Factor all data feed endpoints into `.ib.feed.py`

ib_subpkg
Tyler Goodlet 2022-06-06 15:27:05 -04:00
parent 99eabe34c9
commit 1c1661b783
4 changed files with 958 additions and 893 deletions

View File

@ -32,15 +32,27 @@ Sub-modules within break into the core functionalities:
""" """
from .client import ( from .client import (
get_client, get_client,
trades_dialogue,
)
from .feed import (
open_history_client, open_history_client,
open_symbol_search, open_symbol_search,
stream_quotes, stream_quotes,
trades_dialogue,
) )
__all__ = [
'get_client',
'trades_dialogue',
'open_history_client',
'open_symbol_search',
'stream_quotes',
]
# tractor RPC enable arg # tractor RPC enable arg
__enable_modules__: list[str] = [ __enable_modules__: list[str] = [
'client', 'client',
'feed',
] ]
# passed to ``tractor.ActorNursery.start_actor()`` # passed to ``tractor.ActorNursery.start_actor()``

View File

@ -28,8 +28,9 @@ from functools import partial
import itertools import itertools
from math import isnan from math import isnan
from typing import ( from typing import (
Any, Callable, Optional, Any,
AsyncIterator, Awaitable, Optional,
AsyncIterator,
Union, Union,
) )
import asyncio import asyncio
@ -43,7 +44,6 @@ import trio
from trio_typing import TaskStatus from trio_typing import TaskStatus
import tractor import tractor
from tractor import to_asyncio from tractor import to_asyncio
from async_generator import aclosing
from ib_insync.wrapper import RequestError from ib_insync.wrapper import RequestError
from ib_insync.contract import Contract, ContractDetails, Option from ib_insync.contract import Contract, ContractDetails, Option
from ib_insync.order import Order, Trade, OrderStatus from ib_insync.order import Order, Trade, OrderStatus
@ -53,16 +53,12 @@ from ib_insync.objects import Position
import ib_insync as ibis import ib_insync as ibis
from ib_insync.wrapper import Wrapper from ib_insync.wrapper import Wrapper
from ib_insync.client import Client as ib_Client from ib_insync.client import Client as ib_Client
from fuzzywuzzy import process as fuzzy
import numpy as np import numpy as np
import pendulum
from piker import config from piker import config
from piker.log import get_logger, get_console_log from piker.log import get_logger, get_console_log
from piker.data._source import base_ohlc_dtype from piker.data._source import base_ohlc_dtype
from piker.data._sharedmem import ShmArray
from .._util import SymbolNotFound, NoData
from piker.clearing._messages import ( from piker.clearing._messages import (
BrokerdOrder, BrokerdOrderAck, BrokerdStatus, BrokerdOrder, BrokerdOrderAck, BrokerdStatus,
BrokerdPosition, BrokerdCancel, BrokerdPosition, BrokerdCancel,
@ -1151,27 +1147,6 @@ def get_preferred_data_client(
) )
@acm
async def open_data_client() -> MethodProxy:
'''
Open the first found preferred "data client" as defined in the
user's ``brokers.toml`` in the ``ib.prefer_data_account`` variable
and deliver that client wrapped in a ``MethodProxy``.
'''
async with (
open_client_proxies() as (proxies, clients),
):
account_name, client = get_preferred_data_client(clients)
proxy = proxies.get(f'ib.{account_name}')
if not proxy:
raise ValueError(
f'No preferred data client could be found for {account_name}!'
)
yield proxy
class MethodProxy: class MethodProxy:
def __init__( def __init__(
@ -1355,725 +1330,14 @@ async def get_client(
a method proxy to it. a method proxy to it.
''' '''
from .feed import open_data_client
# TODO: the IPC via portal relay layer for when this current # TODO: the IPC via portal relay layer for when this current
# actor isn't in aio mode. # actor isn't in aio mode.
async with open_data_client() as proxy: async with open_data_client() as proxy:
yield proxy yield proxy
# https://interactivebrokers.github.io/tws-api/tick_types.html
tick_types = {
77: 'trade',
# a "utrade" aka an off exchange "unreportable" (dark) vlm:
# https://interactivebrokers.github.io/tws-api/tick_types.html#rt_volume
48: 'dark_trade',
# standard L1 ticks
0: 'bsize',
1: 'bid',
2: 'ask',
3: 'asize',
4: 'last',
5: 'size',
8: 'volume',
# ``ib_insync`` already packs these into
# quotes under the following fields.
# 55: 'trades_per_min', # `'tradeRate'`
# 56: 'vlm_per_min', # `'volumeRate'`
# 89: 'shortable', # `'shortableShares'`
}
# TODO: cython/mypyc/numba this!
def normalize(
ticker: Ticker,
calc_price: bool = False
) -> dict:
# should be real volume for this contract by default
calc_price = False
# check for special contract types
con = ticker.contract
if type(con) in (
ibis.Commodity,
ibis.Forex,
):
# 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
else:
suffix = con.primaryExchange
if not suffix:
suffix = con.exchange
# append a `.<suffix>` to the returned symbol
# key for derivatives that normally is the expiry
# date key.
expiry = con.lastTradeDateOrContractMonth
if expiry:
suffix += f'.{expiry}'
# convert named tuples to dicts so we send usable keys
new_ticks = []
for tick in ticker.ticks:
if tick and not isinstance(tick, dict):
td = tick._asdict()
td['type'] = tick_types.get(
td['tickType'],
'n/a',
)
new_ticks.append(td)
tbt = ticker.tickByTicks
if tbt:
print(f'tickbyticks:\n {ticker.tickByTicks}')
ticker.ticks = new_ticks
# some contracts don't have volume so we may want to calculate
# a midpoint price based on data we can acquire (such as bid / ask)
if calc_price:
ticker.ticks.append(
{'type': 'trade', 'price': ticker.marketPrice()}
)
# serialize for transport
data = asdict(ticker)
# generate fqsn with possible specialized suffix
# for derivatives, note the lowercase.
data['symbol'] = data['fqsn'] = '.'.join(
(con.symbol, suffix)
).lower()
# convert named tuples to dicts for transport
tbts = data.get('tickByTicks')
if tbts:
data['tickByTicks'] = [tbt._asdict() for tbt in tbts]
# add time stamps for downstream latency measurements
data['brokerd_ts'] = time.time()
# stupid stupid shit...don't even care any more..
# leave it until we do a proper latency study
# if ticker.rtTime is not None:
# data['broker_ts'] = data['rtTime_s'] = float(
# ticker.rtTime.timestamp) / 1000.
data.pop('rtTime')
return data
_pacing: str = (
'Historical Market Data Service error '
'message:Historical data request pacing violation'
)
async def get_bars(
proxy: MethodProxy,
fqsn: str,
# blank to start which tells ib to look up the latest datum
end_dt: str = '',
) -> (dict, np.ndarray):
'''
Retrieve historical data from a ``trio``-side task using
a ``MethoProxy``.
'''
fails = 0
bars: Optional[list] = None
first_dt: datetime = None
last_dt: datetime = None
if end_dt:
last_dt = pendulum.from_timestamp(end_dt.timestamp())
for _ in range(10):
try:
out = await proxy.bars(
fqsn=fqsn,
end_dt=end_dt,
)
if out:
bars, bars_array = out
else:
await tractor.breakpoint()
if bars_array is None:
raise SymbolNotFound(fqsn)
first_dt = pendulum.from_timestamp(
bars[0].date.timestamp())
last_dt = pendulum.from_timestamp(
bars[-1].date.timestamp())
time = bars_array['time']
assert time[-1] == last_dt.timestamp()
assert time[0] == first_dt.timestamp()
log.info(
f'{len(bars)} bars retreived for {first_dt} -> {last_dt}'
)
return (bars, bars_array, first_dt, last_dt), fails
except RequestError as err:
msg = err.message
# why do we always need to rebind this?
# _err = err
if 'No market data permissions for' in msg:
# TODO: signalling for no permissions searches
raise NoData(
f'Symbol: {fqsn}',
)
elif (
err.code == 162
and 'HMDS query returned no data' in err.message
):
# XXX: this is now done in the storage mgmt layer
# and we shouldn't implicitly decrement the frame dt
# index since the upper layer may be doing so
# concurrently and we don't want to be delivering frames
# that weren't asked for.
log.warning(
f'NO DATA found ending @ {end_dt}\n'
)
# try to decrement start point and look further back
# end_dt = last_dt = last_dt.subtract(seconds=2000)
raise NoData(
f'Symbol: {fqsn}',
frame_size=2000,
)
elif _pacing in msg:
log.warning(
'History throttle rate reached!\n'
'Resetting farms with `ctrl-alt-f` hack\n'
)
# TODO: we might have to put a task lock around this
# method..
hist_ev = proxy.status_event(
'HMDS data farm connection is OK:ushmds'
)
# XXX: other event messages we might want to try and
# wait for but i wasn't able to get any of this
# reliable..
# reconnect_start = proxy.status_event(
# 'Market data farm is connecting:usfuture'
# )
# live_ev = proxy.status_event(
# 'Market data farm connection is OK:usfuture'
# )
# try to wait on the reset event(s) to arrive, a timeout
# will trigger a retry up to 6 times (for now).
tries: int = 2
timeout: float = 10
# try 3 time with a data reset then fail over to
# a connection reset.
for i in range(1, tries):
log.warning('Sending DATA RESET request')
await data_reset_hack(reset_type='data')
with trio.move_on_after(timeout) as cs:
for name, ev in [
# TODO: not sure if waiting on other events
# is all that useful here or not. in theory
# you could wait on one of the ones above
# first to verify the reset request was
# sent?
('history', hist_ev),
]:
await ev.wait()
log.info(f"{name} DATA RESET")
break
if cs.cancelled_caught:
fails += 1
log.warning(
f'Data reset {name} timeout, retrying {i}.'
)
continue
else:
log.warning('Sending CONNECTION RESET')
await data_reset_hack(reset_type='connection')
with trio.move_on_after(timeout) as cs:
for name, ev in [
# TODO: not sure if waiting on other events
# is all that useful here or not. in theory
# you could wait on one of the ones above
# first to verify the reset request was
# sent?
('history', hist_ev),
]:
await ev.wait()
log.info(f"{name} DATA RESET")
if cs.cancelled_caught:
fails += 1
log.warning('Data CONNECTION RESET timeout!?')
else:
raise
return None, None
# else: # throttle wasn't fixed so error out immediately
# raise _err
@acm
async def open_history_client(
symbol: str,
) -> tuple[Callable, int]:
'''
History retreival endpoint - delivers a historical frame callble
that takes in ``pendulum.datetime`` and returns ``numpy`` arrays.
'''
async with open_data_client() as proxy:
async def get_hist(
end_dt: Optional[datetime] = None,
start_dt: Optional[datetime] = None,
) -> tuple[np.ndarray, str]:
out, fails = await get_bars(proxy, symbol, end_dt=end_dt)
# TODO: add logic here to handle tradable hours and only grab
# valid bars in the range
if out is None:
# could be trying to retreive bars over weekend
log.error(f"Can't grab bars starting at {end_dt}!?!?")
raise NoData(
f'{end_dt}',
frame_size=2000,
)
bars, bars_array, first_dt, last_dt = out
# volume cleaning since there's -ve entries,
# wood luv to know what crookery that is..
vlm = bars_array['volume']
vlm[vlm < 0] = 0
return bars_array, first_dt, last_dt
# TODO: it seems like we can do async queries for ohlc
# but getting the order right still isn't working and I'm not
# 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, 'rate': 6}
async def backfill_bars(
fqsn: str,
shm: ShmArray, # type: ignore # noqa
# TODO: we want to avoid overrunning the underlying shm array buffer
# and we should probably calc the number of calls to make depending
# on that until we have the `marketstore` daemon in place in which
# case the shm size will be driven by user config and available sys
# memory.
count: int = 16,
task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Fill historical bars into shared mem / storage afap.
TODO: avoid pacing constraints:
https://github.com/pikers/piker/issues/128
'''
# last_dt1 = None
last_dt = None
with trio.CancelScope() as cs:
async with open_data_client() as proxy:
out, fails = await get_bars(proxy, fqsn)
if out is None:
raise RuntimeError("Could not pull currrent history?!")
(first_bars, bars_array, first_dt, last_dt) = out
vlm = bars_array['volume']
vlm[vlm < 0] = 0
last_dt = first_dt
# write historical data to buffer
shm.push(bars_array)
task_status.started(cs)
i = 0
while i < count:
out, fails = await get_bars(proxy, fqsn, end_dt=first_dt)
if out is None:
# could be trying to retreive bars over weekend
# TODO: add logic here to handle tradable hours and
# only grab valid bars in the range
log.error(f"Can't grab bars starting at {first_dt}!?!?")
# XXX: get_bars() should internally decrement dt by
# 2k seconds and try again.
continue
(first_bars, bars_array, first_dt, last_dt) = out
# last_dt1 = last_dt
# last_dt = first_dt
# volume cleaning since there's -ve entries,
# wood luv to know what crookery that is..
vlm = bars_array['volume']
vlm[vlm < 0] = 0
# TODO we should probably dig into forums to see what peeps
# think this data "means" and then use it as an indicator of
# sorts? dinkus has mentioned that $vlms for the day dont'
# match other platforms nor the summary stat tws shows in
# the monitor - it's probably worth investigating.
shm.push(bars_array, prepend=True)
i += 1
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',
# 'NEWS': 'news',
}
_quote_streams: dict[str, trio.abc.ReceiveStream] = {}
async def _setup_quote_stream(
from_trio: asyncio.Queue,
to_trio: trio.abc.SendChannel,
symbol: str,
opts: tuple[int] = (
'375', # RT trade volume (excludes utrades)
'233', # RT trade volume (includes utrades)
'236', # Shortable shares
# these all appear to only be updated every 25s thus
# 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
),
contract: Optional[Contract] = None,
) -> trio.abc.ReceiveChannel:
'''
Stream a ticker using the std L1 api.
This task is ``asyncio``-side and must be called from
``tractor.to_asyncio.open_channel_from()``.
'''
global _quote_streams
to_trio.send_nowait(None)
async with load_aio_clients() as accts2clients:
caccount_name, client = get_preferred_data_client(accts2clients)
contract = contract or (await client.find_contract(symbol))
ticker: Ticker = client.ib.reqMktData(contract, ','.join(opts))
# NOTE: it's batch-wise and slow af but I guess could
# be good for backchecking? Seems to be every 5s maybe?
# ticker: Ticker = client.ib.reqTickByTickData(
# contract, 'Last',
# )
# # define a simple queue push routine that streams quote packets
# # to trio over the ``to_trio`` memory channel.
# to_trio, from_aio = trio.open_memory_channel(2**8) # type: ignore
def teardown():
ticker.updateEvent.disconnect(push)
log.error(f"Disconnected stream for `{symbol}`")
client.ib.cancelMktData(contract)
# decouple broadcast mem chan
_quote_streams.pop(symbol, None)
def push(t: Ticker) -> None:
"""
Push quotes to trio task.
"""
# log.debug(t)
try:
to_trio.send_nowait(t)
except (
trio.BrokenResourceError,
# XXX: HACK, not sure why this gets left stale (probably
# due to our terrible ``tractor.to_asyncio``
# implementation for streams.. but if the mem chan
# gets left here and starts blocking just kill the feed?
# trio.WouldBlock,
):
# XXX: eventkit's ``Event.emit()`` for whatever redic
# reason will catch and ignore regular exceptions
# resulting in tracebacks spammed to console..
# Manually do the dereg ourselves.
teardown()
except trio.WouldBlock:
log.warning(
f'channel is blocking symbol feed for {symbol}?'
f'\n{to_trio.statistics}'
)
# except trio.WouldBlock:
# # for slow debugging purposes to avoid clobbering prompt
# # with log msgs
# pass
ticker.updateEvent.connect(push)
try:
await asyncio.sleep(float('inf'))
finally:
teardown()
# return from_aio
@acm
async def open_aio_quote_stream(
symbol: str,
contract: Optional[Contract] = None,
) -> trio.abc.ReceiveStream:
from tractor.trionics import broadcast_receiver
global _quote_streams
from_aio = _quote_streams.get(symbol)
if from_aio:
# if we already have a cached feed deliver a rx side clone to consumer
async with broadcast_receiver(
from_aio,
2**6,
) as from_aio:
yield from_aio
return
async with tractor.to_asyncio.open_channel_from(
_setup_quote_stream,
symbol=symbol,
contract=contract,
) as (first, from_aio):
# cache feed for later consumers
_quote_streams[symbol] = from_aio
yield from_aio
async def stream_quotes(
send_chan: trio.abc.SendChannel,
symbols: list[str],
feed_is_live: trio.Event,
loglevel: str = None,
# startup sync
task_status: TaskStatus[tuple[dict, dict]] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Stream symbol quotes.
This is a ``trio`` callable routine meant to be invoked
once the brokerd is up.
'''
# TODO: support multiple subscriptions
sym = symbols[0]
log.info(f'request for real-time quotes: {sym}')
async with open_data_client() as proxy:
con, first_ticker, details = await proxy.get_sym_details(symbol=sym)
first_quote = normalize(first_ticker)
# print(f'first quote: {first_quote}')
def mk_init_msgs() -> dict[str, dict]:
'''
Collect a bunch of meta-data useful for feed startup and
pack in a `dict`-msg.
'''
# pass back some symbol info like min_tick, trading_hours, etc.
syminfo = asdict(details)
syminfo.update(syminfo['contract'])
# nested dataclass we probably don't need and that won't IPC
# serialize
syminfo.pop('secIdList')
# TODO: more consistent field translation
atype = syminfo['asset_type'] = asset_type_map[syminfo['secType']]
# for stocks it seems TWS reports too small a tick size
# such that you can't submit orders with that granularity?
min_tick = 0.01 if atype == 'stock' else 0
syminfo['price_tick_size'] = max(syminfo['minTick'], min_tick)
# for "traditional" assets, volume is normally discreet, not
# a float
syminfo['lot_tick_size'] = 0.0
ibclient = proxy._aio_ns.ib.client
host, port = ibclient.host, ibclient.port
# TODO: for loop through all symbols passed in
init_msgs = {
# pass back token, and bool, signalling if we're the writer
# and that history has been written
sym: {
'symbol_info': syminfo,
'fqsn': first_quote['fqsn'],
},
'status': {
'data_ep': f'{host}:{port}',
},
}
return init_msgs
init_msgs = mk_init_msgs()
# 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):
contract, first_ticker, details = await proxy.get_quote(symbol=sym)
# it might be outside regular trading hours so see if we can at
# least grab history.
if isnan(first_ticker.last):
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?
feed_is_live.set()
# block and let data history backfill code run.
await trio.sleep_forever()
return # we never expect feed to come up?
async with open_aio_quote_stream(
symbol=sym,
contract=con,
) as stream:
# ugh, clear ticks since we've consumed them
# (ahem, ib_insync is stateful trash)
first_ticker.ticks = []
task_status.started((init_msgs, first_quote))
async with aclosing(stream):
if type(first_ticker.contract) not in (
ibis.Commodity,
ibis.Forex
):
# wait for real volume on feed (trading might be closed)
while True:
ticker = await stream.receive()
# for a real volume contract we rait for the first
# "real" trade to take place
if (
# not calc_price
# and not ticker.rtTime
not ticker.rtTime
):
# spin consuming tickers until we get a real
# market datum
log.debug(f"New unsent ticker: {ticker}")
continue
else:
log.debug("Received first real volume tick")
# ugh, clear ticks since we've consumed them
# (ahem, ib_insync is truly stateful trash)
ticker.ticks = []
# XXX: this works because we don't use
# ``aclosing()`` above?
break
quote = normalize(ticker)
log.debug(f"First ticker received {quote}")
# tell caller quotes are now coming in live
feed_is_live.set()
# last = time.time()
async for ticker in stream:
quote = normalize(ticker)
await send_chan.send({quote['fqsn']: quote})
# ugh, clear ticks since we've consumed them
ticker.ticks = []
# last = time.time()
def pack_position( def pack_position(
pos: Position pos: Position
@ -2461,156 +1725,6 @@ async def deliver_trade_events(
await ems_stream.send(msg.dict()) await ems_stream.send(msg.dict())
@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_data_client() as proxy:
async with ctx.open_stream() as stream:
last = time.time()
async for pattern in stream:
log.debug(f'received {pattern}')
now = time.time()
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():
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.debug(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]):
stock_results.extend(await target)
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)
# 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 | {
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)
async def data_reset_hack(
reset_type: str = 'data',
) -> None:
'''
Run key combos for resetting data feeds and yield back to caller
when complete.
This is a linux-only hack around:
https://interactivebrokers.github.io/tws-api/historical_limitations.html#pacing_violations
TODOs:
- a return type that hopefully determines if the hack was
successful.
- other OS support?
- integration with ``ib-gw`` run in docker + Xorg?
'''
async def vnc_click_hack(
reset_type: str = 'data'
) -> None:
'''
Reset the data or netowork connection for the VNC attached
ib gateway using magic combos.
'''
key = {'data': 'f', 'connection': 'r'}[reset_type]
import asyncvnc
async with asyncvnc.connect(
'localhost',
port=3003,
# password='ibcansmbz',
) as client:
# move to middle of screen
# 640x1800
client.mouse.move(
x=500,
y=500,
)
client.mouse.click()
client.keyboard.press('Ctrl', 'Alt', key) # keys are stacked
await tractor.to_asyncio.run_task(vnc_click_hack)
# we don't really need the ``xdotool`` approach any more B)
return True
def load_flex_trades( def load_flex_trades(
path: Optional[str] = None, path: Optional[str] = None,
@ -2680,7 +1794,7 @@ def load_flex_trades(
try: try:
config.write(section, 'trades') config.write(section, 'trades')
except KeyError: except KeyError:
import pdbpp; pdbpp.set_trace() import pdbpp; pdbpp.set_trace() # noqa
if __name__ == '__main__': if __name__ == '__main__':

View File

@ -0,0 +1,938 @@
# 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/>.
"""
Data feed endpoints pre-wrapped and ready for use with ``tractor``/``trio``.
"""
from __future__ import annotations
import asyncio
from contextlib import asynccontextmanager as acm
from dataclasses import asdict
from datetime import datetime
from math import isnan
import time
from typing import (
Callable,
Optional,
Awaitable,
)
from async_generator import aclosing
from fuzzywuzzy import process as fuzzy
import numpy as np
import pendulum
import tractor
import trio
from trio_typing import TaskStatus
from piker.data._sharedmem import ShmArray
from .._util import SymbolNotFound, NoData
from .client import (
_adhoc_futes_set,
log,
load_aio_clients,
ibis,
MethodProxy,
open_client_proxies,
get_preferred_data_client,
Ticker,
RequestError,
Contract,
)
# https://interactivebrokers.github.io/tws-api/tick_types.html
tick_types = {
77: 'trade',
# a "utrade" aka an off exchange "unreportable" (dark) vlm:
# https://interactivebrokers.github.io/tws-api/tick_types.html#rt_volume
48: 'dark_trade',
# standard L1 ticks
0: 'bsize',
1: 'bid',
2: 'ask',
3: 'asize',
4: 'last',
5: 'size',
8: 'volume',
# ``ib_insync`` already packs these into
# quotes under the following fields.
# 55: 'trades_per_min', # `'tradeRate'`
# 56: 'vlm_per_min', # `'volumeRate'`
# 89: 'shortable', # `'shortableShares'`
}
@acm
async def open_data_client() -> MethodProxy:
'''
Open the first found preferred "data client" as defined in the
user's ``brokers.toml`` in the ``ib.prefer_data_account`` variable
and deliver that client wrapped in a ``MethodProxy``.
'''
async with (
open_client_proxies() as (proxies, clients),
):
account_name, client = get_preferred_data_client(clients)
proxy = proxies.get(f'ib.{account_name}')
if not proxy:
raise ValueError(
f'No preferred data client could be found for {account_name}!'
)
yield proxy
@acm
async def open_history_client(
symbol: str,
) -> tuple[Callable, int]:
'''
History retreival endpoint - delivers a historical frame callble
that takes in ``pendulum.datetime`` and returns ``numpy`` arrays.
'''
async with open_data_client() as proxy:
async def get_hist(
end_dt: Optional[datetime] = None,
start_dt: Optional[datetime] = None,
) -> tuple[np.ndarray, str]:
out, fails = await get_bars(proxy, symbol, end_dt=end_dt)
# TODO: add logic here to handle tradable hours and only grab
# valid bars in the range
if out is None:
# could be trying to retreive bars over weekend
log.error(f"Can't grab bars starting at {end_dt}!?!?")
raise NoData(
f'{end_dt}',
frame_size=2000,
)
bars, bars_array, first_dt, last_dt = out
# volume cleaning since there's -ve entries,
# wood luv to know what crookery that is..
vlm = bars_array['volume']
vlm[vlm < 0] = 0
return bars_array, first_dt, last_dt
# TODO: it seems like we can do async queries for ohlc
# but getting the order right still isn't working and I'm not
# 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, 'rate': 6}
_pacing: str = (
'Historical Market Data Service error '
'message:Historical data request pacing violation'
)
async def get_bars(
proxy: MethodProxy,
fqsn: str,
# blank to start which tells ib to look up the latest datum
end_dt: str = '',
) -> (dict, np.ndarray):
'''
Retrieve historical data from a ``trio``-side task using
a ``MethoProxy``.
'''
fails = 0
bars: Optional[list] = None
first_dt: datetime = None
last_dt: datetime = None
if end_dt:
last_dt = pendulum.from_timestamp(end_dt.timestamp())
for _ in range(10):
try:
out = await proxy.bars(
fqsn=fqsn,
end_dt=end_dt,
)
if out:
bars, bars_array = out
else:
await tractor.breakpoint()
if bars_array is None:
raise SymbolNotFound(fqsn)
first_dt = pendulum.from_timestamp(
bars[0].date.timestamp())
last_dt = pendulum.from_timestamp(
bars[-1].date.timestamp())
time = bars_array['time']
assert time[-1] == last_dt.timestamp()
assert time[0] == first_dt.timestamp()
log.info(
f'{len(bars)} bars retreived for {first_dt} -> {last_dt}'
)
return (bars, bars_array, first_dt, last_dt), fails
except RequestError as err:
msg = err.message
# why do we always need to rebind this?
# _err = err
if 'No market data permissions for' in msg:
# TODO: signalling for no permissions searches
raise NoData(
f'Symbol: {fqsn}',
)
elif (
err.code == 162
and 'HMDS query returned no data' in err.message
):
# XXX: this is now done in the storage mgmt layer
# and we shouldn't implicitly decrement the frame dt
# index since the upper layer may be doing so
# concurrently and we don't want to be delivering frames
# that weren't asked for.
log.warning(
f'NO DATA found ending @ {end_dt}\n'
)
# try to decrement start point and look further back
# end_dt = last_dt = last_dt.subtract(seconds=2000)
raise NoData(
f'Symbol: {fqsn}',
frame_size=2000,
)
elif _pacing in msg:
log.warning(
'History throttle rate reached!\n'
'Resetting farms with `ctrl-alt-f` hack\n'
)
# TODO: we might have to put a task lock around this
# method..
hist_ev = proxy.status_event(
'HMDS data farm connection is OK:ushmds'
)
# XXX: other event messages we might want to try and
# wait for but i wasn't able to get any of this
# reliable..
# reconnect_start = proxy.status_event(
# 'Market data farm is connecting:usfuture'
# )
# live_ev = proxy.status_event(
# 'Market data farm connection is OK:usfuture'
# )
# try to wait on the reset event(s) to arrive, a timeout
# will trigger a retry up to 6 times (for now).
tries: int = 2
timeout: float = 10
# try 3 time with a data reset then fail over to
# a connection reset.
for i in range(1, tries):
log.warning('Sending DATA RESET request')
await data_reset_hack(reset_type='data')
with trio.move_on_after(timeout) as cs:
for name, ev in [
# TODO: not sure if waiting on other events
# is all that useful here or not. in theory
# you could wait on one of the ones above
# first to verify the reset request was
# sent?
('history', hist_ev),
]:
await ev.wait()
log.info(f"{name} DATA RESET")
break
if cs.cancelled_caught:
fails += 1
log.warning(
f'Data reset {name} timeout, retrying {i}.'
)
continue
else:
log.warning('Sending CONNECTION RESET')
await data_reset_hack(reset_type='connection')
with trio.move_on_after(timeout) as cs:
for name, ev in [
# TODO: not sure if waiting on other events
# is all that useful here or not. in theory
# you could wait on one of the ones above
# first to verify the reset request was
# sent?
('history', hist_ev),
]:
await ev.wait()
log.info(f"{name} DATA RESET")
if cs.cancelled_caught:
fails += 1
log.warning('Data CONNECTION RESET timeout!?')
else:
raise
return None, None
# else: # throttle wasn't fixed so error out immediately
# raise _err
async def backfill_bars(
fqsn: str,
shm: ShmArray, # type: ignore # noqa
# TODO: we want to avoid overrunning the underlying shm array buffer
# and we should probably calc the number of calls to make depending
# on that until we have the `marketstore` daemon in place in which
# case the shm size will be driven by user config and available sys
# memory.
count: int = 16,
task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Fill historical bars into shared mem / storage afap.
TODO: avoid pacing constraints:
https://github.com/pikers/piker/issues/128
'''
# last_dt1 = None
last_dt = None
with trio.CancelScope() as cs:
async with open_data_client() as proxy:
out, fails = await get_bars(proxy, fqsn)
if out is None:
raise RuntimeError("Could not pull currrent history?!")
(first_bars, bars_array, first_dt, last_dt) = out
vlm = bars_array['volume']
vlm[vlm < 0] = 0
last_dt = first_dt
# write historical data to buffer
shm.push(bars_array)
task_status.started(cs)
i = 0
while i < count:
out, fails = await get_bars(proxy, fqsn, end_dt=first_dt)
if out is None:
# could be trying to retreive bars over weekend
# TODO: add logic here to handle tradable hours and
# only grab valid bars in the range
log.error(f"Can't grab bars starting at {first_dt}!?!?")
# XXX: get_bars() should internally decrement dt by
# 2k seconds and try again.
continue
(first_bars, bars_array, first_dt, last_dt) = out
# last_dt1 = last_dt
# last_dt = first_dt
# volume cleaning since there's -ve entries,
# wood luv to know what crookery that is..
vlm = bars_array['volume']
vlm[vlm < 0] = 0
# TODO we should probably dig into forums to see what peeps
# think this data "means" and then use it as an indicator of
# sorts? dinkus has mentioned that $vlms for the day dont'
# match other platforms nor the summary stat tws shows in
# the monitor - it's probably worth investigating.
shm.push(bars_array, prepend=True)
i += 1
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',
# 'NEWS': 'news',
}
_quote_streams: dict[str, trio.abc.ReceiveStream] = {}
async def _setup_quote_stream(
from_trio: asyncio.Queue,
to_trio: trio.abc.SendChannel,
symbol: str,
opts: tuple[int] = (
'375', # RT trade volume (excludes utrades)
'233', # RT trade volume (includes utrades)
'236', # Shortable shares
# these all appear to only be updated every 25s thus
# 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
),
contract: Optional[Contract] = None,
) -> trio.abc.ReceiveChannel:
'''
Stream a ticker using the std L1 api.
This task is ``asyncio``-side and must be called from
``tractor.to_asyncio.open_channel_from()``.
'''
global _quote_streams
to_trio.send_nowait(None)
async with load_aio_clients() as accts2clients:
caccount_name, client = get_preferred_data_client(accts2clients)
contract = contract or (await client.find_contract(symbol))
ticker: Ticker = client.ib.reqMktData(contract, ','.join(opts))
# NOTE: it's batch-wise and slow af but I guess could
# be good for backchecking? Seems to be every 5s maybe?
# ticker: Ticker = client.ib.reqTickByTickData(
# contract, 'Last',
# )
# # define a simple queue push routine that streams quote packets
# # to trio over the ``to_trio`` memory channel.
# to_trio, from_aio = trio.open_memory_channel(2**8) # type: ignore
def teardown():
ticker.updateEvent.disconnect(push)
log.error(f"Disconnected stream for `{symbol}`")
client.ib.cancelMktData(contract)
# decouple broadcast mem chan
_quote_streams.pop(symbol, None)
def push(t: Ticker) -> None:
"""
Push quotes to trio task.
"""
# log.debug(t)
try:
to_trio.send_nowait(t)
except (
trio.BrokenResourceError,
# XXX: HACK, not sure why this gets left stale (probably
# due to our terrible ``tractor.to_asyncio``
# implementation for streams.. but if the mem chan
# gets left here and starts blocking just kill the feed?
# trio.WouldBlock,
):
# XXX: eventkit's ``Event.emit()`` for whatever redic
# reason will catch and ignore regular exceptions
# resulting in tracebacks spammed to console..
# Manually do the dereg ourselves.
teardown()
except trio.WouldBlock:
log.warning(
f'channel is blocking symbol feed for {symbol}?'
f'\n{to_trio.statistics}'
)
# except trio.WouldBlock:
# # for slow debugging purposes to avoid clobbering prompt
# # with log msgs
# pass
ticker.updateEvent.connect(push)
try:
await asyncio.sleep(float('inf'))
finally:
teardown()
# return from_aio
@acm
async def open_aio_quote_stream(
symbol: str,
contract: Optional[Contract] = None,
) -> trio.abc.ReceiveStream:
from tractor.trionics import broadcast_receiver
global _quote_streams
from_aio = _quote_streams.get(symbol)
if from_aio:
# if we already have a cached feed deliver a rx side clone to consumer
async with broadcast_receiver(
from_aio,
2**6,
) as from_aio:
yield from_aio
return
async with tractor.to_asyncio.open_channel_from(
_setup_quote_stream,
symbol=symbol,
contract=contract,
) as (first, from_aio):
# cache feed for later consumers
_quote_streams[symbol] = from_aio
yield from_aio
# TODO: cython/mypyc/numba this!
def normalize(
ticker: Ticker,
calc_price: bool = False
) -> dict:
# should be real volume for this contract by default
calc_price = False
# check for special contract types
con = ticker.contract
if type(con) in (
ibis.Commodity,
ibis.Forex,
):
# 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
else:
suffix = con.primaryExchange
if not suffix:
suffix = con.exchange
# append a `.<suffix>` to the returned symbol
# key for derivatives that normally is the expiry
# date key.
expiry = con.lastTradeDateOrContractMonth
if expiry:
suffix += f'.{expiry}'
# convert named tuples to dicts so we send usable keys
new_ticks = []
for tick in ticker.ticks:
if tick and not isinstance(tick, dict):
td = tick._asdict()
td['type'] = tick_types.get(
td['tickType'],
'n/a',
)
new_ticks.append(td)
tbt = ticker.tickByTicks
if tbt:
print(f'tickbyticks:\n {ticker.tickByTicks}')
ticker.ticks = new_ticks
# some contracts don't have volume so we may want to calculate
# a midpoint price based on data we can acquire (such as bid / ask)
if calc_price:
ticker.ticks.append(
{'type': 'trade', 'price': ticker.marketPrice()}
)
# serialize for transport
data = asdict(ticker)
# generate fqsn with possible specialized suffix
# for derivatives, note the lowercase.
data['symbol'] = data['fqsn'] = '.'.join(
(con.symbol, suffix)
).lower()
# convert named tuples to dicts for transport
tbts = data.get('tickByTicks')
if tbts:
data['tickByTicks'] = [tbt._asdict() for tbt in tbts]
# add time stamps for downstream latency measurements
data['brokerd_ts'] = time.time()
# stupid stupid shit...don't even care any more..
# leave it until we do a proper latency study
# if ticker.rtTime is not None:
# data['broker_ts'] = data['rtTime_s'] = float(
# ticker.rtTime.timestamp) / 1000.
data.pop('rtTime')
return data
async def stream_quotes(
send_chan: trio.abc.SendChannel,
symbols: list[str],
feed_is_live: trio.Event,
loglevel: str = None,
# startup sync
task_status: TaskStatus[tuple[dict, dict]] = trio.TASK_STATUS_IGNORED,
) -> None:
'''
Stream symbol quotes.
This is a ``trio`` callable routine meant to be invoked
once the brokerd is up.
'''
# TODO: support multiple subscriptions
sym = symbols[0]
log.info(f'request for real-time quotes: {sym}')
async with open_data_client() as proxy:
con, first_ticker, details = await proxy.get_sym_details(symbol=sym)
first_quote = normalize(first_ticker)
# print(f'first quote: {first_quote}')
def mk_init_msgs() -> dict[str, dict]:
'''
Collect a bunch of meta-data useful for feed startup and
pack in a `dict`-msg.
'''
# pass back some symbol info like min_tick, trading_hours, etc.
syminfo = asdict(details)
syminfo.update(syminfo['contract'])
# nested dataclass we probably don't need and that won't IPC
# serialize
syminfo.pop('secIdList')
# TODO: more consistent field translation
atype = syminfo['asset_type'] = asset_type_map[syminfo['secType']]
# for stocks it seems TWS reports too small a tick size
# such that you can't submit orders with that granularity?
min_tick = 0.01 if atype == 'stock' else 0
syminfo['price_tick_size'] = max(syminfo['minTick'], min_tick)
# for "traditional" assets, volume is normally discreet, not
# a float
syminfo['lot_tick_size'] = 0.0
ibclient = proxy._aio_ns.ib.client
host, port = ibclient.host, ibclient.port
# TODO: for loop through all symbols passed in
init_msgs = {
# pass back token, and bool, signalling if we're the writer
# and that history has been written
sym: {
'symbol_info': syminfo,
'fqsn': first_quote['fqsn'],
},
'status': {
'data_ep': f'{host}:{port}',
},
}
return init_msgs
init_msgs = mk_init_msgs()
# 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):
contract, first_ticker, details = await proxy.get_quote(symbol=sym)
# it might be outside regular trading hours so see if we can at
# least grab history.
if isnan(first_ticker.last):
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?
feed_is_live.set()
# block and let data history backfill code run.
await trio.sleep_forever()
return # we never expect feed to come up?
async with open_aio_quote_stream(
symbol=sym,
contract=con,
) as stream:
# ugh, clear ticks since we've consumed them
# (ahem, ib_insync is stateful trash)
first_ticker.ticks = []
task_status.started((init_msgs, first_quote))
async with aclosing(stream):
if type(first_ticker.contract) not in (
ibis.Commodity,
ibis.Forex
):
# wait for real volume on feed (trading might be closed)
while True:
ticker = await stream.receive()
# for a real volume contract we rait for the first
# "real" trade to take place
if (
# not calc_price
# and not ticker.rtTime
not ticker.rtTime
):
# spin consuming tickers until we get a real
# market datum
log.debug(f"New unsent ticker: {ticker}")
continue
else:
log.debug("Received first real volume tick")
# ugh, clear ticks since we've consumed them
# (ahem, ib_insync is truly stateful trash)
ticker.ticks = []
# XXX: this works because we don't use
# ``aclosing()`` above?
break
quote = normalize(ticker)
log.debug(f"First ticker received {quote}")
# tell caller quotes are now coming in live
feed_is_live.set()
# last = time.time()
async for ticker in stream:
quote = normalize(ticker)
await send_chan.send({quote['fqsn']: quote})
# ugh, clear ticks since we've consumed them
ticker.ticks = []
# last = time.time()
async def data_reset_hack(
reset_type: str = 'data',
) -> None:
'''
Run key combos for resetting data feeds and yield back to caller
when complete.
This is a linux-only hack around:
https://interactivebrokers.github.io/tws-api/historical_limitations.html#pacing_violations
TODOs:
- a return type that hopefully determines if the hack was
successful.
- other OS support?
- integration with ``ib-gw`` run in docker + Xorg?
'''
async def vnc_click_hack(
reset_type: str = 'data'
) -> None:
'''
Reset the data or netowork connection for the VNC attached
ib gateway using magic combos.
'''
key = {'data': 'f', 'connection': 'r'}[reset_type]
import asyncvnc
async with asyncvnc.connect(
'localhost',
port=3003,
# password='ibcansmbz',
) as client:
# move to middle of screen
# 640x1800
client.mouse.move(
x=500,
y=500,
)
client.mouse.click()
client.keyboard.press('Ctrl', 'Alt', key) # keys are stacked
await tractor.to_asyncio.run_task(vnc_click_hack)
# we don't really need the ``xdotool`` approach any more B)
return True
@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_data_client() as proxy:
async with ctx.open_stream() as stream:
last = time.time()
async for pattern in stream:
log.debug(f'received {pattern}')
now = time.time()
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():
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.debug(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]):
stock_results.extend(await target)
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)
# 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 | {
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

@ -700,6 +700,7 @@ async def manage_history(
bfqsn = fqsn.replace('.' + mod.name, '') bfqsn = fqsn.replace('.' + mod.name, '')
open_history_client = getattr(mod, 'open_history_client', None) open_history_client = getattr(mod, 'open_history_client', None)
assert open_history_client
if is_up and opened and open_history_client: if is_up and opened and open_history_client: