567 lines
15 KiB
Python
567 lines
15 KiB
Python
# piker: trading gear for hackers
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# Copyright (C) Guillermo Rodriguez (in stewardship for piker0)
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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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Binance backend
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"""
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from contextlib import asynccontextmanager as acm
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from datetime import datetime
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from typing import (
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Any, Union, Optional,
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AsyncGenerator, Callable,
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)
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import time
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import trio
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from trio_typing import TaskStatus
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import pendulum
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import asks
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from fuzzywuzzy import process as fuzzy
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import numpy as np
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import tractor
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from pydantic.dataclasses import dataclass
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from pydantic import BaseModel
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import wsproto
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from .._cacheables import open_cached_client
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from ._util import resproc, SymbolNotFound
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from ..log import get_logger, get_console_log
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from ..data import ShmArray
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from ..data._web_bs import open_autorecon_ws, NoBsWs
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log = get_logger(__name__)
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_url = 'https://api.binance.com'
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# Broker specific ohlc schema (rest)
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_ohlc_dtype = [
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('index', int),
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('time', int),
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('open', float),
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('high', float),
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('low', float),
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('close', float),
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('volume', float),
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('bar_wap', float), # will be zeroed by sampler if not filled
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# XXX: some additional fields are defined in the docs:
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# https://binance-docs.github.io/apidocs/spot/en/#kline-candlestick-data
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# ('close_time', int),
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# ('quote_vol', float),
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# ('num_trades', int),
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# ('buy_base_vol', float),
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# ('buy_quote_vol', float),
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# ('ignore', float),
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]
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# UI components allow this to be declared such that additional
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# (historical) fields can be exposed.
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ohlc_dtype = np.dtype(_ohlc_dtype)
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_show_wap_in_history = False
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# https://binance-docs.github.io/apidocs/spot/en/#exchange-information
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class Pair(BaseModel):
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symbol: str
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status: str
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baseAsset: str
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baseAssetPrecision: int
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quoteAsset: str
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quotePrecision: int
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quoteAssetPrecision: int
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baseCommissionPrecision: int
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quoteCommissionPrecision: int
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orderTypes: list[str]
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icebergAllowed: bool
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ocoAllowed: bool
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quoteOrderQtyMarketAllowed: bool
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isSpotTradingAllowed: bool
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isMarginTradingAllowed: bool
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filters: list[dict[str, Union[str, int, float]]]
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permissions: list[str]
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@dataclass
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class OHLC:
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"""Description of the flattened OHLC quote format.
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For schema details see:
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https://binance-docs.github.io/apidocs/spot/en/#kline-candlestick-streams
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"""
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time: int
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open: float
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high: float
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low: float
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close: float
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volume: float
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close_time: int
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quote_vol: float
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num_trades: int
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buy_base_vol: float
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buy_quote_vol: float
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ignore: int
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# null the place holder for `bar_wap` until we
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# figure out what to extract for this.
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bar_wap: float = 0.0
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# convert datetime obj timestamp to unixtime in milliseconds
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def binance_timestamp(when):
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return int((when.timestamp() * 1000) + (when.microsecond / 1000))
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class Client:
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def __init__(self) -> None:
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self._sesh = asks.Session(connections=4)
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self._sesh.base_location = _url
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self._pairs: dict[str, Any] = {}
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async def _api(
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self,
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method: str,
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params: dict,
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) -> dict[str, Any]:
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resp = await self._sesh.get(
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path=f'/api/v3/{method}',
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params=params,
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timeout=float('inf')
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)
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return resproc(resp, log)
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async def symbol_info(
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self,
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sym: Optional[str] = None,
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) -> dict[str, Any]:
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'''Get symbol info for the exchange.
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'''
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# TODO: we can load from our self._pairs cache
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# on repeat calls...
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# will retrieve all symbols by default
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params = {}
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if sym is not None:
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sym = sym.upper()
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params = {'symbol': sym}
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resp = await self._api(
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'exchangeInfo',
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params=params,
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)
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entries = resp['symbols']
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if not entries:
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raise SymbolNotFound(f'{sym} not found')
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syms = {item['symbol']: item for item in entries}
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if sym is not None:
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return syms[sym]
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else:
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return syms
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async def cache_symbols(
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self,
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) -> dict:
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if not self._pairs:
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self._pairs = await self.symbol_info()
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return self._pairs
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async def search_symbols(
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self,
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pattern: str,
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limit: int = None,
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) -> dict[str, Any]:
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if self._pairs is not None:
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data = self._pairs
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else:
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data = await self.symbol_info()
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matches = fuzzy.extractBests(
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pattern,
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data,
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score_cutoff=50,
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)
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# repack in dict form
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return {item[0]['symbol']: item[0]
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for item in matches}
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async def bars(
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self,
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symbol: str,
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start_dt: Optional[datetime] = None,
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end_dt: Optional[datetime] = None,
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limit: int = 1000, # <- max allowed per query
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as_np: bool = True,
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) -> dict:
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if end_dt is None:
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end_dt = pendulum.now('UTC')
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if start_dt is None:
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start_dt = end_dt.start_of(
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'minute').subtract(minutes=limit)
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start_time = binance_timestamp(start_dt)
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end_time = binance_timestamp(end_dt)
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# https://binance-docs.github.io/apidocs/spot/en/#kline-candlestick-data
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bars = await self._api(
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'klines',
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params={
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'symbol': symbol.upper(),
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'interval': '1m',
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'startTime': start_time,
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'endTime': end_time,
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'limit': limit
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}
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)
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# TODO: pack this bars scheme into a ``pydantic`` validator type:
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# https://binance-docs.github.io/apidocs/spot/en/#kline-candlestick-data
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# TODO: we should port this to ``pydantic`` to avoid doing
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# manual validation ourselves..
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new_bars = []
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for i, bar in enumerate(bars):
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bar = OHLC(*bar)
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row = []
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for j, (name, ftype) in enumerate(_ohlc_dtype[1:]):
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# TODO: maybe we should go nanoseconds on all
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# history time stamps?
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if name == 'time':
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# convert to epoch seconds: float
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row.append(bar.time / 1000.0)
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else:
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row.append(getattr(bar, name))
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new_bars.append((i,) + tuple(row))
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array = np.array(new_bars, dtype=_ohlc_dtype) if as_np else bars
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return array
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@acm
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async def get_client() -> Client:
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client = Client()
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await client.cache_symbols()
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yield client
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# validation type
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class AggTrade(BaseModel):
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e: str # Event type
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E: int # Event time
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s: str # Symbol
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a: int # Aggregate trade ID
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p: float # Price
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q: float # Quantity
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f: int # First trade ID
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l: int # Last trade ID
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T: int # Trade time
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m: bool # Is the buyer the market maker?
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M: bool # Ignore
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async def stream_messages(ws: NoBsWs) -> AsyncGenerator[NoBsWs, dict]:
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timeouts = 0
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while True:
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with trio.move_on_after(3) as cs:
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msg = await ws.recv_msg()
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if cs.cancelled_caught:
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timeouts += 1
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if timeouts > 2:
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log.error("binance feed seems down and slow af? rebooting...")
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await ws._connect()
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continue
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# for l1 streams binance doesn't add an event type field so
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# identify those messages by matching keys
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# https://binance-docs.github.io/apidocs/spot/en/#individual-symbol-book-ticker-streams
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if msg.get('u'):
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sym = msg['s']
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bid = float(msg['b'])
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bsize = float(msg['B'])
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ask = float(msg['a'])
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asize = float(msg['A'])
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yield 'l1', {
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'symbol': sym,
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'ticks': [
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{'type': 'bid', 'price': bid, 'size': bsize},
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{'type': 'bsize', 'price': bid, 'size': bsize},
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{'type': 'ask', 'price': ask, 'size': asize},
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{'type': 'asize', 'price': ask, 'size': asize}
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]
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}
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elif msg.get('e') == 'aggTrade':
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# validate
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msg = AggTrade(**msg)
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# TODO: type out and require this quote format
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# from all backends!
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yield 'trade', {
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'symbol': msg.s,
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'last': msg.p,
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'brokerd_ts': time.time(),
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'ticks': [{
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'type': 'trade',
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'price': msg.p,
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'size': msg.q,
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'broker_ts': msg.T,
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}],
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}
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def make_sub(pairs: list[str], sub_name: str, uid: int) -> dict[str, str]:
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"""Create a request subscription packet dict.
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https://binance-docs.github.io/apidocs/spot/en/#live-subscribing-unsubscribing-to-streams
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"""
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return {
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'method': 'SUBSCRIBE',
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'params': [
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f'{pair.lower()}@{sub_name}'
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for pair in pairs
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],
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'id': uid
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}
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@acm
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async def open_history_client(
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symbol: str,
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) -> tuple[Callable, int]:
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# TODO implement history getter for the new storage layer.
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async with open_cached_client('binance') as client:
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async def get_ohlc(
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end_dt: Optional[datetime] = None,
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start_dt: Optional[datetime] = None,
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) -> tuple[
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np.ndarray,
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datetime, # start
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datetime, # end
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]:
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array = await client.bars(
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symbol,
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start_dt=start_dt,
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end_dt=end_dt,
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)
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start_dt = pendulum.from_timestamp(array[0]['time'])
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end_dt = pendulum.from_timestamp(array[-1]['time'])
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return array, start_dt, end_dt
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yield get_ohlc, {'erlangs': 3, 'rate': 3}
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async def backfill_bars(
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sym: str,
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shm: ShmArray, # type: ignore # noqa
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task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
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) -> None:
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"""Fill historical bars into shared mem / storage afap.
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"""
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with trio.CancelScope() as cs:
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async with open_cached_client('binance') as client:
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bars = await client.bars(symbol=sym)
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shm.push(bars)
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task_status.started(cs)
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async def stream_quotes(
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send_chan: trio.abc.SendChannel,
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symbols: list[str],
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feed_is_live: trio.Event,
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loglevel: str = None,
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# startup sync
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task_status: TaskStatus[tuple[dict, dict]] = trio.TASK_STATUS_IGNORED,
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) -> None:
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# XXX: required to propagate ``tractor`` loglevel to piker logging
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get_console_log(loglevel or tractor.current_actor().loglevel)
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sym_infos = {}
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uid = 0
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async with (
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open_cached_client('binance') as client,
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send_chan as send_chan,
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):
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# keep client cached for real-time section
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cache = await client.cache_symbols()
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for sym in symbols:
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d = cache[sym.upper()]
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syminfo = Pair(**d) # validation
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si = sym_infos[sym] = syminfo.dict()
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# XXX: after manually inspecting the response format we
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# just directly pick out the info we need
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si['price_tick_size'] = float(syminfo.filters[0]['tickSize'])
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si['lot_tick_size'] = float(syminfo.filters[2]['stepSize'])
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si['asset_type'] = 'crypto'
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symbol = symbols[0]
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init_msgs = {
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# pass back token, and bool, signalling if we're the writer
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# and that history has been written
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symbol: {
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'symbol_info': sym_infos[sym],
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'shm_write_opts': {'sum_tick_vml': False},
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'fqsn': sym,
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},
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}
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@acm
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async def subscribe(ws: wsproto.WSConnection):
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# setup subs
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# trade data (aka L1)
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# https://binance-docs.github.io/apidocs/spot/en/#symbol-order-book-ticker
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l1_sub = make_sub(symbols, 'bookTicker', uid)
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await ws.send_msg(l1_sub)
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# aggregate (each order clear by taker **not** by maker)
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# trades data:
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# https://binance-docs.github.io/apidocs/spot/en/#aggregate-trade-streams
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agg_trades_sub = make_sub(symbols, 'aggTrade', uid)
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await ws.send_msg(agg_trades_sub)
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# ack from ws server
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res = await ws.recv_msg()
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assert res['id'] == uid
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yield
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subs = []
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for sym in symbols:
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subs.append("{sym}@aggTrade")
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subs.append("{sym}@bookTicker")
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# unsub from all pairs on teardown
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await ws.send_msg({
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"method": "UNSUBSCRIBE",
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"params": subs,
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"id": uid,
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})
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# XXX: do we need to ack the unsub?
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# await ws.recv_msg()
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async with open_autorecon_ws(
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'wss://stream.binance.com/ws',
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fixture=subscribe,
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) as ws:
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# pull a first quote and deliver
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msg_gen = stream_messages(ws)
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typ, quote = await msg_gen.__anext__()
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while typ != 'trade':
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# TODO: use ``anext()`` when it lands in 3.10!
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typ, quote = await msg_gen.__anext__()
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task_status.started((init_msgs, quote))
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# signal to caller feed is ready for consumption
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feed_is_live.set()
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# import time
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# last = time.time()
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# start streaming
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async for typ, msg in msg_gen:
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# period = time.time() - last
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# hz = 1/period if period else float('inf')
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# if hz > 60:
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# log.info(f'Binance quotez : {hz}')
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topic = msg['symbol'].lower()
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await send_chan.send({topic: msg})
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# last = time.time()
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@tractor.context
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async def open_symbol_search(
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ctx: tractor.Context,
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) -> Client:
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async with open_cached_client('binance') as client:
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# load all symbols locally for fast search
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cache = await client.cache_symbols()
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await ctx.started()
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async with ctx.open_stream() as stream:
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async for pattern in stream:
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# results = await client.symbol_info(sym=pattern.upper())
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matches = fuzzy.extractBests(
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pattern,
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cache,
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score_cutoff=50,
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)
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# repack in dict form
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await stream.send(
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{item[0]['symbol']: item[0]
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for item in matches}
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)
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