piker/piker/ui/_display.py

1205 lines
36 KiB
Python

# 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/>.
'''
real-time display tasks for charting graphics update.
this module ties together quote and computational (fsp) streams with
graphics update methods via our custom ``pyqtgraph`` charting api.
'''
from contextlib import asynccontextmanager as acm
from functools import partial
from itertools import cycle
import time
from types import ModuleType
from typing import Optional, AsyncGenerator
import numpy as np
from pydantic import create_model
import pyqtgraph as pg
import tractor
import trio
from .. import brokers
from .._cacheables import maybe_open_context
from ..trionics import async_enter_all
from ..data.feed import open_feed, Feed
from ._chart import (
ChartPlotWidget,
LinkedSplits,
GodWidget,
)
from .. import fsp
from ._l1 import L1Labels
from ..data._sharedmem import ShmArray, maybe_open_shm_array
from ._forms import (
FieldsForm,
mk_form,
mk_order_pane_layout,
open_form_input_handling,
)
from .order_mode import open_order_mode
from ..log import get_logger
log = get_logger(__name__)
# TODO: load this from a config.toml!
_quote_throttle_rate: int = 58 # Hz
def try_read(array: np.ndarray) -> Optional[np.ndarray]:
'''
Try to read the last row from a shared mem array or ``None``
if the array read returns a zero-length array result.
Can be used to check for backfilling race conditions where an array
is currently being (re-)written by a writer actor but the reader is
unaware and reads during the window where the first and last indexes
are being updated.
'''
try:
return array[-1]
except IndexError:
# XXX: race condition with backfilling shm.
#
# the underlying issue is that a backfill (aka prepend) and subsequent
# shm array first/last index update could result in an empty array
# read here since the indices may be updated in such a way that
# a read delivers an empty array (though it seems like we
# *should* be able to prevent that?). also, as and alt and
# something we need anyway, maybe there should be some kind of
# signal that a prepend is taking place and this consumer can
# respond (eg. redrawing graphics) accordingly.
log.warning(f'Read-race on shm array: {graphics_name}@{shm.token}')
# the array read was emtpy
return None
def update_fsp_chart(
chart: ChartPlotWidget,
shm: ShmArray,
graphics_name: str,
array_key: Optional[str],
) -> None:
array = shm.array
last_row = try_read(array)
# guard against unreadable case
if not last_row:
return
# update graphics
# NOTE: this does a length check internally which allows it
# staying above the last row check below..
chart.update_curve_from_array(
graphics_name,
array,
array_key=array_key or graphics_name,
)
chart._set_yrange()
# XXX: re: ``array_key``: fsp func names must be unique meaning we
# can't have duplicates of the underlying data even if multiple
# sub-charts reference it under different 'named charts'.
# read from last calculated value and update any label
last_val_sticky = chart._ysticks.get(graphics_name)
if last_val_sticky:
# array = shm.array[array_key]
# if len(array):
# value = array[-1]
last = last_row[array_key]
last_val_sticky.update_from_data(-1, last)
# a working tick-type-classes template
_tick_groups = {
'clears': {'trade', 'utrade', 'last'},
'bids': {'bid', 'bsize'},
'asks': {'ask', 'asize'},
}
def chart_maxmin(
chart: ChartPlotWidget,
vlm_chart: Optional[ChartPlotWidget] = None,
) -> tuple[
tuple[int, int, int, int],
float,
float,
float,
]:
# TODO: implement this
# https://arxiv.org/abs/cs/0610046
# https://github.com/lemire/pythonmaxmin
array = chart._arrays['ohlc']
ifirst = array[0]['index']
last_bars_range = chart.bars_range()
l, lbar, rbar, r = last_bars_range
in_view = array[lbar - ifirst:rbar - ifirst + 1]
assert in_view.size
mx, mn = np.nanmax(in_view['high']), np.nanmin(in_view['low'])
# TODO: when we start using line charts, probably want to make
# this an overloaded call on our `DataView
# sym = chart.name
# mx, mn = np.nanmax(in_view[sym]), np.nanmin(in_view[sym])
mx_vlm_in_view = 0
if vlm_chart:
mx_vlm_in_view = np.max(in_view['volume'])
return last_bars_range, mx, max(mn, 0), mx_vlm_in_view
async def update_chart_from_quotes(
linked: LinkedSplits,
stream: tractor.MsgStream,
ohlcv: np.ndarray,
wap_in_history: bool = False,
vlm_chart: Optional[ChartPlotWidget] = None,
) -> None:
'''The 'main' (price) chart real-time update loop.
Receive from the quote stream and update the OHLC chart.
'''
# TODO: bunch of stuff:
# - I'm starting to think all this logic should be
# done in one place and "graphics update routines"
# should not be doing any length checking and array diffing.
# - handle odd lot orders
# - update last open price correctly instead
# of copying it from last bar's close
# - 1-5 sec bar lookback-autocorrection like tws does?
# (would require a background history checker task)
chart = linked.chart
# update last price sticky
last_price_sticky = chart._ysticks[chart.name]
last_price_sticky.update_from_data(
*ohlcv.array[-1][['index', 'close']]
)
if vlm_chart:
vlm_sticky = vlm_chart._ysticks['volume']
maxmin = partial(chart_maxmin, chart, vlm_chart)
chart.default_view()
(
last_bars_range,
last_mx,
last_mn,
last_mx_vlm,
) = maxmin()
last, volume = ohlcv.array[-1][['close', 'volume']]
symbol = chart.linked.symbol
l1 = L1Labels(
chart,
# determine precision/decimal lengths
digits=symbol.tick_size_digits,
size_digits=symbol.lot_size_digits,
)
chart._l1_labels = l1
# TODO:
# - in theory we should be able to read buffer data faster
# then msgs arrive.. needs some tinkering and testing
# - if trade volume jumps above / below prior L1 price
# levels this might be dark volume we need to
# present differently -> likely dark vlm
tick_size = chart.linked.symbol.tick_size
tick_margin = 3 * tick_size
chart.show()
last_quote = time.time()
# NOTE: all code below this loop is expected to be synchronous
# and thus draw instructions are not picked up jntil the next
# wait / iteration.
async for quotes in stream:
now = time.time()
quote_period = now - last_quote
quote_rate = round(1/quote_period, 1) if quote_period else float('inf')
if (
quote_period <= 1/_quote_throttle_rate
and quote_rate > _quote_throttle_rate + 2
):
log.warning(f'High quote rate {symbol.key}: {quote_rate}')
last_quote = now
# chart isn't active/shown so skip render cycle and pause feed(s)
if chart.linked.isHidden():
await chart.pause_all_feeds()
continue
for sym, quote in quotes.items():
(
brange,
mx_in_view,
mn_in_view,
mx_vlm_in_view,
) = maxmin()
l, lbar, rbar, r = brange
mx = mx_in_view + tick_margin
mn = mn_in_view - tick_margin
# NOTE: vlm may be written by the ``brokerd`` backend
# event though a tick sample is not emitted.
# TODO: show dark trades differently
# https://github.com/pikers/piker/issues/116
array = ohlcv.array
if vlm_chart:
vlm_chart.update_curve_from_array('volume', array)
vlm_sticky.update_from_data(*array[-1][['index', 'volume']])
if (
mx_vlm_in_view != last_mx_vlm or
mx_vlm_in_view > last_mx_vlm
):
# print(f'mx vlm: {last_mx_vlm} -> {mx_vlm_in_view}')
vlm_chart._set_yrange(yrange=(0, mx_vlm_in_view * 1.375))
last_mx_vlm = mx_vlm_in_view
ticks_frame = quote.get('ticks', ())
frames_by_type: dict[str, dict] = {}
lasts = {}
# build tick-type "frames" of tick sequences since
# likely the tick arrival rate is higher then our
# (throttled) quote stream rate.
for tick in ticks_frame:
price = tick.get('price')
ticktype = tick.get('type')
if ticktype == 'n/a' or price == -1:
# okkk..
continue
# keys are entered in olded-event-inserted-first order
# since we iterate ``ticks_frame`` in standard order
# above. in other words the order of the keys is the order
# of tick events by type from the provider feed.
frames_by_type.setdefault(ticktype, []).append(tick)
# overwrites so the last tick per type is the entry
lasts[ticktype] = tick
# from pprint import pformat
# frame_counts = {
# typ: len(frame) for typ, frame in frames_by_type.items()
# }
# print(f'{pformat(frame_counts)}')
# print(f'framed: {pformat(frames_by_type)}')
# print(f'lasts: {pformat(lasts)}')
# TODO: eventually we want to separate out the utrade (aka
# dark vlm prices) here and show them as an additional
# graphic.
clear_types = _tick_groups['clears']
# XXX: if we wanted to iterate in "latest" (i.e. most
# current) tick first order as an optimization where we only
# update from the last tick from each type class.
# last_clear_updated: bool = False
# for typ, tick in reversed(lasts.items()):
# iterate in FIFO order per frame
for typ, tick in lasts.items():
price = tick.get('price')
size = tick.get('size')
# compute max and min prices (including bid/ask) from
# tick frames to determine the y-range for chart
# auto-scaling.
# TODO: we need a streaming minmax algo here, see def above.
mx = max(price + tick_margin, mx)
mn = min(price - tick_margin, mn)
if typ in clear_types:
# XXX: if we only wanted to update graphics from the
# "current"/"latest received" clearing price tick
# once (see alt iteration order above).
# if last_clear_updated:
# continue
# last_clear_updated = True
# we only want to update grahpics from the *last*
# tick event that falls under the "clearing price"
# set.
# update price sticky(s)
end = array[-1]
last_price_sticky.update_from_data(
*end[['index', 'close']]
)
# update ohlc sampled price bars
chart.update_ohlc_from_array(
chart.name,
array,
)
if wap_in_history:
# update vwap overlay line
chart.update_curve_from_array('bar_wap', ohlcv.array)
# L1 book label-line updates
# XXX: is this correct for ib?
# if ticktype in ('trade', 'last'):
# if ticktype in ('last',): # 'size'):
if typ in ('last',): # 'size'):
label = {
l1.ask_label.fields['level']: l1.ask_label,
l1.bid_label.fields['level']: l1.bid_label,
}.get(price)
if label is not None:
label.update_fields({'level': price, 'size': size})
# TODO: on trades should we be knocking down
# the relevant L1 queue?
# label.size -= size
# elif ticktype in ('ask', 'asize'):
elif typ in _tick_groups['asks']:
l1.ask_label.update_fields({'level': price, 'size': size})
# elif ticktype in ('bid', 'bsize'):
elif typ in _tick_groups['bids']:
l1.bid_label.update_fields({'level': price, 'size': size})
# check for y-range re-size
if (mx > last_mx) or (mn < last_mn):
# print(f'new y range: {(mn, mx)}')
chart._set_yrange(
yrange=(mn, mx),
# TODO: we should probably scale
# the view margin based on the size
# of the true range? This way you can
# slap in orders outside the current
# L1 (only) book range.
# range_margin=0.1,
)
last_mx, last_mn = mx, mn
# run synchronous update on all derived fsp subplots
for name, subchart in linked.subplots.items():
update_fsp_chart(
subchart,
subchart._shm,
# XXX: do we really needs seperate names here?
name,
array_key=name,
)
# TODO: all overlays on all subplots..
# run synchronous update on all derived overlays
for curve_name, shm in chart._overlays.items():
update_fsp_chart(
chart,
shm,
curve_name,
array_key=curve_name,
)
def maybe_mk_fsp_shm(
sym: str,
field_name: str,
display_name: Optional[str] = None,
readonly: bool = True,
) -> (ShmArray, bool):
'''Allocate a single row shm array for an symbol-fsp pair if none
exists, otherwise load the shm already existing for that token.
'''
uid = tractor.current_actor().uid
if not display_name:
display_name = field_name
# TODO: load function here and introspect
# return stream type(s)
# TODO: should `index` be a required internal field?
fsp_dtype = np.dtype([('index', int), (field_name, float)])
key = f'{sym}.fsp.{display_name}.{".".join(uid)}'
shm, opened = maybe_open_shm_array(
key,
# TODO: create entry for each time frame
dtype=fsp_dtype,
readonly=True,
)
return shm, opened
@acm
async def open_fsp_sidepane(
linked: LinkedSplits,
conf: dict[str, dict[str, str]],
) -> FieldsForm:
schema = {}
assert len(conf) == 1 # for now
# add (single) selection widget
for display_name, config in conf.items():
schema[display_name] = {
'label': '**fsp**:',
'type': 'select',
'default_value': [display_name],
}
# add parameters for selection "options"
params = config.get('params', {})
for name, config in params.items():
default = config['default_value']
kwargs = config.get('widget_kwargs', {})
# add to ORM schema
schema.update({
name: {
'label': f'**{name}**:',
'type': 'edit',
'default_value': default,
'kwargs': kwargs,
},
})
sidepane: FieldsForm = mk_form(
parent=linked.godwidget,
fields_schema=schema,
)
# https://pydantic-docs.helpmanual.io/usage/models/#dynamic-model-creation
FspConfig = create_model(
'FspConfig',
name=display_name,
**params,
)
sidepane.model = FspConfig()
# just a logger for now until we get fsp configs up and running.
async def settings_change(key: str, value: str) -> bool:
print(f'{key}: {value}')
return True
# TODO:
async with (
open_form_input_handling(
sidepane,
focus_next=linked.godwidget,
on_value_change=settings_change,
)
):
yield sidepane
@acm
async def open_fsp_cluster(
workers: int = 2
) -> AsyncGenerator[int, dict[str, tractor.Portal]]:
from tractor._clustering import open_actor_cluster
profiler = pg.debug.Profiler(
delayed=False,
disabled=False
)
async with open_actor_cluster(
count=2,
names=['fsp_0', 'fsp_1'],
modules=['piker.fsp._engine'],
) as cluster_map:
profiler('started fsp cluster')
yield cluster_map
@acm
async def maybe_open_fsp_cluster(
workers: int = 2,
**kwargs,
) -> AsyncGenerator[int, dict[str, tractor.Portal]]:
kwargs.update(
{'workers': workers}
)
async with maybe_open_context(
# for now make a cluster per client?
acm_func=open_fsp_cluster,
kwargs=kwargs,
) as (cache_hit, cluster_map):
if cache_hit:
log.info('re-using existing fsp cluster')
yield cluster_map
else:
yield cluster_map
async def start_fsp_displays(
cluster_map: dict[str, tractor.Portal],
linkedsplits: LinkedSplits,
fsps: dict[str, str],
sym: str,
src_shm: list,
brokermod: ModuleType,
group_status_key: str,
loglevel: str,
# this con
display_in_own_task: bool = False,
) -> None:
'''Create sub-actors (under flat tree)
for each entry in config and attach to local graphics update tasks.
Pass target entrypoint and historical data.
'''
linkedsplits.focus()
profiler = pg.debug.Profiler(
delayed=False,
disabled=False
)
async with trio.open_nursery() as n:
# Currently we spawn an actor per fsp chain but
# likely we'll want to pool them eventually to
# scale horizonatlly once cores are used up.
for (display_name, conf), (name, portal) in zip(
fsps.items(),
# rr to cluster for now..
cycle(cluster_map.items()),
):
func_name = conf['func_name']
shm, opened = maybe_mk_fsp_shm(
sym,
field_name=func_name,
display_name=display_name,
readonly=True,
)
profiler(f'created shm for fsp actor: {display_name}')
# XXX: fsp may have been opened by a duplicate chart.
# Error for now until we figure out how to wrap fsps as
# "feeds". assert opened, f"A chart for {key} likely
# already exists?"
profiler(f'attached to fsp portal: {display_name}')
# init async
n.start_soon(
partial(
update_chart_from_fsp,
portal,
linkedsplits,
brokermod,
sym,
src_shm,
func_name,
display_name,
conf=conf,
shm=shm,
is_overlay=conf.get('overlay', False),
group_status_key=group_status_key,
loglevel=loglevel,
profiler=profiler,
)
)
# blocks here until all fsp actors complete
async def update_chart_from_fsp(
portal: tractor.Portal,
linkedsplits: LinkedSplits,
brokermod: ModuleType,
sym: str,
src_shm: ShmArray,
func_name: str,
display_name: str,
conf: dict[str, dict],
shm: ShmArray,
is_overlay: bool,
group_status_key: str,
loglevel: str,
profiler: pg.debug.Profiler,
) -> None:
'''FSP stream chart update loop.
This is called once for each entry in the fsp
config map.
'''
profiler(f'started chart task for fsp: {func_name}')
done = linkedsplits.window().status_bar.open_status(
f'loading fsp, {display_name}..',
group_key=group_status_key,
)
async with (
portal.open_context(
# chaining entrypoint
fsp.cascade,
# name as title of sub-chart
brokername=brokermod.name,
src_shm_token=src_shm.token,
dst_shm_token=shm.token,
symbol=sym,
func_name=func_name,
loglevel=loglevel,
zero_on_step=conf.get('zero_on_step', False),
) as (ctx, last_index),
ctx.open_stream() as stream,
open_fsp_sidepane(linkedsplits, {display_name: conf},) as sidepane,
):
profiler(f'fsp:{func_name} attached to fsp ctx-stream')
if is_overlay:
chart = linkedsplits.chart
chart.draw_curve(
name=display_name,
data=shm.array,
overlay=True,
color='default_light',
)
# specially store ref to shm for lookup in display loop
chart._overlays[display_name] = shm
else:
chart = linkedsplits.add_plot(
name=display_name,
array=shm.array,
array_key=conf['func_name'],
sidepane=sidepane,
# curve by default
ohlc=False,
# settings passed down to ``ChartPlotWidget``
**conf.get('chart_kwargs', {})
# static_yrange=(0, 100),
)
# XXX: ONLY for sub-chart fsps, overlays have their
# data looked up from the chart's internal array set.
# TODO: we must get a data view api going STAT!!
chart._shm = shm
# should **not** be the same sub-chart widget
assert chart.name != linkedsplits.chart.name
array_key = func_name
profiler(f'fsp:{func_name} chart created')
# first UI update, usually from shm pushed history
update_fsp_chart(
chart,
shm,
display_name,
array_key=array_key,
)
chart.linked.focus()
# TODO: figure out if we can roll our own `FillToThreshold` to
# get brush filled polygons for OS/OB conditions.
# ``pg.FillBetweenItems`` seems to be one technique using
# generic fills between curve types while ``PlotCurveItem`` has
# logic inside ``.paint()`` for ``self.opts['fillLevel']`` which
# might be the best solution?
# graphics = chart.update_from_array(chart.name, array[func_name])
# graphics.curve.setBrush(50, 50, 200, 100)
# graphics.curve.setFillLevel(50)
if func_name == 'rsi':
from ._lines import level_line
# add moveable over-[sold/bought] lines
# and labels only for the 70/30 lines
level_line(chart, 20)
level_line(chart, 30, orient_v='top')
level_line(chart, 70, orient_v='bottom')
level_line(chart, 80, orient_v='top')
chart._set_yrange()
done()
chart.linked.resize_sidepanes()
profiler(f'fsp:{func_name} starting update loop')
profiler.finish()
# update chart graphics
last = time.time()
async for value in stream:
# chart isn't actively shown so just skip render cycle
if chart.linked.isHidden():
continue
else:
now = time.time()
period = now - last
if period <= 1/_quote_throttle_rate:
# faster then display refresh rate
print(f'fsp too fast: {1/period}')
continue
# run synchronous update
update_fsp_chart(
chart,
shm,
display_name,
array_key=func_name,
)
# set time of last graphics update
last = time.time()
async def check_for_new_bars(
feed: Feed,
ohlcv: np.ndarray,
linkedsplits: LinkedSplits,
) -> None:
'''
Task which updates from new bars in the shared ohlcv buffer every
``delay_s`` seconds.
'''
# TODO: right now we'll spin printing bars if the last time
# stamp is before a large period of no market activity.
# Likely the best way to solve this is to make this task
# aware of the instrument's tradable hours?
price_chart = linkedsplits.chart
price_chart.default_view()
async with feed.index_stream() as stream:
async for index in stream:
# update chart historical bars graphics by incrementing
# a time step and drawing the history and new bar
# When appending a new bar, in the time between the insert
# from the writing process and the Qt render call, here,
# the index of the shm buffer may be incremented and the
# (render) call here might read the new flat bar appended
# to the buffer (since -1 index read). In that case H==L and the
# body will be set as None (not drawn) on what this render call
# *thinks* is the curent bar (even though it's reading data from
# the newly inserted flat bar.
#
# HACK: We need to therefore write only the history (not the
# current bar) and then either write the current bar manually
# or place a cursor for visual cue of the current time step.
array = ohlcv.array
# avoid unreadable race case on backfills
while not try_read(array):
await trio.sleep(0.01)
# XXX: this puts a flat bar on the current time step
# TODO: if we eventually have an x-axis time-step "cursor"
# we can get rid of this since it is extra overhead.
price_chart.update_ohlc_from_array(
price_chart.name,
array,
just_history=False,
)
# main chart overlays
for name in price_chart._overlays:
price_chart.update_curve_from_array(
name,
price_chart._arrays[name]
)
# each subplot
for name, chart in linkedsplits.subplots.items():
# TODO: do we need the same unreadable guard as for the
# price chart (above) here?
chart.update_curve_from_array(
chart.name,
chart._shm.array,
array_key=chart.data_key
)
# shift the view if in follow mode
price_chart.increment_view()
def has_vlm(ohlcv: ShmArray) -> bool:
# make sure that the instrument supports volume history
# (sometimes this is not the case for some commodities and
# derivatives)
volm = ohlcv.array['volume']
return not bool(np.all(np.isin(volm, -1)) or np.all(np.isnan(volm)))
@acm
async def maybe_open_vlm_display(
linked: LinkedSplits,
ohlcv: ShmArray,
) -> ChartPlotWidget:
if not has_vlm(ohlcv):
log.warning(f"{linked.symbol.key} does not seem to have volume info")
yield
return
else:
shm, opened = maybe_mk_fsp_shm(
linked.symbol.key,
'$_vlm',
readonly=True,
)
async with open_fsp_sidepane(
linked, {
'vlm': {
'params': {
'price_func': {
'default_value': 'chl3',
# tell target ``Edit`` widget to not allow
# edits for now.
'widget_kwargs': {'readonly': True},
},
},
}
},
) as sidepane:
# built-in $vlm
shm = ohlcv
chart = linked.add_plot(
name='volume',
array=shm.array,
array_key='volume',
sidepane=sidepane,
# curve by default
ohlc=False,
# Draw vertical bars from zero.
# we do this internally ourselves since
# the curve item internals are pretty convoluted.
style='step',
# original pyqtgraph flag for reference
# stepMode=True,
)
# XXX: ONLY for sub-chart fsps, overlays have their
# data looked up from the chart's internal array set.
# TODO: we must get a data view api going STAT!!
chart._shm = shm
# should **not** be the same sub-chart widget
assert chart.name != linked.chart.name
# sticky only on sub-charts atm
last_val_sticky = chart._ysticks[chart.name]
# read from last calculated value
value = shm.array['volume'][-1]
last_val_sticky.update_from_data(-1, value)
chart.update_curve_from_array(
'volume',
shm.array,
)
# size view to data once at outset
chart._set_yrange()
# size pain to parent chart
# TODO: this appears to nearly fix a bug where the vlm sidepane
# could be sized correctly nearly immediately (since the
# order pane is already sized), right now it doesn't seem to
# fully align until the VWAP fsp-actor comes up...
await trio.sleep(0)
chart.linked.resize_sidepanes()
await trio.sleep(0)
yield chart
async def display_symbol_data(
godwidget: GodWidget,
provider: str,
sym: str,
loglevel: str,
order_mode_started: trio.Event,
) -> None:
'''
Spawn a real-time updated chart for ``symbol``.
Spawned ``LinkedSplits`` chart widgets can remain up but hidden so
that multiple symbols can be viewed and switched between extremely
fast from a cached watch-list.
'''
sbar = godwidget.window.status_bar
loading_sym_key = sbar.open_status(
f'loading {sym}.{provider} ->',
group_key=True
)
# historical data fetch
brokermod = brokers.get_brokermod(provider)
# ohlc_status_done = sbar.open_status(
# 'retreiving OHLC history.. ',
# clear_on_next=True,
# group_key=loading_sym_key,
# )
async with async_enter_all(
open_feed(
provider,
[sym],
loglevel=loglevel,
# limit to at least display's FPS
# avoiding needless Qt-in-guest-mode context switches
tick_throttle=_quote_throttle_rate,
),
maybe_open_fsp_cluster(),
) as (feed, cluster_map):
ohlcv: ShmArray = feed.shm
bars = ohlcv.array
symbol = feed.symbols[sym]
# load in symbol's ohlc data
godwidget.window.setWindowTitle(
f'{symbol.key}@{symbol.brokers} '
f'tick:{symbol.tick_size}'
)
linkedsplits = godwidget.linkedsplits
linkedsplits._symbol = symbol
# generate order mode side-pane UI
# A ``FieldsForm`` form to configure order entry
pp_pane: FieldsForm = mk_order_pane_layout(godwidget)
# add as next-to-y-axis singleton pane
godwidget.pp_pane = pp_pane
# create main OHLC chart
chart = linkedsplits.plot_ohlc_main(
symbol,
bars,
sidepane=pp_pane,
)
chart._feeds[symbol.key] = feed
chart.setFocus()
# plot historical vwap if available
wap_in_history = False
if brokermod._show_wap_in_history:
if 'bar_wap' in bars.dtype.fields:
wap_in_history = True
chart.draw_curve(
name='bar_wap',
data=bars,
add_label=False,
)
# size view to data once at outset
chart._set_yrange()
# TODO: a data view api that makes this less shit
chart._shm = ohlcv
# TODO: eventually we'll support some kind of n-compose syntax
fsp_conf = {
'dolla_vlm': {
'func_name': 'dolla_vlm',
'zero_on_step': True,
'params': {
'price_func': {
'default_value': 'chl3',
# tell target ``Edit`` widget to not allow
# edits for now.
'widget_kwargs': {'readonly': True},
},
},
'chart_kwargs': {'style': 'step'}
},
'rsi': {
'func_name': 'rsi', # literal python func ref lookup name
# map of parameters to place on the fsp sidepane widget
# which should map to dynamic inputs available to the
# fsp function at runtime.
'params': {
'period': {
'default_value': 14,
'widget_kwargs': {'readonly': True},
},
},
# ``ChartPlotWidget`` options passthrough
'chart_kwargs': {
'static_yrange': (0, 100),
},
},
}
if has_vlm(ohlcv): # and provider != 'binance':
# binance is too fast atm for FSPs until we wrap
# the fsp streams as throttled ``Feeds``, see
#
# add VWAP to fsp config for downstream loading
fsp_conf.update({
'vwap': {
'func_name': 'vwap',
'overlay': True,
'anchor': 'session',
},
})
# NOTE: we must immediately tell Qt to show the OHLC chart
# to avoid a race where the subplots get added/shown to
# the linked set *before* the main price chart!
linkedsplits.show()
linkedsplits.focus()
await trio.sleep(0)
vlm_chart = None
async with (
trio.open_nursery() as ln,
maybe_open_vlm_display(linkedsplits, ohlcv) as vlm_chart,
):
# load initial fsp chain (otherwise known as "indicators")
ln.start_soon(
start_fsp_displays,
cluster_map,
linkedsplits,
fsp_conf,
sym,
ohlcv,
brokermod,
loading_sym_key,
loglevel,
)
# start graphics update loop(s)after receiving first live quote
ln.start_soon(
update_chart_from_quotes,
linkedsplits,
feed.stream,
ohlcv,
wap_in_history,
vlm_chart,
)
ln.start_soon(
check_for_new_bars,
feed,
ohlcv,
linkedsplits
)
async with (
open_order_mode(
feed,
chart,
symbol,
provider,
order_mode_started
)
):
await trio.sleep_forever()