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513646c802
Author | SHA1 | Date |
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Tyler Goodlet | 513646c802 | |
Tyler Goodlet | 4bd42b52c9 |
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@ -1,5 +1,5 @@
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# piker: trading gear for hackers
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# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
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# Copyright (C) Tyler Goodlet (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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@ -15,10 +15,12 @@
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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"""
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Kraken backend.
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kraken buttz.
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Get da crypto bois pampin da btcccccssssss (and or da tezos)
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"""
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import sys
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from contextlib import asynccontextmanager
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from dataclasses import dataclass, asdict, field
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from typing import List, Dict, Any, Tuple, Optional, AsyncIterator
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@ -30,6 +32,8 @@ from trio_websocket._impl import ConnectionClosed, DisconnectionTimeout
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import arrow
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import asks
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import numpy as np
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from numba import njit, float64
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from numba import from_dtype
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import trio
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import tractor
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@ -46,8 +50,9 @@ log = get_logger(__name__)
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# <uri>/<version>/
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_url = 'https://api.kraken.com/0'
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_url: str = 'https://api.kraken.com/0'
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_epoch_s: int = 1499000000
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# Broker specific ohlc schema which includes a vwap field
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_ohlc_dtype = [
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@ -62,13 +67,49 @@ _ohlc_dtype = [
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('bar_wap', float),
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]
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_trade_dtype = [
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# ('index', int),
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('price', float),
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('volume', float),
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('time', int),
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('is_bid', bool),
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('is_limit', bool),
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('exchange', 'U16'),
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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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trade_dtype = np.dtype(_trade_dtype)
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trade_ndtype = from_dtype(trade_dtype)
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_show_wap_in_history = True
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# @njit
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def json2np(
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trades: list,
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out: np.ndarray,
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# _dtype=_trade_dtype,
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) -> np.ndarray:
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for i, trade in enumerate(trades):
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price, volume, t, direction, typ, misc = trade
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time_ns = float64(t) * 1e9
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is_bid = {'s': False, 'b': True}[direction]
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is_trade = True # do we care if it's a market vs. limti?
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out[i] = (
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float64(price),
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float64(volume),
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time_ns,
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is_bid,
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is_trade,
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'kraken',
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)
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return out
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class Client:
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def __init__(self) -> None:
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@ -102,19 +143,57 @@ class Client:
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true_pair_key, data = next(iter(resp['result'].items()))
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return data
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async def trades(
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self,
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symbol: str = 'XBTUSD',
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# UTC 2017-07-02 12:53:20
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since: int = 0, # this is a special value indicating epoch of symbol
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as_np: bool = True,
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) -> dict:
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# UTC 2017-07-02 12:53:20 is oldest seconds value
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# since_s = max(_epoch_s, int(since))
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# pick a timestamp 1H ago
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since_ns = time.time_ns() - 60*60*1e9
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json = await self._public(
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'Trades',
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data={
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'pair': symbol,
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'since': since_ns,
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},
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)
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res = json['result']
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last_ns = res.pop('last')
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trades = next(iter(res.values()))
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out = np.zeros(1000, dtype=trade_ndtype)
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array = json2np(trades, out)
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return array
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async def bars(
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self,
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symbol: str = 'XBTUSD',
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# UTC 2017-07-02 12:53:20
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since: int = None,
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count: int = 720, # <- max allowed per query
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as_np: bool = True,
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) -> dict:
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if since is None:
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since = arrow.utcnow().floor('minute').shift(
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minutes=-count).timestamp
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# UTC 2017-07-02 12:53:20 is oldest seconds value
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since = str(max(1499000000, since))
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"""Retreive OHLC bars.
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Note only a max of 720 candles for each sampling interval
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can be retreived. To acquire longer term history use .`trades()`
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above. See here:
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https://support.kraken.com/hc/en-us/articles/218198197-How-to-retrieve-historical-time-and-sales-trading-history-using-the-REST-API-Trades-endpoint-
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We're mostly just keeping this method for bookkeeping
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but we can probably just remove it eventually.
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"""
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# member 720 is farthest back they'll go
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since = arrow.utcnow().floor('minute').shift(
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minutes=-720).timestamp
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json = await self._public(
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'OHLC',
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data={
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@ -131,12 +210,14 @@ class Client:
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first = bars[0]
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last_nz_vwap = first[-3]
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if last_nz_vwap == 0:
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# use close if vwap is zero
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last_nz_vwap = first[-4]
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# convert all fields to native types
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for i, bar in enumerate(bars):
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# normalize weird zero-ed vwap values..cmon kraken..
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# indicates vwap didn't change since last bar
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vwap = float(bar.pop(-3))
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@ -295,31 +376,34 @@ def make_sub(pairs: List[str], data: Dict[str, Any]) -> Dict[str, str]:
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async def fill_bars(
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first_bars,
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shm,
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client,
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symbol: str,
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count: int = 75
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) -> None:
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async with get_client() as client:
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# async with get_client() as client:
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next_dt = first_bars[0][1]
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i = 0
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while i < count:
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try:
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bars_array = await client.bars(
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symbol=symbol,
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since=arrow.get(next_dt).floor('minute')
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.shift(minutes=-720).timestamp
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)
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shm.push(bars_array, prepend=True)
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i += 1
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next_dt = bars_array[0][1]
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next_dt = first_bars[0][1]
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i = 0
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while i < count:
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await trio.sleep(5)
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# timestamp in seconds?
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since = arrow.get(next_dt).floor(
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'minute').shift(minutes=-(2*720)).timestamp
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except BaseException as e:
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log.exception(e)
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await tractor.breakpoint()
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try:
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bars_array = await client.bars(symbol=symbol, since=since)
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# push to shared mem
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shm.push(bars_array, prepend=True)
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i += 1
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next_dt = bars_array[0][1]
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except BaseException as e:
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log.exception(e)
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await tractor.breakpoint()
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_local_buffer_writers = {}
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@ -372,17 +456,19 @@ async def stream_quotes(
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# we are writer
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readonly=False,
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)
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bars = await client.bars(symbol=symbol)
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trades = await client.trades(symbol=symbol)
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await tractor.breakpoint()
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shm.push(bars)
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shm_token = shm.token
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ln.start_soon(fill_bars, bars, shm, symbol)
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ln.start_soon(fill_bars, bars, shm, client, symbol)
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#
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times = shm.array['time']
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delay_s = times[-1] - times[times != times[-1]][-1]
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subscribe_ohlc_for_increment(shm, delay_s)
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# pass back token, and bool, signalling if we're the writer
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await ctx.send_yield((shm_token, not writer_already_exists))
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@ -391,7 +477,7 @@ async def stream_quotes(
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async with trio_websocket.open_websocket_url(
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'wss://ws.kraken.com',
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) as ws:
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# XXX: setup subs
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# https://docs.kraken.com/websockets/#message-subscribe
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# specific logic for this in kraken's shitty sync client:
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@ -1,5 +1,5 @@
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# piker: trading gear for hackers
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# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
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# Copyright (C) Tyler Goodlet (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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@ -20,7 +20,7 @@ Momentum bby.
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from typing import AsyncIterator, Optional
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import numpy as np
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from numba import jit, float64, optional, int64
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from numba import njit, float64, optional, int64
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from ..data._normalize import iterticks
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# - how to handle non-plottable values
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# - composition of fsps / implicit chaining
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@jit(
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@njit(
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float64[:](
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float64[:],
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optional(float64),
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optional(float64)
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),
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nopython=True,
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nogil=True
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)
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def ema(
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return s
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# @jit(
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# @njit(
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# float64[:](
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# float64[:],
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# int64,
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@ -1,5 +1,5 @@
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# piker: trading gear for hackers
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# Copyright (C) 2018-present Tyler Goodlet (in stewardship of piker0)
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# Copyright (C) Tyler Goodlet (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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@ -21,7 +21,7 @@ from typing import List, Optional, Tuple
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import numpy as np
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import pyqtgraph as pg
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from numba import jit, float64, int64 # , optional
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from numba import njit, float64, int64 # , optional
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from PyQt5 import QtCore, QtGui, QtWidgets
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from PyQt5.QtCore import QLineF, QPointF
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# from numba import types as ntypes
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@ -70,7 +70,7 @@ def lines_from_ohlc(row: np.ndarray, w: float) -> Tuple[QLineF]:
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return [hl, o, c]
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@jit(
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@njit(
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# TODO: for now need to construct this manually for readonly arrays, see
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# https://github.com/numba/numba/issues/4511
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# ntypes.Tuple((float64[:], float64[:], float64[:]))(
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@ -78,7 +78,6 @@ def lines_from_ohlc(row: np.ndarray, w: float) -> Tuple[QLineF]:
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# int64,
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# optional(float64),
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# ),
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nopython=True,
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nogil=True
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)
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def path_arrays_from_ohlc(
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