software: you can redistribute it and/or
# modify it under the terms of the GNU Affero General Public
# License as published by the Free Software Foundation, either
# version 3 of the License, or (at your option) any later version.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Affero General Public License for more details.
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public
# License along with this program. If not, see
# <https://www.gnu.org/licenses/>.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
CLI commons.
'''
import os
# from contextlib import AsyncExitStack
from contextlib import AsyncExitStack
from types import ModuleType
import click
import trio
import tractor
from tractor._multiaddr import parse_maddr
from ..log import (
get_console_log,
@ -45,97 +42,35 @@ from .. import config
log = get_logger('piker.cli')
def load_trans_eps(
network: dict | None = None,
maddrs: list[tuple] | None = None,
) -> dict[str, dict[str, dict]]:
# transport-oriented endpoint multi-addresses
eps: dict[
str, # service name, eg. `pikerd`, `emsd`..
# libp2p style multi-addresses parsed into prot layers
list[dict[str, str | int]]
] = {}
if (
network
and not maddrs
):
# load network section and (attempt to) connect all endpoints
# which are reachable B)
for key, maddrs in network.items():
match key:
# TODO: resolve table across multiple discov
# prots Bo
case 'resolv':
pass
case 'pikerd':
dname: str = key
for maddr in maddrs:
layers: dict = parse_maddr(maddr)
eps.setdefault(
dname,
[],
).append(layers)
elif maddrs:
# presume user is manually specifying the root actor ep.
eps['pikerd'] = [parse_maddr(maddr)]
return eps
@click.command()
@click.option('--loglevel', '-l', default='warning', help='Logging level')
@click.option('--tl', is_flag=True, help='Enable tractor logging')
@click.option('--pdb', is_flag=True, help='Enable tractor debug mode')
@click.option('--host', '-h', default=None, help='Host addr to bind')
@click.option('--port', '-p', default=None, help='Port number to bind')
@click.option(
'--loglevel',
'-l',
default='warning',
help='Logging level',
)
@click.option(
'--tl',
'--tsdb',
is_flag=True,
help='Enable tractor-runtime logs',
help='Enable local ``marketstore`` instance'
)
@click.option(
'--pdb',
'--es',
is_flag=True,
help='Enable tractor debug mode',
help='Enable local ``elasticsearch`` instance'
)
@click.option(
'--maddr',
'-m',
default=None,
help='Multiaddrs to bind or contact',
)
# @click.option(
# '--tsdb',
# is_flag=True,
# help='Enable local ``marketstore`` instance'
# )
# @click.option(
# '--es',
# is_flag=True,
# help='Enable local ``elasticsearch`` instance'
# )
def pikerd(
maddr: list[str] | None,
loglevel: str,
host: str,
port: int,
tl: bool,
pdb: bool,
# tsdb: bool,
# es: bool,
tsdb: bool,
es: bool,
):
'''
Spawn the piker broker-daemon.
'''
from tractor.devx import maybe_open_crash_handler
with maybe_open_crash_handler(pdb=pdb):
log = get_console_log(loglevel, name='cli')
if pdb:
@ -147,32 +82,12 @@ def pikerd(
"\n"
))
# service-actor registry endpoint socket-address set
regaddrs: list[tuple[str, int]] = []
conf, _ = config.load(
conf_name='conf',
reg_addr: None | tuple[str, int] = None
if host or port:
reg_addr = (
host or _default_registry_host,
int(port) or _default_registry_port,
)
network: dict = conf.get('network')
if (
network is None
and not maddr
):
regaddrs = [(
_default_registry_host,
_default_registry_port,
)]
else:
eps: dict = load_trans_eps(
network,
maddr,
)
for layers in eps['pikerd']:
regaddrs.append((
layers['ipv4']['addr'],
layers['tcp']['port'],
))
from .. import service
@ -181,35 +96,31 @@ def pikerd(
async with (
service.open_pikerd(
registry_addrs=regaddrs,
loglevel=loglevel,
debug_mode=pdb,
registry_addr=reg_addr,
) as service_mngr, # normally delivers a ``Services`` handle
# AsyncExitStack() as stack,
AsyncExitStack() as stack,
):
# TODO: spawn all other sub-actor daemons according to
# multiaddress endpoint spec defined by user config
assert service_mngr
if tsdb:
dname, conf = await stack.enter_async_context(
service.marketstore.start_ahab_daemon(
service_mngr,
loglevel=loglevel,
)
)
log.info(f'TSDB `{dname}` up with conf:\n{conf}')
# if tsdb:
# dname, conf = await stack.enter_async_context(
# service.marketstore.start_ahab_daemon(
# service_mngr,
# loglevel=loglevel,
# )
# )
# log.info(f'TSDB `{dname}` up with conf:\n{conf}')
# if es:
# dname, conf = await stack.enter_async_context(
# service.elastic.start_ahab_daemon(
# service_mngr,
# loglevel=loglevel,
# )
# )
# log.info(f'DB `{dname}` up with conf:\n{conf}')
if es:
dname, conf = await stack.enter_async_context(
service.elastic.start_ahab_daemon(
service_mngr,
loglevel=loglevel,
)
)
log.info(f'DB `{dname}` up with conf:\n{conf}')
await trio.sleep_forever()
@ -226,24 +137,8 @@ def pikerd(
@click.option('--loglevel', '-l', default='warning', help='Logging level')
@click.option('--tl', is_flag=True, help='Enable tractor logging')
@click.option('--configdir', '-c', help='Configuration directory')
@click.option(
'--pdb',
is_flag=True,
help='Enable runtime debug mode ',
)
@click.option(
'--maddr',
'-m',
default=None,
multiple=True,
help='Multiaddr to bind',
)
@click.option(
'--regaddr',
'-r',
default=None,
help='Registrar addr to contact',
)
@click.option('--host', '-h', default=None, help='Host addr to bind')
@click.option('--port', '-p', default=None, help='Port number to bind')
@click.pass_context
def cli(
ctx: click.Context,
@ -251,11 +146,8 @@ def cli(
loglevel: str,
tl: bool,
configdir: str,
pdb: bool,
# TODO: make these list[str] with multiple -m maddr0 -m maddr1
maddr: list[str],
regaddr: str,
host: str,
port: int,
) -> None:
if configdir is not None:
@ -276,20 +168,12 @@ def cli(
}
assert brokermods
# TODO: load endpoints from `conf::[network].pikerd`
# - pikerd vs. regd, separate registry daemon?
# - expose datad vs. brokerd?
# - bind emsd with certain perms on public iface?
regaddrs: list[tuple[str, int]] = regaddr or [(
_default_registry_host,
_default_registry_port,
)]
# TODO: factor [network] section parsing out from pikerd
# above and call it here as well.
# if maddr:
# for addr in maddr:
# layers: dict = parse_maddr(addr)
reg_addr: None | tuple[str, int] = None
if host or port:
reg_addr = (
host or _default_registry_host,
int(port) or _default_registry_port,
)
ctx.obj.update({
'brokers': brokers,
@ -299,12 +183,7 @@ def cli(
'log': get_console_log(loglevel),
'confdir': config._config_dir,
'wl_path': config._watchlists_data_path,
'registry_addrs': regaddrs,
'pdb': pdb, # debug mode flag
# TODO: endpoint parsing, pinging and binding
# on no existing server.
# 'maddrs': maddr,
'registry_addr': reg_addr,
})
# allow enabling same loglevel in ``tractor`` machinery
@ -351,7 +230,8 @@ def services(config, tl, ports):
def _load_clis() -> None:
# from ..service import elastic # noqa
from ..service import marketstore # noqa
from ..service import elastic # noqa
from ..brokers import cli # noqa
from ..ui import cli # noqa
from ..watchlists import cli # noqa

View File

@ -104,15 +104,14 @@ def get_app_dir(
# `tractor`) with the testing dir and check for it whenever we
# detect `pytest` is being used (which it isn't under normal
# operation).
# if "pytest" in sys.modules:
# import tractor
# actor = tractor.current_actor(err_on_no_runtime=False)
# if actor: # runtime is up
# rvs = tractor._state._runtime_vars
# import pdbp; pdbp.set_trace()
# testdirpath = Path(rvs['piker_vars']['piker_test_dir'])
# assert testdirpath.exists(), 'piker test harness might be borked!?'
# app_name = str(testdirpath)
if "pytest" in sys.modules:
import tractor
actor = tractor.current_actor(err_on_no_runtime=False)
if actor: # runtime is up
rvs = tractor._state._runtime_vars
testdirpath = Path(rvs['piker_vars']['piker_test_dir'])
assert testdirpath.exists(), 'piker test harness might be borked!?'
app_name = str(testdirpath)
if platform.system() == 'Windows':
key = "APPDATA" if roaming else "LOCALAPPDATA"
@ -135,19 +134,14 @@ def get_app_dir(
_click_config_dir: Path = Path(get_app_dir('piker'))
_config_dir: Path = _click_config_dir
_parent_user: str = os.environ.get('SUDO_USER')
# NOTE: when using `sudo` we attempt to determine the non-root user
# and still use their normal config dir.
if (
(_parent_user := os.environ.get('SUDO_USER'))
and
_parent_user != 'root'
):
if _parent_user:
non_root_user_dir = Path(
os.path.expanduser(f'~{_parent_user}')
)
root: str = 'root'
_ccds: str = str(_click_config_dir) # click config dir as string
_ccds: str = str(_click_config_dir) # click config dir string
i_tail: int = int(_ccds.rfind(root) + len(root))
_config_dir = (
non_root_user_dir
@ -252,8 +246,7 @@ def repodir() -> Path:
def load(
# NOTE: always appended with .toml suffix
conf_name: str = 'conf',
conf_name: str = 'brokers', # appended with .toml suffix
path: Path | None = None,
decode: Callable[
@ -364,9 +357,7 @@ def load_accounts(
) -> bidict[str, str | None]:
conf, path = load(
conf_name='brokers',
)
conf, path = load()
accounts = bidict()
for provider_name, section in conf.items():
accounts_section = section.get('accounts')
@ -387,3 +378,51 @@ def load_accounts(
accounts['paper'] = None
return accounts
# XXX: Recursive getting & setting
def get_value(_dict, _section):
subs = _section.split('.')
if len(subs) > 1:
return get_value(
_dict[subs[0]],
'.'.join(subs[1:]),
)
else:
return _dict[_section]
def set_value(_dict, _section, val):
subs = _section.split('.')
if len(subs) > 1:
if subs[0] not in _dict:
_dict[subs[0]] = {}
return set_value(
_dict[subs[0]],
'.'.join(subs[1:]),
val
)
else:
_dict[_section] = val
def del_value(_dict, _section):
subs = _section.split('.')
if len(subs) > 1:
if subs[0] not in _dict:
return
return del_value(
_dict[subs[0]],
'.'.join(subs[1:])
)
else:
if _section not in _dict:
return
del _dict[_section]

View File

@ -39,33 +39,18 @@ from .feed import (
open_feed,
)
from .flows import Flume
from ._symcache import (
SymbologyCache,
open_symcache,
get_symcache,
match_from_pairs,
)
from ._sampling import open_sample_stream
from ..types import Struct
__all__: list[str] = [
__all__ = [
'Flume',
'Feed',
'open_feed',
'ShmArray',
'iterticks',
'maybe_open_shm_array',
'match_from_pairs',
'attach_shm_array',
'open_shm_array',
'get_shm_token',
'def_iohlcv_fields',
'def_ohlcv_fields',
'open_symcache',
'open_sample_stream',
'get_symcache',
'Struct',
'SymbologyCache',
'types',
]

View File

@ -1,5 +1,5 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
@ -13,10 +13,10 @@
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
"""
Pre-(path)-graphics formatted x/y nd/1d rendering subsystem.
'''
"""
from __future__ import annotations
from typing import (
Optional,
@ -39,12 +39,7 @@ if TYPE_CHECKING:
from ._dataviz import (
Viz,
)
from piker.toolz import Profiler
# default gap between bars: "bar gap multiplier"
# - 0.5 is no overlap between OC arms,
# - 1.0 is full overlap on each neighbor sample
BGM: float = 0.16
from .._profile import Profiler
class IncrementalFormatter(msgspec.Struct):
@ -518,7 +513,6 @@ class IncrementalFormatter(msgspec.Struct):
class OHLCBarsFmtr(IncrementalFormatter):
x_offset: np.ndarray = np.array([
-0.5,
0,
@ -610,9 +604,8 @@ class OHLCBarsFmtr(IncrementalFormatter):
vr: tuple[int, int],
start: int = 0, # XXX: do we need this?
# 0.5 is no overlap between arms, 1.0 is full overlap
gap: float = BGM,
w: float = 0.16,
) -> tuple[
np.ndarray,
@ -629,7 +622,7 @@ class OHLCBarsFmtr(IncrementalFormatter):
array[:-1],
start,
bar_w=self.index_step_size,
bar_gap=gap * self.index_step_size,
bar_gap=w * self.index_step_size,
# XXX: don't ask, due to a ``numba`` bug..
use_time_index=(self.index_field == 'time'),

View File

@ -17,6 +17,11 @@
Super fast ``QPainterPath`` generation related operator routines.
"""
from math import (
ceil,
floor,
)
import numpy as np
from numpy.lib import recfunctions as rfn
from numba import (
@ -30,6 +35,11 @@ from numba import (
# TODO: for ``numba`` typing..
# from ._source import numba_ohlc_dtype
from ._m4 import ds_m4
from .._profile import (
Profiler,
pg_profile_enabled,
ms_slower_then,
)
def xy_downsample(
@ -125,7 +135,7 @@ def path_arrays_from_ohlc(
half_w: float = bar_w/2
# TODO: report bug for assert @
# ../piker/env/lib/python3.8/site-packages/numba/core/typing/builtins.py:991
# /home/goodboy/repos/piker/env/lib/python3.8/site-packages/numba/core/typing/builtins.py:991
for i, q in enumerate(data[start:], start):
open = q['open']
@ -227,20 +237,20 @@ def trace_hl(
for i in range(hl.size):
row = hl[i]
lo, hi = row['low'], row['high']
l, h = row['low'], row['high']
up_diff = hi - last_l
down_diff = last_h - lo
up_diff = h - last_l
down_diff = last_h - l
if up_diff > down_diff:
out[2*i + 1] = hi
out[2*i + 1] = h
out[2*i] = last_l
else:
out[2*i + 1] = lo
out[2*i + 1] = l
out[2*i] = last_h
last_l = lo
last_h = hi
last_l = l
last_h = h
x[2*i] = int(i) - margin
x[2*i + 1] = int(i) + margin

View File

@ -33,11 +33,6 @@ from typing import (
)
import tractor
from tractor import (
Context,
MsgStream,
Channel,
)
from tractor.trionics import (
maybe_open_nursery,
)
@ -58,10 +53,7 @@ if TYPE_CHECKING:
from ._sharedmem import (
ShmArray,
)
from .feed import (
_FeedsBus,
Sub,
)
from .feed import _FeedsBus
# highest frequency sample step is 1 second by default, though in
@ -102,7 +94,7 @@ class Sampler:
float,
list[
float,
set[MsgStream]
set[tractor.MsgStream]
],
] = defaultdict(
lambda: [
@ -266,8 +258,8 @@ class Sampler:
f'broadcasting {period_s} -> {last_ts}\n'
# f'consumers: {subs}'
)
borked: set[MsgStream] = set()
sent: set[MsgStream] = set()
borked: set[tractor.MsgStream] = set()
sent: set[tractor.MsgStream] = set()
while True:
try:
for stream in (subs - sent):
@ -322,7 +314,7 @@ class Sampler:
@tractor.context
async def register_with_sampler(
ctx: Context,
ctx: tractor.Context,
period_s: float,
shms_by_period: dict[float, dict] | None = None,
@ -657,7 +649,12 @@ async def sample_and_broadcast(
# eventually block this producer end of the feed and
# thus other consumers still attached.
sub_key: str = broker_symbol.lower()
subs: set[Sub] = bus.get_subs(sub_key)
subs: list[
tuple[
tractor.MsgStream | trio.MemorySendChannel,
float | None, # tick throttle in Hz
]
] = bus.get_subs(sub_key)
# NOTE: by default the broker backend doesn't append
# it's own "name" into the fqme schema (but maybe it
@ -666,40 +663,34 @@ async def sample_and_broadcast(
fqme: str = f'{broker_symbol}.{brokername}'
lags: int = 0
# XXX TODO XXX: speed up this loop in an AOT compiled
# lang (like rust or nim or zig)!
# AND/OR instead of doing a fan out to TCP sockets
# here, we add a shm-style tick queue which readers can
# pull from instead of placing the burden of broadcast
# on solely on this `brokerd` actor. see issues:
# TODO: speed up this loop in an AOT compiled lang (like
# rust or nim or zig) and/or instead of doing a fan out to
# TCP sockets here, we add a shm-style tick queue which
# readers can pull from instead of placing the burden of
# broadcast on solely on this `brokerd` actor. see issues:
# - https://github.com/pikers/piker/issues/98
# - https://github.com/pikers/piker/issues/107
# for (stream, tick_throttle) in subs.copy():
for sub in subs.copy():
ipc: MsgStream = sub.ipc
throttle: float = sub.throttle_rate
for (stream, tick_throttle) in subs.copy():
try:
with trio.move_on_after(0.2) as cs:
if throttle:
send_chan: trio.abc.SendChannel = sub.send_chan
if tick_throttle:
# this is a send mem chan that likely
# pushes to the ``uniform_rate_send()`` below.
try:
send_chan.send_nowait(
stream.send_nowait(
(fqme, quote)
)
except trio.WouldBlock:
overruns[sub_key] += 1
ctx: Context = ipc._ctx
chan: Channel = ctx.chan
ctx = stream._ctx
chan = ctx.chan
log.warning(
f'Feed OVERRUN {sub_key}'
'@{bus.brokername} -> \n'
f'feed @ {chan.uid}\n'
f'throttle = {throttle} Hz'
f'throttle = {tick_throttle} Hz'
)
if overruns[sub_key] > 6:
@ -716,33 +707,33 @@ async def sample_and_broadcast(
f'{sub_key}:'
f'{ctx.cid}@{chan.uid}'
)
await ipc.aclose()
await stream.aclose()
raise trio.BrokenResourceError
else:
await ipc.send(
await stream.send(
{fqme: quote}
)
if cs.cancelled_caught:
lags += 1
if lags > 10:
await tractor.pause()
await tractor.breakpoint()
except (
trio.BrokenResourceError,
trio.ClosedResourceError,
trio.EndOfChannel,
):
ctx: Context = ipc._ctx
chan: Channel = ctx.chan
ctx = stream._ctx
chan = ctx.chan
if ctx:
log.warning(
'Dropped `brokerd`-quotes-feed connection:\n'
f'{broker_symbol}:'
f'{ctx.cid}@{chan.uid}'
)
if sub.throttle_rate:
assert ipc._closed
if tick_throttle:
assert stream._closed
# XXX: do we need to deregister here
# if it's done in the fee bus code?
@ -751,7 +742,7 @@ async def sample_and_broadcast(
# since there seems to be some kinda race..
bus.remove_subs(
sub_key,
{sub},
{(stream, tick_throttle)},
)
@ -759,7 +750,7 @@ async def uniform_rate_send(
rate: float,
quote_stream: trio.abc.ReceiveChannel,
stream: MsgStream,
stream: tractor.MsgStream,
task_status: TaskStatus = trio.TASK_STATUS_IGNORED,

View File

@ -34,7 +34,7 @@ import tractor
from ._util import log
from ._source import def_iohlcv_fields
from piker.types import Struct
from .types import Struct
def cuckoff_mantracker():

View File

@ -1,510 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Mega-simple symbology cache via TOML files.
Allow backend data providers and/or brokers to stash their
symbology sets (aka the meta data we normalize into our
`.accounting.MktPair` type) to the filesystem for faster lookup and
offline usage.
'''
from __future__ import annotations
from contextlib import (
asynccontextmanager as acm,
)
from pathlib import Path
from pprint import pformat
from typing import (
Any,
Sequence,
Hashable,
TYPE_CHECKING,
)
from types import ModuleType
from rapidfuzz import process as fuzzy
import tomli_w # for fast symbol cache writing
import tractor
import trio
try:
import tomllib
except ModuleNotFoundError:
import tomli as tomllib
from msgspec import field
from piker.log import get_logger
from piker import config
from piker.types import Struct
from piker.brokers import (
open_cached_client,
get_brokermod,
)
if TYPE_CHECKING:
from ..accounting import (
Asset,
MktPair,
)
log = get_logger('data.cache')
class SymbologyCache(Struct):
'''
Asset meta-data cache which holds lookup tables for 3 sets of
market-symbology related struct-types required by the
`.accounting` and `.data` subsystems.
'''
mod: ModuleType
fp: Path
# all asset-money-systems descriptions as minimally defined by
# in `.accounting.Asset`
assets: dict[str, Asset] = field(default_factory=dict)
# backend-system pairs loaded in provider (schema) specific
# structs.
pairs: dict[str, Struct] = field(default_factory=dict)
# serialized namespace path to the backend's pair-info-`Struct`
# defn B)
pair_ns_path: tractor.msg.NamespacePath | None = None
# TODO: piker-normalized `.accounting.MktPair` table?
# loaded from the `.pairs` and a normalizer
# provided by the backend pkg.
mktmaps: dict[str, MktPair] = field(default_factory=dict)
def write_config(self) -> None:
# put the backend's pair-struct type ref at the top
# of file if possible.
cachedict: dict[str, Any] = {
'pair_ns_path': str(self.pair_ns_path) or '',
}
# serialize all tables as dicts for TOML.
for key, table in {
'assets': self.assets,
'pairs': self.pairs,
'mktmaps': self.mktmaps,
}.items():
if not table:
log.warning(
f'Asset cache table for `{key}` is empty?'
)
continue
dct = cachedict[key] = {}
for key, struct in table.items():
dct[key] = struct.to_dict(include_non_members=False)
try:
with self.fp.open(mode='wb') as fp:
tomli_w.dump(cachedict, fp)
except TypeError:
self.fp.unlink()
raise
async def load(self) -> None:
'''
Explicitly load the "symbology set" for this provider by using
2 required `Client` methods:
- `.get_assets()`: returning a table of `Asset`s
- `.get_mkt_pairs()`: returning a table of pair-`Struct`
types, custom defined by the particular backend.
AND, the required `.get_mkt_info()` module-level endpoint
which maps `fqme: str` -> `MktPair`s.
These tables are then used to fill out the `.assets`, `.pairs` and
`.mktmaps` tables on this cache instance, respectively.
'''
async with open_cached_client(self.mod.name) as client:
if get_assets := getattr(client, 'get_assets', None):
assets: dict[str, Asset] = await get_assets()
for bs_mktid, asset in assets.items():
self.assets[bs_mktid] = asset
else:
log.warning(
'No symbology cache `Asset` support for `{provider}`..\n'
'Implement `Client.get_assets()`!'
)
if get_mkt_pairs := getattr(client, 'get_mkt_pairs', None):
pairs: dict[str, Struct] = await get_mkt_pairs()
for bs_fqme, pair in pairs.items():
# NOTE: every backend defined pair should
# declare it's ns path for roundtrip
# serialization lookup.
if not getattr(pair, 'ns_path', None):
raise TypeError(
f'Pair-struct for {self.mod.name} MUST define a '
'`.ns_path: str`!\n'
f'{pair}'
)
entry = await self.mod.get_mkt_info(pair.bs_fqme)
if not entry:
continue
mkt: MktPair
pair: Struct
mkt, _pair = entry
assert _pair is pair, (
f'`{self.mod.name}` backend probably has a '
'keying-symmetry problem between the pair-`Struct` '
'returned from `Client.get_mkt_pairs()`and the '
'module level endpoint: `.get_mkt_info()`\n\n'
"Here's the struct diff:\n"
f'{_pair - pair}'
)
# NOTE XXX: this means backends MUST implement
# a `Struct.bs_mktid: str` field to provide
# a native-keyed map to their own symbol
# set(s).
self.pairs[pair.bs_mktid] = pair
# NOTE: `MktPair`s are keyed here using piker's
# internal FQME schema so that search,
# accounting and feed init can be accomplished
# a sane, uniform, normalized basis.
self.mktmaps[mkt.fqme] = mkt
self.pair_ns_path: str = tractor.msg.NamespacePath.from_ref(
pair,
)
else:
log.warning(
'No symbology cache `Pair` support for `{provider}`..\n'
'Implement `Client.get_mkt_pairs()`!'
)
return self
@classmethod
def from_dict(
cls: type,
data: dict,
**kwargs,
) -> SymbologyCache:
# normal init inputs
cache = cls(**kwargs)
# XXX WARNING: this may break if backend namespacing
# changes (eg. `Pair` class def is moved to another
# module) in which case you can manually update the
# `pair_ns_path` in the symcache file and try again.
# TODO: probably a verbose error about this?
Pair: type = tractor.msg.NamespacePath(
str(data['pair_ns_path'])
).load_ref()
pairtable = data.pop('pairs')
for key, pairtable in pairtable.items():
# allow each serialized pair-dict-table to declare its
# specific struct type's path in cases where a backend
# supports multiples (normally with different
# schemas..) and we are storing them in a flat `.pairs`
# table.
ThisPair = Pair
if this_pair_type := pairtable.get('ns_path'):
ThisPair: type = tractor.msg.NamespacePath(
str(this_pair_type)
).load_ref()
pair: Struct = ThisPair(**pairtable)
cache.pairs[key] = pair
from ..accounting import (
Asset,
MktPair,
)
# load `dict` -> `Asset`
assettable = data.pop('assets')
for name, asdict in assettable.items():
cache.assets[name] = Asset.from_msg(asdict)
# load `dict` -> `MktPair`
dne: list[str] = []
mkttable = data.pop('mktmaps')
for fqme, mktdict in mkttable.items():
mkt = MktPair.from_msg(mktdict)
assert mkt.fqme == fqme
# sanity check asset refs from those (presumably)
# loaded asset set above.
src: Asset = cache.assets[mkt.src.name]
assert src == mkt.src
dst: Asset
if not (dst := cache.assets.get(mkt.dst.name)):
dne.append(mkt.dst.name)
continue
else:
assert dst.name == mkt.dst.name
cache.mktmaps[fqme] = mkt
log.warning(
f'These `MktPair.dst: Asset`s DNE says `{cache.mod.name}`?\n'
f'{pformat(dne)}'
)
return cache
@staticmethod
async def from_scratch(
mod: ModuleType,
fp: Path,
**kwargs,
) -> SymbologyCache:
'''
Generate (a) new symcache (contents) entirely from scratch
including all (TOML) serialized data and file.
'''
log.info(f'GENERATING symbology cache for `{mod.name}`')
cache = SymbologyCache(
mod=mod,
fp=fp,
**kwargs,
)
await cache.load()
cache.write_config()
return cache
def search(
self,
pattern: str,
table: str = 'mktmaps'
) -> dict[str, Struct]:
'''
(Fuzzy) search this cache's `.mktmaps` table, which is
keyed by FQMEs, for `pattern: str` and return the best
matches in a `dict` including the `MktPair` values.
'''
matches = fuzzy.extract(
pattern,
getattr(self, table),
score_cutoff=50,
)
# repack in dict[fqme, MktPair] form
return {
item[0].fqme: item[0]
for item in matches
}
# actor-process-local in-mem-cache of symcaches (by backend).
_caches: dict[str, SymbologyCache] = {}
def mk_cachefile(
provider: str,
) -> Path:
cachedir: Path = config.get_conf_dir() / '_cache'
if not cachedir.is_dir():
log.info(f'Creating `nativedb` director: {cachedir}')
cachedir.mkdir()
cachefile: Path = cachedir / f'{str(provider)}.symcache.toml'
cachefile.touch()
return cachefile
@acm
async def open_symcache(
mod_or_name: ModuleType | str,
reload: bool = False,
only_from_memcache: bool = False, # no API req
_no_symcache: bool = False, # no backend support
) -> SymbologyCache:
if isinstance(mod_or_name, str):
mod = get_brokermod(mod_or_name)
else:
mod: ModuleType = mod_or_name
provider: str = mod.name
cachefile: Path = mk_cachefile(provider)
# NOTE: certain backends might not support a symbology cache
# (easily) and thus we allow for an empty instance to be loaded
# and manually filled in at the whim of the caller presuming
# the backend pkg-module is annotated appropriately.
if (
getattr(mod, '_no_symcache', False)
or _no_symcache
):
yield SymbologyCache(
mod=mod,
fp=cachefile,
)
# don't do nuttin
return
# actor-level cache-cache XD
global _caches
if not reload:
try:
yield _caches[provider]
except KeyError:
msg: str = (
f'No asset info cache exists yet for `{provider}`'
)
if only_from_memcache:
raise RuntimeError(msg)
else:
log.warning(msg)
# if no cache exists or an explicit reload is requested, load
# the provider API and call appropriate endpoints to populate
# the mkt and asset tables.
if (
reload
or not cachefile.is_file()
):
cache = await SymbologyCache.from_scratch(
mod=mod,
fp=cachefile,
)
else:
log.info(
f'Loading EXISTING `{mod.name}` symbology cache:\n'
f'> {cachefile}'
)
import time
now = time.time()
with cachefile.open('rb') as existing_fp:
data: dict[str, dict] = tomllib.load(existing_fp)
log.runtime(f'SYMCACHE TOML LOAD TIME: {time.time() - now}')
# if there's an empty file for some reason we need
# to do a full reload as well!
if not data:
cache = await SymbologyCache.from_scratch(
mod=mod,
fp=cachefile,
)
else:
cache = SymbologyCache.from_dict(
data,
mod=mod,
fp=cachefile,
)
# TODO: use a real profiling sys..
# https://github.com/pikers/piker/issues/337
log.info(f'SYMCACHE LOAD TIME: {time.time() - now}')
yield cache
# TODO: write only when changes detected? but that should
# never happen right except on reload?
# cache.write_config()
def get_symcache(
provider: str,
force_reload: bool = False,
) -> SymbologyCache:
'''
Get any available symbology/assets cache from sync code by
(maybe) manually running `trio` to do the work.
'''
# spawn tractor runtime and generate cache
# if not existing.
async def sched_gen_symcache():
async with (
# only for runtime's debug mode
tractor.open_nursery(debug_mode=True),
open_symcache(
get_brokermod(provider),
reload=force_reload,
) as symcache,
):
return symcache
try:
symcache: SymbologyCache = trio.run(sched_gen_symcache)
assert symcache
except BaseException:
import pdbp
pdbp.xpm()
return symcache
def match_from_pairs(
pairs: dict[str, Struct],
query: str,
score_cutoff: int = 50,
**extract_kwargs,
) -> dict[str, Struct]:
'''
Fuzzy search over a "pairs table" maintained by most backends
as part of their symbology-info caching internals.
Scan the native symbol key set and return best ranked
matches back in a new `dict`.
'''
# TODO: somehow cache this list (per call) like we were in
# `open_symbol_search()`?
keys: list[str] = list(pairs)
matches: list[tuple[
Sequence[Hashable], # matching input key
Any, # scores
Any,
]] = fuzzy.extract(
# NOTE: most backends provide keys uppercased
query=query,
choices=keys,
score_cutoff=score_cutoff,
**extract_kwargs,
)
# pop and repack pairs in output dict
matched_pairs: dict[str, Struct] = {}
for item in matches:
pair_key: str = item[0]
matched_pairs[pair_key] = pairs[pair_key]
return matched_pairs

View File

@ -0,0 +1,326 @@
# piker: trading gear for hackers
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Financial time series processing utilities usually
pertaining to OHLCV style sampled data.
Routines are generally implemented in either ``numpy`` or ``polars`` B)
'''
from __future__ import annotations
from typing import Literal
from math import (
ceil,
floor,
)
import numpy as np
import polars as pl
from ._sharedmem import ShmArray
from .._profile import (
Profiler,
pg_profile_enabled,
ms_slower_then,
)
def slice_from_time(
arr: np.ndarray,
start_t: float,
stop_t: float,
step: float, # sampler period step-diff
) -> slice:
'''
Calculate array indices mapped from a time range and return them in
a slice.
Given an input array with an epoch `'time'` series entry, calculate
the indices which span the time range and return in a slice. Presume
each `'time'` step increment is uniform and when the time stamp
series contains gaps (the uniform presumption is untrue) use
``np.searchsorted()`` binary search to look up the appropriate
index.
'''
profiler = Profiler(
msg='slice_from_time()',
disabled=not pg_profile_enabled(),
ms_threshold=ms_slower_then,
)
times = arr['time']
t_first = floor(times[0])
t_last = ceil(times[-1])
# the greatest index we can return which slices to the
# end of the input array.
read_i_max = arr.shape[0]
# compute (presumed) uniform-time-step index offsets
i_start_t = floor(start_t)
read_i_start = floor(((i_start_t - t_first) // step)) - 1
i_stop_t = ceil(stop_t)
# XXX: edge case -> always set stop index to last in array whenever
# the input stop time is detected to be greater then the equiv time
# stamp at that last entry.
if i_stop_t >= t_last:
read_i_stop = read_i_max
else:
read_i_stop = ceil((i_stop_t - t_first) // step) + 1
# always clip outputs to array support
# for read start:
# - never allow a start < the 0 index
# - never allow an end index > the read array len
read_i_start = min(
max(0, read_i_start),
read_i_max - 1,
)
read_i_stop = max(
0,
min(read_i_stop, read_i_max),
)
# check for larger-then-latest calculated index for given start
# time, in which case we do a binary search for the correct index.
# NOTE: this is usually the result of a time series with time gaps
# where it is expected that each index step maps to a uniform step
# in the time stamp series.
t_iv_start = times[read_i_start]
if (
t_iv_start > i_start_t
):
# do a binary search for the best index mapping to ``start_t``
# given we measured an overshoot using the uniform-time-step
# calculation from above.
# TODO: once we start caching these per source-array,
# we can just overwrite ``read_i_start`` directly.
new_read_i_start = np.searchsorted(
times,
i_start_t,
side='left',
)
# TODO: minimize binary search work as much as possible:
# - cache these remap values which compensate for gaps in the
# uniform time step basis where we calc a later start
# index for the given input ``start_t``.
# - can we shorten the input search sequence by heuristic?
# up_to_arith_start = index[:read_i_start]
if (
new_read_i_start <= read_i_start
):
# t_diff = t_iv_start - start_t
# print(
# f"WE'RE CUTTING OUT TIME - STEP:{step}\n"
# f'start_t:{start_t} -> 0index start_t:{t_iv_start}\n'
# f'diff: {t_diff}\n'
# f'REMAPPED START i: {read_i_start} -> {new_read_i_start}\n'
# )
read_i_start = new_read_i_start
t_iv_stop = times[read_i_stop - 1]
if (
t_iv_stop > i_stop_t
):
# t_diff = stop_t - t_iv_stop
# print(
# f"WE'RE CUTTING OUT TIME - STEP:{step}\n"
# f'calced iv stop:{t_iv_stop} -> stop_t:{stop_t}\n'
# f'diff: {t_diff}\n'
# # f'SHOULD REMAP STOP: {read_i_start} -> {new_read_i_start}\n'
# )
new_read_i_stop = np.searchsorted(
times[read_i_start:],
# times,
i_stop_t,
side='right',
)
if (
new_read_i_stop <= read_i_stop
):
read_i_stop = read_i_start + new_read_i_stop + 1
# sanity checks for range size
# samples = (i_stop_t - i_start_t) // step
# index_diff = read_i_stop - read_i_start + 1
# if index_diff > (samples + 3):
# breakpoint()
# read-relative indexes: gives a slice where `shm.array[read_slc]`
# will be the data spanning the input time range `start_t` ->
# `stop_t`
read_slc = slice(
int(read_i_start),
int(read_i_stop),
)
profiler(
'slicing complete'
# f'{start_t} -> {abs_slc.start} | {read_slc.start}\n'
# f'{stop_t} -> {abs_slc.stop} | {read_slc.stop}\n'
)
# NOTE: if caller needs absolute buffer indices they can
# slice the buffer abs index like so:
# index = arr['index']
# abs_indx = index[read_slc]
# abs_slc = slice(
# int(abs_indx[0]),
# int(abs_indx[-1]),
# )
return read_slc
def detect_null_time_gap(
shm: ShmArray,
imargin: int = 1,
) -> tuple[float, float] | None:
'''
Detect if there are any zero-epoch stamped rows in
the presumed 'time' field-column.
Filter to the gap and return a surrounding index range.
NOTE: for now presumes only ONE gap XD
'''
zero_pred: np.ndarray = shm.array['time'] == 0
zero_t: np.ndarray = shm.array[zero_pred]
if zero_t.size:
istart, iend = zero_t['index'][[0, -1]]
start, end = shm._array['time'][
[istart - imargin, iend + imargin]
]
return (
istart - imargin,
start,
end,
iend + imargin,
)
return None
t_unit: Literal[
'days',
'hours',
'minutes',
'seconds',
'miliseconds',
'microseconds',
'nanoseconds',
]
def with_dts(
df: pl.DataFrame,
time_col: str = 'time',
) -> pl.DataFrame:
'''
Insert datetime (casted) columns to a (presumably) OHLC sampled
time series with an epoch-time column keyed by ``time_col``.
'''
return df.with_columns([
pl.col(time_col).shift(1).suffix('_prev'),
pl.col(time_col).diff().alias('s_diff'),
pl.from_epoch(pl.col(time_col)).alias('dt'),
]).with_columns([
pl.from_epoch(pl.col(f'{time_col}_prev')).alias('dt_prev'),
pl.col('dt').diff().alias('dt_diff'),
]) #.with_columns(
# pl.col('dt').diff().dt.days().alias('days_dt_diff'),
# )
def detect_time_gaps(
df: pl.DataFrame,
time_col: str = 'time',
# epoch sampling step diff
expect_period: float = 60,
# datetime diff unit and gap value
# crypto mkts
# gap_dt_unit: t_unit = 'minutes',
# gap_thresh: int = 1,
# legacy stock mkts
gap_dt_unit: t_unit = 'days',
gap_thresh: int = 2,
) -> pl.DataFrame:
'''
Filter to OHLC datums which contain sample step gaps.
For eg. legacy markets which have venue close gaps and/or
actual missing data segments.
'''
dt_gap_col: str = f'{gap_dt_unit}_diff'
return with_dts(
df
).filter(
pl.col('s_diff').abs() > expect_period
).with_columns(
getattr(
pl.col('dt_diff').dt,
gap_dt_unit, # NOTE: must be valid ``Expr.dt.<name>``
)().alias(dt_gap_col)
).filter(
pl.col(dt_gap_col).abs() > gap_thresh
)
def detect_price_gaps(
df: pl.DataFrame,
gt_multiplier: float = 2.,
price_fields: list[str] = ['high', 'low'],
) -> pl.DataFrame:
'''
Detect gaps in clearing price over an OHLC series.
2 types of gaps generally exist; up gaps and down gaps:
- UP gap: when any next sample's lo price is strictly greater
then the current sample's hi price.
- DOWN gap: when any next sample's hi price is strictly
less then the current samples lo price.
'''
# return df.filter(
# pl.col('high') - ) > expect_period,
# ).select([
# pl.dt.datetime(pl.col(time_col).shift(1)).suffix('_previous'),
# pl.all(),
# ]).select([
# pl.all(),
# (pl.col(time_col) - pl.col(f'{time_col}_previous')).alias('diff'),
# ])
...

View File

@ -50,8 +50,8 @@ from trio_websocket._impl import (
ConnectionTimeout,
)
from piker.types import Struct
from ._util import log
from .types import Struct
class NoBsWs:
@ -234,13 +234,10 @@ async def _reconnect_forever(
f'{url} trying (RE)CONNECT'
)
ws: WebSocketConnection
try:
async with (
trio.open_nursery() as n,
open_websocket_url(url) as ws,
):
async with trio.open_nursery() as n:
cs = nobsws._cs = n.cancel_scope
ws: WebSocketConnection
async with open_websocket_url(url) as ws:
nobsws._ws = ws
log.info(
f'{src_mod}\n'
@ -272,11 +269,9 @@ async def _reconnect_forever(
# to let tasks run **inside** the ws open block above.
nobsws._connected.set()
await trio.sleep_forever()
except HandshakeError:
log.exception('Retrying connection')
# ws & nursery block ends
# ws open block end
# nursery block end
nobsws._connected = trio.Event()
if cs.cancelled_caught:
log.cancel(
@ -289,8 +284,7 @@ async def _reconnect_forever(
and not nobsws._connected.is_set()
)
# -> from here, move to next reconnect attempt iteration
# in the while loop above Bp
# -> from here, move to next reconnect attempt
else:
log.exception(
@ -359,8 +353,8 @@ async def open_autorecon_ws(
'''
JSONRPC response-request style machinery for transparent multiplexing
of msgs over a `NoBsWs`.
JSONRPC response-request style machinery for transparent multiplexing of msgs
over a NoBsWs.
'''
@ -377,82 +371,43 @@ async def open_jsonrpc_session(
url: str,
start_id: int = 0,
response_type: type = JSONRPCResult,
msg_recv_timeout: float = float('inf'),
# ^NOTE, since only `deribit` is using this jsonrpc stuff atm
# and options mkts are generally "slow moving"..
#
# FURTHER if we break the underlying ws connection then since we
# don't pass a `fixture` to the task that manages `NoBsWs`, i.e.
# `_reconnect_forever()`, the jsonrpc "transport pipe" get's
# broken and never restored with wtv init sequence is required to
# re-establish a working req-resp session.
request_type: Optional[type] = None,
request_hook: Optional[Callable] = None,
error_hook: Optional[Callable] = None,
) -> Callable[[str, dict], dict]:
'''
Init a json-RPC-over-websocket connection to the provided `url`.
A `json_rpc: Callable[[str, dict], dict` is delivered to the
caller for sending requests and a bg-`trio.Task` handles
processing of response msgs including error reporting/raising in
the parent/caller task.
'''
# NOTE, store all request msgs so we can raise errors on the
# caller side!
req_msgs: dict[int, dict] = {}
async with (
trio.open_nursery() as tn,
open_autorecon_ws(
url=url,
msg_recv_timeout=msg_recv_timeout,
) as ws
trio.open_nursery() as n,
open_autorecon_ws(url) as ws
):
rpc_id: Iterable[int] = count(start_id)
rpc_id: Iterable = count(start_id)
rpc_results: dict[int, dict] = {}
async def json_rpc(
method: str,
params: dict,
) -> dict:
async def json_rpc(method: str, params: dict) -> dict:
'''
perform a json rpc call and wait for the result, raise exception in
case of error field present on response
'''
nonlocal req_msgs
req_id: int = next(rpc_id)
msg = {
'jsonrpc': '2.0',
'id': req_id,
'id': next(rpc_id),
'method': method,
'params': params
}
_id = msg['id']
result = rpc_results[_id] = {
rpc_results[_id] = {
'result': None,
'error': None,
'event': trio.Event(), # signal caller resp arrived
'event': trio.Event()
}
req_msgs[_id] = msg
await ws.send_msg(msg)
# wait for reponse before unblocking requester code
await rpc_results[_id]['event'].wait()
if (maybe_result := result['result']):
ret = maybe_result
del rpc_results[_id]
ret = rpc_results[_id]['result']
else:
err = result['error']
raise Exception(
f'JSONRPC request failed\n'
f'req: {msg}\n'
f'resp: {err}\n'
)
del rpc_results[_id]
if ret.error is not None:
raise Exception(json.dumps(ret.error, indent=4))
@ -467,7 +422,6 @@ async def open_jsonrpc_session(
the server side.
'''
nonlocal req_msgs
async for msg in ws:
match msg:
case {
@ -491,28 +445,19 @@ async def open_jsonrpc_session(
'params': _,
}:
log.debug(f'Recieved\n{msg}')
if request_hook:
await request_hook(request_type(**msg))
case {
'error': error
}:
# retreive orig request msg, set error
# response in original "result" msg,
# THEN FINALLY set the event to signal caller
# to raise the error in the parent task.
req_id: int = error['id']
req_msg: dict = req_msgs[req_id]
result: dict = rpc_results[req_id]
result['error'] = error
result['event'].set()
log.error(
f'JSONRPC request failed\n'
f'req: {req_msg}\n'
f'resp: {error}\n'
)
log.warning(f'Recieved\n{error}')
if error_hook:
await error_hook(response_type(**msg))
case _:
log.warning(f'Unhandled JSON-RPC msg!?\n{msg}')
tn.start_soon(recv_task)
n.start_soon(recv_task)
yield json_rpc
tn.cancel_scope.cancel()
n.cancel_scope.cancel()

View File

@ -28,7 +28,6 @@ module.
from __future__ import annotations
from collections import (
defaultdict,
abc,
)
from contextlib import asynccontextmanager as acm
from functools import partial
@ -37,6 +36,7 @@ from types import ModuleType
from typing import (
Any,
AsyncContextManager,
Optional,
Awaitable,
Sequence,
)
@ -45,62 +45,41 @@ import trio
from trio.abc import ReceiveChannel
from trio_typing import TaskStatus
import tractor
from tractor import trionics
from tractor.trionics import (
maybe_open_context,
gather_contexts,
)
from piker.accounting import (
MktPair,
unpack_fqme,
)
from piker.types import Struct
from piker.brokers import get_brokermod
from piker.service import (
maybe_spawn_brokerd,
)
from piker.calc import humanize
from ..brokers import get_brokermod
from ..calc import humanize
from ._util import (
log,
get_console_log,
)
from ..service import (
maybe_spawn_brokerd,
)
from .flows import Flume
from .validate import (
FeedInit,
validate_backend,
)
from ..tsp import (
from .history import (
manage_history,
)
from .ingest import get_ingestormod
from .types import Struct
from ..accounting import (
MktPair,
unpack_fqme,
)
from ..ui import _search
from ._sampling import (
sample_and_broadcast,
uniform_rate_send,
)
class Sub(Struct, frozen=True):
'''
A live feed subscription entry.
Contains meta-data on the remote-actor type (in functionality
terms) as well as refs to IPC streams and sampler runtime
params.
'''
ipc: tractor.MsgStream
send_chan: trio.abc.SendChannel | None = None
# tick throttle rate in Hz; determines how live
# quotes/ticks should be downsampled before relay
# to the receiving remote consumer (process).
throttle_rate: float | None = None
_throttle_cs: trio.CancelScope | None = None
# TODO: actually stash comms info for the far end to allow
# `.tsp`, `.fsp` and `.data._sampling` sub-systems to re-render
# the data view as needed via msging with the `._remote_ctl`
# ipc ctx.
rc_ui: bool = False
class _FeedsBus(Struct):
'''
Data feeds broadcaster and persistence management.
@ -125,7 +104,13 @@ class _FeedsBus(Struct):
_subscribers: defaultdict[
str,
set[Sub]
set[
tuple[
tractor.MsgStream | trio.MemorySendChannel,
# tractor.Context,
float | None, # tick throttle in Hz
]
]
] = defaultdict(set)
async def start_task(
@ -140,8 +125,6 @@ class _FeedsBus(Struct):
trio.CancelScope] = trio.TASK_STATUS_IGNORED,
) -> None:
with trio.CancelScope() as cs:
# TODO: shouldn't this be a direct await to avoid
# cancellation contagion to the bus nursery!?!?!
await self.nursery.start(
target,
*args,
@ -159,28 +142,31 @@ class _FeedsBus(Struct):
def get_subs(
self,
key: str,
) -> set[Sub]:
) -> set[
tuple[
tractor.MsgStream | trio.MemorySendChannel,
float | None, # tick throttle in Hz
]
]:
'''
Get the ``set`` of consumer subscription entries for the given key.
'''
return self._subscribers[key]
def subs_items(self) -> abc.ItemsView[str, set[Sub]]:
return self._subscribers.items()
def add_subs(
self,
key: str,
subs: set[Sub],
) -> set[Sub]:
subs: set[tuple[
tractor.MsgStream | trio.MemorySendChannel,
float | None, # tick throttle in Hz
]],
) -> set[tuple]:
'''
Add a ``set`` of consumer subscription entries for the given key.
'''
_subs: set[Sub] = self._subscribers.setdefault(key, set())
_subs: set[tuple] = self._subscribers[key]
_subs.update(subs)
return _subs
@ -345,6 +331,7 @@ async def allocate_persistent_feed(
) = await bus.nursery.start(
manage_history,
mod,
bus,
mkt,
some_data_ready,
feed_is_live,
@ -421,12 +408,6 @@ async def allocate_persistent_feed(
rt_shm.array['time'][1] = ts + 1
elif hist_shm.array.size == 0:
for i in range(100):
await trio.sleep(0.1)
if hist_shm.array.size > 0:
break
else:
await tractor.pause()
raise RuntimeError(f'History (1m) Shm for {fqme} is empty!?')
# wait the spawning parent task to register its subscriber
@ -457,9 +438,8 @@ async def open_feed_bus(
symbols: list[str], # normally expected to the broker-specific fqme
loglevel: str = 'error',
tick_throttle: float | None = None,
tick_throttle: Optional[float] = None,
start_stream: bool = True,
allow_remote_ctl_ui: bool = False,
) -> dict[
str, # fqme
@ -474,12 +454,8 @@ async def open_feed_bus(
if loglevel is None:
loglevel = tractor.current_actor().loglevel
# XXX: required to propagate ``tractor`` loglevel to piker
# logging
get_console_log(
loglevel
or tractor.current_actor().loglevel
)
# XXX: required to propagate ``tractor`` loglevel to piker logging
get_console_log(loglevel or tractor.current_actor().loglevel)
# local state sanity checks
# TODO: check for any stale shm entries for this symbol
@ -489,7 +465,7 @@ async def open_feed_bus(
assert 'brokerd' in servicename
assert brokername in servicename
bus: _FeedsBus = get_feed_bus(brokername)
bus = get_feed_bus(brokername)
sub_registered = trio.Event()
flumes: dict[str, Flume] = {}
@ -536,10 +512,10 @@ async def open_feed_bus(
# pack for ``.started()`` sync msg
flumes[fqme] = flume
# we use the broker-specific fqme (bs_fqme) for the sampler
# subscription since the backend isn't (yet) expected to
# append it's own name to the fqme, so we filter on keys
# which *do not* include that name (e.g .ib) .
# we use the broker-specific fqme (bs_fqme) for the
# sampler subscription since the backend isn't (yet) expected to
# append it's own name to the fqme, so we filter on keys which
# *do not* include that name (e.g .ib) .
bus._subscribers.setdefault(bs_fqme, set())
# sync feed subscribers with flume handles
@ -578,60 +554,49 @@ async def open_feed_bus(
# that the ``sample_and_broadcast()`` task (spawned inside
# ``allocate_persistent_feed()``) will push real-time quote
# (ticks) to this new consumer.
cs: trio.CancelScope | None = None
send: trio.MemorySendChannel | None = None
if tick_throttle:
flume.throttle_rate = tick_throttle
# open a bg task which receives quotes over a mem
# chan and only pushes them to the target
# actor-consumer at a max ``tick_throttle``
# (instantaneous) rate.
# open a bg task which receives quotes over a mem chan
# and only pushes them to the target actor-consumer at
# a max ``tick_throttle`` instantaneous rate.
send, recv = trio.open_memory_channel(2**10)
# NOTE: the ``.send`` channel here is a swapped-in
# trio mem chan which gets `.send()`-ed by the normal
# sampler task but instead of being sent directly
# over the IPC msg stream it's the throttle task
# does the work of incrementally forwarding to the
# IPC stream at the throttle rate.
cs: trio.CancelScope = await bus.start_task(
cs = await bus.start_task(
uniform_rate_send,
tick_throttle,
recv,
stream,
)
# NOTE: so the ``send`` channel here is actually a swapped
# in trio mem chan which gets pushed by the normal sampler
# task but instead of being sent directly over the IPC msg
# stream it's the throttle task does the work of
# incrementally forwarding to the IPC stream at the throttle
# rate.
send._ctx = ctx # mock internal ``tractor.MsgStream`` ref
sub = (send, tick_throttle)
sub = Sub(
ipc=stream,
send_chan=send,
throttle_rate=tick_throttle,
_throttle_cs=cs,
rc_ui=allow_remote_ctl_ui,
)
else:
sub = (stream, tick_throttle)
# TODO: add an api for this on the bus?
# maybe use the current task-id to key the sub list that's
# added / removed? Or maybe we can add a general
# pause-resume by sub-key api?
bs_fqme = fqme.removesuffix(f'.{brokername}')
local_subs.setdefault(
bs_fqme,
set()
).add(sub)
bus.add_subs(
bs_fqme,
{sub}
)
local_subs.setdefault(bs_fqme, set()).add(sub)
bus.add_subs(bs_fqme, {sub})
# sync caller with all subs registered state
sub_registered.set()
uid: tuple[str, str] = ctx.chan.uid
uid = ctx.chan.uid
try:
# ctrl protocol for start/stop of live quote streams
# based on UI state (eg. don't need a stream when
# a symbol isn't being displayed).
# ctrl protocol for start/stop of quote streams based on UI
# state (eg. don't need a stream when a symbol isn't being
# displayed).
async for msg in stream:
if msg == 'pause':
@ -769,7 +734,6 @@ async def install_brokerd_search(
except trio.EndOfChannel:
return {}
from piker.ui import _search
async with _search.register_symbol_search(
provider_name=brokermod.name,
@ -788,7 +752,7 @@ async def install_brokerd_search(
async def maybe_open_feed(
fqmes: list[str],
loglevel: str | None = None,
loglevel: Optional[str] = None,
**kwargs,
@ -804,7 +768,7 @@ async def maybe_open_feed(
'''
fqme = fqmes[0]
async with trionics.maybe_open_context(
async with maybe_open_context(
acm_func=open_feed,
kwargs={
'fqmes': fqmes,
@ -824,7 +788,7 @@ async def maybe_open_feed(
# add a new broadcast subscription for the quote stream
# if this feed is likely already in use
async with trionics.gather_contexts(
async with gather_contexts(
mngrs=[stream.subscribe() for stream in feed.streams.values()]
) as bstreams:
for bstream, flume in zip(bstreams, feed.flumes.values()):
@ -848,8 +812,6 @@ async def open_feed(
start_stream: bool = True,
tick_throttle: float | None = None, # Hz
allow_remote_ctl_ui: bool = False,
) -> Feed:
'''
Open a "data feed" which provides streamed real-time quotes.
@ -886,7 +848,7 @@ async def open_feed(
)
portals: tuple[tractor.Portal]
async with trionics.gather_contexts(
async with gather_contexts(
brokerd_ctxs,
) as portals:
@ -932,19 +894,13 @@ async def open_feed(
# of these stream open sequences sequentially per
# backend? .. need some thot!
allow_overruns=True,
# NOTE: UI actors (like charts) can allow
# remote control of certain graphics rendering
# capabilities via the
# `.ui._remote_ctl.remote_annotate()` msg loop.
allow_remote_ctl_ui=allow_remote_ctl_ui,
)
)
assert len(feed.mods) == len(feed.portals)
async with (
trionics.gather_contexts(bus_ctxs) as ctxs,
gather_contexts(bus_ctxs) as ctxs,
):
stream_ctxs: list[tractor.MsgStream] = []
for (
@ -986,7 +942,7 @@ async def open_feed(
brokermod: ModuleType
fqmes: list[str]
async with (
trionics.gather_contexts(stream_ctxs) as streams,
gather_contexts(stream_ctxs) as streams,
):
for (
stream,
@ -1002,12 +958,6 @@ async def open_feed(
if brokermod.name == flume.mkt.broker:
flume.stream = stream
assert (
len(feed.mods)
==
len(feed.portals)
==
len(feed.streams)
)
assert len(feed.mods) == len(feed.portals) == len(feed.streams)
yield feed

View File

@ -30,27 +30,53 @@ import tractor
import pendulum
import numpy as np
from piker.types import Struct
from ..accounting import MktPair
from ._util import log
from .types import Struct
from ._sharedmem import (
attach_shm_array,
ShmArray,
_Token,
)
# from .._profile import (
# Profiler,
# pg_profile_enabled,
# )
if TYPE_CHECKING:
from ..accounting import MktPair
# from pyqtgraph import PlotItem
from .feed import Feed
# TODO: ideas for further abstractions as per
# https://github.com/pikers/piker/issues/216 and
# https://github.com/pikers/piker/issues/270:
# - a ``Cascade`` would be the minimal "connection" of 2 ``Flumes``
# as per circuit parlance:
# https://en.wikipedia.org/wiki/Two-port_network#Cascade_connection
# - could cover the combination of our `FspAdmin` and the
# backend `.fsp._engine` related machinery to "connect" one flume
# to another?
# - a (financial signal) ``Flow`` would be the a "collection" of such
# minmial cascades. Some engineering based jargon concepts:
# - https://en.wikipedia.org/wiki/Signal_chain
# - https://en.wikipedia.org/wiki/Daisy_chain_(electrical_engineering)
# - https://en.wikipedia.org/wiki/Audio_signal_flow
# - https://en.wikipedia.org/wiki/Digital_signal_processing#Implementation
# - https://en.wikipedia.org/wiki/Dataflow_programming
# - https://en.wikipedia.org/wiki/Signal_programming
# - https://en.wikipedia.org/wiki/Incremental_computing
class Flume(Struct):
'''
Composite reference type which points to all the addressing
handles and other meta-data necessary for the read, measure and
management of a set of real-time updated data flows.
Composite reference type which points to all the addressing handles
and other meta-data necessary for the read, measure and management
of a set of real-time updated data flows.
Can be thought of as a "flow descriptor" or "flow frame" which
describes the high level properties of a set of data flows that
can be used seamlessly across process-memory boundaries.
describes the high level properties of a set of data flows that can
be used seamlessly across process-memory boundaries.
Each instance's sub-components normally includes:
- a msg oriented quote stream provided via an IPC transport
@ -73,7 +99,6 @@ class Flume(Struct):
# private shm refs loaded dynamically from tokens
_hist_shm: ShmArray | None = None
_rt_shm: ShmArray | None = None
_readonly: bool = True
stream: tractor.MsgStream | None = None
izero_hist: int = 0
@ -90,7 +115,7 @@ class Flume(Struct):
if self._rt_shm is None:
self._rt_shm = attach_shm_array(
token=self._rt_shm_token,
readonly=self._readonly,
readonly=True,
)
return self._rt_shm
@ -103,10 +128,12 @@ class Flume(Struct):
'No shm token has been set for the history buffer?'
)
if self._hist_shm is None:
if (
self._hist_shm is None
):
self._hist_shm = attach_shm_array(
token=self._hist_shm_token,
readonly=self._readonly,
readonly=True,
)
return self._hist_shm
@ -125,10 +152,10 @@ class Flume(Struct):
period and ratio between them.
'''
times: np.ndarray = self.hist_shm.array['time']
end: float | int = pendulum.from_timestamp(times[-1])
start: float | int = pendulum.from_timestamp(times[times != times[-1]][-1])
hist_step_size_s: float = (end - start).seconds
times = self.hist_shm.array['time']
end = pendulum.from_timestamp(times[-1])
start = pendulum.from_timestamp(times[times != times[-1]][-1])
hist_step_size_s = (end - start).seconds
times = self.rt_shm.array['time']
end = pendulum.from_timestamp(times[-1])
@ -148,25 +175,17 @@ class Flume(Struct):
msg = self.to_dict()
msg['mkt'] = self.mkt.to_dict()
# NOTE: pop all un-msg-serializable fields:
# - `tractor.MsgStream`
# - `Feed`
# - `Shmarray`
# it's expected the `.from_msg()` on the other side
# will get instead some kind of msg-compat version
# that it can load.
# can't serialize the stream or feed objects, it's expected
# you'll have a ref to it since this msg should be rxed on
# a stream on whatever far end IPC..
msg.pop('stream')
msg.pop('feed')
msg.pop('_rt_shm')
msg.pop('_hist_shm')
return msg
@classmethod
def from_msg(
cls,
msg: dict,
readonly: bool = True,
) -> dict:
'''
@ -175,13 +194,8 @@ class Flume(Struct):
'''
mkt_msg = msg.pop('mkt')
from ..accounting import MktPair # cycle otherwise..
mkt = MktPair.from_msg(mkt_msg)
msg |= {'_readonly': readonly}
return cls(
mkt=mkt,
**msg,
)
return cls(mkt=mkt, **msg)
def get_index(
self,
@ -219,3 +233,5 @@ class Flume(Struct):
np.all(np.isin(vlm, -1))
or np.all(np.isnan(vlm))
)

View File

@ -0,0 +1,967 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Historical data business logic for load, backfill and tsdb storage.
'''
from __future__ import annotations
# from collections import (
# Counter,
# )
from datetime import datetime
from functools import partial
# import time
from types import ModuleType
from typing import (
Callable,
TYPE_CHECKING,
)
import trio
from trio_typing import TaskStatus
import tractor
from pendulum import (
Duration,
from_timestamp,
)
import numpy as np
from ..accounting import (
MktPair,
)
from ._util import (
log,
)
from ._sharedmem import (
maybe_open_shm_array,
ShmArray,
)
from ._source import def_iohlcv_fields
from ._sampling import (
open_sample_stream,
)
from ..brokers._util import (
DataUnavailable,
)
if TYPE_CHECKING:
from bidict import bidict
from ..service.marketstore import StorageClient
from .feed import _FeedsBus
# `ShmArray` buffer sizing configuration:
_mins_in_day = int(60 * 24)
# how much is probably dependent on lifestyle
# but we reco a buncha times (but only on a
# run-every-other-day kinda week).
_secs_in_day = int(60 * _mins_in_day)
_days_in_week: int = 7
_days_worth: int = 3
_default_hist_size: int = 6 * 365 * _mins_in_day
_hist_buffer_start = int(
_default_hist_size - round(7 * _mins_in_day)
)
_default_rt_size: int = _days_worth * _secs_in_day
# NOTE: start the append index in rt buffer such that 1 day's worth
# can be appenened before overrun.
_rt_buffer_start = int((_days_worth - 1) * _secs_in_day)
def diff_history(
array: np.ndarray,
append_until_dt: datetime | None = None,
prepend_until_dt: datetime | None = None,
) -> np.ndarray:
# no diffing with tsdb dt index possible..
if (
prepend_until_dt is None
and append_until_dt is None
):
return array
times = array['time']
if append_until_dt:
return array[times < append_until_dt.timestamp()]
else:
return array[times >= prepend_until_dt.timestamp()]
async def shm_push_in_between(
shm: ShmArray,
to_push: np.ndarray,
prepend_index: int,
update_start_on_prepend: bool = False,
) -> int:
shm.push(
to_push,
prepend=True,
# XXX: only update the ._first index if no tsdb
# segment was previously prepended by the
# parent task.
update_first=update_start_on_prepend,
# XXX: only prepend from a manually calculated shm
# index if there was already a tsdb history
# segment prepended (since then the
# ._first.value is going to be wayyy in the
# past!)
start=(
prepend_index
if not update_start_on_prepend
else None
),
)
# XXX: extremely important, there can be no checkpoints
# in the block above to avoid entering new ``frames``
# values while we're pipelining the current ones to
# memory...
array = shm.array
zeros = array[array['low'] == 0]
if (
0 < zeros.size < 1000
):
tractor.breakpoint()
async def start_backfill(
get_hist,
mod: ModuleType,
mkt: MktPair,
shm: ShmArray,
timeframe: float,
backfill_from_shm_index: int,
backfill_from_dt: datetime,
sampler_stream: tractor.MsgStream,
backfill_until_dt: datetime | None = None,
storage: StorageClient | None = None,
write_tsdb: bool = True,
task_status: TaskStatus[tuple] = trio.TASK_STATUS_IGNORED,
) -> int:
# let caller unblock and deliver latest history frame
# and use to signal that backfilling the shm gap until
# the tsdb end is complete!
bf_done = trio.Event()
task_status.started(bf_done)
# based on the sample step size, maybe load a certain amount history
update_start_on_prepend: bool = False
if backfill_until_dt is None:
# TODO: drop this right and just expose the backfill
# limits inside a [storage] section in conf.toml?
# when no tsdb "last datum" is provided, we just load
# some near-term history.
# periods = {
# 1: {'days': 1},
# 60: {'days': 14},
# }
# do a decently sized backfill and load it into storage.
periods = {
1: {'days': 6},
60: {'years': 6},
}
period_duration: int = periods[timeframe]
update_start_on_prepend = True
# NOTE: manually set the "latest" datetime which we intend to
# backfill history "until" so as to adhere to the history
# settings above when the tsdb is detected as being empty.
backfill_until_dt = backfill_from_dt.subtract(**period_duration)
# TODO: can we drop this? without conc i don't think this
# is necessary any more?
# configure async query throttling
# rate = config.get('rate', 1)
# XXX: legacy from ``trimeter`` code but unsupported now.
# erlangs = config.get('erlangs', 1)
# avoid duplicate history frames with a set of datetime frame
# starts and associated counts of how many duplicates we see
# per time stamp.
# starts: Counter[datetime] = Counter()
# conduct "backward history gap filling" where we push to
# the shm buffer until we have history back until the
# latest entry loaded from the tsdb's table B)
last_start_dt: datetime = backfill_from_dt
next_prepend_index: int = backfill_from_shm_index
while last_start_dt > backfill_until_dt:
log.debug(
f'Requesting {timeframe}s frame ending in {last_start_dt}'
)
try:
(
array,
next_start_dt,
next_end_dt,
) = await get_hist(
timeframe,
end_dt=last_start_dt,
)
# broker says there never was or is no more history to pull
except DataUnavailable:
log.warning(
f'NO-MORE-DATA: backend {mod.name} halted history!?'
)
# ugh, what's a better way?
# TODO: fwiw, we probably want a way to signal a throttle
# condition (eg. with ib) so that we can halt the
# request loop until the condition is resolved?
return
# TODO: drop this? see todo above..
# if (
# next_start_dt in starts
# and starts[next_start_dt] <= 6
# ):
# start_dt = min(starts)
# log.warning(
# f"{mkt.fqme}: skipping duplicate frame @ {next_start_dt}"
# )
# starts[start_dt] += 1
# await tractor.breakpoint()
# continue
# elif starts[next_start_dt] > 6:
# log.warning(
# f'NO-MORE-DATA: backend {mod.name} before {next_start_dt}?'
# )
# return
# # only update new start point if not-yet-seen
# starts[next_start_dt] += 1
assert array['time'][0] == next_start_dt.timestamp()
diff = last_start_dt - next_start_dt
frame_time_diff_s = diff.seconds
# frame's worth of sample-period-steps, in seconds
frame_size_s = len(array) * timeframe
expected_frame_size_s = frame_size_s + timeframe
if frame_time_diff_s > expected_frame_size_s:
# XXX: query result includes a start point prior to our
# expected "frame size" and thus is likely some kind of
# history gap (eg. market closed period, outage, etc.)
# so just report it to console for now.
log.warning(
f'History frame ending @ {last_start_dt} appears to have a gap:\n'
f'{diff} ~= {frame_time_diff_s} seconds'
)
to_push = diff_history(
array,
prepend_until_dt=backfill_until_dt,
)
ln = len(to_push)
if ln:
log.info(f'{ln} bars for {next_start_dt} -> {last_start_dt}')
else:
log.warning(
'0 BARS TO PUSH after diff!?\n'
f'{next_start_dt} -> {last_start_dt}'
)
# bail gracefully on shm allocation overrun/full
# condition
try:
await shm_push_in_between(
shm,
to_push,
prepend_index=next_prepend_index,
update_start_on_prepend=update_start_on_prepend,
)
await sampler_stream.send({
'broadcast_all': {
'backfilling': (mkt.fqme, timeframe),
},
})
# decrement next prepend point
next_prepend_index = next_prepend_index - ln
last_start_dt = next_start_dt
except ValueError as ve:
_ve = ve
log.error(
f'Shm prepend OVERRUN on: {next_start_dt} -> {last_start_dt}?'
)
if next_prepend_index < ln:
log.warning(
f'Shm buffer can only hold {next_prepend_index} more rows..\n'
f'Appending those from recent {ln}-sized frame, no more!'
)
to_push = to_push[-next_prepend_index + 1:]
await shm_push_in_between(
shm,
to_push,
prepend_index=next_prepend_index,
update_start_on_prepend=update_start_on_prepend,
)
await sampler_stream.send({
'broadcast_all': {
'backfilling': (mkt.fqme, timeframe),
},
})
# can't push the entire frame? so
# push only the amount that can fit..
break
log.info(
f'Shm pushed {ln} frame:\n'
f'{next_start_dt} -> {last_start_dt}'
)
# FINALLY, maybe write immediately to the tsdb backend for
# long-term storage.
if (
storage is not None
and write_tsdb
):
log.info(
f'Writing {ln} frame to storage:\n'
f'{next_start_dt} -> {last_start_dt}'
)
if mkt.dst.atype not in {'crypto', 'crypto_currency'}:
# for now, our table key schema is not including
# the dst[/src] source asset token.
col_sym_key: str = mkt.get_fqme(
delim_char='',
without_src=True,
)
else:
col_sym_key: str = mkt.get_fqme(delim_char='')
# TODO: implement parquet append!?
await storage.write_ohlcv(
col_sym_key,
shm.array,
timeframe,
)
else:
# finally filled gap
log.info(
f'Finished filling gap to tsdb start @ {backfill_until_dt}!'
)
# conduct tsdb timestamp gap detection and backfill any
# seemingly missing sequence segments..
# TODO: ideally these never exist but somehow it seems
# sometimes we're writing zero-ed segments on certain
# (teardown) cases?
from ._timeseries import detect_null_time_gap
gap_indices: tuple | None = detect_null_time_gap(shm)
while gap_indices:
(
istart,
start,
end,
iend,
) = gap_indices
start_dt = from_timestamp(start)
end_dt = from_timestamp(end)
(
array,
next_start_dt,
next_end_dt,
) = await get_hist(
timeframe,
start_dt=start_dt,
end_dt=end_dt,
)
# XXX TODO: pretty sure if i plot tsla, btcusdt.binance
# and mnq.cme.ib this causes a Qt crash XXDDD
# make sure we don't overrun the buffer start
len_to_push: int = min(iend, array.size)
to_push: np.ndarray = array[-len_to_push:]
await shm_push_in_between(
shm,
to_push,
prepend_index=iend,
update_start_on_prepend=False,
)
# TODO: UI side needs IPC event to update..
# - make sure the UI actually always handles
# this update!
# - remember that in the display side, only refersh this
# if the respective history is actually "in view".
# loop
await sampler_stream.send({
'broadcast_all': {
'backfilling': (mkt.fqme, timeframe),
},
})
gap_indices: tuple | None = detect_null_time_gap(shm)
# XXX: extremely important, there can be no checkpoints
# in the block above to avoid entering new ``frames``
# values while we're pipelining the current ones to
# memory...
# await sampler_stream.send('broadcast_all')
# short-circuit (for now)
bf_done.set()
async def back_load_from_tsdb(
storemod: ModuleType,
storage: StorageClient,
fqme: str,
tsdb_history: np.ndarray,
last_tsdb_dt: datetime,
latest_start_dt: datetime,
latest_end_dt: datetime,
bf_done: trio.Event,
timeframe: int,
shm: ShmArray,
):
assert len(tsdb_history)
# sync to backend history task's query/load completion
# if bf_done:
# await bf_done.wait()
# TODO: eventually it'd be nice to not require a shm array/buffer
# to accomplish this.. maybe we can do some kind of tsdb direct to
# graphics format eventually in a child-actor?
if storemod.name == 'nativedb':
return
await tractor.breakpoint()
assert shm._first.value == 0
array = shm.array
# if timeframe == 1:
# times = shm.array['time']
# assert (times[1] - times[0]) == 1
if len(array):
shm_last_dt = from_timestamp(
shm.array[0]['time']
)
else:
shm_last_dt = None
if last_tsdb_dt:
assert shm_last_dt >= last_tsdb_dt
# do diff against start index of last frame of history and only
# fill in an amount of datums from tsdb allows for most recent
# to be loaded into mem *before* tsdb data.
if (
last_tsdb_dt
and latest_start_dt
):
backfilled_size_s = (
latest_start_dt - last_tsdb_dt
).seconds
# if the shm buffer len is not large enough to contain
# all missing data between the most recent backend-queried frame
# and the most recent dt-index in the db we warn that we only
# want to load a portion of the next tsdb query to fill that
# space.
log.info(
f'{backfilled_size_s} seconds worth of {timeframe}s loaded'
)
# Load TSDB history into shm buffer (for display) if there is
# remaining buffer space.
time_key: str = 'time'
if getattr(storemod, 'ohlc_key_map', False):
keymap: bidict = storemod.ohlc_key_map
time_key: str = keymap.inverse['time']
# if (
# not len(tsdb_history)
# ):
# return
tsdb_last_frame_start: datetime = last_tsdb_dt
# load as much from storage into shm possible (depends on
# user's shm size settings).
while shm._first.value > 0:
tsdb_history = await storage.read_ohlcv(
fqme,
timeframe=timeframe,
end=tsdb_last_frame_start,
)
# # empty query
# if not len(tsdb_history):
# break
next_start = tsdb_history[time_key][0]
if next_start >= tsdb_last_frame_start:
# no earlier data detected
break
else:
tsdb_last_frame_start = next_start
# TODO: see if there's faster multi-field reads:
# https://numpy.org/doc/stable/user/basics.rec.html#accessing-multiple-fields
# re-index with a `time` and index field
prepend_start = shm._first.value
to_push = tsdb_history[-prepend_start:]
shm.push(
to_push,
# insert the history pre a "days worth" of samples
# to leave some real-time buffer space at the end.
prepend=True,
# update_first=False,
# start=prepend_start,
field_map=storemod.ohlc_key_map,
)
log.info(f'Loaded {to_push.shape} datums from storage')
tsdb_last_frame_start = tsdb_history[time_key][0]
# manually trigger step update to update charts/fsps
# which need an incremental update.
# NOTE: the way this works is super duper
# un-intuitive right now:
# - the broadcaster fires a msg to the fsp subsystem.
# - fsp subsys then checks for a sample step diff and
# possibly recomputes prepended history.
# - the fsp then sends back to the parent actor
# (usually a chart showing graphics for said fsp)
# which tells the chart to conduct a manual full
# graphics loop cycle.
# await sampler_stream.send('broadcast_all')
async def tsdb_backfill(
mod: ModuleType,
storemod: ModuleType,
tn: trio.Nursery,
storage: StorageClient,
mkt: MktPair,
shm: ShmArray,
timeframe: float,
sampler_stream: tractor.MsgStream,
task_status: TaskStatus[
tuple[ShmArray, ShmArray]
] = trio.TASK_STATUS_IGNORED,
) -> None:
get_hist: Callable[
[int, datetime, datetime],
tuple[np.ndarray, str]
]
config: dict[str, int]
async with mod.open_history_client(
mkt,
) as (get_hist, config):
log.info(f'{mod} history client returned backfill config: {config}')
# get latest query's worth of history all the way
# back to what is recorded in the tsdb
try:
array, mr_start_dt, mr_end_dt = await get_hist(
timeframe,
end_dt=None,
)
# XXX: timeframe not supported for backend (since
# above exception type), terminate immediately since
# there's no backfilling possible.
except DataUnavailable:
task_status.started()
return
times: np.ndarray = array['time']
# sample period step size in seconds
step_size_s = (
from_timestamp(times[-1])
- from_timestamp(times[-2])
).seconds
if step_size_s not in (1, 60):
log.error(f'Last 2 sample period is off!? -> {step_size_s}')
step_size_s = (
from_timestamp(times[-2])
- from_timestamp(times[-3])
).seconds
# NOTE: on the first history, most recent history
# frame we PREPEND from the current shm ._last index
# and thus a gap between the earliest datum loaded here
# and the latest loaded from the tsdb may exist!
log.info(f'Pushing {array.size} to shm!')
shm.push(
array,
prepend=True, # append on first frame
)
backfill_gap_from_shm_index: int = shm._first.value + 1
# tell parent task to continue
task_status.started()
# loads a (large) frame of data from the tsdb depending
# on the db's query size limit; our "nativedb" (using
# parquet) generally can load the entire history into mem
# but if not then below the remaining history can be lazy
# loaded?
fqme: str = mkt.fqme
tsdb_entry: tuple | None = await storage.load(
fqme,
timeframe=timeframe,
)
last_tsdb_dt: datetime | None = None
if tsdb_entry:
(
tsdb_history,
first_tsdb_dt,
last_tsdb_dt,
) = tsdb_entry
# calc the index from which the tsdb data should be
# prepended, presuming there is a gap between the
# latest frame (loaded/read above) and the latest
# sample loaded from the tsdb.
backfill_diff: Duration = mr_start_dt - last_tsdb_dt
offset_s: float = backfill_diff.in_seconds()
offset_samples: int = round(offset_s / timeframe)
# TODO: see if there's faster multi-field reads:
# https://numpy.org/doc/stable/user/basics.rec.html#accessing-multiple-fields
# re-index with a `time` and index field
prepend_start = shm._first.value - offset_samples + 1
# tsdb history is so far in the past we can't fit it in
# shm buffer space so simply don't load it!
if prepend_start > 0:
to_push = tsdb_history[-prepend_start:]
shm.push(
to_push,
# insert the history pre a "days worth" of samples
# to leave some real-time buffer space at the end.
prepend=True,
# update_first=False,
start=prepend_start,
field_map=storemod.ohlc_key_map,
)
log.info(f'Loaded {to_push.shape} datums from storage')
# TODO: maybe start history anal and load missing "history
# gaps" via backend..
if timeframe not in (1, 60):
raise ValueError(
'`piker` only needs to support 1m and 1s sampling '
'but ur api is trying to deliver a longer '
f'timeframe of {timeframe} seconds..\n'
'So yuh.. dun do dat brudder.'
)
# if there is a gap to backfill from the first
# history frame until the last datum loaded from the tsdb
# continue that now in the background
bf_done = await tn.start(
partial(
start_backfill,
get_hist,
mod,
mkt,
shm,
timeframe,
backfill_from_shm_index=backfill_gap_from_shm_index,
backfill_from_dt=mr_start_dt,
sampler_stream=sampler_stream,
backfill_until_dt=last_tsdb_dt,
storage=storage,
)
)
# if len(hist_shm.array) < 2:
# TODO: there's an edge case here to solve where if the last
# frame before market close (at least on ib) was pushed and
# there was only "1 new" row pushed from the first backfill
# query-iteration, then the sample step sizing calcs will
# break upstream from here since you can't diff on at least
# 2 steps... probably should also add logic to compute from
# the tsdb series and stash that somewhere as meta data on
# the shm buffer?.. no se.
# backload any further data from tsdb (concurrently per
# timeframe) if not all data was able to be loaded (in memory)
# from the ``StorageClient.load()`` call above.
try:
await trio.sleep_forever()
finally:
return
# IF we need to continue backloading incrementall from the
# tsdb client..
tn.start_soon(
back_load_from_tsdb,
storemod,
storage,
fqme,
tsdb_history,
last_tsdb_dt,
mr_start_dt,
mr_end_dt,
bf_done,
timeframe,
shm,
)
async def manage_history(
mod: ModuleType,
bus: _FeedsBus,
mkt: MktPair,
some_data_ready: trio.Event,
feed_is_live: trio.Event,
timeframe: float = 60, # in seconds
task_status: TaskStatus[
tuple[ShmArray, ShmArray]
] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Load and manage historical data including the loading of any
available series from any connected tsdb as well as conduct
real-time update of both that existing db and the allocated
shared memory buffer.
Init sequence:
- allocate shm (numpy array) buffers for 60s & 1s sample rates
- configure "zero index" for each buffer: the index where
history will prepended *to* and new live data will be
appened *from*.
- open a ``.storage.StorageClient`` and load any existing tsdb
history as well as (async) start a backfill task which loads
missing (newer) history from the data provider backend:
- tsdb history is loaded first and pushed to shm ASAP.
- the backfill task loads the most recent history before
unblocking its parent task, so that the `ShmArray._last` is
up to date to allow the OHLC sampler to begin writing new
samples as the correct buffer index once the provider feed
engages.
'''
# TODO: is there a way to make each shm file key
# actor-tree-discovery-addr unique so we avoid collisions
# when doing tests which also allocate shms for certain instruments
# that may be in use on the system by some other running daemons?
# from tractor._state import _runtime_vars
# port = _runtime_vars['_root_mailbox'][1]
uid = tractor.current_actor().uid
name, uuid = uid
service = name.rstrip(f'.{mod.name}')
fqme: str = mkt.get_fqme(delim_char='')
# (maybe) allocate shm array for this broker/symbol which will
# be used for fast near-term history capture and processing.
hist_shm, opened = maybe_open_shm_array(
size=_default_hist_size,
append_start_index=_hist_buffer_start,
key=f'piker.{service}[{uuid[:16]}].{fqme}.hist',
# use any broker defined ohlc dtype:
dtype=getattr(mod, '_ohlc_dtype', def_iohlcv_fields),
# we expect the sub-actor to write
readonly=False,
)
hist_zero_index = hist_shm.index - 1
# TODO: history validation
if not opened:
raise RuntimeError(
"Persistent shm for sym was already open?!"
)
rt_shm, opened = maybe_open_shm_array(
size=_default_rt_size,
append_start_index=_rt_buffer_start,
key=f'piker.{service}[{uuid[:16]}].{fqme}.rt',
# use any broker defined ohlc dtype:
dtype=getattr(mod, '_ohlc_dtype', def_iohlcv_fields),
# we expect the sub-actor to write
readonly=False,
)
# (for now) set the rt (hft) shm array with space to prepend
# only a few days worth of 1s history.
days = 2
start_index = days*_secs_in_day
rt_shm._first.value = start_index
rt_shm._last.value = start_index
rt_zero_index = rt_shm.index - 1
if not opened:
raise RuntimeError(
"Persistent shm for sym was already open?!"
)
open_history_client = getattr(
mod,
'open_history_client',
None,
)
assert open_history_client
# TODO: maybe it should be a subpkg of `.data`?
from piker import storage
async with (
storage.open_storage_client() as (storemod, client),
trio.open_nursery() as tn,
):
log.info(
f'Connecting to storage backend `{storemod.name}`:\n'
f'location: {client.address}\n'
f'db cardinality: {client.cardinality}\n'
# TODO: show backend config, eg:
# - network settings
# - storage size with compression
# - number of loaded time series?
)
# NOTE: this call ONLY UNBLOCKS once the latest-most frame
# (i.e. history just before the live feed latest datum) of
# history has been loaded and written to the shm buffer:
# - the backfiller task can write in reverse chronological
# to the shm and tsdb
# - the tsdb data can be loaded immediately and the
# backfiller can do a single append from it's end datum and
# then prepends backward to that from the current time
# step.
tf2mem: dict = {
1: rt_shm,
60: hist_shm,
}
async with open_sample_stream(
period_s=1.,
shms_by_period={
1.: rt_shm.token,
60.: hist_shm.token,
},
# NOTE: we want to only open a stream for doing
# broadcasts on backfill operations, not receive the
# sample index-stream (since there's no code in this
# data feed layer that needs to consume it).
open_index_stream=True,
sub_for_broadcasts=False,
) as sample_stream:
# register 1s and 1m buffers with the global incrementer task
log.info(f'Connected to sampler stream: {sample_stream}')
for timeframe in [60, 1]:
await tn.start(
tsdb_backfill,
mod,
storemod,
tn,
# bus,
client,
mkt,
tf2mem[timeframe],
timeframe,
sample_stream,
)
# indicate to caller that feed can be delivered to
# remote requesting client since we've loaded history
# data that can be used.
some_data_ready.set()
# wait for a live feed before starting the sampler.
await feed_is_live.wait()
# yield back after client connect with filled shm
task_status.started((
hist_zero_index,
hist_shm,
rt_zero_index,
rt_shm,
))
# history retreival loop depending on user interaction
# and thus a small RPC-prot for remotely controllinlg
# what data is loaded for viewing.
await trio.sleep_forever()

104
piker/data/types.py 100644
View File

@ -0,0 +1,104 @@
# piker: trading gear for hackers
# Copyright (C) (in stewardship for pikers)
# - Tyler Goodlet
# - Guillermo Rodriguez
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Extensions to built-in or (heavily used but 3rd party) friend-lib
types.
'''
from pprint import pformat
from msgspec import (
msgpack,
Struct,
structs,
)
class Struct(
Struct,
# https://jcristharif.com/msgspec/structs.html#tagged-unions
# tag='pikerstruct',
# tag=True,
):
'''
A "human friendlier" (aka repl buddy) struct subtype.
'''
def to_dict(self) -> dict:
'''
Like it sounds.. direct delegation to:
https://jcristharif.com/msgspec/api.html#msgspec.structs.asdict
TODO: probably just drop this method since it's now a built-int method?
'''
return structs.asdict(self)
def pformat(self) -> str:
return f'Struct({pformat(self.to_dict())})'
def copy(
self,
update: dict | None = None,
) -> Struct:
'''
Validate-typecast all self defined fields, return a copy of
us with all such fields.
NOTE: This is kinda like the default behaviour in
`pydantic.BaseModel` except a copy of the object is
returned making it compat with `frozen=True`.
'''
if update:
for k, v in update.items():
setattr(self, k, v)
# NOTE: roundtrip serialize to validate
# - enode to msgpack binary format,
# - decode that back to a struct.
return msgpack.Decoder(type=type(self)).decode(
msgpack.Encoder().encode(self)
)
def typecast(
self,
# TODO: allow only casting a named subset?
# fields: set[str] | None = None,
) -> None:
'''
Cast all fields using their declared type annotations
(kinda like what `pydantic` does by default).
NOTE: this of course won't work on frozen types, use
``.copy()`` above in such cases.
'''
# https://jcristharif.com/msgspec/api.html#msgspec.structs.fields
fi: structs.FieldInfo
for fi in structs.fields(self):
setattr(
self,
fi.name,
fi.type(getattr(self, fi.name)),
)

View File

@ -18,7 +18,6 @@ Data feed synchronization protocols, init msgs, and general
data-provider-backend-agnostic schema definitions.
'''
from __future__ import annotations
from decimal import Decimal
from pprint import pformat
from types import ModuleType
@ -29,8 +28,8 @@ from typing import (
from msgspec import field
from piker.types import Struct
from piker.accounting import (
from .types import Struct
from ..accounting import (
Asset,
MktPair,
)
@ -82,8 +81,8 @@ _eps: dict[str, list[str]] = {
# live order control and trading
'brokerd': [
'trades_dialogue',
'open_trade_dialog', # live order ctl
'norm_trade', # ledger normalizer for txns
# TODO: ledger normalizer helper?
# norm_trades(records: dict[str, Any]) -> TransactionLedger)
],
}

View File

@ -22,40 +22,17 @@ from typing import AsyncIterator
import numpy as np
from ._api import (
maybe_mk_fsp_shm,
Fsp,
)
from ._engine import (
cascade,
Cascade,
)
from ._volume import (
dolla_vlm,
flow_rates,
tina_vwap,
)
from ._engine import cascade
__all__: list[str] = [
'cascade',
'Cascade',
'maybe_mk_fsp_shm',
'Fsp',
'dolla_vlm',
'flow_rates',
'tina_vwap',
]
__all__ = ['cascade']
async def latency(
source: 'TickStream[Dict[str, float]]', # noqa
ohlcv: np.ndarray
) -> AsyncIterator[np.ndarray]:
'''
Latency measurements, broker to piker.
'''
"""Latency measurements, broker to piker.
"""
# TODO: do we want to offer yielding this async
# before the rt data connection comes up?

View File

@ -18,12 +18,13 @@
core task logic for processing chains
'''
from __future__ import annotations
from contextlib import asynccontextmanager as acm
from dataclasses import dataclass
from functools import partial
from typing import (
AsyncIterator,
Callable,
Optional,
Union,
)
import numpy as np
@ -32,9 +33,9 @@ from trio_typing import TaskStatus
import tractor
from tractor.msg import NamespacePath
from piker.types import Struct
from ..log import get_logger, get_console_log
from .. import data
from ..data import attach_shm_array
from ..data.feed import (
Flume,
Feed,
@ -50,11 +51,17 @@ from ._api import (
_load_builtins,
_Token,
)
from ..toolz import Profiler
from .._profile import Profiler
log = get_logger(__name__)
@dataclass
class TaskTracker:
complete: trio.Event
cs: trio.CancelScope
async def filter_quotes_by_sym(
sym: str,
@ -75,168 +82,30 @@ async def filter_quotes_by_sym(
if quote:
yield quote
# TODO: unifying the abstractions in this FSP subsys/layer:
# -[ ] move the `.data.flows.Flume` type into this
# module/subsys/pkg?
# -[ ] ideas for further abstractions as per
# - https://github.com/pikers/piker/issues/216,
# - https://github.com/pikers/piker/issues/270:
# - a (financial signal) ``Flow`` would be the a "collection" of such
# minmial cascades. Some engineering based jargon concepts:
# - https://en.wikipedia.org/wiki/Signal_chain
# - https://en.wikipedia.org/wiki/Daisy_chain_(electrical_engineering)
# - https://en.wikipedia.org/wiki/Audio_signal_flow
# - https://en.wikipedia.org/wiki/Digital_signal_processing#Implementation
# - https://en.wikipedia.org/wiki/Dataflow_programming
# - https://en.wikipedia.org/wiki/Signal_programming
# - https://en.wikipedia.org/wiki/Incremental_computing
# - https://en.wikipedia.org/wiki/Signal-flow_graph
# - https://en.wikipedia.org/wiki/Signal-flow_graph#Basic_components
# -[ ] we probably want to eval THE BELOW design and unify with the
# proto `TaskManager` in the `tractor` dev branch as well as with
# our below idea for `Cascade`:
# - https://github.com/goodboy/tractor/pull/363
class Cascade(Struct):
'''
As per sig-proc engineering parlance, this is a chaining of
`Flume`s, which are themselves collections of "Streams"
implemented currently via `ShmArray`s.
async def fsp_compute(
A `Cascade` is be the minimal "connection" of 2 `Flumes`
as per circuit parlance:
https://en.wikipedia.org/wiki/Two-port_network#Cascade_connection
TODO:
-[ ] could cover the combination of our `FspAdmin` and the
backend `.fsp._engine` related machinery to "connect" one flume
to another?
'''
# TODO: make these `Flume`s
src: Flume
dst: Flume
tn: trio.Nursery
fsp: Fsp # UI-side middleware ctl API
# filled during cascade/.bind_func() (fsp_compute) init phases
bind_func: Callable | None = None
complete: trio.Event | None = None
cs: trio.CancelScope | None = None
client_stream: tractor.MsgStream | None = None
async def resync(self) -> int:
# TODO: adopt an incremental update engine/approach
# where possible here eventually!
log.info(f're-syncing fsp {self.fsp.name} to source')
self.cs.cancel()
await self.complete.wait()
index: int = await self.tn.start(self.bind_func)
# always trigger UI refresh after history update,
# see ``piker.ui._fsp.FspAdmin.open_chain()`` and
# ``piker.ui._display.trigger_update()``.
dst_shm: ShmArray = self.dst.rt_shm
await self.client_stream.send({
'fsp_update': {
'key': dst_shm.token,
'first': dst_shm._first.value,
'last': dst_shm._last.value,
}
})
return index
def is_synced(self) -> tuple[bool, int, int]:
'''
Predicate to dertmine if a destination FSP
output array is aligned to its source array.
'''
src_shm: ShmArray = self.src.rt_shm
dst_shm: ShmArray = self.dst.rt_shm
step_diff = src_shm.index - dst_shm.index
len_diff = abs(len(src_shm.array) - len(dst_shm.array))
synced: bool = not (
# the source is likely backfilling and we must
# sync history calculations
len_diff > 2
# we aren't step synced to the source and may be
# leading/lagging by a step
or step_diff > 1
or step_diff < 0
)
if not synced:
fsp: Fsp = self.fsp
log.warning(
'***DESYNCED FSP***\n'
f'{fsp.ns_path}@{src_shm.token}\n'
f'step_diff: {step_diff}\n'
f'len_diff: {len_diff}\n'
)
return (
synced,
step_diff,
len_diff,
)
async def poll_and_sync_to_step(self) -> int:
synced, step_diff, _ = self.is_synced()
while not synced:
await self.resync()
synced, step_diff, _ = self.is_synced()
return step_diff
@acm
async def open_edge(
self,
bind_func: Callable,
) -> int:
self.bind_func = bind_func
index = await self.tn.start(bind_func)
yield index
# TODO: what do we want on teardown/error?
# -[ ] dynamic reconnection after update?
async def connect_streams(
casc: Cascade,
mkt: MktPair,
flume: Flume,
quote_stream: trio.abc.ReceiveChannel,
src: Flume,
dst: Flume,
edge_func: Callable,
src: ShmArray,
dst: ShmArray,
func: Callable,
# attach_stream: bool = False,
task_status: TaskStatus[None] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Stream and per-sample compute and write the cascade of
2 `Flumes`/streams given some operating `func`.
https://en.wikipedia.org/wiki/Signal-flow_graph#Basic_components
Not literally, but something like:
edge_func(Flume_in) -> Flume_out
'''
profiler = Profiler(
delayed=False,
disabled=True
)
# TODO: just pull it from src.mkt.fqme no?
# fqme: str = mkt.fqme
fqme: str = src.mkt.fqme
# TODO: dynamic introspection of what the underlying (vertex)
# function actually requires from input node (flumes) then
# deliver those inputs as part of a graph "compilation" step?
out_stream = edge_func(
fqme = mkt.fqme
out_stream = func(
# TODO: do we even need this if we do the feed api right?
# shouldn't a local stream do this before we get a handle
@ -244,21 +113,20 @@ async def connect_streams(
# async itertools style?
filter_quotes_by_sym(fqme, quote_stream),
# XXX: currently the ``ohlcv`` arg, but we should allow
# (dynamic) requests for src flume (node) streams?
src.rt_shm,
# XXX: currently the ``ohlcv`` arg
flume.rt_shm,
)
# HISTORY COMPUTE PHASE
# conduct a single iteration of fsp with historical bars input
# and get historical output.
history_output: (
dict[str, np.ndarray] # multi-output case
| np.ndarray, # single output case
)
history_output: Union[
dict[str, np.ndarray], # multi-output case
np.ndarray, # single output case
]
history_output = await anext(out_stream)
func_name = edge_func.__name__
func_name = func.__name__
profiler(f'{func_name} generated history')
# build struct array with an 'index' field to push as history
@ -266,12 +134,10 @@ async def connect_streams(
# TODO: push using a[['f0', 'f1', .., 'fn']] = .. syntax no?
# if the output array is multi-field then push
# each respective field.
dst_shm: ShmArray = dst.rt_shm
fields = getattr(dst_shm.array.dtype, 'fields', None).copy()
fields = getattr(dst.array.dtype, 'fields', None).copy()
fields.pop('index')
history_by_field: np.ndarray | None = None
src_shm: ShmArray = src.rt_shm
src_time = src_shm.array['time']
history_by_field: Optional[np.ndarray] = None
src_time = src.array['time']
if (
fields and
@ -290,7 +156,7 @@ async def connect_streams(
if history_by_field is None:
if output is None:
length = len(src_shm.array)
length = len(src.array)
else:
length = len(output)
@ -299,7 +165,7 @@ async def connect_streams(
# will be pushed to shm.
history_by_field = np.zeros(
length,
dtype=dst_shm.array.dtype
dtype=dst.array.dtype
)
if output is None:
@ -316,13 +182,13 @@ async def connect_streams(
)
history_by_field = np.zeros(
len(history_output),
dtype=dst_shm.array.dtype
dtype=dst.array.dtype
)
history_by_field[func_name] = history_output
history_by_field['time'] = src_time[-len(history_by_field):]
history_output['time'] = src_shm.array['time']
history_output['time'] = src.array['time']
# TODO: XXX:
# THERE'S A BIG BUG HERE WITH THE `index` field since we're
@ -335,11 +201,11 @@ async def connect_streams(
# is `index` aware such that historical data can be indexed
# relative to the true first datum? Not sure if this is sane
# for incremental compuations.
first = dst_shm._first.value = src_shm._first.value
first = dst._first.value = src._first.value
# TODO: can we use this `start` flag instead of the manual
# setting above?
index = dst_shm.push(
index = dst.push(
history_by_field,
start=first,
)
@ -350,9 +216,12 @@ async def connect_streams(
# setup a respawn handle
with trio.CancelScope() as cs:
casc.cs = cs
casc.complete = trio.Event()
task_status.started(index)
# TODO: might be better to just make a "restart" method where
# the target task is spawned implicitly and then the event is
# set via some higher level api? At that poing we might as well
# be writing a one-cancels-one nursery though right?
tracker = TaskTracker(trio.Event(), cs)
task_status.started((tracker, index))
profiler(f'{func_name} yield last index')
@ -366,12 +235,12 @@ async def connect_streams(
log.debug(f"{func_name}: {processed}")
key, output = processed
# dst.array[-1][key] = output
dst_shm.array[[key, 'time']][-1] = (
dst.array[[key, 'time']][-1] = (
output,
# TODO: what about pushing ``time.time_ns()``
# in which case we'll need to round at the graphics
# processing / sampling layer?
src_shm.array[-1]['time']
src.array[-1]['time']
)
# NOTE: for now we aren't streaming this to the consumer
@ -383,7 +252,7 @@ async def connect_streams(
# N-consumers who subscribe for the real-time output,
# which we'll likely want to implement using local-mem
# chans for the fan out?
# index = src_shm.index
# index = src.index
# if attach_stream:
# await client_stream.send(index)
@ -393,7 +262,7 @@ async def connect_streams(
# log.info(f'FSP quote too fast: {hz}')
# last = time.time()
finally:
casc.complete.set()
tracker.complete.set()
@tractor.context
@ -404,15 +273,15 @@ async def cascade(
# data feed key
fqme: str,
# flume pair cascaded using an "edge function"
src_flume_addr: dict,
dst_flume_addr: dict,
src_shm_token: dict,
dst_shm_token: tuple[str, np.dtype],
ns_path: NamespacePath,
shm_registry: dict[str, _Token],
zero_on_step: bool = False,
loglevel: str | None = None,
loglevel: Optional[str] = None,
) -> None:
'''
@ -428,14 +297,8 @@ async def cascade(
if loglevel:
get_console_log(loglevel)
src: Flume = Flume.from_msg(src_flume_addr)
dst: Flume = Flume.from_msg(
dst_flume_addr,
readonly=False,
)
# src: ShmArray = attach_shm_array(token=src_shm_token)
# dst: ShmArray = attach_shm_array(readonly=False, token=dst_shm_token)
src = attach_shm_array(token=src_shm_token)
dst = attach_shm_array(readonly=False, token=dst_shm_token)
reg = _load_builtins()
lines = '\n'.join([f'{key.rpartition(":")[2]} => {key}' for key in reg])
@ -443,11 +306,11 @@ async def cascade(
f'Registered FSP set:\n{lines}'
)
# NOTE XXX: update actorlocal flows table which registers
# readonly "instances" of this fsp for symbol/source so that
# consumer fsps can look it up by source + fsp.
# TODO: ugh i hate this wind/unwind to list over the wire but
# not sure how else to do it.
# update actorlocal flows table which registers
# readonly "instances" of this fsp for symbol/source
# so that consumer fsps can look it up by source + fsp.
# TODO: ugh i hate this wind/unwind to list over the wire
# but not sure how else to do it.
for (token, fsp_name, dst_token) in shm_registry:
Fsp._flow_registry[(
_Token.from_msg(token),
@ -457,15 +320,12 @@ async def cascade(
fsp: Fsp = reg.get(
NamespacePath(ns_path)
)
func: Callable = fsp.func
func = fsp.func
if not func:
# TODO: assume it's a func target path
raise ValueError(f'Unknown fsp target: {ns_path}')
_fqme: str = src.mkt.fqme
assert _fqme == fqme
# open a data feed stream with requested broker
feed: Feed
async with data.feed.maybe_open_feed(
@ -479,68 +339,40 @@ async def cascade(
) as feed:
flume: Flume = feed.flumes[fqme]
# XXX: can't do this since flume.feed will be set XD
# assert flume == src
assert flume.mkt == src.mkt
mkt: MktPair = flume.mkt
# NOTE: FOR NOW, sanity checks around the feed as being
# always the src flume (until we get to fancier/lengthier
# chains/graphs.
assert src.rt_shm.token == flume.rt_shm.token
# XXX: won't work bc the _hist_shm_token value will be
# list[list] after IPC..
# assert flume.to_msg() == src_flume_addr
flume = feed.flumes[fqme]
mkt = flume.mkt
assert src.token == flume.rt_shm.token
profiler(f'{func}: feed up')
func_name: str = func.__name__
func_name = func.__name__
async with (
trio.open_nursery() as tn,
trio.open_nursery() as n,
):
# TODO: might be better to just make a "restart" method where
# the target task is spawned implicitly and then the event is
# set via some higher level api? At that poing we might as well
# be writing a one-cancels-one nursery though right?
casc = Cascade(
src,
dst,
tn,
fsp,
)
# TODO: this seems like it should be wrapped somewhere?
fsp_target = partial(
connect_streams,
casc=casc,
fsp_compute,
mkt=mkt,
flume=flume,
quote_stream=flume.stream,
# flumes and shm passthrough
# shm
src=src,
dst=dst,
# chain function which takes src flume input(s)
# and renders dst flume output(s)
edge_func=func
# target
func=func
)
async with casc.open_edge(
bind_func=fsp_target,
) as index:
# casc.bind_func = fsp_target
# index = await tn.start(fsp_target)
dst_shm: ShmArray = dst.rt_shm
src_shm: ShmArray = src.rt_shm
tracker, index = await n.start(fsp_target)
if zero_on_step:
last = dst.rt_shm.array[-1:]
last = dst.array[-1:]
zeroed = np.zeros(last.shape, dtype=last.dtype)
profiler(f'{func_name}: fsp up')
# sync to client-side actor
# sync client
await ctx.started(index)
# XXX: rt stream with client which we MUST
@ -548,26 +380,85 @@ async def cascade(
# incremental "updates" as history prepends take
# place.
async with ctx.open_stream() as client_stream:
casc.client_stream: tractor.MsgStream = client_stream
s, step, ld = casc.is_synced()
# TODO: these likely should all become
# methods of this ``TaskLifetime`` or wtv
# abstraction..
async def resync(
tracker: TaskTracker,
) -> tuple[TaskTracker, int]:
# TODO: adopt an incremental update engine/approach
# where possible here eventually!
log.info(f're-syncing fsp {func_name} to source')
tracker.cs.cancel()
await tracker.complete.wait()
tracker, index = await n.start(fsp_target)
# always trigger UI refresh after history update,
# see ``piker.ui._fsp.FspAdmin.open_chain()`` and
# ``piker.ui._display.trigger_update()``.
await client_stream.send({
'fsp_update': {
'key': dst_shm_token,
'first': dst._first.value,
'last': dst._last.value,
}
})
return tracker, index
def is_synced(
src: ShmArray,
dst: ShmArray
) -> tuple[bool, int, int]:
'''
Predicate to dertmine if a destination FSP
output array is aligned to its source array.
'''
step_diff = src.index - dst.index
len_diff = abs(len(src.array) - len(dst.array))
return not (
# the source is likely backfilling and we must
# sync history calculations
len_diff > 2
# we aren't step synced to the source and may be
# leading/lagging by a step
or step_diff > 1
or step_diff < 0
), step_diff, len_diff
async def poll_and_sync_to_step(
tracker: TaskTracker,
src: ShmArray,
dst: ShmArray,
) -> tuple[TaskTracker, int]:
synced, step_diff, _ = is_synced(src, dst)
while not synced:
tracker, index = await resync(tracker)
synced, step_diff, _ = is_synced(src, dst)
return tracker, step_diff
s, step, ld = is_synced(src, dst)
# detect sample period step for subscription to increment
# signal
times = src.rt_shm.array['time']
times = src.array['time']
if len(times) > 1:
last_ts = times[-1]
delay_s: float = float(last_ts - times[times != last_ts][-1])
delay_s = float(last_ts - times[times != last_ts][-1])
else:
# our default "HFT" sample rate.
delay_s: float = _default_delay_s
delay_s = _default_delay_s
# sub and increment the underlying shared memory buffer
# on every step msg received from the global `samplerd`
# service.
async with open_sample_stream(
float(delay_s)
) as istream:
async with open_sample_stream(float(delay_s)) as istream:
profiler(f'{func_name}: sample stream up')
profiler.finish()
@ -578,9 +469,13 @@ async def cascade(
# respawn the compute task if the source
# array has been updated such that we compute
# new history from the (prepended) source.
synced, step_diff, _ = casc.is_synced()
synced, step_diff, _ = is_synced(src, dst)
if not synced:
step_diff: int = await casc.poll_and_sync_to_step()
tracker, step_diff = await poll_and_sync_to_step(
tracker,
src,
dst,
)
# skip adding a last bar since we should already
# be step alinged
@ -588,7 +483,7 @@ async def cascade(
continue
# read out last shm row, copy and write new row
array = dst_shm.array
array = dst.array
# some metrics like vlm should be reset
# to zero every step.
@ -597,14 +492,14 @@ async def cascade(
else:
last = array[-1:].copy()
dst.rt_shm.push(last)
dst.push(last)
# sync with source buffer's time step
src_l2 = src_shm.array[-2:]
src_l2 = src.array[-2:]
src_li, src_lt = src_l2[-1][['index', 'time']]
src_2li, src_2lt = src_l2[-2][['index', 'time']]
dst_shm._array['time'][src_li] = src_lt
dst_shm._array['time'][src_2li] = src_2lt
dst._array['time'][src_li] = src_lt
dst._array['time'][src_2li] = src_2lt
# last2 = dst.array[-2:]
# if (

View File

@ -14,45 +14,49 @@
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Actor runtime primtives and (distributed) service APIs for,
"""
Actor-runtime service orchestration machinery.
- daemon-service mgmt: `_daemon` (i.e. low-level spawn and supervise machinery
for sub-actors like `brokerd`, `emsd`, datad`, etc.)
"""
from __future__ import annotations
- service-actor supervision (via `trio` tasks) API: `._mngr`
- discovery interface (via light wrapping around `tractor`'s built-in
prot): `._registry`
- `docker` cntr SC supervision for use with `trio`: `_ahab`
- wrappers for marketstore and elasticsearch dbs
=> TODO: maybe to (re)move elsewhere?
'''
from ._mngr import Services as Services
from ._registry import (
_tractor_kwargs as _tractor_kwargs,
_default_reg_addr as _default_reg_addr,
_default_registry_host as _default_registry_host,
_default_registry_port as _default_registry_port,
open_registry as open_registry,
find_service as find_service,
check_for_service as check_for_service,
from ._mngr import Services
from ._registry import ( # noqa
_tractor_kwargs,
_default_reg_addr,
_default_registry_host,
_default_registry_port,
open_registry,
find_service,
check_for_service,
)
from ._daemon import (
maybe_spawn_daemon as maybe_spawn_daemon,
spawn_emsd as spawn_emsd,
maybe_open_emsd as maybe_open_emsd,
from ._daemon import ( # noqa
maybe_spawn_daemon,
spawn_emsd,
maybe_open_emsd,
)
from ._actor_runtime import (
open_piker_runtime as open_piker_runtime,
maybe_open_pikerd as maybe_open_pikerd,
open_pikerd as open_pikerd,
get_runtime_vars as get_runtime_vars,
open_piker_runtime,
maybe_open_pikerd,
open_pikerd,
get_tractor_runtime_kwargs,
)
from ..brokers._daemon import (
spawn_brokerd as spawn_brokerd,
maybe_spawn_brokerd as maybe_spawn_brokerd,
spawn_brokerd,
maybe_spawn_brokerd,
)
__all__ = [
'check_for_service',
'Services',
'maybe_spawn_daemon',
'spawn_brokerd',
'maybe_spawn_brokerd',
'spawn_emsd',
'maybe_open_emsd',
'open_piker_runtime',
'maybe_open_pikerd',
'open_pikerd',
'get_tractor_runtime_kwargs',
]

View File

@ -45,7 +45,7 @@ from ._registry import ( # noqa
)
def get_runtime_vars() -> dict[str, Any]:
def get_tractor_runtime_kwargs() -> dict[str, Any]:
'''
Deliver ``tractor`` related runtime variables in a `dict`.
@ -56,8 +56,6 @@ def get_runtime_vars() -> dict[str, Any]:
@acm
async def open_piker_runtime(
name: str,
registry_addrs: list[tuple[str, int]] = [],
enable_modules: list[str] = [],
loglevel: Optional[str] = None,
@ -65,6 +63,8 @@ async def open_piker_runtime(
# for data daemons when running in production.
debug_mode: bool = False,
registry_addr: None | tuple[str, int] = None,
# TODO: once we have `rsyscall` support we will read a config
# and spawn the service tree distributed per that.
start_method: str = 'trio',
@ -74,7 +74,7 @@ async def open_piker_runtime(
) -> tuple[
tractor.Actor,
list[tuple[str, int]],
tuple[str, int],
]:
'''
Start a piker actor who's runtime will automatically sync with
@ -84,31 +84,21 @@ async def open_piker_runtime(
a root actor.
'''
# check for existing runtime, boot it
# if not already running.
try:
actor = tractor.current_actor()
# check for existing runtime
actor = tractor.current_actor().uid
except tractor._exceptions.NoRuntime:
tractor._state._runtime_vars[
'piker_vars'
] = tractor_runtime_overrides
'piker_vars'] = tractor_runtime_overrides
# NOTE: if no registrar list passed used the default of just
# setting it as the root actor on localhost.
registry_addrs = (
registry_addrs
or [_default_reg_addr]
)
if ems := tractor_kwargs.pop('enable_modules', None):
# import pdbp; pdbp.set_trace()
enable_modules.extend(ems)
registry_addr = registry_addr or _default_reg_addr
async with (
tractor.open_root_actor(
# passed through to ``open_root_actor``
registry_addrs=registry_addrs,
arbiter_addr=registry_addr,
name=name,
loglevel=loglevel,
debug_mode=debug_mode,
@ -120,30 +110,24 @@ async def open_piker_runtime(
enable_modules=enable_modules,
**tractor_kwargs,
) as actor,
) as _,
open_registry(
registry_addrs,
ensure_exists=False,
) as addrs,
open_registry(registry_addr, ensure_exists=False) as addr,
):
assert actor is tractor.current_actor()
yield (
actor,
addrs,
tractor.current_actor(),
addr,
)
else:
async with open_registry(
registry_addrs
) as addrs:
async with open_registry(registry_addr) as addr:
yield (
actor,
addrs,
addr,
)
_root_dname: str = 'pikerd'
_root_modules: list[str] = [
_root_dname = 'pikerd'
_root_modules = [
__name__,
'piker.service._daemon',
'piker.brokers._daemon',
@ -157,13 +141,13 @@ _root_modules: list[str] = [
@acm
async def open_pikerd(
registry_addrs: list[tuple[str, int]],
loglevel: str | None = None,
# XXX: you should pretty much never want debug mode
# for data daemons when running in production.
debug_mode: bool = False,
registry_addr: None | tuple[str, int] = None,
**kwargs,
@ -175,37 +159,27 @@ async def open_pikerd(
alive underling services (see below).
'''
# NOTE: for the root daemon we always enable the root
# mod set and we `list.extend()` it into wtv the
# caller requested.
# TODO: make this mod set more strict?
# -[ ] eventually we should be able to avoid
# having the root have more then permissions to spawn other
# specialized daemons I think?
ems: list[str] = kwargs.setdefault('enable_modules', [])
ems.extend(_root_modules)
async with (
open_piker_runtime(
name=_root_dname,
# TODO: eventually we should be able to avoid
# having the root have more then permissions to
# spawn other specialized daemons I think?
enable_modules=_root_modules,
loglevel=loglevel,
debug_mode=debug_mode,
registry_addrs=registry_addrs,
registry_addr=registry_addr,
**kwargs,
) as (
root_actor,
reg_addrs,
),
) as (root_actor, reg_addr),
tractor.open_nursery() as actor_nursery,
trio.open_nursery() as service_nursery,
):
for addr in reg_addrs:
if addr not in root_actor.accept_addrs:
if root_actor.accept_addr != reg_addr:
raise RuntimeError(
f'`pikerd` failed to bind on {addr}!\n'
f'`pikerd` failed to bind on {reg_addr}!\n'
'Maybe you have another daemon already running?'
)
@ -251,9 +225,9 @@ async def open_pikerd(
@acm
async def maybe_open_pikerd(
registry_addrs: list[tuple[str, int]] | None = None,
loglevel: Optional[str] = None,
registry_addr: None | tuple = None,
loglevel: str | None = None,
**kwargs,
) -> tractor._portal.Portal | ClassVar[Services]:
@ -279,51 +253,32 @@ async def maybe_open_pikerd(
# async with open_portal(chan) as arb_portal:
# yield arb_portal
registry_addrs: list[tuple[str, int]] = (
registry_addrs
or [_default_reg_addr]
)
pikerd_portal: tractor.Portal | None
async with (
open_piker_runtime(
name=query_name,
registry_addrs=registry_addrs,
registry_addr=registry_addr,
loglevel=loglevel,
**kwargs,
) as (actor, addrs),
):
if _root_dname in actor.uid:
yield None
return
) as _,
# NOTE: IFF running in disti mode, try to attach to any
# existing (host-local) `pikerd`.
else:
async with tractor.find_actor(
tractor.find_actor(
_root_dname,
registry_addrs=registry_addrs,
only_first=True,
# raise_on_none=True,
) as pikerd_portal:
# connect to any existing remote daemon presuming its
# registry socket was selected.
if pikerd_portal is not None:
# sanity check that we are actually connecting to
# a remote process and not ourselves.
assert actor.uid != pikerd_portal.channel.uid
assert registry_addrs
yield pikerd_portal
arbiter_sockaddr=registry_addr,
) as portal
):
# connect to any existing daemon presuming
# its registry socket was selected.
if (
portal is not None
):
yield portal
return
# presume pikerd role since no daemon could be found at
# configured address
async with open_pikerd(
loglevel=loglevel,
registry_addrs=registry_addrs,
registry_addr=registry_addr,
# passthrough to ``tractor`` init
**kwargs,

View File

@ -15,8 +15,8 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Supervisor for ``docker`` with included async and SC wrapping to
ensure a cancellable container lifetime system.
Supervisor for ``docker`` with included async and SC wrapping
to ensure a cancellable container lifetime system.
'''
from __future__ import annotations

View File

@ -70,10 +70,7 @@ async def maybe_spawn_daemon(
lock = Services.locks[service_name]
await lock.acquire()
async with find_service(
service_name,
registry_addrs=[('127.0.0.1', 6116)],
) as portal:
async with find_service(service_name) as portal:
if portal is not None:
lock.release()
yield portal

View File

@ -27,12 +27,6 @@ from typing import (
import trio
from trio_typing import TaskStatus
import tractor
from tractor import (
current_actor,
ContextCancelled,
Context,
Portal,
)
from ._util import (
log, # sub-sys logger
@ -44,8 +38,6 @@ from ._util import (
# library.
# - wrap a "remote api" wherein you can get a method proxy
# to the pikerd actor for starting services remotely!
# - prolly rename this to ActorServicesNursery since it spawns
# new actors and supervises them to completion?
class Services:
actor_n: tractor._supervise.ActorNursery
@ -55,7 +47,7 @@ class Services:
str,
tuple[
trio.CancelScope,
Portal,
tractor.Portal,
trio.Event,
]
] = {}
@ -65,12 +57,12 @@ class Services:
async def start_service_task(
self,
name: str,
portal: Portal,
portal: tractor.Portal,
target: Callable,
allow_overruns: bool = False,
**ctx_kwargs,
) -> (trio.CancelScope, Context):
) -> (trio.CancelScope, tractor.Context):
'''
Open a context in a service sub-actor, add to a stack
that gets unwound at ``pikerd`` teardown.
@ -109,30 +101,13 @@ class Services:
# wait on any context's return value
# and any final portal result from the
# sub-actor.
ctx_res: Any = await ctx.result()
ctx_res = await ctx.result()
# NOTE: blocks indefinitely until cancelled
# either by error from the target context
# function or by being cancelled here by the
# surrounding cancel scope.
return (await portal.result(), ctx_res)
except ContextCancelled as ctxe:
canceller: tuple[str, str] = ctxe.canceller
our_uid: tuple[str, str] = current_actor().uid
if (
canceller != portal.channel.uid
and
canceller != our_uid
):
log.cancel(
f'Actor-service {name} was remotely cancelled?\n'
f'remote canceller: {canceller}\n'
f'Keeping {our_uid} alive, ignoring sub-actor cancel..\n'
)
else:
raise
finally:
await portal.cancel_actor()

View File

@ -27,7 +27,6 @@ from typing import (
)
import tractor
from tractor import Portal
from ._util import (
log, # sub-sys logger
@ -47,9 +46,7 @@ _registry: Registry | None = None
class Registry:
# TODO: should this be a set or should we complain
# on duplicates?
addrs: list[tuple[str, int]] = []
addr: None | tuple[str, int] = None
# TODO: table of uids to sockaddrs
peers: dict[
@ -63,115 +60,69 @@ _tractor_kwargs: dict[str, Any] = {}
@acm
async def open_registry(
addrs: list[tuple[str, int]],
addr: None | tuple[str, int] = None,
ensure_exists: bool = True,
) -> list[tuple[str, int]]:
'''
Open the service-actor-discovery registry by returning a set of
tranport socket-addrs to registrar actors which may be
contacted and queried for similar addresses for other
non-registrar actors.
) -> tuple[str, int]:
'''
global _tractor_kwargs
actor = tractor.current_actor()
uid = actor.uid
preset_reg_addrs: list[tuple[str, int]] = Registry.addrs
if (
preset_reg_addrs
and addrs
Registry.addr is not None
and addr
):
if preset_reg_addrs != addrs:
# if any(addr in preset_reg_addrs for addr in addrs):
diff: set[tuple[str, int]] = set(preset_reg_addrs) - set(addrs)
if diff:
log.warning(
f'`{uid}` requested only subset of registrars: {addrs}\n'
f'However there are more @{diff}'
)
else:
raise RuntimeError(
f'`{uid}` has non-matching registrar addresses?\n'
f'request: {addrs}\n'
f'already set: {preset_reg_addrs}'
f'`{uid}` registry addr already bound @ {_registry.sockaddr}'
)
was_set: bool = False
if (
not tractor.is_root_process()
and not Registry.addrs
and Registry.addr is None
):
Registry.addrs.extend(actor.reg_addrs)
Registry.addr = actor._arb_addr
if (
ensure_exists
and not Registry.addrs
and Registry.addr is None
):
raise RuntimeError(
f"`{uid}` registry should already exist but doesn't?"
f"`{uid}` registry should already exist bug doesn't?"
)
if (
not Registry.addrs
Registry.addr is None
):
was_set = True
Registry.addrs = addrs or [_default_reg_addr]
Registry.addr = addr or _default_reg_addr
# NOTE: only spot this seems currently used is inside
# `.ui._exec` which is the (eventual qtloops) bootstrapping
# with guest mode.
_tractor_kwargs['registry_addrs'] = Registry.addrs
_tractor_kwargs['arbiter_addr'] = Registry.addr
try:
yield Registry.addrs
yield Registry.addr
finally:
# XXX: always clear the global addr if we set it so that the
# next (set of) calls will apply whatever new one is passed
# in.
if was_set:
Registry.addrs = None
Registry.addr = None
@acm
async def find_service(
service_name: str,
registry_addrs: list[tuple[str, int]] | None = None,
) -> tractor.Portal | None:
first_only: bool = True,
) -> (
Portal
| list[Portal]
| None
):
reg_addrs: list[tuple[str, int]]
async with open_registry(
addrs=(
registry_addrs
# NOTE: if no addr set is passed assume the registry has
# already been opened and use the previously applied
# startup set.
or Registry.addrs
),
) as reg_addrs:
async with open_registry() as reg_addr:
log.info(f'Scanning for service `{service_name}`')
maybe_portals: list[Portal] | Portal | None
# attach to existing daemon by name if possible
async with tractor.find_actor(
service_name,
registry_addrs=reg_addrs,
only_first=first_only, # if set only returns single ref
) as maybe_portals:
if not maybe_portals:
yield None
return
yield maybe_portals
arbiter_sockaddr=reg_addr,
) as maybe_portal:
yield maybe_portal
async def check_for_service(
@ -182,11 +133,9 @@ async def check_for_service(
Service daemon "liveness" predicate.
'''
async with (
open_registry(ensure_exists=False) as reg_addr,
tractor.query_actor(
async with open_registry(ensure_exists=False) as reg_addr:
async with tractor.query_actor(
service_name,
arbiter_sockaddr=reg_addr,
) as sockaddr,
):
) as sockaddr:
return sockaddr

View File

@ -139,13 +139,6 @@ class StorageClient(
...
class TimeseriesNotFound(Exception):
'''
No timeseries entry can be found for this backend.
'''
class StorageConnectionError(ConnectionError):
'''
Can't connect to the desired tsdb subsys/service.
@ -176,13 +169,10 @@ async def open_storage_client(
tsdb_host: str = 'localhost'
# load root config and any tsdb user defined settings
conf, path = config.load(
conf_name='conf',
touch_if_dne=True,
)
conf, path = config.load('conf', touch_if_dne=True)
# TODO: maybe not under a "network" section.. since
# no more chitty `marketstore`..
# no more chitty mkts..
tsdbconf: dict = {}
service_section = conf.get('service')
if (
@ -193,11 +183,8 @@ async def open_storage_client(
# lookup backend tsdb module by name and load any user service
# settings for connecting to the tsdb service.
backend: str = tsdbconf.pop(
'name',
def_backend,
)
tsdb_host: str = tsdbconf.get('maddrs', [])
backend: str = tsdbconf.pop('backend')
tsdb_host: str = tsdbconf['host']
if backend is None:
backend: str = def_backend
@ -259,7 +246,7 @@ async def open_tsdb_client(
# * the original data feed arch blurb:
# - https://github.com/pikers/piker/issues/98
#
from ..toolz import Profiler
from .._profile import Profiler
profiler = Profiler(
disabled=True, # not pg_profile_enabled(),
delayed=False,

View File

@ -1,5 +1,5 @@
# piker: trading gear for hackers
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of pikers)
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
@ -19,18 +19,10 @@ Storage middle-ware CLIs.
"""
from __future__ import annotations
# from datetime import datetime
# from contextlib import (
# AsyncExitStack,
# )
from pathlib import Path
from math import copysign
import time
from types import ModuleType
from typing import (
Any,
TYPE_CHECKING,
)
from typing import Generator
# from typing import TYPE_CHECKING
import polars as pl
import numpy as np
@ -43,21 +35,24 @@ import typer
from piker.service import open_piker_runtime
from piker.cli import cli
from piker.config import get_conf_dir
from piker.data import (
maybe_open_shm_array,
def_iohlcv_fields,
ShmArray,
)
from piker import tsp
from piker.data._formatters import BGM
from . import log
from piker.data.history import (
_default_hist_size,
_default_rt_size,
)
from . import (
log,
)
from . import (
__tsdbs__,
open_storage_client,
StorageClient,
)
if TYPE_CHECKING:
from piker.ui._remote_ctl import AnnotCtl
store = typer.Typer()
@ -82,6 +77,7 @@ def ls(
async with (
open_piker_runtime(
'tsdb_storage',
enable_modules=['piker.service._ahab'],
),
):
for i, backend in enumerate(backends):
@ -103,18 +99,6 @@ def ls(
trio.run(query_all)
# TODO: like ls but takes in a pattern and matches
# @store.command()
# def search(
# patt: str,
# backends: list[str] = typer.Argument(
# default=None,
# help='Storage backends to query, default is all.'
# ),
# ):
# ...
@store.command()
def delete(
symbols: list[str],
@ -137,6 +121,7 @@ def delete(
async with (
open_piker_runtime(
'tsdb_storage',
enable_modules=['piker.service._ahab']
),
open_storage_client(backend) as (_, client),
trio.open_nursery() as n,
@ -157,33 +142,20 @@ def delete(
def anal(
fqme: str,
period: int = 60,
pdb: bool = False,
) -> np.ndarray:
'''
Anal-ysis is when you take the data do stuff to it.
NOTE: This ONLY loads the offline timeseries data (by default
from a parquet file) NOT the in-shm version you might be seeing
in a chart.
'''
async def main():
async with (
open_piker_runtime(
# are you a bear or boi?
'tsdb_polars_anal',
debug_mode=pdb,
),
open_storage_client() as (
mod,
client,
# enable_modules=['piker.service._ahab']
),
open_storage_client() as (mod, client),
):
syms: list[str] = await client.list_keys()
log.info(f'{len(syms)} FOUND for {mod.name}')
print(f'{len(syms)} FOUND for {mod.name}')
history: ShmArray # np buffer format
(
history,
first_dt,
@ -194,357 +166,166 @@ def anal(
)
assert first_dt < last_dt
null_segs: tuple = tsp.get_null_segs(
frame=history,
period=period,
)
# TODO: do tsp queries to backcend to fill i missing
# history and then prolly write it to tsdb!
src_df = await client.as_df(fqme, period)
from piker.data import _timeseries as tsmod
df = tsmod.with_dts(src_df)
gaps: pl.DataFrame = tsmod.detect_time_gaps(df)
shm_df: pl.DataFrame = await client.as_df(
fqme,
period,
)
if gaps:
print(f'Gaps found:\n{gaps}')
df: pl.DataFrame # with dts
deduped: pl.DataFrame # deduplicated dts
(
df,
deduped,
diff,
) = tsp.dedupe(
shm_df,
period=period,
)
write_edits: bool = True
if (
write_edits
and (
diff
or null_segs
)
):
await tractor.pause()
await client.write_ohlcv(
fqme,
ohlcv=deduped,
timeframe=period,
)
else:
# TODO: something better with tab completion..
# is there something more minimal but nearly as
# functional as ipython?
await tractor.pause()
assert not null_segs
await tractor.breakpoint()
trio.run(main)
async def markup_gaps(
fqme: str,
timeframe: float,
actl: AnnotCtl,
wdts: pl.DataFrame,
gaps: pl.DataFrame,
def iter_dfs_from_shms(fqme: str) -> Generator[
tuple[Path, ShmArray, pl.DataFrame],
None,
None,
]:
# shm buffer size table based on known sample rates
sizes: dict[str, int] = {
'hist': _default_hist_size,
'rt': _default_rt_size,
}
) -> dict[int, dict]:
'''
Remote annotate time-gaps in a dt-fielded ts (normally OHLC)
with rectangles.
# load all detected shm buffer files which have the
# passed FQME pattern in the file name.
shmfiles: list[Path] = []
shmdir = Path('/dev/shm/')
'''
aids: dict[int] = {}
for i in range(gaps.height):
for shmfile in shmdir.glob(f'*{fqme}*'):
filename: str = shmfile.name
row: pl.DataFrame = gaps[i]
# skip index files
if (
'_first' in filename
or '_last' in filename
):
continue
# the gap's RIGHT-most bar's OPEN value
# at that time (sample) step.
iend: int = row['index'][0]
# dt: datetime = row['dt'][0]
# dt_prev: datetime = row['dt_prev'][0]
# dt_end_t: float = dt.timestamp()
assert shmfile.is_file()
log.debug(f'Found matching shm buffer file: {filename}')
shmfiles.append(shmfile)
for shmfile in shmfiles:
# TODO: can we eventually remove this
# once we figure out why the epoch cols
# don't match?
# TODO: FIX HOW/WHY these aren't matching
# and are instead off by 4hours (EST
# vs. UTC?!?!)
# end_t: float = row['time']
# assert (
# dt.timestamp()
# ==
# end_t
# )
# lookup array buffer size based on file suffix
# being either .rt or .hist
size: int = sizes[shmfile.name.rsplit('.')[-1]]
# the gap's LEFT-most bar's CLOSE value
# at that time (sample) step.
prev_r: pl.DataFrame = wdts.filter(
pl.col('index') == iend - 1
# attach to any shm buffer, load array into polars df,
# write to local parquet file.
shm, opened = maybe_open_shm_array(
key=shmfile.name,
size=size,
dtype=def_iohlcv_fields,
readonly=True,
)
# XXX: probably a gap in the (newly sorted or de-duplicated)
# dt-df, so we might need to re-index first..
if prev_r.is_empty():
await tractor.pause()
assert not opened
ohlcv = shm.array
istart: int = prev_r['index'][0]
# dt_start_t: float = dt_prev.timestamp()
start = time.time()
# start_t: float = prev_r['time']
# assert (
# dt_start_t
# ==
# start_t
# )
# TODO: implement px-col width measure
# and ensure at least as many px-cols
# shown per rect as configured by user.
# gap_w: float = abs((iend - istart))
# if gap_w < 6:
# margin: float = 6
# iend += margin
# istart -= margin
rect_gap: float = BGM*3/8
opn: float = row['open'][0]
ro: tuple[float, float] = (
# dt_end_t,
iend + rect_gap + 1,
opn,
# XXX: thanks to this SO answer for this conversion tip:
# https://stackoverflow.com/a/72054819
df = pl.DataFrame({
field_name: ohlcv[field_name]
for field_name in ohlcv.dtype.fields
})
delay: float = round(
time.time() - start,
ndigits=6,
)
cls: float = prev_r['close'][0]
lc: tuple[float, float] = (
# dt_start_t,
istart - rect_gap, # + 1 ,
cls,
log.info(
f'numpy -> polars conversion took {delay} secs\n'
f'polars df: {df}'
)
color: str = 'dad_blue'
diff: float = cls - opn
sgn: float = copysign(1, diff)
color: str = {
-1: 'buy_green',
1: 'sell_red',
}[sgn]
rect_kwargs: dict[str, Any] = dict(
fqme=fqme,
timeframe=timeframe,
start_pos=lc,
end_pos=ro,
color=color,
yield (
shmfile,
shm,
df,
)
aid: int = await actl.add_rect(**rect_kwargs)
assert aid
aids[aid] = rect_kwargs
# tell chart to redraw all its
# graphics view layers Bo
await actl.redraw(
fqme=fqme,
timeframe=timeframe,
)
return aids
@store.command()
def ldshm(
fqme: str,
write_parquet: bool = True,
reload_parquet_to_shm: bool = True,
write_parquet: bool = False,
) -> None:
'''
Linux ONLY: load any fqme file name matching shm buffer from
/dev/shm/ into an OHLCV numpy array and polars DataFrame,
optionally write to offline storage via `.parquet` file.
optionally write to .parquet file.
'''
async def main():
from piker.ui._remote_ctl import (
open_annot_ctl,
)
actl: AnnotCtl
mod: ModuleType
client: StorageClient
async with (
open_piker_runtime(
'polars_boi',
enable_modules=['piker.data._sharedmem'],
debug_mode=True,
),
open_storage_client() as (
mod,
client,
),
open_annot_ctl() as actl,
):
shm_df: pl.DataFrame | None = None
tf2aids: dict[float, dict] = {}
for (
shmfile,
shm,
# parquet_path,
shm_df,
) in tsp.iter_dfs_from_shms(fqme):
df: pl.DataFrame | None = None
for shmfile, shm, df in iter_dfs_from_shms(fqme):
# compute ohlc properties for naming
times: np.ndarray = shm.array['time']
d1: float = float(times[-1] - times[-2])
d2: float = float(times[-2] - times[-3])
med: float = np.median(np.diff(times))
if (
d1 < 1.
and d2 < 1.
and med < 1.
):
secs: float = times[-1] - times[-2]
if secs < 1.:
breakpoint()
raise ValueError(
f'Something is wrong with time period for {shm}:\n{times}'
)
period_s: float = float(max(d1, d2, med))
# TODO: maybe only optionally enter this depending
# on some CLI flags and/or gap detection?
await tractor.breakpoint()
null_segs: tuple = tsp.get_null_segs(
frame=shm.array,
period=period_s,
)
# TODO: call null-seg fixer somehow?
if null_segs:
await tractor.pause()
# async with (
# trio.open_nursery() as tn,
# mod.open_history_client(
# mkt,
# ) as (get_hist, config),
# ):
# nulls_detected: trio.Event = await tn.start(partial(
# tsp.maybe_fill_null_segments,
# shm=shm,
# timeframe=timeframe,
# get_hist=get_hist,
# sampler_stream=sampler_stream,
# mkt=mkt,
# ))
# over-write back to shm?
wdts: pl.DataFrame # with dts
deduped: pl.DataFrame # deduplicated dts
(
wdts,
deduped,
diff,
) = tsp.dedupe(
shm_df,
period=period_s,
)
# detect gaps from in expected (uniform OHLC) sample period
step_gaps: pl.DataFrame = tsp.detect_time_gaps(
deduped,
expect_period=period_s,
)
# TODO: by default we always want to mark these up
# with rects showing up/down gaps Bo
venue_gaps: pl.DataFrame = tsp.detect_time_gaps(
deduped,
expect_period=period_s,
# TODO: actually pull the exact duration
# expected for each venue operational period?
gap_dt_unit='days',
gap_thresh=1,
)
# TODO: find the disjoint set of step gaps from
# venue (closure) set!
# -[ ] do a set diff by checking for the unique
# gap set only in the step_gaps?
if (
not venue_gaps.is_empty()
or (
period_s < 60
and not step_gaps.is_empty()
)
):
# write repaired ts to parquet-file?
# write to parquet file?
if write_parquet:
start: float = time.time()
path: Path = await client.write_ohlcv(
fqme,
ohlcv=deduped,
timeframe=period_s,
)
write_delay: float = round(
time.time() - start,
ndigits=6,
)
timeframe: str = f'{secs}s'
# read back from fs
start: float = time.time()
read_df: pl.DataFrame = pl.read_parquet(path)
read_delay: float = round(
datadir: Path = get_conf_dir() / 'nativedb'
if not datadir.is_dir():
datadir.mkdir()
path: Path = datadir / f'{fqme}.{timeframe}.parquet'
# write to fs
start = time.time()
df.write_parquet(path)
delay: float = round(
time.time() - start,
ndigits=6,
)
log.info(
f'parquet write took {write_delay} secs\n'
f'parquet write took {delay} secs\n'
f'file path: {path}'
f'parquet read took {read_delay} secs\n'
)
# read back from fs
start = time.time()
read_df: pl.DataFrame = pl.read_parquet(path)
delay: float = round(
time.time() - start,
ndigits=6,
)
print(
f'parquet read took {delay} secs\n'
f'polars df: {read_df}'
)
if reload_parquet_to_shm:
new = tsp.pl2np(
deduped,
dtype=shm.array.dtype,
)
# since normally readonly
shm._array.setflags(
write=int(1),
)
shm.push(
new,
prepend=True,
start=new['index'][-1],
update_first=False, # don't update ._first
)
do_markup_gaps: bool = True
if do_markup_gaps:
new_df: pl.DataFrame = tsp.np2pl(new)
aids: dict = await markup_gaps(
fqme,
period_s,
actl,
new_df,
step_gaps,
)
# last chance manual overwrites in REPL
# await tractor.pause()
assert aids
tf2aids[period_s] = aids
else:
# allow interaction even when no ts problems.
assert not diff
await tractor.pause()
log.info('Exiting TSP shm anal-izer!')
if shm_df is None:
log.error(
f'No matching shm buffers for {fqme} ?'
)
if df is None:
log.error(f'No matching shm buffers for {fqme} ?')
trio.run(main)

View File

@ -59,6 +59,7 @@ from anyio_marketstore import ( # noqa
Params,
)
from piker.log import get_logger
# from .._profile import Profiler
log = get_logger(__name__)
@ -204,7 +205,7 @@ class MktsStorageClient:
# break
# except purerpc.grpclib.exceptions.UnknownError as err:
# if 'snappy' in err.args:
# await tractor.pause()
# await tractor.breakpoint()
# # indicate there is no history for this timeframe
# log.exception(
@ -232,7 +233,7 @@ class MktsStorageClient:
'YOUR DATABASE LIKELY CONTAINS BAD DATA FROM AN OLD BUG '
f'WIPING HISTORY FOR {ts}s'
)
await tractor.pause()
await tractor.breakpoint()
# await self.delete_ts(fqme, timeframe)
# try reading again..

View File

@ -19,8 +19,7 @@
call a poor man's tsdb).
AKA a `piker`-native file-system native "time series database"
without needing an extra process and no standard TSDB features,
YET!
without needing an extra process and no standard TSDB features, YET!
'''
# TODO: like there's soo much..
@ -56,6 +55,8 @@ from datetime import datetime
from pathlib import Path
import time
# from bidict import bidict
# import tractor
import numpy as np
import polars as pl
from pendulum import (
@ -63,18 +64,46 @@ from pendulum import (
)
from piker import config
from piker import tsp
from piker.data import (
def_iohlcv_fields,
ShmArray,
)
from piker.data import def_iohlcv_fields
from piker.data import ShmArray
from piker.log import get_logger
from . import TimeseriesNotFound
# from .._profile import Profiler
log = get_logger('storage.nativedb')
# NOTE: thanks to this SO answer for the below conversion routines
# to go from numpy struct-arrays to polars dataframes and back:
# https://stackoverflow.com/a/72054819
def np2pl(array: np.ndarray) -> pl.DataFrame:
return pl.DataFrame({
field_name: array[field_name]
for field_name in array.dtype.fields
})
def pl2np(
df: pl.DataFrame,
dtype: np.dtype,
) -> np.ndarray:
# Create numpy struct array of the correct size and dtype
# and loop through df columns to fill in array fields.
array = np.empty(
df.height,
dtype,
)
for field, col in zip(
dtype.fields,
df.columns,
):
array[field] = df.get_column(col).to_numpy()
return array
def detect_period(shm: ShmArray) -> float:
'''
Attempt to detect the series time step sampling period
@ -95,19 +124,16 @@ def detect_period(shm: ShmArray) -> float:
def mk_ohlcv_shm_keyed_filepath(
fqme: str,
period: float | int, # ow known as the "timeframe"
period: float, # ow known as the "timeframe"
datadir: Path,
) -> Path:
) -> str:
if period < 1.:
raise ValueError('Sample period should be >= 1.!?')
path: Path = (
datadir
/
f'{fqme}.ohlcv{int(period)}s.parquet'
)
period_s: str = f'{period}s'
path: Path = datadir / f'{fqme}.ohlcv{period_s}.parquet'
return path
@ -161,13 +187,7 @@ class NativeStorageClient:
def index_files(self):
for path in self._datadir.iterdir():
if (
path.is_dir()
or
'.parquet' not in str(path)
# or
# path.name in {'borked', 'expired',}
):
if 'borked' in path.name:
continue
key: str = path.name.rstrip('.parquet')
@ -209,21 +229,8 @@ class NativeStorageClient:
fqme,
timeframe,
)
except FileNotFoundError as fnfe:
bs_fqme, _, *_ = fqme.rpartition('.')
possible_matches: list[str] = []
for tskey in self._index:
if bs_fqme in tskey:
possible_matches.append(tskey)
match_str: str = '\n'.join(sorted(possible_matches))
raise TimeseriesNotFound(
f'No entry for `{fqme}`?\n'
f'Maybe you need a more specific fqme-key like:\n\n'
f'{match_str}'
) from fnfe
except FileNotFoundError:
return None
times = array['time']
return (
@ -236,7 +243,6 @@ class NativeStorageClient:
self,
fqme: str,
period: float,
) -> Path:
return mk_ohlcv_shm_keyed_filepath(
fqme=fqme,
@ -244,23 +250,6 @@ class NativeStorageClient:
datadir=self._datadir,
)
def _cache_df(
self,
fqme: str,
df: pl.DataFrame,
timeframe: float,
) -> None:
# cache df for later usage since we (currently) need to
# convert to np.ndarrays to push to our `ShmArray` rt
# buffers subsys but later we may operate entirely on
# pyarrow arrays/buffers so keeping the dfs around for
# a variety of purposes is handy.
self._dfs.setdefault(
timeframe,
{},
)[fqme] = df
async def read_ohlcv(
self,
fqme: str,
@ -269,20 +258,13 @@ class NativeStorageClient:
# limit: int = int(200e3),
) -> np.ndarray:
path: Path = self.mk_path(
fqme,
period=int(timeframe),
)
path: Path = self.mk_path(fqme, period=int(timeframe))
df: pl.DataFrame = pl.read_parquet(path)
self._dfs.setdefault(timeframe, {})[fqme] = df
self._cache_df(
fqme=fqme,
df=df,
timeframe=timeframe,
)
# TODO: filter by end and limit inputs
# times: pl.Series = df['time']
array: np.ndarray = tsp.pl2np(
array: np.ndarray = pl2np(
df,
dtype=np.dtype(def_iohlcv_fields),
)
@ -292,15 +274,11 @@ class NativeStorageClient:
self,
fqme: str,
period: int = 60,
load_from_offline: bool = True,
) -> pl.DataFrame:
try:
return self._dfs[period][fqme]
except KeyError:
if not load_from_offline:
raise
await self.read_ohlcv(fqme, period)
return self._dfs[period][fqme]
@ -322,22 +300,14 @@ class NativeStorageClient:
datadir=self._datadir,
)
if isinstance(ohlcv, np.ndarray):
df: pl.DataFrame = tsp.np2pl(ohlcv)
df: pl.DataFrame = np2pl(ohlcv)
else:
df = ohlcv
self._cache_df(
fqme=fqme,
df=df,
timeframe=timeframe,
)
# TODO: in terms of managing the ultra long term data
# -[ ] use a proper profiler to measure all this IO and
# - use a proper profiler to measure all this IO and
# roundtripping!
# -[ ] implement parquet append!? see issue:
# https://github.com/pikers/piker/issues/536
# -[ ] try out ``fastparquet``'s append writing:
# - try out ``fastparquet``'s append writing:
# https://fastparquet.readthedocs.io/en/latest/api.html#fastparquet.write
start = time.time()
df.write_parquet(path)
@ -345,16 +315,17 @@ class NativeStorageClient:
time.time() - start,
ndigits=6,
)
log.info(
print(
f'parquet write took {delay} secs\n'
f'file path: {path}'
)
return path
async def write_ohlcv(
self,
fqme: str,
ohlcv: np.ndarray | pl.DataFrame,
ohlcv: np.ndarray,
timeframe: int,
) -> Path:
@ -406,8 +377,6 @@ class NativeStorageClient:
# ...
# TODO: does this need to be async on average?
# I guess for any IPC connected backend yes?
@acm
async def get_client(
@ -425,7 +394,7 @@ async def get_client(
'''
datadir: Path = config.get_conf_dir() / 'nativedb'
if not datadir.is_dir():
log.info(f'Creating `nativedb` dir: {datadir}')
log.info(f'Creating `nativedb` director: {datadir}')
datadir.mkdir()
client = NativeStorageClient(datadir)

View File

@ -1,29 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Toolz for debug, profile and trace of the distributed runtime :surfer:
'''
from tractor.devx import (
open_crash_handler as open_crash_handler,
)
from .profile import (
Profiler as Profiler,
pg_profile_enabled as pg_profile_enabled,
ms_slower_then as ms_slower_then,
timeit as timeit,
)

80
piker/trionics.py 100644
View File

@ -0,0 +1,80 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship of piker0)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
sugarz for trio/tractor conc peeps.
'''
from typing import AsyncContextManager
from typing import TypeVar
from contextlib import asynccontextmanager as acm
import trio
# A regular invariant generic type
T = TypeVar("T")
async def _enter_and_sleep(
mngr: AsyncContextManager[T],
to_yield: dict[int, T],
all_entered: trio.Event,
# task_status: TaskStatus[T] = trio.TASK_STATUS_IGNORED,
) -> T:
'''Open the async context manager deliver it's value
to this task's spawner and sleep until cancelled.
'''
async with mngr as value:
to_yield[id(mngr)] = value
if all(to_yield.values()):
all_entered.set()
# sleep until cancelled
await trio.sleep_forever()
@acm
async def async_enter_all(
*mngrs: list[AsyncContextManager[T]],
) -> tuple[T]:
to_yield = {}.fromkeys(id(mngr) for mngr in mngrs)
all_entered = trio.Event()
async with trio.open_nursery() as n:
for mngr in mngrs:
n.start_soon(
_enter_and_sleep,
mngr,
to_yield,
all_entered,
)
# deliver control once all managers have started up
await all_entered.wait()
yield tuple(to_yield.values())
# tear down all sleeper tasks thus triggering individual
# mngr ``__aexit__()``s.
n.cancel_scope.cancel()

File diff suppressed because it is too large Load Diff

View File

@ -1,746 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) 2018-present Tyler Goodlet (in stewardship of pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Financial time series processing utilities usually
pertaining to OHLCV style sampled data.
Routines are generally implemented in either ``numpy`` or
``polars`` B)
'''
from __future__ import annotations
from functools import partial
from math import (
ceil,
floor,
)
import time
from typing import (
Literal,
# AsyncGenerator,
Generator,
)
import numpy as np
import polars as pl
from pendulum import (
DateTime,
from_timestamp,
)
from ..toolz.profile import (
Profiler,
pg_profile_enabled,
ms_slower_then,
)
from ..log import (
get_logger,
get_console_log,
)
# for "time series processing"
subsys: str = 'piker.tsp'
log = get_logger(subsys)
get_console_log = partial(
get_console_log,
name=subsys,
)
# NOTE: union type-defs to handle generic `numpy` and `polars` types
# side-by-side Bo
# |_ TODO: schema spec typing?
# -[ ] nptyping!
# -[ ] wtv we can with polars?
Frame = pl.DataFrame | np.ndarray
Seq = pl.Series | np.ndarray
def slice_from_time(
arr: np.ndarray,
start_t: float,
stop_t: float,
step: float, # sampler period step-diff
) -> slice:
'''
Calculate array indices mapped from a time range and return them in
a slice.
Given an input array with an epoch `'time'` series entry, calculate
the indices which span the time range and return in a slice. Presume
each `'time'` step increment is uniform and when the time stamp
series contains gaps (the uniform presumption is untrue) use
``np.searchsorted()`` binary search to look up the appropriate
index.
'''
profiler = Profiler(
msg='slice_from_time()',
disabled=not pg_profile_enabled(),
ms_threshold=ms_slower_then,
)
times = arr['time']
t_first = floor(times[0])
t_last = ceil(times[-1])
# the greatest index we can return which slices to the
# end of the input array.
read_i_max = arr.shape[0]
# compute (presumed) uniform-time-step index offsets
i_start_t = floor(start_t)
read_i_start = floor(((i_start_t - t_first) // step)) - 1
i_stop_t = ceil(stop_t)
# XXX: edge case -> always set stop index to last in array whenever
# the input stop time is detected to be greater then the equiv time
# stamp at that last entry.
if i_stop_t >= t_last:
read_i_stop = read_i_max
else:
read_i_stop = ceil((i_stop_t - t_first) // step) + 1
# always clip outputs to array support
# for read start:
# - never allow a start < the 0 index
# - never allow an end index > the read array len
read_i_start = min(
max(0, read_i_start),
read_i_max - 1,
)
read_i_stop = max(
0,
min(read_i_stop, read_i_max),
)
# check for larger-then-latest calculated index for given start
# time, in which case we do a binary search for the correct index.
# NOTE: this is usually the result of a time series with time gaps
# where it is expected that each index step maps to a uniform step
# in the time stamp series.
t_iv_start = times[read_i_start]
if (
t_iv_start > i_start_t
):
# do a binary search for the best index mapping to ``start_t``
# given we measured an overshoot using the uniform-time-step
# calculation from above.
# TODO: once we start caching these per source-array,
# we can just overwrite ``read_i_start`` directly.
new_read_i_start = np.searchsorted(
times,
i_start_t,
side='left',
)
# TODO: minimize binary search work as much as possible:
# - cache these remap values which compensate for gaps in the
# uniform time step basis where we calc a later start
# index for the given input ``start_t``.
# - can we shorten the input search sequence by heuristic?
# up_to_arith_start = index[:read_i_start]
if (
new_read_i_start <= read_i_start
):
# t_diff = t_iv_start - start_t
# print(
# f"WE'RE CUTTING OUT TIME - STEP:{step}\n"
# f'start_t:{start_t} -> 0index start_t:{t_iv_start}\n'
# f'diff: {t_diff}\n'
# f'REMAPPED START i: {read_i_start} -> {new_read_i_start}\n'
# )
read_i_start = new_read_i_start
t_iv_stop = times[read_i_stop - 1]
if (
t_iv_stop > i_stop_t
):
# t_diff = stop_t - t_iv_stop
# print(
# f"WE'RE CUTTING OUT TIME - STEP:{step}\n"
# f'calced iv stop:{t_iv_stop} -> stop_t:{stop_t}\n'
# f'diff: {t_diff}\n'
# # f'SHOULD REMAP STOP: {read_i_start} -> {new_read_i_start}\n'
# )
new_read_i_stop = np.searchsorted(
times[read_i_start:],
# times,
i_stop_t,
side='right',
)
if (
new_read_i_stop <= read_i_stop
):
read_i_stop = read_i_start + new_read_i_stop + 1
# sanity checks for range size
# samples = (i_stop_t - i_start_t) // step
# index_diff = read_i_stop - read_i_start + 1
# if index_diff > (samples + 3):
# breakpoint()
# read-relative indexes: gives a slice where `shm.array[read_slc]`
# will be the data spanning the input time range `start_t` ->
# `stop_t`
read_slc = slice(
int(read_i_start),
int(read_i_stop),
)
profiler(
'slicing complete'
# f'{start_t} -> {abs_slc.start} | {read_slc.start}\n'
# f'{stop_t} -> {abs_slc.stop} | {read_slc.stop}\n'
)
# NOTE: if caller needs absolute buffer indices they can
# slice the buffer abs index like so:
# index = arr['index']
# abs_indx = index[read_slc]
# abs_slc = slice(
# int(abs_indx[0]),
# int(abs_indx[-1]),
# )
return read_slc
def get_null_segs(
frame: Frame,
period: float, # sampling step in seconds
imargin: int = 1,
col: str = 'time',
) -> tuple[
# Seq, # TODO: can we make it an array-type instead?
list[
list[int, int],
],
Seq,
Frame
] | None:
'''
Detect if there are any zero(-epoch stamped) valued
rows in for the provided `col: str` column; by default
presume the 'time' field/column.
Filter to all such zero (time) segments and return
the corresponding frame zeroed segment's,
- gap absolute (in buffer terms) indices-endpoints as
`absi_zsegs`
- abs indices of all rows with zeroed `col` values as `absi_zeros`
- the corresponding frame's row-entries (view) which are
zeroed for the `col` as `zero_t`
'''
times: Seq = frame['time']
zero_pred: Seq = (times == 0)
if isinstance(frame, np.ndarray):
tis_zeros: int = zero_pred.any()
else:
tis_zeros: int = zero_pred.any()
if not tis_zeros:
return None
# TODO: use ndarray for this?!
absi_zsegs: list[list[int, int]] = []
if isinstance(frame, np.ndarray):
# view of ONLY the zero segments as one continuous chunk
zero_t: np.ndarray = frame[zero_pred]
# abs indices of said zeroed rows
absi_zeros = zero_t['index']
# diff of abs index steps between each zeroed row
absi_zdiff: np.ndarray = np.diff(absi_zeros)
# scan for all frame-indices where the
# zeroed-row-abs-index-step-diff is greater then the
# expected increment of 1.
# data 1st zero seg data zeros
# ---- ------------ ---- ----- ------ ----
# ||||..000000000000..||||..00000..||||||..0000
# ---- ------------ ---- ----- ------ ----
# ^zero_t[0] ^zero_t[-1]
# ^fi_zgaps[0] ^fi_zgaps[1]
# ^absi_zsegs[0][0] ^---^ => absi_zsegs[1]: tuple
# absi_zsegs[0][1]^
#
# NOTE: the first entry in `fi_zgaps` is where
# the first (absolute) index step diff is > 1.
# and it is a frame-relative index into `zero_t`.
fi_zgaps = np.argwhere(
absi_zdiff > 1
# NOTE: +1 here is ensure we index to the "start" of each
# segment (if we didn't the below loop needs to be
# re-written to expect `fi_end_rows`!
) + 1
# the rows from the contiguous zeroed segments which have
# abs-index steps >1 compared to the previous zero row
# (indicating an end of zeroed segment).
fi_zseg_start_rows = zero_t[fi_zgaps]
# TODO: equiv for pl.DataFrame case!
else:
izeros: pl.Series = zero_pred.arg_true()
zero_t: pl.DataFrame = frame[izeros]
absi_zeros = zero_t['index']
absi_zdiff: pl.Series = absi_zeros.diff()
fi_zgaps = (absi_zdiff > 1).arg_true()
# XXX: our goal (in this func) is to select out slice index
# pairs (zseg0_start, zseg_end) in abs index units for each
# null-segment portion detected throughout entire input frame.
# only up to one null-segment in entire frame?
num_gaps: int = fi_zgaps.size + 1
if num_gaps < 1:
if absi_zeros.size > 1:
absi_zsegs = [[
# TODO: maybe mk these max()/min() limits func
# consts instead of called more then once?
max(
absi_zeros[0] - 1,
0,
),
# NOTE: need the + 1 to guarantee we index "up to"
# the next non-null row-datum.
min(
absi_zeros[-1] + 1,
frame['index'][-1],
),
]]
else:
# XXX EDGE CASE: only one null-datum found so
# mark the start abs index as None to trigger
# a full frame-len query to the respective backend?
absi_zsegs = [[
# see `get_hist()` in backend, should ALWAYS be
# able to handle a `start_dt=None`!
# None,
None,
absi_zeros[0] + 1,
]]
# XXX NOTE XXX: if >= 2 zeroed segments are found, there should
# ALWAYS be more then one zero-segment-abs-index-step-diff row
# in `absi_zdiff`, so loop through all such
# abs-index-step-diffs >1 (i.e. the entries of `absi_zdiff`)
# and add them as the "end index" entries for each segment.
# Then, iif NOT iterating the first such segment end, look back
# for the prior segments zero-segment start indext by relative
# indexing the `zero_t` frame by -1 and grabbing the abs index
# of what should be the prior zero-segment abs start index.
else:
# NOTE: since `absi_zdiff` will never have a row
# corresponding to the first zero-segment's row, we add it
# manually here.
absi_zsegs.append([
max(
absi_zeros[0] - 1,
0,
),
None,
])
# TODO: can we do it with vec ops?
for i, (
fi, # frame index of zero-seg start
zseg_start_row, # full row for ^
) in enumerate(zip(
fi_zgaps,
fi_zseg_start_rows,
)):
assert (zseg_start_row == zero_t[fi]).all()
iabs: int = zseg_start_row['index'][0]
absi_zsegs.append([
iabs - 1,
None, # backfilled on next iter
])
# final iter case, backfill FINAL end iabs!
if (i + 1) == fi_zgaps.size:
absi_zsegs[-1][1] = absi_zeros[-1] + 1
# NOTE: only after the first segment (due to `.diff()`
# usage above) can we do a lookback to the prior
# segment's end row and determine it's abs index to
# retroactively insert to the prior
# `absi_zsegs[i-1][1]` entry Bo
last_end: int = absi_zsegs[i][1]
if last_end is None:
prev_zseg_row = zero_t[fi - 1]
absi_post_zseg = prev_zseg_row['index'][0] + 1
# XXX: MUST BACKFILL previous end iabs!
absi_zsegs[i][1] = absi_post_zseg
else:
if 0 < num_gaps < 2:
absi_zsegs[-1][1] = min(
absi_zeros[-1] + 1,
frame['index'][-1],
)
iabs_first: int = frame['index'][0]
for start, end in absi_zsegs:
ts_start: float = times[start - iabs_first]
ts_end: float = times[end - iabs_first]
if (
(ts_start == 0 and not start == 0)
or
ts_end == 0
):
import pdbp
pdbp.set_trace()
assert end
assert start < end
log.warning(
f'Frame has {len(absi_zsegs)} NULL GAPS!?\n'
f'period: {period}\n'
f'total null samples: {len(zero_t)}\n'
)
return (
absi_zsegs, # [start, end] abs slice indices of seg
absi_zeros, # all abs indices within all null-segs
zero_t, # sliced-view of all null-segment rows-datums
)
def iter_null_segs(
timeframe: float,
frame: Frame | None = None,
null_segs: tuple | None = None,
) -> Generator[
tuple[
int, int,
int, int,
float, float,
float, float,
# Seq, # TODO: can we make it an array-type instead?
# list[
# list[int, int],
# ],
# Seq,
# Frame
],
None,
]:
if not (
null_segs := get_null_segs(
frame,
period=timeframe,
)
):
return
absi_pairs_zsegs: list[list[float, float]]
izeros: Seq
zero_t: Frame
(
absi_pairs_zsegs,
izeros,
zero_t,
) = null_segs
absi_first: int = frame[0]['index']
for (
absi_start,
absi_end,
) in absi_pairs_zsegs:
fi_end: int = absi_end - absi_first
end_row: Seq = frame[fi_end]
end_t: float = end_row['time']
end_dt: DateTime = from_timestamp(end_t)
fi_start = None
start_row = None
start_t = None
start_dt = None
if (
absi_start is not None
and start_t != 0
):
fi_start: int = absi_start - absi_first
start_row: Seq = frame[fi_start]
start_t: float = start_row['time']
start_dt: DateTime = from_timestamp(start_t)
if absi_start < 0:
import pdbp
pdbp.set_trace()
yield (
absi_start, absi_end, # abs indices
fi_start, fi_end, # relative "frame" indices
start_t, end_t,
start_dt, end_dt,
)
def with_dts(
df: pl.DataFrame,
time_col: str = 'time',
) -> pl.DataFrame:
'''
Insert datetime (casted) columns to a (presumably) OHLC sampled
time series with an epoch-time column keyed by `time_col: str`.
'''
return df.with_columns([
pl.col(time_col).shift(1).suffix('_prev'),
pl.col(time_col).diff().alias('s_diff'),
pl.from_epoch(pl.col(time_col)).alias('dt'),
]).with_columns([
pl.from_epoch(
column=pl.col(f'{time_col}_prev'),
).alias('dt_prev'),
pl.col('dt').diff().alias('dt_diff'),
])
t_unit: Literal = Literal[
'days',
'hours',
'minutes',
'seconds',
'miliseconds',
'microseconds',
'nanoseconds',
]
def detect_time_gaps(
w_dts: pl.DataFrame,
time_col: str = 'time',
# epoch sampling step diff
expect_period: float = 60,
# NOTE: legacy stock mkts have venue operating hours
# and thus gaps normally no more then 1-2 days at
# a time.
gap_thresh: float = 1.,
# TODO: allow passing in a frame of operating hours?
# -[ ] durations/ranges for faster legit gap checks?
# XXX -> must be valid ``polars.Expr.dt.<name>``
# like 'days' which a sane default for venue closures
# though will detect weekend gaps which are normal :o
gap_dt_unit: t_unit | None = None,
) -> pl.DataFrame:
'''
Filter to OHLC datums which contain sample step gaps.
For eg. legacy markets which have venue close gaps and/or
actual missing data segments.
'''
# first select by any sample-period (in seconds unit) step size
# greater then expected.
step_gaps: pl.DataFrame = w_dts.filter(
pl.col('s_diff').abs() > expect_period
)
if gap_dt_unit is None:
return step_gaps
# NOTE: this flag is to indicate that on this (sampling) time
# scale we expect to only be filtering against larger venue
# closures-scale time gaps.
return step_gaps.filter(
# Second by an arbitrary dt-unit step size
getattr(
pl.col('dt_diff').dt,
gap_dt_unit,
)().abs() > gap_thresh
)
def detect_price_gaps(
df: pl.DataFrame,
gt_multiplier: float = 2.,
price_fields: list[str] = ['high', 'low'],
) -> pl.DataFrame:
'''
Detect gaps in clearing price over an OHLC series.
2 types of gaps generally exist; up gaps and down gaps:
- UP gap: when any next sample's lo price is strictly greater
then the current sample's hi price.
- DOWN gap: when any next sample's hi price is strictly
less then the current samples lo price.
'''
# return df.filter(
# pl.col('high') - ) > expect_period,
# ).select([
# pl.dt.datetime(pl.col(time_col).shift(1)).suffix('_previous'),
# pl.all(),
# ]).select([
# pl.all(),
# (pl.col(time_col) - pl.col(f'{time_col}_previous')).alias('diff'),
# ])
...
# TODO: probably just use the null_segs impl above?
def detect_vlm_gaps(
df: pl.DataFrame,
col: str = 'volume',
) -> pl.DataFrame:
vnull: pl.DataFrame = w_dts.filter(
pl.col(col) == 0
)
return vnull
def dedupe(
src_df: pl.DataFrame,
time_gaps: pl.DataFrame | None = None,
sort: bool = True,
period: float = 60,
) -> tuple[
pl.DataFrame, # with dts
pl.DataFrame, # with deduplicated dts (aka gap/repeat removal)
int, # len diff between input and deduped
]:
'''
Check for time series gaps and if found
de-duplicate any datetime entries, check for
a frame height diff and return the newly
dt-deduplicated frame.
'''
wdts: pl.DataFrame = with_dts(src_df)
deduped = wdts
# remove duplicated datetime samples/sections
deduped: pl.DataFrame = wdts.unique(
# subset=['dt'],
subset=['time'],
maintain_order=True,
)
# maybe sort on any time field
if sort:
deduped = deduped.sort(by='time')
# TODO: detect out-of-order segments which were corrected!
# -[ ] report in log msg
# -[ ] possibly return segment sections which were moved?
diff: int = (
wdts.height
-
deduped.height
)
return (
wdts,
deduped,
diff,
)
def sort_diff(
src_df: pl.DataFrame,
col: str = 'time',
) -> tuple[
pl.DataFrame, # with dts
pl.DataFrame, # sorted
list[int], # indices of segments that are out-of-order
]:
ser: pl.Series = src_df[col]
sortd: pl.DataFrame = ser.sort()
diff: pl.Series = ser.diff()
sortd_diff: pl.Series = sortd.diff()
i_step_diff = (diff != sortd_diff).arg_true()
frame_reorders: int = i_step_diff.len()
if frame_reorders:
log.warn(
f'Resorted frame on col: {col}\n'
f'{frame_reorders}'
)
# import pdbp; pdbp.set_trace()
# NOTE: thanks to this SO answer for the below conversion routines
# to go from numpy struct-arrays to polars dataframes and back:
# https://stackoverflow.com/a/72054819
def np2pl(array: np.ndarray) -> pl.DataFrame:
start: float = time.time()
# XXX: thanks to this SO answer for this conversion tip:
# https://stackoverflow.com/a/72054819
df = pl.DataFrame({
field_name: array[field_name]
for field_name in array.dtype.fields
})
delay: float = round(
time.time() - start,
ndigits=6,
)
log.info(
f'numpy -> polars conversion took {delay} secs\n'
f'polars df: {df}'
)
return df
def pl2np(
df: pl.DataFrame,
dtype: np.dtype,
) -> np.ndarray:
# Create numpy struct array of the correct size and dtype
# and loop through df columns to fill in array fields.
array = np.empty(
df.height,
dtype,
)
for field, col in zip(
dtype.fields,
df.columns,
):
array[field] = df.get_column(col).to_numpy()
return array

View File

@ -1,250 +0,0 @@
# piker: trading gear for hackers
# Copyright (C) (in stewardship for pikers)
# - Tyler Goodlet
# - Guillermo Rodriguez
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Extensions to built-in or (heavily used but 3rd party) friend-lib
types.
'''
from __future__ import annotations
from collections import UserList
from pprint import (
saferepr,
)
from typing import Any
from msgspec import (
msgpack,
Struct as _Struct,
structs,
)
class DiffDump(UserList):
'''
Very simple list delegator that repr() dumps (presumed) tuple
elements of the form `tuple[str, Any, Any]` in a nice
multi-line readable form for analyzing `Struct` diffs.
'''
def __repr__(self) -> str:
if not len(self):
return super().__repr__()
# format by displaying item pair's ``repr()`` on multiple,
# indented lines such that they are more easily visually
# comparable when printed to console when printed to
# console.
repstr: str = '[\n'
for k, left, right in self:
repstr += (
f'({k},\n'
f'\t{repr(left)},\n'
f'\t{repr(right)},\n'
')\n'
)
repstr += ']\n'
return repstr
class Struct(
_Struct,
# https://jcristharif.com/msgspec/structs.html#tagged-unions
# tag='pikerstruct',
# tag=True,
):
'''
A "human friendlier" (aka repl buddy) struct subtype.
'''
def _sin_props(self) -> Iterator[
tuple[
structs.FieldIinfo,
str,
Any,
]
]:
'''
Iterate over all non-@property fields of this struct.
'''
fi: structs.FieldInfo
for fi in structs.fields(self):
key: str = fi.name
val: Any = getattr(self, key)
yield fi, key, val
def to_dict(
self,
include_non_members: bool = True,
) -> dict:
'''
Like it sounds.. direct delegation to:
https://jcristharif.com/msgspec/api.html#msgspec.structs.asdict
BUT, by default we pop all non-member (aka not defined as
struct fields) fields by default.
'''
asdict: dict = structs.asdict(self)
if include_non_members:
return asdict
# only return a dict of the struct members
# which were provided as input, NOT anything
# added as type-defined `@property` methods!
sin_props: dict = {}
fi: structs.FieldInfo
for fi, k, v in self._sin_props():
sin_props[k] = asdict[k]
return sin_props
def pformat(
self,
field_indent: int = 2,
indent: int = 0,
) -> str:
'''
Recursion-safe `pprint.pformat()` style formatting of
a `msgspec.Struct` for sane reading by a human using a REPL.
'''
# global whitespace indent
ws: str = ' '*indent
# field whitespace indent
field_ws: str = ' '*(field_indent + indent)
# qtn: str = ws + self.__class__.__qualname__
qtn: str = self.__class__.__qualname__
obj_str: str = '' # accumulator
fi: structs.FieldInfo
k: str
v: Any
for fi, k, v in self._sin_props():
# TODO: how can we prefer `Literal['option1', 'option2,
# ..]` over .__name__ == `Literal` but still get only the
# latter for simple types like `str | int | None` etc..?
ft: type = fi.type
typ_name: str = getattr(ft, '__name__', str(ft))
# recurse to get sub-struct's `.pformat()` output Bo
if isinstance(v, Struct):
val_str: str = v.pformat(
indent=field_indent + indent,
field_indent=indent + field_indent,
)
else: # the `pprint` recursion-safe format:
# https://docs.python.org/3.11/library/pprint.html#pprint.saferepr
val_str: str = saferepr(v)
obj_str += (field_ws + f'{k}: {typ_name} = {val_str},\n')
return (
f'{qtn}(\n'
f'{obj_str}'
f'{ws})'
)
# TODO: use a pprint.PrettyPrinter instance around ONLY rendering
# inside a known tty?
# def __repr__(self) -> str:
# ...
# __str__ = __repr__ = pformat
__repr__ = pformat
def copy(
self,
update: dict | None = None,
) -> Struct:
'''
Validate-typecast all self defined fields, return a copy of
us with all such fields.
NOTE: This is kinda like the default behaviour in
`pydantic.BaseModel` except a copy of the object is
returned making it compat with `frozen=True`.
'''
if update:
for k, v in update.items():
setattr(self, k, v)
# NOTE: roundtrip serialize to validate
# - enode to msgpack binary format,
# - decode that back to a struct.
return msgpack.Decoder(type=type(self)).decode(
msgpack.Encoder().encode(self)
)
def typecast(
self,
# TODO: allow only casting a named subset?
# fields: set[str] | None = None,
) -> None:
'''
Cast all fields using their declared type annotations
(kinda like what `pydantic` does by default).
NOTE: this of course won't work on frozen types, use
``.copy()`` above in such cases.
'''
# https://jcristharif.com/msgspec/api.html#msgspec.structs.fields
fi: structs.FieldInfo
for fi in structs.fields(self):
setattr(
self,
fi.name,
fi.type(getattr(self, fi.name)),
)
def __sub__(
self,
other: Struct,
) -> DiffDump[tuple[str, Any, Any]]:
'''
Compare fields/items key-wise and return a ``DiffDump``
for easy visual REPL comparison B)
'''
diffs: DiffDump[tuple[str, Any, Any]] = DiffDump()
for fi in structs.fields(self):
attr_name: str = fi.name
ours: Any = getattr(self, attr_name)
theirs: Any = getattr(other, attr_name)
if ours != theirs:
diffs.append((
attr_name,
ours,
theirs,
))
return diffs

View File

@ -14,8 +14,9 @@
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
UI components built using `Qt` with major versions swapped in via
the import indirection in the `.qt` sub-mod.
"""
Stuff for your eyes, aka super hawt Qt UI components.
'''
Currently we only support PyQt5 due to this issue in Pyside2:
https://bugreports.qt.io/projects/PYSIDE/issues/PYSIDE-1313
"""

View File

@ -21,10 +21,8 @@ Anchor funtions for UI placement of annotions.
from __future__ import annotations
from typing import Callable, TYPE_CHECKING
from piker.ui.qt import (
QPointF,
QGraphicsPathItem,
)
from PyQt5.QtCore import QPointF
from PyQt5.QtWidgets import QGraphicsPathItem
if TYPE_CHECKING:
from ._chart import ChartPlotWidget

View File

@ -20,22 +20,12 @@ Annotations for ur faces.
"""
from typing import Callable
from pyqtgraph import (
Point,
functions as fn,
Color,
)
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtCore import QPointF, QRectF
from PyQt5.QtWidgets import QGraphicsPathItem
from pyqtgraph import Point, functions as fn, Color
import numpy as np
from piker.ui.qt import (
QtCore,
QtGui,
QtWidgets,
QPointF,
QRectF,
QGraphicsPathItem,
)
def mk_marker_path(

View File

@ -21,16 +21,13 @@ Main app startup and run.
from functools import partial
from types import ModuleType
from PyQt5.QtCore import QEvent
import trio
from piker.ui.qt import (
QEvent,
)
from ..service import maybe_spawn_brokerd
from . import _event
from ._exec import run_qtractor
from ..data.feed import install_brokerd_search
from ..data._symcache import open_symcache
from ..accounting import unpack_fqme
from . import _search
from ._chart import GodWidget
@ -59,13 +56,7 @@ async def load_provider_search(
portal,
brokermod,
),
open_symcache(brokermod) as symcache,
):
if not symcache.mktmaps:
log.warning(
f'BACKEND DOES NOT (yet) support symcaching: `{brokermod.name}`'
)
# keep search engine stream up until cancelled
await trio.sleep_forever()
@ -108,8 +99,6 @@ async def _async_main(
sbar = godwidget.window.status_bar
starting_done = sbar.open_status('starting ze sexy chartz')
# NOTE: by default we load all "builtin" backends for search
# and that includes loading their symcaches if possible B)
needed_brokermods: dict[str, ModuleType] = {}
for fqme in syms:
brokername, *_ = unpack_fqme(fqme)

View File

@ -23,24 +23,16 @@ from functools import lru_cache
from typing import Callable
from math import floor
import polars as pl
import numpy as np
import pyqtgraph as pg
from PyQt5 import QtCore, QtGui, QtWidgets
from PyQt5.QtCore import QPointF
from piker.ui.qt import (
QtCore,
QtGui,
QtWidgets,
QPointF,
txt_flag,
align_flag,
px_cache_mode,
)
from . import _pg_overrides as pgo
from ..accounting._mktinfo import float_digits
from ._label import Label
from ._style import DpiAwareFont, hcolor, _font
from ._interaction import ChartView
from ._dataviz import Viz
_axis_pen = pg.mkPen(hcolor('bracket'))
@ -295,7 +287,9 @@ class DynamicDateAxis(Axis):
# time formats mapped by seconds between bars
tick_tpl = {
60 * 60 * 24: '%Y-%b-%d',
60: '%Y-%b-%d(%H:%M)',
60: '%H:%M',
30: '%H:%M:%S',
5: '%H:%M:%S',
1: '%H:%M:%S',
}
@ -311,10 +305,10 @@ class DynamicDateAxis(Axis):
# XX: ARGGGGG AG:LKSKDJF:LKJSDFD
chart = self.pi.chart_widget
viz: Viz = chart._vizs[chart.name]
viz = chart._vizs[chart.name]
shm = viz.shm
array = shm.array
ifield: str = viz.index_field
ifield = viz.index_field
index = array[ifield]
i_0, i_l = index[0], index[-1]
@ -335,7 +329,7 @@ class DynamicDateAxis(Axis):
arr_len = index.shape[0]
first = shm._first.value
times = array['time']
epochs: list[int] = times[
epochs = times[
list(
map(
int,
@ -347,30 +341,23 @@ class DynamicDateAxis(Axis):
)
]
else:
epochs: list[int] = list(map(int, indexes))
epochs = list(map(int, indexes))
# TODO: **don't** have this hard coded shift to EST
delay: float = viz.time_step()
if delay > 1:
# NOTE: use less granular dt-str when using 1M+ OHLC
fmtstr: str = self.tick_tpl[delay]
else:
fmtstr: str = '%Y-%m-%d(%H:%M:%S)'
# https://pola-rs.github.io/polars/py-polars/html/reference/expressions/api/polars.from_epoch.html#polars-from-epoch
pl_dts: pl.Series = pl.from_epoch(
# delay = times[-1] - times[-2]
dts = np.array(
epochs,
time_unit='s',
# NOTE: kinda weird we can pass it to `.from_epoch()` no?
).dt.replace_time_zone(
time_zone='UTC'
).dt.convert_time_zone(
# TODO: pull this from either:
# -[ ] the mkt venue tz by default
# -[ ] the user's config under `sys.mkt_timezone: str`
'EST'
dtype='datetime64[s]',
)
return pl_dts.dt.to_string(fmtstr).to_list()
# see units listing:
# https://numpy.org/devdocs/reference/arrays.datetime.html#datetime-units
return list(np.datetime_as_string(dts))
# TODO: per timeframe formatting?
# - we probably need this based on zoom now right?
# prec = self.np_dt_precision[delay]
# return dts.strftime(self.tick_tpl[delay])
def tickStrings(
self,
@ -421,15 +408,11 @@ class AxisLabel(pg.GraphicsObject):
super().__init__()
self.setParentItem(parent)
self.setFlag(
self.GraphicsItemFlag.ItemIgnoresTransformations
)
self.setFlag(self.ItemIgnoresTransformations)
self.setZValue(100)
# XXX: pretty sure this is faster
self.setCacheMode(
px_cache_mode.DeviceCoordinateCache
)
self.setCacheMode(QtWidgets.QGraphicsItem.DeviceCoordinateCache)
self._parent = parent
@ -566,14 +549,21 @@ class AxisLabel(pg.GraphicsObject):
return (self.rect.width(), self.rect.height())
# _common_text_flags = (
# QtCore.Qt.TextDontClip |
# QtCore.Qt.AlignCenter |
# QtCore.Qt.AlignTop |
# QtCore.Qt.AlignHCenter |
# QtCore.Qt.AlignVCenter
# )
class XAxisLabel(AxisLabel):
_x_margin = 8
text_flags = (
align_flag.AlignCenter
| txt_flag.TextDontClip
QtCore.Qt.TextDontClip
| QtCore.Qt.AlignCenter
)
def size_hint(self) -> tuple[float, float]:
@ -630,10 +620,10 @@ class YAxisLabel(AxisLabel):
_y_margin: int = 4
text_flags = (
align_flag.AlignLeft
| align_flag.AlignVCenter
# | align_flag.AlignHCenter
| txt_flag.TextDontClip
QtCore.Qt.AlignLeft
# QtCore.Qt.AlignHCenter
| QtCore.Qt.AlignVCenter
| QtCore.Qt.TextDontClip
)
def __init__(

View File

@ -28,20 +28,22 @@ from typing import (
TYPE_CHECKING,
)
import pyqtgraph as pg
import trio
from piker.ui.qt import (
QtCore,
QtWidgets,
from PyQt5 import QtCore, QtWidgets
from PyQt5.QtCore import (
Qt,
QLineF,
# QPointF,
)
from PyQt5.QtWidgets import (
QFrame,
QWidget,
QHBoxLayout,
QVBoxLayout,
QSplitter,
)
import pyqtgraph as pg
import trio
from ._axes import (
DynamicDateAxis,
PriceAxis,
@ -280,7 +282,7 @@ class GodWidget(QWidget):
# TODO: probably stick this in some kinda `LooknFeel` API?
for tracker in self.rt_linked.mode.trackers.values():
pp_nav = tracker.nav
if tracker.live_pp.cumsize:
if tracker.live_pp.size:
pp_nav.show()
pp_nav.hide_info()
else:
@ -404,7 +406,6 @@ class ChartnPane(QFrame):
)
self._sidepane = sidepane
@property
def sidepane(self) -> FieldsForm | SearchWidget:
return self._sidepane
@ -494,7 +495,7 @@ class LinkedSplits(QWidget):
Set the proportion of space allocated for linked subcharts.
'''
ln: int = len(self.subplots) or 1
ln = len(self.subplots) or 1
# proportion allocated to consumer subcharts
if not prop:
@ -568,8 +569,8 @@ class LinkedSplits(QWidget):
# style?
self.chart.setFrameStyle(
QFrame.Shape.StyledPanel |
QFrame.Shadow.Plain
QFrame.StyledPanel |
QFrame.Plain
)
return self.chart
@ -687,8 +688,8 @@ class LinkedSplits(QWidget):
cpw.plotItem.vb.linked = self
cpw.setFrameStyle(
QFrame.Shape.StyledPanel
# | QFrame.Shadow.Plain
QtWidgets.QFrame.StyledPanel
# | QtWidgets.QFrame.Plain
)
# don't show the little "autoscale" A label.
@ -924,7 +925,6 @@ class ChartPlotWidget(pg.PlotWidget):
self.useOpenGL(use_open_gl)
self.name = name
self.data_key = data_key or name
self.qframe: ChartnPane | None = None
# scene-local placeholder for book graphics
# sizing to avoid overlap with data contents

View File

@ -28,14 +28,9 @@ from typing import (
import inspect
import numpy as np
import pyqtgraph as pg
from PyQt5 import QtCore, QtWidgets
from PyQt5.QtCore import QPointF, QRectF
from piker.ui.qt import (
QPointF,
QRectF,
QtCore,
QtWidgets,
px_cache_mode,
)
from ._style import (
_xaxis_at,
hcolor,
@ -109,9 +104,7 @@ class LineDot(pg.CurvePoint):
dot.setParentItem(self)
# keep a static size
self.setFlag(
self.GraphicsItemFlag.ItemIgnoresTransformations
)
self.setFlag(self.ItemIgnoresTransformations)
def event(
self,
@ -214,10 +207,9 @@ class ContentsLabel(pg.LabelItem):
# this being "html" is the dumbest shit :eyeroll:
self.setText(
"<b>i_arr</b>:{index}<br/>"
"<b>i</b>:{index}<br/>"
# NB: these fields must be indexed in the correct order via
# the slice syntax below.
"<b>i_shm</b>:{}<br/>"
"<b>epoch</b>:{}<br/>"
"<b>O</b>:{}<br/>"
"<b>H</b>:{}<br/>"
@ -227,7 +219,6 @@ class ContentsLabel(pg.LabelItem):
# "<b>wap</b>:{}".format(
*array[ix][
[
'index',
'time',
'open',
'high',
@ -279,15 +270,10 @@ class ContentsLabels:
x_in: int,
) -> None:
for (
chart,
name,
label,
update,
)in self._labels:
for chart, name, label, update in self._labels:
viz = chart.get_viz(name)
array: np.ndarray = viz.shm._array
array = viz.shm.array
index = array[viz.index_field]
start = index[0]
stop = index[-1]
@ -298,7 +284,7 @@ class ContentsLabels:
):
# out of range
print('WTF out of range?')
# continue
continue
# call provided update func with data point
try:
@ -306,7 +292,6 @@ class ContentsLabels:
ix = np.searchsorted(index, x_in)
if ix > len(array):
breakpoint()
update(ix, array)
except IndexError:
@ -431,10 +416,10 @@ class Cursor(pg.GraphicsObject):
# vertical and horizonal lines and a y-axis label
vl = plot.addLine(x=0, pen=self.lines_pen, movable=False)
vl.setCacheMode(px_cache_mode.DeviceCoordinateCache)
vl.setCacheMode(QtWidgets.QGraphicsItem.DeviceCoordinateCache)
hl = plot.addLine(y=0, pen=self.lines_pen, movable=False)
hl.setCacheMode(px_cache_mode.DeviceCoordinateCache)
hl.setCacheMode(QtWidgets.QGraphicsItem.DeviceCoordinateCache)
hl.hide()
yl = YAxisLabel(
@ -518,10 +503,7 @@ class Cursor(pg.GraphicsObject):
plot=chart
)
chart.addItem(cursor)
self.graphics[chart].setdefault(
'cursors',
[],
).append(cursor)
self.graphics[chart].setdefault('cursors', []).append(cursor)
return cursor
def mouseAction(

View File

@ -19,47 +19,42 @@ Fast, smooth, sexy curves.
"""
from contextlib import contextmanager as cm
from enum import EnumType
from typing import Callable
import numpy as np
import pyqtgraph as pg
from piker.ui.qt import (
QtWidgets,
QGraphicsItem,
from PyQt5 import QtWidgets
from PyQt5.QtWidgets import QGraphicsItem
from PyQt5.QtCore import (
Qt,
QLineF,
QRectF,
)
from PyQt5.QtGui import (
QPainter,
QPainterPath,
px_cache_mode,
)
from .._profile import pg_profile_enabled, ms_slower_then
from ._style import hcolor
from ..log import get_logger
from ..toolz.profile import (
Profiler,
pg_profile_enabled,
ms_slower_then,
)
from .._profile import Profiler
log = get_logger(__name__)
pen_style: EnumType = Qt.PenStyle
_line_styles: dict[str, int] = {
'solid': pen_style.SolidLine,
'dash': pen_style.DashLine,
'dot': pen_style.DotLine,
'dashdot': pen_style.DashDotLine,
'solid': Qt.PenStyle.SolidLine,
'dash': Qt.PenStyle.DashLine,
'dot': Qt.PenStyle.DotLine,
'dashdot': Qt.PenStyle.DashDotLine,
}
class FlowGraphic(pg.GraphicsObject):
'''
Base class with minimal interface for `QPainterPath`
implemented, real-time updated "data flow" graphics.
Base class with minimal interface for `QPainterPath` implemented,
real-time updated "data flow" graphics.
See subtypes below.
@ -71,12 +66,12 @@ class FlowGraphic(pg.GraphicsObject):
# XXX-NOTE-XXX: graphics caching B)
# see explanation for different caching modes:
# https://stackoverflow.com/a/39410081
cache_mode: int = px_cache_mode.DeviceCoordinateCache
cache_mode: int = QGraphicsItem.DeviceCoordinateCache
# XXX: WARNING item caching seems to only be useful
# if we don't re-generate the entire QPainterPath every time
# don't ever use this - it's a colossal nightmare of artefacts
# and is disastrous for performance.
# cache_mode.ItemCoordinateCache
# QGraphicsItem.ItemCoordinateCache
# TODO: still questions todo with coord-cacheing that we should
# probably talk to a core dev about:
# - if this makes trasform interactions slower (such as zooming)
@ -169,16 +164,15 @@ class FlowGraphic(pg.GraphicsObject):
return None
# XXX: due to a variety of weird jitter bugs and "smearing"
# artifacts when click-drag panning and viewing history time
# series, we offer this ctx-mngr interface to allow temporarily
# disabling Qt's graphics caching mode; this is now currently
# used from ``ChartView.start/signal_ic()`` methods which also
# disable the rt-display loop when the user is moving around
# a view.
# artifacts when click-drag panning and viewing history time series,
# we offer this ctx-mngr interface to allow temporarily disabling
# Qt's graphics caching mode; this is now currently used from
# ``ChartView.start/signal_ic()`` methods which also disable the
# rt-display loop when the user is moving around a view.
@cm
def reset_cache(self) -> None:
try:
none = px_cache_mode.NoCache
none = QGraphicsItem.NoCache
log.debug(
f'{self._name} -> CACHE DISABLE: {none}'
)

View File

@ -36,12 +36,9 @@ from msgspec import (
field,
)
import numpy as np
from numpy import (
ndarray,
)
import pyqtgraph as pg
from PyQt5.QtCore import QLineF
from piker.ui.qt import QLineF
from ..data._sharedmem import (
ShmArray,
)
@ -52,7 +49,7 @@ from ..data._formatters import (
OHLCBarsAsCurveFmtr, # OHLC converted to line
StepCurveFmtr, # "step" curve (like for vlm)
)
from ..tsp import (
from ..data._timeseries import (
slice_from_time,
)
from ._ohlc import (
@ -65,7 +62,7 @@ from ._curve import (
)
from ._render import Renderer
from ..log import get_logger
from ..toolz.profile import (
from .._profile import (
Profiler,
pg_profile_enabled,
ms_slower_then,
@ -85,11 +82,10 @@ def render_baritems(
viz: Viz,
graphics: BarItems,
read: tuple[
int, int, ndarray,
int, int, ndarray,
int, int, np.ndarray,
int, int, np.ndarray,
],
profiler: Profiler,
force_redraw: bool = False,
**kwargs,
) -> None:
@ -220,11 +216,9 @@ def render_baritems(
viz._in_ds = should_line
should_redraw = (
force_redraw
or changed_to_line
changed_to_line
or not should_line
)
# print(f'should_redraw: {should_redraw}')
return (
graphics,
r,
@ -256,7 +250,7 @@ class ViewState(Struct):
] | None = None
# last in view ``ShmArray.array[read_slc]`` data
in_view: ndarray | None = None
in_view: np.ndarray | None = None
class Viz(Struct):
@ -319,7 +313,6 @@ class Viz(Struct):
_last_uppx: float = 0
_in_ds: bool = False
_index_step: float | None = None
_time_step: float | None = None
# map from uppx -> (downsampled data, incremental graphics)
_src_r: Renderer | None = None
@ -366,8 +359,7 @@ class Viz(Struct):
def index_step(
self,
index_field: str | None = None,
reset: bool = False,
) -> float:
'''
Return the size between sample steps in the units of the
@ -375,17 +367,12 @@ class Viz(Struct):
epoch time in seconds.
'''
# attempt to detect the best step size by scanning a sample
# of the source data.
if (
self._index_step is None
or index_field is not None
):
index: ndarray = self.shm.array[
index_field
or self.index_field
]
isample: ndarray = index[-16:]
# attempt to dectect the best step size by scanning a sample of
# the source data.
if self._index_step is None:
index: np.ndarray = self.shm.array[self.index_field]
isample: np.ndarray = index[-16:]
mxdiff: None | float = None
for step in np.diff(isample):
@ -399,15 +386,7 @@ class Viz(Struct):
)
mxdiff = step
step: float = max(mxdiff, 1)
# only SET the internal index step if an explicit
# field name is NOT passed, since in such cases this
# is likely just being called from `.time_step()`.
if index_field is not None:
return step
self._index_step = step
self._index_step = max(mxdiff, 1)
if (
mxdiff < 1
or 1 < mxdiff < 60
@ -418,17 +397,6 @@ class Viz(Struct):
return self._index_step
def time_step(self) -> float:
'''
Attempt to determine the per-sample time-step period by
forcing an epoch-index and calling `.index_step()`.
'''
if self._time_step is None:
self._time_step: float = self.index_step(index_field='time')
return self._time_step
def maxmin(
self,
@ -436,9 +404,6 @@ class Viz(Struct):
i_read_range: tuple[int, int] | None = None,
use_caching: bool = True,
# XXX: internal debug
_do_print: bool = False
) -> tuple[float, float] | None:
'''
Compute the cached max and min y-range values for a given
@ -458,14 +423,15 @@ class Viz(Struct):
if shm is None:
return None
arr: ndarray = shm.array
do_print: bool = False
arr = shm.array
if i_read_range is not None:
read_slc = slice(*i_read_range)
index: float | int = arr[read_slc][self.index_field]
index = arr[read_slc][self.index_field]
if not index.size:
return None
ixrng: tuple[int, int] = (index[0], index[-1])
ixrng = (index[0], index[-1])
else:
if x_range is None:
@ -483,24 +449,15 @@ class Viz(Struct):
# TODO: hash the slice instead maybe?
# https://stackoverflow.com/a/29980872
ixrng = lbar, rbar = (
round(x_range[0]),
round(x_range[1]),
)
ixrng = lbar, rbar = round(x_range[0]), round(x_range[1])
if (
use_caching
and self._mxmn_cache_enabled
):
# TODO: is there a way to ONLY clear ranges containing
# a certain sub-range?
# -[ ] currently we have a problem where a previously
# cached mxmn will persist even if the viz is "hard
# re-rendered" (usually bc underlying data was
# corrected)
cached_result = self._mxmns.get(ixrng)
if cached_result:
if _do_print:
if do_print:
print(
f'{self.name} CACHED maxmin\n'
f'{ixrng} -> {cached_result}'
@ -530,7 +487,7 @@ class Viz(Struct):
(rbar - ifirst) + 1
)
slice_view: ndarray = arr[read_slc]
slice_view = arr[read_slc]
if not slice_view.size:
log.warning(
@ -541,7 +498,7 @@ class Viz(Struct):
elif self.ds_yrange:
mxmn = self.ds_yrange
if _do_print:
if do_print:
print(
f'{self.name} M4 maxmin:\n'
f'{ixrng} -> {mxmn}'
@ -558,7 +515,7 @@ class Viz(Struct):
mxmn = ylow, yhigh
if (
_do_print
do_print
):
s = 3
print(
@ -572,23 +529,14 @@ class Viz(Struct):
# cache result for input range
ylow, yhi = mxmn
diff: float = yhi - ylow
# order-of-magnitude check
# TODO: really we should be checking the hi or low
# against the previous sample to catch stuff like,
# - rando stock (reverse-)split
# - null-segments written by some prior
# crash-during-backfil
if diff > 0:
omg: float = abs(logf(diff, 10))
else:
omg: float = 0
try:
prolly_anomaly: bool = (
# diff == 0
(ylow and omg > 10)
(
abs(logf(ylow, 10)) > 16
if ylow
else False
)
or (
isnan(ylow) or isnan(yhi)
)
@ -615,8 +563,7 @@ class Viz(Struct):
def view_range(self) -> tuple[int, int]:
'''
Return the start and stop x-indexes for the managed
``ViewBox``.
Return the start and stop x-indexes for the managed ``ViewBox``.
'''
vr = self.plot.viewRect()
@ -629,7 +576,7 @@ class Viz(Struct):
self,
view_range: None | tuple[float, float] = None,
index_field: str | None = None,
array: ndarray | None = None,
array: np.ndarray | None = None,
) -> tuple[
int, int, int, int, int, int
@ -700,8 +647,8 @@ class Viz(Struct):
profiler: None | Profiler = None,
) -> tuple[
int, int, ndarray,
int, int, ndarray,
int, int, np.ndarray,
int, int, np.ndarray,
]:
'''
Read the underlying shm array buffer and
@ -871,10 +818,6 @@ class Viz(Struct):
graphics,
read,
profiler,
# NOTE: only set when caller says to
force_redraw=should_redraw,
**kwargs,
)
@ -1037,39 +980,6 @@ class Viz(Struct):
graphics,
)
def reset_graphics(
self,
# TODO: allow only resetting within some x-domain range?
# ixrng: tuple[int, int] | None = None,
) -> None:
'''
Hard reset all graphics (rendering) layers for this
data viz including clearing the mxmn auto-y-range
cache.
Normally called when the underlying data set is modified
(probably by some `.tsp` correcting/editing routine) and
the (now cached) graphics need to be fully re-rendered from
source.
'''
log.warning(
f'Forcing hard Viz graphihcs RESET:\n'
f'.name: {self.name}\n'
f'.index_field: {self.index_field}\n'
f'.index_step(): {self.index_step()}\n'
f'.time_step(): {self.time_step()}\n'
)
# XXX: always clear the mxn y-range cache
# to avoid old data (anomalies) from being
# retained in auto-yrange output.
self._mxmn_cache_enabled = False
self._mxmns.clear()
self.update_graphics(force_redraw=True)
self._mxmn_cache_enabled = True
def draw_last(
self,
array_key: str | None = None,
@ -1162,7 +1072,7 @@ class Viz(Struct):
'''
shm: ShmArray = self.shm
array: ndarray = shm.array
array: np.ndarray = shm.array
view: ChartView = self.plot.vb
(
vl,

View File

@ -36,28 +36,25 @@ import pyqtgraph as pg
from msgspec import field
# from .. import brokers
from piker.accounting import (
from ..accounting import (
MktPair,
)
from piker.types import Struct
from piker.data import (
from ..data import (
open_feed,
Feed,
Flume,
open_sample_stream,
ShmArray,
)
from piker.data.ticktools import (
from ..data.ticktools import (
_tick_groups,
_auction_ticks,
)
from piker.toolz import (
pg_profile_enabled,
ms_slower_then,
Profiler,
from ..data.types import Struct
from ..data._sharedmem import (
ShmArray,
)
from ..data._sampling import (
open_sample_stream,
)
from piker.log import get_logger
from piker import config
# from ..data._source import tf_in_1s
from ._axes import YAxisLabel
from ._chart import (
@ -82,6 +79,12 @@ from .order_mode import (
open_order_mode,
OrderMode,
)
from .._profile import (
pg_profile_enabled,
ms_slower_then,
)
from ..log import get_logger
from .._profile import Profiler
if TYPE_CHECKING:
from ._interaction import ChartView
@ -211,9 +214,9 @@ async def increment_history_view(
):
hist_chart: ChartPlotWidget = ds.hist_chart
hist_viz: Viz = ds.hist_viz
# viz: Viz = ds.viz
viz: Viz = ds.viz
assert 'hist' in hist_viz.shm.token['shm_name']
# name: str = hist_viz.name
name: str = hist_viz.name
# TODO: seems this is more reliable at keeping the slow
# chart incremented in view more correctly?
@ -226,8 +229,7 @@ async def increment_history_view(
# draw everything from scratch on first entry!
for curve_name, hist_viz in hist_chart._vizs.items():
log.info(f'Forcing hard redraw -> {curve_name}')
hist_viz.reset_graphics()
# hist_viz.update_graphics(force_redraw=True)
hist_viz.update_graphics(force_redraw=True)
async with open_sample_stream(1.) as min_istream:
async for msg in min_istream:
@ -250,27 +252,17 @@ async def increment_history_view(
# - samplerd could emit the actual update range via
# tuple and then we only enter the below block if that
# range is detected as in-view?
# match msg:
# case {
# 'backfilling': (viz_name, timeframe),
# } if (
# viz_name == name
# ):
# log.warning(
# f'Forcing HARD REDRAW:\n'
# f'name: {name}\n'
# f'timeframe: {timeframe}\n'
# )
# # TODO: only allow this when the data is IN VIEW!
# # also, we probably can do this more efficiently
# # / smarter by only redrawing the portion of the
# # path necessary?
# {
# 60: hist_viz,
# 1: viz,
# }[timeframe].update_graphics(
# force_redraw=True
# )
if (
(bf_wut := msg.get('backfilling', False))
):
viz_name, timeframe = bf_wut
if viz_name == name:
log.info(f'Forcing hard redraw -> {name}@{timeframe}')
match timeframe:
case 60:
hist_viz.update_graphics(force_redraw=True)
case 1:
viz.update_graphics(force_redraw=True)
# check if slow chart needs an x-domain shift and/or
# y-range resize.
@ -311,7 +303,6 @@ async def increment_history_view(
async def graphics_update_loop(
dss: dict[str, DisplayState],
nurse: trio.Nursery,
godwidget: GodWidget,
feed: Feed,
@ -353,6 +344,8 @@ async def graphics_update_loop(
'i_last_slow_t': 0, # multiview-global slow (1m) step index
}
dss: dict[str, DisplayState] = {}
for fqme, flume in feed.flumes.items():
ohlcv = flume.rt_shm
hist_ohlcv = flume.hist_shm
@ -469,20 +462,12 @@ async def graphics_update_loop(
await trio.sleep(0)
if ds.hist_vars['i_last'] < ds.hist_vars['i_last_append']:
await tractor.pause()
# try:
# XXX TODO: we need to do _dss UPDATE here so that when
# a feed-view is switched you can still remote annotate the
# prior view..
from . import _remote_ctl
_remote_ctl._dss.update(dss)
await tractor.breakpoint()
# main real-time quotes update loop
stream: tractor.MsgStream
async with feed.open_multi_stream() as stream:
# assert stream
assert stream
async for quotes in stream:
quote_period = time.time() - last_quote_s
quote_rate = round(
@ -498,7 +483,7 @@ async def graphics_update_loop(
pass
# log.warning(f'High quote rate {mkt.fqme}: {quote_rate}')
last_quote_s: float = time.time()
last_quote_s = time.time()
for fqme, quote in quotes.items():
ds = dss[fqme]
@ -528,12 +513,6 @@ async def graphics_update_loop(
quote,
)
# finally:
# # XXX: cancel any remote annotation control ctxs
# _remote_ctl._dss = None
# for cid, (ctx, aids) in _remote_ctl._ctxs.items():
# await ctx.cancel()
def graphics_update_cycle(
ds: DisplayState,
@ -1232,8 +1211,6 @@ async def link_views_with_region(
# region.sigRegionChangeFinished.connect(update_pi_from_region)
# NOTE: default is set to 60 FPS until the runtime delivers the
# discoverd hw value below.
_quote_throttle_rate: int = 60 - 6
@ -1252,7 +1229,7 @@ async def display_symbol_data(
fast from a cached watch-list.
'''
# sbar = godwidget.window.status_bar
sbar = godwidget.window.status_bar
# historical data fetch
# brokermod = brokers.get_brokermod(provider)
@ -1262,11 +1239,11 @@ async def display_symbol_data(
# group_key=loading_sym_key,
# )
# for fqme in fqmes:
# loading_sym_key = sbar.open_status(
# f'loading {fqme} ->',
# group_key=True
# )
for fqme in fqmes:
loading_sym_key = sbar.open_status(
f'loading {fqme} ->',
group_key=True
)
# (TODO: make this not so shit XD)
# close group status once a symbol feed fully loads to view.
@ -1275,54 +1252,26 @@ async def display_symbol_data(
# TODO: ctl over update loop's maximum frequency.
# - load this from a config.toml!
# - allow dyanmic configuration from chart UI?
(
conf,
path,
) = config.load()
ui_conf: dict = conf['ui']
global _quote_throttle_rate
from ._window import main_window
display_rate: int = floor(
main_window().current_screen().refreshRate()
) - 6
mx_redraw_rate: int = ui_conf.get(
'max_redraw_rate',
_quote_throttle_rate,
)
if mx_redraw_rate < display_rate:
log.info(
'Down-throttling redraw rate to config setting\n'
f'display FPS: {display_rate}\n'
'max_redraw_rate: {max_redraw_rate}\n'
)
else:
_quote_throttle_rate = display_rate
display_rate = main_window().current_screen().refreshRate()
_quote_throttle_rate = floor(display_rate) - 6
# TODO: we should be able to increase this if we use some
# `mypyc` speedups elsewhere? 22ish seems to be the sweet
# spot for single-feed chart.
num_of_feeds = len(fqmes)
# if num_of_feeds > 1:
mx: int = 22
if num_of_feeds > 1:
# there will be more ctx switches with more than 1 feed so we
# max throttle down a bit more.
mx_per_feed: int = (
ui_conf.get(
'per_feed_redraw_rate',
mx_redraw_rate,
)
or 16
)
mx = 16
# limit to at least display's FPS
# avoiding needless Qt-in-guest-mode context switches
cycles_per_feed = min(
round(_quote_throttle_rate/num_of_feeds),
mx_per_feed,
mx,
)
feed: Feed
@ -1467,7 +1416,7 @@ async def display_symbol_data(
start_fsp_displays,
rt_linked,
flume,
# loading_sym_key,
loading_sym_key,
loglevel,
)
@ -1586,10 +1535,8 @@ async def display_symbol_data(
)
# start update loop task
dss: dict[str, DisplayState] = {}
ln.start_soon(
graphics_update_loop,
dss,
ln,
godwidget,
feed,
@ -1603,31 +1550,15 @@ async def display_symbol_data(
order_ctl_fqme: str = fqmes[0]
mode: OrderMode
async with (
open_order_mode(
feed,
godwidget,
order_ctl_fqme,
order_mode_started,
loglevel=loglevel
) as mode,
# TODO: maybe have these startup sooner before
# order mode fully boots? but we gotta,
# -[ ] decouple the order mode bindings until
# the mode has fully booted..
# -[ ] maybe do an Event to sync?
# start input handling for ``ChartView`` input
# (i.e. kb + mouse handling loops)
rt_chart.view.open_async_input_handler(
dss=dss,
),
hist_chart.view.open_async_input_handler(
dss=dss,
),
) as mode
):
rt_linked.mode = mode
rt_viz = rt_chart.get_viz(order_ctl_fqme)

View File

@ -21,8 +21,7 @@ Higher level annotation editors.
from __future__ import annotations
from collections import defaultdict
from typing import (
Sequence,
TYPE_CHECKING,
TYPE_CHECKING
)
import pyqtgraph as pg
@ -32,34 +31,24 @@ from pyqtgraph import (
QtCore,
QtWidgets,
)
from PyQt5.QtGui import (
QColor,
)
from PyQt5.QtWidgets import (
QLabel,
)
from pyqtgraph import functions as fn
from PyQt5.QtCore import QPointF
import numpy as np
from piker.types import Struct
from piker.ui.qt import (
Qt,
QPointF,
QRectF,
QGraphicsProxyWidget,
QGraphicsScene,
QLabel,
QColor,
QTransform,
)
from ._style import (
hcolor,
_font,
)
from ._style import hcolor, _font
from ._lines import LevelLine
from ..log import get_logger
from ..data.types import Struct
if TYPE_CHECKING:
from ._chart import (
GodWidget,
ChartPlotWidget,
)
from ._interaction import ChartView
from ._chart import GodWidget
log = get_logger(__name__)
@ -76,7 +65,7 @@ class ArrowEditor(Struct):
uid: str,
x: float,
y: float,
color: str = 'default',
color='default',
pointing: str | None = None,
) -> pg.ArrowItem:
@ -262,75 +251,43 @@ class LineEditor(Struct):
return lines
def as_point(
pair: Sequence[float, float] | QPointF,
) -> list[QPointF, QPointF]:
'''
Case any input tuple of floats to a a list of `QPoint` objects
for use in Qt geometry routines.
'''
if isinstance(pair, QPointF):
return pair
return QPointF(pair[0], pair[1])
# TODO: maybe implement better, something something RectItemProxy??
# -[ ] dig into details of how proxy's work?
# https://doc.qt.io/qt-5/qgraphicsscene.html#addWidget
# -[ ] consider using `.addRect()` maybe?
class SelectRect(QtWidgets.QGraphicsRectItem):
'''
A data-view "selection rectangle": the most fundamental
geometry for annotating data views.
- https://doc.qt.io/qt-5/qgraphicsrectitem.html
- https://doc.qt.io/qt-6/qgraphicsrectitem.html
'''
def __init__(
self,
viewbox: ViewBox,
color: str | None = None,
color: str = 'dad_blue',
) -> None:
super().__init__(0, 0, 1, 1)
# self.rbScaleBox = QGraphicsRectItem(0, 0, 1, 1)
self.vb: ViewBox = viewbox
self.vb = viewbox
self._chart: 'ChartPlotWidget' = None # noqa
self._chart: ChartPlotWidget | None = None # noqa
# TODO: maybe allow this to be dynamic via a method?
#l override selection box color
color: str = color or 'dad_blue'
# override selection box color
color = QColor(hcolor(color))
self.setPen(fn.mkPen(color, width=1))
color.setAlpha(66)
self.setBrush(fn.mkBrush(color))
self.setZValue(1e9)
self.hide()
self._label = None
label = self._label = QLabel()
label.setTextFormat(
Qt.TextFormat.MarkdownText
)
label.setTextFormat(0) # markdown
label.setFont(_font.font)
label.setMargin(0)
label.setAlignment(
QtCore.Qt.AlignLeft
# | QtCore.Qt.AlignVCenter
)
label.hide() # always right after init
# proxy is created after containing scene is initialized
self._label_proxy: QGraphicsProxyWidget | None = None
self._abs_top_right: Point | None = None
self._label_proxy = None
self._abs_top_right = None
# TODO: "swing %" might be handy here (data's max/min
# # % change)?
self._contents: list[str] = [
# TODO: "swing %" might be handy here (data's max/min # % change)
self._contents = [
'change: {pchng:.2f} %',
'range: {rng:.2f}',
'bars: {nbars}',
@ -340,31 +297,12 @@ class SelectRect(QtWidgets.QGraphicsRectItem):
'sigma: {std:.2f}',
]
self.add_to_view(viewbox)
self.hide()
def add_to_view(
self,
view: ChartView,
) -> None:
'''
Self-defined view hookup impl which will
also re-assign the internal ref.
'''
view.addItem(
self,
ignoreBounds=True,
)
if self.vb is not view:
self.vb = view
@property
def chart(self) -> ChartPlotWidget: # noqa
def chart(self) -> 'ChartPlotWidget': # noqa
return self._chart
@chart.setter
def chart(self, chart: ChartPlotWidget) -> None: # noqa
def chart(self, chart: 'ChartPlotWidget') -> None: # noqa
self._chart = chart
chart.sigRangeChanged.connect(self.update_on_resize)
palette = self._label.palette()
@ -377,155 +315,57 @@ class SelectRect(QtWidgets.QGraphicsRectItem):
)
def update_on_resize(self, vr, r):
'''
Re-position measure label on view range change.
"""Re-position measure label on view range change.
'''
"""
if self._abs_top_right:
self._label_proxy.setPos(
self.vb.mapFromView(self._abs_top_right)
)
def set_scen_pos(
def mouse_drag_released(
self,
scen_p1: QPointF,
scen_p2: QPointF,
update_label: bool = True,
p1: QPointF,
p2: QPointF
) -> None:
'''
Set position from scene coords of selection rect (normally
from mouse position) and accompanying label, move label to
match.
"""Called on final button release for mouse drag with start and
end positions.
'''
# NOTE XXX: apparently just setting it doesn't work!?
# i have no idea why but it's pretty weird we have to do
# this transform thing which was basically pulled verbatim
# from the `pg.ViewBox.updateScaleBox()` method.
view_rect: QRectF = self.vb.childGroup.mapRectFromScene(
QRectF(
scen_p1,
scen_p2,
)
)
self.setPos(view_rect.topLeft())
# XXX: does not work..!?!?
# https://doc.qt.io/qt-5/qgraphicsrectitem.html#setRect
# self.setRect(view_rect)
"""
self.set_pos(p1, p2)
tr = QTransform.fromScale(
view_rect.width(),
view_rect.height(),
)
self.setTransform(tr)
# XXX: never got this working, was always offset
# / transformed completely wrong (and off to the far right
# from the cursor?)
# self.set_view_pos(
# view_rect=view_rect,
# # self.vwqpToView(p1),
# # self.vb.mapToView(p2),
# # start_pos=self.vb.mapToScene(p1),
# # end_pos=self.vb.mapToScene(p2),
# )
self.show()
if update_label:
self.init_label(view_rect)
def set_view_pos(
def set_pos(
self,
start_pos: QPointF | Sequence[float, float] | None = None,
end_pos: QPointF | Sequence[float, float] | None = None,
view_rect: QRectF | None = None,
update_label: bool = True,
p1: QPointF,
p2: QPointF
) -> None:
'''
Set position from `ViewBox` coords (i.e. from the actual
data domain) of rect (and any accompanying label which is
moved to match).
"""Set position of selection rect and accompanying label, move
label to match.
'''
if self._chart is None:
raise RuntimeError(
'You MUST assign a `SelectRect.chart: ChartPlotWidget`!'
)
"""
if self._label_proxy is None:
# https://doc.qt.io/qt-5/qgraphicsproxywidget.html
self._label_proxy = self.vb.scene().addWidget(self._label)
if view_rect is None:
# ensure point casting
start_pos: QPointF = as_point(start_pos)
end_pos: QPointF = as_point(end_pos)
start_pos = self.vb.mapToView(p1)
end_pos = self.vb.mapToView(p2)
# map to view coords and update area
view_rect = QtCore.QRectF(
start_pos,
end_pos,
)
r = QtCore.QRectF(start_pos, end_pos)
self.setPos(view_rect.topLeft())
# old way; don't need right?
# lr = QtCore.QRectF(p1, p2)
# r = self.vb.childGroup.mapRectFromParent(lr)
# NOTE: SERIOUSLY NO IDEA WHY THIS WORKS...
# but it does and all the other commented stuff above
# dint, dawg..
# self.resetTransform()
# self.setRect(view_rect)
tr = QTransform.fromScale(
view_rect.width(),
view_rect.height(),
)
self.setTransform(tr)
if update_label:
self.init_label(view_rect)
print(
'SelectRect modify:\n'
f'QRectF: {view_rect}\n'
f'start_pos: {start_pos}\n'
f'end_pos: {end_pos}\n'
)
self.setPos(r.topLeft())
self.resetTransform()
self.setRect(r)
self.show()
def init_label(
self,
view_rect: QRectF,
) -> QLabel:
y1, y2 = start_pos.y(), end_pos.y()
x1, x2 = start_pos.x(), end_pos.x()
# should be init-ed in `.__init__()`
label: QLabel = self._label
cv: ChartView = self.vb
# https://doc.qt.io/qt-5/qgraphicsproxywidget.html
if self._label_proxy is None:
scen: QGraphicsScene = cv.scene()
# NOTE: specifically this is passing a widget
# pointer to the scene's `.addWidget()` as per,
# https://doc.qt.io/qt-5/qgraphicsproxywidget.html#embedding-a-widget-with-qgraphicsproxywidget
self._label_proxy: QGraphicsProxyWidget = scen.addWidget(label)
# get label startup coords
tl: QPointF = view_rect.topLeft()
br: QPointF = view_rect.bottomRight()
x1, y1 = tl.x(), tl.y()
x2, y2 = br.x(), br.y()
# TODO: to remove, previous label corner point unpacking
# x1, y1 = start_pos.x(), start_pos.y()
# x2, y2 = end_pos.x(), end_pos.y()
# y1, y2 = start_pos.y(), end_pos.y()
# x1, x2 = start_pos.x(), end_pos.x()
# TODO: heh, could probably use a max-min streamin algo
# here too?
# TODO: heh, could probably use a max-min streamin algo here too
_, xmn = min(y1, y2), min(x1, x2)
ymx, xmx = max(y1, y2), max(x1, x2)
@ -535,35 +375,26 @@ class SelectRect(QtWidgets.QGraphicsRectItem):
ixmn, ixmx = round(xmn), round(xmx)
nbars = ixmx - ixmn + 1
chart: ChartPlotWidget = self._chart
data: np.ndarray = chart.get_viz(
chart.name
).shm.array[ixmn:ixmx]
chart = self._chart
data = chart.get_viz(chart.name).shm.array[ixmn:ixmx]
if len(data):
std: float = data['close'].std()
dmx: float = data['high'].max()
dmn: float = data['low'].min()
std = data['close'].std()
dmx = data['high'].max()
dmn = data['low'].min()
else:
dmn = dmx = std = np.nan
# update label info
label.setText('\n'.join(self._contents).format(
pchng=pchng,
rng=rng,
nbars=nbars,
std=std,
dmx=dmx,
dmn=dmn,
self._label.setText('\n'.join(self._contents).format(
pchng=pchng, rng=rng, nbars=nbars,
std=std, dmx=dmx, dmn=dmn,
))
# print(f'x2, y2: {(x2, y2)}')
# print(f'xmn, ymn: {(xmn, ymx)}')
label_anchor = Point(
xmx + 2,
ymx,
)
label_anchor = Point(xmx + 2, ymx)
# XXX: in the drag bottom-right -> top-left case we don't
# want the label to overlay the box.
@ -572,40 +403,13 @@ class SelectRect(QtWidgets.QGraphicsRectItem):
# # label_anchor = Point(x2, y2 + self._label.height())
# label_anchor = Point(xmn, ymn)
self._abs_top_right: Point = label_anchor
self._label_proxy.setPos(
cv.mapFromView(label_anchor)
)
label.show()
self._abs_top_right = label_anchor
self._label_proxy.setPos(self.vb.mapFromView(label_anchor))
# self._label.show()
def hide(self):
'''
Clear the selection box from its graphics scene but
don't delete it permanently.
def clear(self):
"""Clear the selection box from view.
'''
super().hide()
"""
self._label.hide()
# TODO: ensure noone else using dis.
clear = hide
def delete(self) -> None:
'''
De-allocate this rect from its rendering graphics scene.
Like a permanent hide.
'''
scen: QGraphicsScene = self.scene()
if scen is None:
return
scen.removeItem(self)
if (
self._label
and
self._label_proxy
):
scen.removeItem(self._label_proxy)
self.hide()

View File

@ -23,29 +23,28 @@ from typing import Callable
import trio
from tractor.trionics import gather_contexts
from piker.ui.qt import (
QtCore,
QWidget,
QEvent,
keys,
gs_keys,
pyqtBoundSignal,
from PyQt5 import QtCore
from PyQt5.QtCore import QEvent, pyqtBoundSignal
from PyQt5.QtWidgets import QWidget
from PyQt5.QtWidgets import (
QGraphicsSceneMouseEvent as gs_mouse,
)
from piker.types import Struct
from ..data.types import Struct
MOUSE_EVENTS = {
gs_keys.GraphicsSceneMousePress,
gs_keys.GraphicsSceneMouseRelease,
keys.MouseButtonPress,
keys.MouseButtonRelease,
gs_mouse.GraphicsSceneMousePress,
gs_mouse.GraphicsSceneMouseRelease,
QEvent.MouseButtonPress,
QEvent.MouseButtonRelease,
# QtGui.QMouseEvent,
}
# TODO: maybe consider some constrained ints down the road?
# https://pydantic-docs.helpmanual.io/usage/types/#constrained-types
class KeyboardMsg(Struct):
'''Unpacked Qt keyboard event data.
@ -115,10 +114,7 @@ class EventRelay(QtCore.QObject):
# something to do with Qt internals and calling the
# parent handler?
if etype in {
QEvent.Type.KeyPress,
QEvent.Type.KeyRelease,
}:
if etype in {QEvent.KeyPress, QEvent.KeyRelease}:
msg = KeyboardMsg(
event=ev,
@ -164,9 +160,7 @@ class EventRelay(QtCore.QObject):
async def open_event_stream(
source_widget: QWidget,
event_types: set[QEvent] = {
QEvent.Type.KeyPress,
},
event_types: set[QEvent] = {QEvent.KeyPress},
filter_auto_repeats: bool = True,
) -> trio.abc.ReceiveChannel:
@ -207,8 +201,8 @@ async def open_signal_handler(
async for args in recv:
await async_handler(*args)
async with trio.open_nursery() as tn:
tn.start_soon(proxy_to_handler)
async with trio.open_nursery() as n:
n.start_soon(proxy_to_handler)
async with send:
yield
@ -218,48 +212,18 @@ async def open_handlers(
source_widgets: list[QWidget],
event_types: set[QEvent],
# NOTE: if you want to bind in additional kwargs to the handler
# pass in a `partial()` instead!
async_handler: Callable[
[QWidget, trio.abc.ReceiveChannel], # required handler args
None
],
# XXX: these are ONLY inputs available to the
# `open_event_stream()` event-relay to mem-chan factor above!
**open_ev_stream_kwargs,
async_handler: Callable[[QWidget, trio.abc.ReceiveChannel], None],
**kwargs,
) -> None:
'''
Connect and schedule an async handler function to receive an
arbitrary `QWidget`'s events with kb/mouse msgs repacked into
structs (see above) and shuttled over a mem-chan to the input
`async_handler` to allow interaction-IO processing from
a `trio` func-as-task.
'''
widget: QWidget
streams: list[trio.abc.ReceiveChannel]
async with (
trio.open_nursery() as tn,
trio.open_nursery() as n,
gather_contexts([
open_event_stream(
widget,
event_types,
**open_ev_stream_kwargs,
)
open_event_stream(widget, event_types, **kwargs)
for widget in source_widgets
]) as streams,
):
for widget, event_recv_stream in zip(
source_widgets,
streams,
):
tn.start_soon(
async_handler,
widget,
event_recv_stream,
)
for widget, event_recv_stream in zip(source_widgets, streams):
n.start_soon(async_handler, widget, event_recv_stream)
yield

View File

@ -30,35 +30,34 @@ from typing import (
import platform
import traceback
# Qt specific
import PyQt5 # noqa
from PyQt5.QtWidgets import (
QWidget,
QMainWindow,
QApplication,
)
from PyQt5 import QtCore
from PyQt5.QtCore import (
pyqtRemoveInputHook,
Qt,
QCoreApplication,
)
import qdarkstyle
from qdarkstyle import DarkPalette
# import qdarkgraystyle # TODO: play with it
import trio
from outcome import Error
# Qt version-agnostic
from .qt import (
QWidget,
QMainWindow,
QApplication,
QtCore,
pyqtRemoveInputHook,
Qt,
QCoreApplication,
)
from ..service import (
maybe_open_pikerd,
get_runtime_vars,
get_tractor_runtime_kwargs,
)
from ..log import get_logger
from ._pg_overrides import _do_overrides
from . import _style
if TYPE_CHECKING:
from ._chart import GodWidget
log = get_logger(__name__)
# pyqtgraph global config
@ -147,7 +146,7 @@ def run_qtractor(
# load dark theme
stylesheet = qdarkstyle.load_stylesheet(
qt_api='pyqt6',
qt_api='pyqt5',
palette=DarkPalette,
)
app.setStyleSheet(stylesheet)
@ -174,9 +173,7 @@ def run_qtractor(
instance.window = window
# override tractor's defaults
tractor_kwargs.update(
get_runtime_vars()
)
tractor_kwargs.update(get_tractor_runtime_kwargs())
# define tractor entrypoint
async def main():

View File

@ -21,6 +21,7 @@ Text entry "forms" widgets (mostly for configuration and UI user input).
from __future__ import annotations
from contextlib import asynccontextmanager
from functools import partial
from math import floor
from typing import (
Any,
Callable,
@ -28,15 +29,9 @@ from typing import (
)
import trio
from piker.ui.qt import (
keys,
size_policy,
QtGui,
QSize,
QModelIndex,
Qt,
QEvent,
from PyQt5 import QtGui
from PyQt5.QtCore import QSize, QModelIndex, Qt, QEvent
from PyQt5.QtWidgets import (
QWidget,
QLabel,
QComboBox,
@ -45,6 +40,7 @@ from piker.ui.qt import (
QVBoxLayout,
QFormLayout,
QProgressBar,
QSizePolicy,
QStyledItemDelegate,
QStyleOptionViewItem,
)
@ -76,14 +72,14 @@ class Edit(QLineEdit):
if width_in_chars:
self._chars = int(width_in_chars)
x_size_policy = size_policy.Fixed
x_size_policy = QSizePolicy.Fixed
else:
# chart count which will be used to calculate
# width of input field.
self._chars: int = 6
# fit to surroundingn frame width
x_size_policy = size_policy.Expanding
x_size_policy = QSizePolicy.Expanding
super().__init__(parent)
@ -91,7 +87,7 @@ class Edit(QLineEdit):
# https://doc.qt.io/qt-5/qsizepolicy.html#Policy-enum
self.setSizePolicy(
x_size_policy,
size_policy.Fixed,
QSizePolicy.Fixed,
)
self.setFont(font.font)
@ -185,13 +181,11 @@ class Selection(QComboBox):
self._items: dict[str, int] = {}
super().__init__(parent=parent)
self.setSizeAdjustPolicy(
QComboBox.SizeAdjustPolicy.AdjustToContents,
)
self.setSizeAdjustPolicy(QComboBox.AdjustToContents)
# make line edit expand to surrounding frame
self.setSizePolicy(
size_policy.Expanding,
size_policy.Fixed,
QSizePolicy.Expanding,
QSizePolicy.Fixed,
)
view = self.view()
view.setUniformItemSizes(True)
@ -315,8 +309,8 @@ class FieldsForm(QWidget):
# size it as we specify
self.setSizePolicy(
size_policy.Expanding,
size_policy.Expanding,
QSizePolicy.Expanding,
QSizePolicy.Expanding,
)
# XXX: not sure why we have to create this here exactly
@ -423,8 +417,8 @@ class FieldsForm(QWidget):
select.set_items(values)
self.setSizePolicy(
size_policy.Fixed,
size_policy.Fixed,
QSizePolicy.Fixed,
QSizePolicy.Fixed,
)
select.show()
self.form.addRow(label, select)
@ -444,10 +438,7 @@ async def handle_field_input(
async for kbmsg in recv_chan:
if kbmsg.etype in {
keys.KeyPress,
keys.KeyRelease,
}:
if kbmsg.etype in {QEvent.KeyPress, QEvent.KeyRelease}:
event, etype, key, mods, txt = kbmsg.to_tuple()
print(f'key: {kbmsg.key}, mods: {kbmsg.mods}, txt: {kbmsg.txt}')
@ -713,8 +704,7 @@ def mk_fill_status_bar(
)
bottom_label = form.add_field_label(
# 'x: {step_size}',
'{unit_prefix}: {step_size}',
'x: {step_size}',
font_size=bar_label_font_size,
font_color='gunmetal',
)

View File

@ -36,27 +36,16 @@ from tractor.trionics import maybe_open_context
import trio
from trio_typing import TaskStatus
from piker.accounting import MktPair
from piker.fsp import (
cascade,
maybe_mk_fsp_shm,
Fsp,
dolla_vlm,
flow_rates,
)
from piker.data import (
Flume,
from piker.data.types import Struct
from ._axes import PriceAxis
from ..calc import humanize
from ..data._sharedmem import (
ShmArray,
)
from piker.data._sharedmem import (
_Token,
try_read,
)
from piker.log import get_logger
from piker.toolz import Profiler
from piker.types import Struct
from ._axes import PriceAxis
from ..calc import humanize
from ..data.feed import Flume
from ..accounting import MktPair
from ._chart import (
ChartPlotWidget,
LinkedSplits,
@ -66,6 +55,18 @@ from ._forms import (
mk_form,
open_form_input_handling,
)
from ..fsp._api import (
maybe_mk_fsp_shm,
Fsp,
)
from ..fsp import cascade
from ..fsp._volume import (
# tina_vwap,
dolla_vlm,
flow_rates,
)
from ..log import get_logger
from .._profile import Profiler
log = get_logger(__name__)
@ -181,10 +182,7 @@ async def open_fsp_sidepane(
async def open_fsp_actor_cluster(
names: list[str] = ['fsp_0', 'fsp_1'],
) -> AsyncGenerator[
int,
dict[str, tractor.Portal]
]:
) -> AsyncGenerator[int, dict[str, tractor.Portal]]:
from tractor._clustering import open_actor_cluster
@ -285,7 +283,6 @@ async def run_fsp_ui(
name,
array_key=array_key,
)
assert chart.qframe
chart.linked.focus()
@ -393,7 +390,7 @@ class FspAdmin:
complete: trio.Event,
started: trio.Event,
fqme: str,
dst_flume: Flume,
dst_fsp_flume: Flume,
conf: dict,
target: Fsp,
loglevel: str,
@ -411,14 +408,16 @@ class FspAdmin:
# chaining entrypoint
cascade,
# TODO: can't we just drop this and expect
# far end to read the src flume's .mkt.fqme?
# data feed key
fqme=fqme,
src_flume_addr=self.flume.to_msg(),
dst_flume_addr=dst_flume.to_msg(),
ns_path=ns_path, # edge-bind-func
# TODO: pass `Flume.to_msg()`s here?
# mems
src_shm_token=self.flume.rt_shm.token,
dst_shm_token=dst_fsp_flume.rt_shm.token,
# target
ns_path=ns_path,
loglevel=loglevel,
zero_on_step=conf.get('zero_on_step', False),
@ -432,14 +431,14 @@ class FspAdmin:
ctx.open_stream() as stream,
):
dst_flume.stream: tractor.MsgStream = stream
dst_fsp_flume.stream: tractor.MsgStream = stream
# register output data
self._registry[
(fqme, ns_path)
] = (
stream,
dst_flume.rt_shm,
dst_fsp_flume.rt_shm,
complete
)
@ -516,7 +515,7 @@ class FspAdmin:
broker='piker',
_atype='fsp',
)
dst_flume = Flume(
dst_fsp_flume = Flume(
mkt=mkt,
_rt_shm_token=dst_shm.token,
first_quote={},
@ -544,13 +543,13 @@ class FspAdmin:
complete,
started,
fqme,
dst_flume,
dst_fsp_flume,
conf,
target,
loglevel,
)
return dst_flume, started
return dst_fsp_flume, started
async def open_fsp_chart(
self,
@ -560,7 +559,7 @@ class FspAdmin:
conf: dict, # yeah probably dumb..
loglevel: str = 'error',
) -> trio.Event:
) -> (trio.Event, ChartPlotWidget):
flume, started = await self.start_engine_task(
target,
@ -927,7 +926,7 @@ async def start_fsp_displays(
linked: LinkedSplits,
flume: Flume,
# group_status_key: str,
group_status_key: str,
loglevel: str,
) -> None:
@ -974,23 +973,21 @@ async def start_fsp_displays(
flume,
) as admin,
):
statuses: list[trio.Event] = []
statuses = []
for target, conf in fsp_conf.items():
started: trio.Event = await admin.open_fsp_chart(
started = await admin.open_fsp_chart(
target,
conf,
)
# done = linked.window().status_bar.open_status(
# f'loading fsp, {target}..',
# group_key=group_status_key,
# )
# statuses.append((started, done))
statuses.append(started)
done = linked.window().status_bar.open_status(
f'loading fsp, {target}..',
group_key=group_status_key,
)
statuses.append((started, done))
# for fsp_loaded, status_cb in statuses:
for fsp_loaded in statuses:
for fsp_loaded, status_cb in statuses:
await fsp_loaded.wait()
profiler(f'attached to fsp portal: {target}')
# status_cb()
status_cb()
# blocks on nursery until all fsp actors complete

View File

@ -15,18 +15,15 @@
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
`QIcon` hackery.
Mostly dynamically loading pixmaps for use with `QGraphicsScene`.
``QIcon`` hackery.
'''
from piker.ui.qt import (
QSize,
QStyle,
QIcon,
QPixmap,
QColor,
from PyQt5.QtWidgets import QStyle
from PyQt5.QtGui import (
QIcon, QPixmap, QColor
)
from PyQt5.QtCore import QSize
from ._style import hcolor
# https://www.pythonguis.com/faq/built-in-qicons-pyqt/
@ -47,8 +44,7 @@ def mk_icons(
size: QSize,
) -> dict[str, QIcon]:
'''
This helper is indempotent.
'''This helper is indempotent.
'''
global _icons, _icon_names
@ -60,11 +56,7 @@ def mk_icons(
# load account selection using current style
for name, icon_name in _icon_names.items():
stdpixmap = getattr(
# https://www.pythonguis.com/faq/built-in-qicons-pyqt/
QStyle.StandardPixmap, # pyqt/pyside6
icon_name,
)
stdpixmap = getattr(QStyle, icon_name)
stdicon = style.standardIcon(stdpixmap)
pixmap = stdicon.pixmap(size)

View File

@ -23,7 +23,6 @@ from contextlib import (
asynccontextmanager,
ExitStack,
)
from functools import partial
import time
from typing import (
Callable,
@ -31,70 +30,46 @@ from typing import (
)
import pyqtgraph as pg
# NOTE XXX: pg is super annoying and re-implements it's own mouse
# event subsystem.. we should really look into re-working/writing
# this down the road.. Bo
from pyqtgraph.GraphicsScene import mouseEvents as mevs
# from pyqtgraph.GraphicsScene.mouseEvents import MouseDragEvent
from pyqtgraph import (
ViewBox,
Point,
QtCore,
functions as fn,
)
# from pyqtgraph.GraphicsScene import mouseEvents
from PyQt5.QtWidgets import QGraphicsSceneMouseEvent as gs_mouse
from PyQt5.QtCore import Qt, QEvent
from pyqtgraph import ViewBox, Point, QtCore
from pyqtgraph import functions as fn
import numpy as np
import trio
from piker.ui.qt import (
QWheelEvent,
QGraphicsSceneMouseEvent as gs_mouse,
Qt,
QEvent,
)
from ..log import get_logger
from ..toolz import (
Profiler,
pg_profile_enabled,
ms_slower_then,
)
from .._profile import Profiler
from .._profile import pg_profile_enabled, ms_slower_then
from .view_mode import overlay_viewlists
# from ._style import _min_points_to_show
from ._editors import SelectRect
from . import _event
if TYPE_CHECKING:
# from ._search import (
# SearchWidget,
# )
from ._chart import (
ChartnPane,
ChartPlotWidget,
GodWidget,
)
from ._chart import ChartPlotWidget
from ._dataviz import Viz
from .order_mode import OrderMode
from ._display import DisplayState
log = get_logger(__name__)
NUMBER_LINE = {
Qt.Key.Key_1,
Qt.Key.Key_2,
Qt.Key.Key_3,
Qt.Key.Key_4,
Qt.Key.Key_5,
Qt.Key.Key_6,
Qt.Key.Key_7,
Qt.Key.Key_8,
Qt.Key.Key_9,
Qt.Key.Key_0,
Qt.Key_1,
Qt.Key_2,
Qt.Key_3,
Qt.Key_4,
Qt.Key_5,
Qt.Key_6,
Qt.Key_7,
Qt.Key_8,
Qt.Key_9,
Qt.Key_0,
}
ORDER_MODE = {
Qt.Key.Key_A,
Qt.Key.Key_F,
Qt.Key.Key_D,
Qt.Key_A,
Qt.Key_F,
Qt.Key_D,
}
@ -102,12 +77,10 @@ async def handle_viewmode_kb_inputs(
view: ChartView,
recv_chan: trio.abc.ReceiveChannel,
dss: dict[str, DisplayState],
) -> None:
order_mode: OrderMode = view.order_mode
godw: GodWidget = order_mode.godw # noqa
order_mode = view.order_mode
# track edge triggered keys
# (https://en.wikipedia.org/wiki/Interrupt#Triggering_methods)
@ -171,55 +144,29 @@ async def handle_viewmode_kb_inputs(
if mods == Qt.ControlModifier:
ctrl = True
# UI REPL-shell, with ctrl-p (for "pause")
# UI REPL-shell
if (
ctrl
and key in {
Qt.Key_P,
ctrl and key in {
Qt.Key_U,
}
):
import tractor
god = order_mode.godw # noqa
feed = order_mode.feed # noqa
chart = order_mode.chart # noqa
viz = chart.main_viz # noqa
vlm_chart = chart.linked.subplots['volume'] # noqa
vlm_viz = vlm_chart.main_viz # noqa
dvlm_pi = vlm_chart._vizs['dolla_vlm'].plot # noqa
import tractor
await tractor.pause()
await tractor.breakpoint()
view.interact_graphics_cycle()
# FORCE graphics reset-and-render of all currently
# shown data `Viz`s for the current chart app.
if (
ctrl
and key in {
Qt.Key_R,
}
):
fqme: str
ds: DisplayState
for fqme, ds in dss.items():
viz: Viz
for tf, viz in {
60: ds.hist_viz,
1: ds.viz,
}.items():
# TODO: only allow this when the data is IN VIEW!
# also, we probably can do this more efficiently
# / smarter by only redrawing the portion of the
# path necessary?
viz.reset_graphics()
# ------ - ------
# SEARCH MODE
# ------ - ------
# SEARCH MODE #
# ctlr-<space>/<l> for "lookup", "search" -> open search tree
if (
ctrl
and key in {
ctrl and key in {
Qt.Key_L,
# Qt.Key_Space,
Qt.Key_Space,
}
):
godw = view._chart.linked.godwidget
@ -227,56 +174,20 @@ async def handle_viewmode_kb_inputs(
godw.search.focus()
# esc and ctrl-c
if (
key == Qt.Key_Escape
or (
ctrl
and key == Qt.Key_C
)
):
if key == Qt.Key_Escape or (ctrl and key == Qt.Key_C):
# ctrl-c as cancel
# https://forum.qt.io/topic/532/how-to-catch-ctrl-c-on-a-widget/9
view.select_box.clear()
view.linked.focus()
# cancel order or clear graphics
if (
key == Qt.Key_C
or key == Qt.Key_Delete
):
if key == Qt.Key_C or key == Qt.Key_Delete:
order_mode.cancel_orders_under_cursor()
# View modes
if (
ctrl
and (
key == Qt.Key_Equal
or key == Qt.Key_I
)
):
view.wheelEvent(
ev=None,
axis=None,
delta=view.def_delta,
)
elif (
ctrl
and (
key == Qt.Key_Minus
or key == Qt.Key_O
)
):
view.wheelEvent(
ev=None,
axis=None,
delta=-view.def_delta,
)
if key == Qt.Key_R:
elif (
not ctrl
and key == Qt.Key_R
):
# NOTE: seems that if we don't yield a Qt render
# cycle then the m4 downsampled curves will show here
# without another reset..
@ -321,47 +232,15 @@ async def handle_viewmode_kb_inputs(
# Toggle position config pane
if (
ctrl
and key in {
Qt.Key_Space,
ctrl and key in {
Qt.Key_P,
}
):
# searchw: SearchWidget = godw.search
# pp_pane = order_mode.current_pp.pane
qframes: list[ChartnPane] = []
for linked in (
godw.rt_linked,
godw.hist_linked,
):
for chartw in (
[linked.chart]
+
list(linked.subplots.values())
):
qframes.append(
chartw.qframe
)
# NOTE: place priority on FIRST hiding all
# panes before showing them.
# TODO: make this more "fancy"?
# - maybe look at majority of hidden states and then
# flip based on that?
# - move these loops into the chart APIs?
# - store the UX-state for a given feed/symbol and
# apply when opening a new one (eg. if panes were
# hidden then also hide them on newly loaded mkt
# feeds).
if not any(
qf.sidepane.isHidden() for qf in qframes
):
for qf in qframes:
qf.sidepane.hide()
pp_pane = order_mode.current_pp.pane
if pp_pane.isHidden():
pp_pane.show()
else:
for qf in qframes:
qf.sidepane.show()
pp_pane.hide()
# ORDER MODE
# ----------
@ -379,7 +258,7 @@ async def handle_viewmode_kb_inputs(
# show the pp size label only if there is
# a non-zero pos existing
tracker = order_mode.current_pp
if tracker.live_pp.cumsize:
if tracker.live_pp.size:
tracker.nav.show()
# TODO: show pp config mini-params in status bar widget
@ -459,7 +338,6 @@ async def handle_viewmode_mouse(
view: ChartView,
recv_chan: trio.abc.ReceiveChannel,
dss: dict[str, DisplayState],
) -> None:
@ -497,9 +375,6 @@ class ChartView(ViewBox):
'''
mode_name: str = 'view'
def_delta: float = 616 * 6
def_scale_factor: float = 1.016 ** (def_delta * -1 / 20)
# annots: dict[int, GraphicsObject] = {}
def __init__(
self,
@ -520,7 +395,6 @@ class ChartView(ViewBox):
# defaultPadding=0.,
**kwargs
)
# for "known y-range style"
self._static_yrange = static_yrange
@ -535,11 +409,7 @@ class ChartView(ViewBox):
# add our selection box annotator
self.select_box = SelectRect(self)
# self.select_box.add_to_view(self)
# self.addItem(
# self.select_box,
# ignoreBounds=True,
# )
self.addItem(self.select_box, ignoreBounds=True)
self.mode = None
self.order_mode: bool = False
@ -596,7 +466,6 @@ class ChartView(ViewBox):
@asynccontextmanager
async def open_async_input_handler(
self,
**handler_kwargs,
) -> ChartView:
@ -607,20 +476,14 @@ class ChartView(ViewBox):
QEvent.KeyPress,
QEvent.KeyRelease,
},
async_handler=partial(
handle_viewmode_kb_inputs,
**handler_kwargs,
),
async_handler=handle_viewmode_kb_inputs,
),
_event.open_handlers(
[self],
event_types={
gs_mouse.GraphicsSceneMousePress,
},
async_handler=partial(
handle_viewmode_mouse,
**handler_kwargs,
),
async_handler=handle_viewmode_mouse,
),
):
yield self
@ -636,9 +499,8 @@ class ChartView(ViewBox):
def wheelEvent(
self,
ev: QWheelEvent | None = None,
axis: int | None = None,
delta: float | None = None,
ev,
axis=None,
):
'''
Override "center-point" location for scrolling.
@ -649,12 +511,6 @@ class ChartView(ViewBox):
TODO: PR a method into ``pyqtgraph`` to make this configurable
'''
# NOTE: certain operations are only avail when this handler is
# actually called on events.
if ev is None:
assert delta
assert axis is None
linked = self.linked
if (
not linked
@ -665,7 +521,7 @@ class ChartView(ViewBox):
mask = [False, False]
mask[axis] = self.state['mouseEnabled'][axis]
else:
mask: list[bool] = self.state['mouseEnabled'][:]
mask = self.state['mouseEnabled'][:]
chart = self.linked.chart
@ -686,15 +542,8 @@ class ChartView(ViewBox):
# return
# actual scaling factor
delta: float = ev.delta() if ev else delta
scale_factor: float = 1.016 ** (delta * -1 / 20)
# NOTE: if elem is False -> None meaning "do not scale that
# axis".
scales: list[float | bool] = [
(None if m is False else scale_factor)
for m in mask
]
s = 1.016 ** (ev.delta() * -1 / 20) # self.state['wheelScaleFactor'])
s = [(None if m is False else s) for m in mask]
if (
# zoom happened on axis
@ -717,7 +566,7 @@ class ChartView(ViewBox):
).map(ev.pos())
)
# scale_y = 1.3 ** (center.y() * -1 / 20)
self.scaleBy(scales, center)
self.scaleBy(s, center)
# zoom in view-box area
else:
@ -732,7 +581,7 @@ class ChartView(ViewBox):
# NOTE: scroll "around" the right most datum-element in view
# gives the feeling of staying "pinned" in place.
self.scaleBy(scales, focal)
self.scaleBy(s, focal)
# XXX: the order of the next 2 lines i'm pretty sure
# matters, we want the resize to trigger before the graphics
@ -752,23 +601,21 @@ class ChartView(ViewBox):
self.interact_graphics_cycle()
self.interact_graphics_cycle()
if ev:
ev.accept()
def mouseDragEvent(
self,
ev: mevs.MouseDragEvent,
ev,
axis: int | None = None,
) -> None:
pos: Point = ev.pos()
lastPos: Point = ev.lastPos()
dif: Point = (pos - lastPos) * -1
# dif: Point = pos - lastPos
# dif: Point = dif * -1
pos = ev.pos()
lastPos = ev.lastPos()
dif = pos - lastPos
dif = dif * -1
# NOTE: if axis is specified, event will only affect that axis.
btn = ev.button()
button = ev.button()
# Ignore axes if mouse is disabled
mouseEnabled = np.array(
@ -780,7 +627,7 @@ class ChartView(ViewBox):
mask[1-axis] = 0.0
# Scale or translate based on mouse button
if btn & (
if button & (
QtCore.Qt.LeftButton | QtCore.Qt.MidButton
):
# zoom y-axis ONLY when click-n-drag on it
@ -803,55 +650,34 @@ class ChartView(ViewBox):
# XXX: WHY
ev.accept()
down_pos: Point = ev.buttonDownPos(
btn=btn,
)
scen_pos: Point = ev.scenePos()
scen_down_pos: Point = ev.buttonDownScenePos(
btn=btn,
)
down_pos = ev.buttonDownPos()
# This is the final position in the drag
if ev.isFinish():
# import pdbp; pdbp.set_trace()
self.select_box.mouse_drag_released(down_pos, pos)
# NOTE: think of this as a `.mouse_drag_release()`
# (bc HINT that's what i called the shit ass
# method that wrapped this call [yes, as a single
# fucking call] originally.. you bish, guille)
# Bo.. oraleeee
self.select_box.set_scen_pos(
# down_pos,
# pos,
scen_down_pos,
scen_pos,
)
# this is the zoom transform cmd
ax = QtCore.QRectF(down_pos, pos)
ax = self.childGroup.mapRectFromParent(ax)
# self.showAxRect(ax)
# this is the zoom transform cmd
self.showAxRect(ax)
# axis history tracking
self.axHistoryPointer += 1
self.axHistory = self.axHistory[
:self.axHistoryPointer] + [ax]
else:
self.select_box.set_scen_pos(
# down_pos,
# pos,
scen_down_pos,
scen_pos,
)
print('drag finish?')
self.select_box.set_pos(down_pos, pos)
# update shape of scale box
# self.updateScaleBox(ev.buttonDownPos(), ev.pos())
# breakpoint()
# self.updateScaleBox(
# down_pos,
# ev.pos(),
# )
self.updateScaleBox(
down_pos,
ev.pos(),
)
# PANNING MODE
else:
@ -890,7 +716,7 @@ class ChartView(ViewBox):
# ev.accept()
# WEIRD "RIGHT-CLICK CENTER ZOOM" MODE
elif btn & QtCore.Qt.RightButton:
elif button & QtCore.Qt.RightButton:
if self.state['aspectLocked'] is not False:
mask[0] = 0

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