1054 lines
33 KiB
Python
1054 lines
33 KiB
Python
# piker: trading gear for hackers
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# Copyright (C) Tyler Goodlet (in stewardship for pikers)
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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"""
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Data feed endpoints pre-wrapped and ready for use with ``tractor``/``trio``.
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"""
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from __future__ import annotations
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import asyncio
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from contextlib import asynccontextmanager as acm
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from dataclasses import asdict
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from datetime import datetime
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from functools import partial
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from math import isnan
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import time
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from typing import (
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Callable,
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Optional,
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Awaitable,
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)
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from async_generator import aclosing
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from fuzzywuzzy import process as fuzzy
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import numpy as np
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import pendulum
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import tractor
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import trio
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from trio_typing import TaskStatus
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from .._util import (
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NoData,
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DataUnavailable,
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SymbolNotFound,
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)
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from .api import (
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# _adhoc_futes_set,
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con2fqsn,
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log,
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load_aio_clients,
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ibis,
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MethodProxy,
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open_client_proxies,
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get_preferred_data_client,
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Ticker,
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RequestError,
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Contract,
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)
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from ._util import data_reset_hack
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# https://interactivebrokers.github.io/tws-api/tick_types.html
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tick_types = {
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77: 'trade',
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# a "utrade" aka an off exchange "unreportable" (dark) vlm:
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# https://interactivebrokers.github.io/tws-api/tick_types.html#rt_volume
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48: 'dark_trade',
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# standard L1 ticks
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0: 'bsize',
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1: 'bid',
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2: 'ask',
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3: 'asize',
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4: 'last',
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5: 'size',
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8: 'volume',
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# ``ib_insync`` already packs these into
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# quotes under the following fields.
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# 55: 'trades_per_min', # `'tradeRate'`
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# 56: 'vlm_per_min', # `'volumeRate'`
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# 89: 'shortable', # `'shortableShares'`
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}
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@acm
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async def open_data_client() -> MethodProxy:
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'''
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Open the first found preferred "data client" as defined in the
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user's ``brokers.toml`` in the ``ib.prefer_data_account`` variable
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and deliver that client wrapped in a ``MethodProxy``.
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'''
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async with (
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open_client_proxies() as (proxies, clients),
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):
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account_name, client = get_preferred_data_client(clients)
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proxy = proxies.get(f'ib.{account_name}')
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if not proxy:
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raise ValueError(
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f'No preferred data client could be found for {account_name}!'
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)
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yield proxy
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@acm
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async def open_history_client(
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fqsn: str,
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) -> tuple[Callable, int]:
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'''
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History retreival endpoint - delivers a historical frame callble
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that takes in ``pendulum.datetime`` and returns ``numpy`` arrays.
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'''
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# TODO:
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# - add logic to handle tradable hours and only grab
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# valid bars in the range?
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# - we want to avoid overrunning the underlying shm array buffer and
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# we should probably calc the number of calls to make depending on
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# that until we have the `marketstore` daemon in place in which case
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# the shm size will be driven by user config and available sys
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# memory.
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async with open_data_client() as proxy:
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max_timeout: float = 2.
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mean: float = 0
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count: int = 0
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head_dt: None | datetime = None
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if (
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# fx cons seem to not provide this endpoint?
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'idealpro' not in fqsn
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):
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try:
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head_dt = await proxy.get_head_time(fqsn=fqsn)
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except RequestError:
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head_dt = None
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async def get_hist(
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timeframe: float,
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end_dt: Optional[datetime] = None,
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start_dt: Optional[datetime] = None,
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) -> tuple[np.ndarray, str]:
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nonlocal max_timeout, mean, count
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query_start = time.time()
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out, timedout = await get_bars(
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proxy,
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fqsn,
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timeframe,
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end_dt=end_dt,
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)
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latency = time.time() - query_start
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if (
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not timedout
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# and latency <= max_timeout
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):
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count += 1
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mean += latency / count
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print(
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f'HISTORY FRAME QUERY LATENCY: {latency}\n'
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f'mean: {mean}'
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)
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if (
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out is None
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):
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# could be trying to retreive bars over weekend
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log.error(f"Can't grab bars starting at {end_dt}!?!?")
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raise NoData(
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f'{end_dt}',
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# frame_size=2000,
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)
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if (
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end_dt
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and head_dt
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and end_dt <= head_dt
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):
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raise DataUnavailable(f'First timestamp is {head_dt}')
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bars, bars_array, first_dt, last_dt = out
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# volume cleaning since there's -ve entries,
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# wood luv to know what crookery that is..
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vlm = bars_array['volume']
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vlm[vlm < 0] = 0
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return bars_array, first_dt, last_dt
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# TODO: it seems like we can do async queries for ohlc
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# but getting the order right still isn't working and I'm not
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# quite sure why.. needs some tinkering and probably
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# a lookthrough of the ``ib_insync`` machinery, for eg. maybe
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# we have to do the batch queries on the `asyncio` side?
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yield get_hist, {'erlangs': 1, 'rate': 3}
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_pacing: str = (
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'Historical Market Data Service error '
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'message:Historical data request pacing violation'
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)
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async def wait_on_data_reset(
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proxy: MethodProxy,
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reset_type: str = 'data',
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timeout: float = 16,
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task_status: TaskStatus[
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tuple[
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trio.CancelScope,
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trio.Event,
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]
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] = trio.TASK_STATUS_IGNORED,
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) -> bool:
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# TODO: we might have to put a task lock around this
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# method..
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hist_ev = proxy.status_event(
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'HMDS data farm connection is OK:ushmds'
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)
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# XXX: other event messages we might want to try and
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# wait for but i wasn't able to get any of this
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# reliable..
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# reconnect_start = proxy.status_event(
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# 'Market data farm is connecting:usfuture'
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# )
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# live_ev = proxy.status_event(
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# 'Market data farm connection is OK:usfuture'
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# )
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# try to wait on the reset event(s) to arrive, a timeout
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# will trigger a retry up to 6 times (for now).
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done = trio.Event()
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with trio.move_on_after(timeout) as cs:
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task_status.started((cs, done))
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log.warning('Sending DATA RESET request')
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res = await data_reset_hack(reset_type=reset_type)
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if not res:
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log.warning(
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'NO VNC DETECTED!\n'
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'Manually press ctrl-alt-f on your IB java app'
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)
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done.set()
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return False
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# TODO: not sure if waiting on other events
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# is all that useful here or not.
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# - in theory you could wait on one of the ones above first
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# to verify the reset request was sent?
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# - we need the same for real-time quote feeds which can
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# sometimes flake out and stop delivering..
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for name, ev in [
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('history', hist_ev),
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]:
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await ev.wait()
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log.info(f"{name} DATA RESET")
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done.set()
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return True
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if cs.cancel_called:
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log.warning(
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'Data reset task canceled?'
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)
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done.set()
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return False
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_data_resetter_task: trio.Task | None = None
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async def get_bars(
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proxy: MethodProxy,
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fqsn: str,
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timeframe: int,
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# blank to start which tells ib to look up the latest datum
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end_dt: str = '',
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# TODO: make this more dynamic based on measured frame rx latency?
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# how long before we trigger a feed reset (seconds)
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feed_reset_timeout: float = 3,
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# how many days to subtract before giving up on further
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# history queries for instrument, presuming that most don't
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# not trade for a week XD
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max_nodatas: int = 6,
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task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
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) -> (dict, np.ndarray):
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'''
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Retrieve historical data from a ``trio``-side task using
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a ``MethoProxy``.
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'''
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global _data_resetter_task
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nodatas_count: int = 0
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data_cs: trio.CancelScope | None = None
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result: tuple[
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ibis.objects.BarDataList,
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np.ndarray,
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datetime,
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datetime,
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] | None = None
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result_ready = trio.Event()
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async def query():
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nonlocal result, data_cs, end_dt, nodatas_count
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while True:
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try:
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out = await proxy.bars(
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fqsn=fqsn,
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end_dt=end_dt,
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sample_period_s=timeframe,
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# ideally we cancel the request just before we
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# cancel on the ``trio``-side and trigger a data
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# reset hack.. the problem is there's no way (with
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# current impl) to detect a cancel case.
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# timeout=timeout,
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)
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if out is None:
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raise NoData(f'{end_dt}')
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bars, bars_array, dt_duration = out
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if not bars:
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log.warning(
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f'History is blank for {dt_duration} from {end_dt}'
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)
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end_dt -= dt_duration
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continue
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if bars_array is None:
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raise SymbolNotFound(fqsn)
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first_dt = pendulum.from_timestamp(
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bars[0].date.timestamp())
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last_dt = pendulum.from_timestamp(
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bars[-1].date.timestamp())
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time = bars_array['time']
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assert time[-1] == last_dt.timestamp()
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assert time[0] == first_dt.timestamp()
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log.info(
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f'{len(bars)} bars retreived {first_dt} -> {last_dt}'
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)
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if data_cs:
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data_cs.cancel()
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result = (bars, bars_array, first_dt, last_dt)
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# signal data reset loop parent task
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result_ready.set()
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return result
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except RequestError as err:
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msg = err.message
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if 'No market data permissions for' in msg:
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# TODO: signalling for no permissions searches
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raise NoData(
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f'Symbol: {fqsn}',
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)
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elif err.code == 162:
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if (
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'HMDS query returned no data' in msg
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):
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# XXX: this is now done in the storage mgmt
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# layer and we shouldn't implicitly decrement
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# the frame dt index since the upper layer may
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# be doing so concurrently and we don't want to
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# be delivering frames that weren't asked for.
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# try to decrement start point and look further back
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# end_dt = end_dt.subtract(seconds=2000)
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logmsg = "SUBTRACTING DAY from DT index"
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if end_dt is not None:
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end_dt = end_dt.subtract(days=1)
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elif end_dt is None:
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end_dt = pendulum.now().subtract(days=1)
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log.warning(
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f'NO DATA found ending @ {end_dt}\n'
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+ logmsg
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)
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if nodatas_count >= max_nodatas:
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raise DataUnavailable(
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f'Presuming {fqsn} has no further history '
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f'after {max_nodatas} tries..'
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)
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nodatas_count += 1
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continue
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elif 'API historical data query cancelled' in err.message:
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log.warning(
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'Query cancelled by IB (:eyeroll:):\n'
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f'{err.message}'
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)
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continue
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elif (
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'Trading TWS session is connected from a different IP'
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in err.message
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):
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log.warning("ignoring ip address warning")
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continue
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# XXX: more or less same as above timeout case
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elif _pacing in msg:
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log.warning(
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'History throttle rate reached!\n'
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'Resetting farms with `ctrl-alt-f` hack\n'
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)
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# cancel any existing reset task
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if data_cs:
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data_cs.cancel()
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# spawn new data reset task
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data_cs, reset_done = await nurse.start(
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partial(
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wait_on_data_reset,
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proxy,
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timeout=float('inf'),
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reset_type='connection'
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)
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)
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continue
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else:
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raise
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# TODO: make this global across all history task/requests
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# such that simultaneous symbol queries don't try data resettingn
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# too fast..
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unset_resetter: bool = False
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async with trio.open_nursery() as nurse:
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# start history request that we allow
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# to run indefinitely until a result is acquired
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nurse.start_soon(query)
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# start history reset loop which waits up to the timeout
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# for a result before triggering a data feed reset.
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while not result_ready.is_set():
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with trio.move_on_after(feed_reset_timeout):
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await result_ready.wait()
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break
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if _data_resetter_task:
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# don't double invoke the reset hack if another
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# requester task already has it covered.
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continue
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else:
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_data_resetter_task = trio.lowlevel.current_task()
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unset_resetter = True
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# spawn new data reset task
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data_cs, reset_done = await nurse.start(
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partial(
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wait_on_data_reset,
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proxy,
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timeout=float('inf'),
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)
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)
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# sync wait on reset to complete
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await reset_done.wait()
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_data_resetter_task = None if unset_resetter else _data_resetter_task
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return result, data_cs is not None
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asset_type_map = {
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'STK': 'stock',
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'OPT': 'option',
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'FUT': 'future',
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'CONTFUT': 'continuous_future',
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'CASH': 'forex',
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'IND': 'index',
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'CFD': 'cfd',
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'BOND': 'bond',
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'CMDTY': 'commodity',
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'FOP': 'futures_option',
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'FUND': 'mutual_fund',
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'WAR': 'warrant',
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'IOPT': 'warran',
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'BAG': 'bag',
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'CRYPTO': 'crypto', # bc it's diff then fiat?
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# 'NEWS': 'news',
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}
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_quote_streams: dict[str, trio.abc.ReceiveStream] = {}
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async def _setup_quote_stream(
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from_trio: asyncio.Queue,
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to_trio: trio.abc.SendChannel,
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symbol: str,
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opts: tuple[int] = (
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'375', # RT trade volume (excludes utrades)
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'233', # RT trade volume (includes utrades)
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'236', # Shortable shares
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# these all appear to only be updated every 25s thus
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# making them mostly useless and explains why the scanner
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# is always slow XD
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# '293', # Trade count for day
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'294', # Trade rate / minute
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'295', # Vlm rate / minute
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),
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contract: Optional[Contract] = None,
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) -> trio.abc.ReceiveChannel:
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'''
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Stream a ticker using the std L1 api.
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This task is ``asyncio``-side and must be called from
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``tractor.to_asyncio.open_channel_from()``.
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'''
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global _quote_streams
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|
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to_trio.send_nowait(None)
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|
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async with load_aio_clients(
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disconnect_on_exit=False,
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) as accts2clients:
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caccount_name, client = get_preferred_data_client(accts2clients)
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contract = contract or (await client.find_contract(symbol))
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ticker: Ticker = client.ib.reqMktData(contract, ','.join(opts))
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|
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# NOTE: it's batch-wise and slow af but I guess could
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# be good for backchecking? Seems to be every 5s maybe?
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# ticker: Ticker = client.ib.reqTickByTickData(
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# contract, 'Last',
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# )
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|
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# # define a simple queue push routine that streams quote packets
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# # to trio over the ``to_trio`` memory channel.
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# to_trio, from_aio = trio.open_memory_channel(2**8) # type: ignore
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def teardown():
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ticker.updateEvent.disconnect(push)
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log.error(f"Disconnected stream for `{symbol}`")
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client.ib.cancelMktData(contract)
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|
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# decouple broadcast mem chan
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_quote_streams.pop(symbol, None)
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|
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def push(t: Ticker) -> None:
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"""
|
|
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}'
|
|
# )
|
|
pass
|
|
|
|
# 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!
|
|
# or we can at least cache a majority of the values
|
|
# except for the ones we expect to change?..
|
|
def normalize(
|
|
ticker: Ticker,
|
|
calc_price: bool = False
|
|
|
|
) -> dict:
|
|
|
|
# check for special contract types
|
|
con = ticker.contract
|
|
fqsn, calc_price = con2fqsn(con)
|
|
|
|
# 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'] = fqsn
|
|
|
|
# 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']]
|
|
|
|
if atype in {
|
|
'forex',
|
|
'index',
|
|
'commodity',
|
|
}:
|
|
syminfo['no_vlm'] = True
|
|
|
|
# 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 "legacy" 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, syminfo
|
|
|
|
init_msgs, syminfo = 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)
|
|
and type(first_ticker.contract) not in (
|
|
ibis.Commodity,
|
|
ibis.Forex,
|
|
ibis.Crypto,
|
|
)
|
|
):
|
|
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?
|
|
|
|
cs: Optional[trio.CancelScope] = None
|
|
startup: bool = True
|
|
while (
|
|
startup
|
|
or cs.cancel_called
|
|
):
|
|
with trio.CancelScope() as cs:
|
|
async with (
|
|
trio.open_nursery() as nurse,
|
|
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 = []
|
|
|
|
# only on first entry at feed boot up
|
|
if startup:
|
|
startup = False
|
|
task_status.started((init_msgs, first_quote))
|
|
|
|
# start a stream restarter task which monitors the
|
|
# data feed event.
|
|
async def reset_on_feed():
|
|
|
|
# TODO: this seems to be surpressed from the
|
|
# traceback in ``tractor``?
|
|
# assert 0
|
|
|
|
rt_ev = proxy.status_event(
|
|
'Market data farm connection is OK:usfarm'
|
|
)
|
|
await rt_ev.wait()
|
|
cs.cancel() # cancel called should now be set
|
|
|
|
nurse.start_soon(reset_on_feed)
|
|
|
|
async with aclosing(stream):
|
|
if syminfo.get('no_vlm', False):
|
|
|
|
# generally speaking these feeds don't
|
|
# include vlm data.
|
|
atype = syminfo['asset_type']
|
|
log.info(
|
|
f'No-vlm {sym}@{atype}, skipping quote poll'
|
|
)
|
|
|
|
else:
|
|
# 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 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)
|
|
fqsn = quote['fqsn']
|
|
# print(f'sending {fqsn}:\n{quote}')
|
|
await send_chan.send({fqsn: quote})
|
|
|
|
# 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, clients),
|
|
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)
|