Add signal backfilling via trio task respawn

tina_free_vwap
Tyler Goodlet 2020-12-16 12:30:40 -05:00
parent 47856666b5
commit 7cf3c4a86c
3 changed files with 119 additions and 54 deletions

View File

@ -20,6 +20,7 @@ Financial signal processing for the peeps.
from typing import AsyncIterator, Callable, Tuple
import trio
from trio_typing import TaskStatus
import tractor
import numpy as np
@ -75,6 +76,7 @@ async def increment_signals(
# write new slot to the buffer
dst_shm.push(last)
len(dst_shm.array)
@tractor.stream
@ -99,9 +101,19 @@ async def cascade(
async with data.open_feed(brokername, [symbol]) as feed:
assert src.token == feed.shm.token
async def fsp_compute(
task_status: TaskStatus[None] = trio.TASK_STATUS_IGNORED,
) -> None:
# TODO: load appropriate fsp with input args
async def filter_by_sym(sym, stream):
async def filter_by_sym(
sym: str,
stream,
):
# task cancellation won't kill the channel
async with stream.shield():
async for quotes in stream:
for symbol, quotes in quotes.items():
if symbol == sym:
@ -122,7 +134,9 @@ async def cascade(
# - developing some system on top of the shared mem array that
# is `index` aware such that historical data can be indexed
# relative to the true first datum? Not sure if this is sane
# for derivatives.
# for incremental compuations.
dst._first.value = src._first.value
dst._last.value = src._first.value
# Conduct a single iteration of fsp with historical bars input
# and get historical output
@ -136,6 +150,7 @@ async def cascade(
)
history[fsp_func_name] = history_output
# check for data length mis-allignment and fill missing values
diff = len(src.array) - len(history)
if diff >= 0:
@ -146,13 +161,47 @@ async def cascade(
# compare with source signal and time align
index = dst.push(history)
yield index
await ctx.send_yield(index)
async with trio.open_nursery() as n:
n.start_soon(increment_signals, feed, dst)
# setup a respawn handle
with trio.CancelScope() as cs:
task_status.started(cs)
# rt stream
async for processed in out_stream:
log.debug(f"{fsp_func_name}: {processed}")
index = src.index
dst.array[-1][fsp_func_name] = processed
# stream latest shm array index entry
await ctx.send_yield(index)
last_len = new_len = len(src.array)
async with trio.open_nursery() as n:
cs = await n.start(fsp_compute)
# Increment the underlying shared memory buffer on every "increment"
# msg received from the underlying data feed.
async for msg in await feed.index_stream():
new_len = len(src.array)
if new_len > last_len + 1:
# respawn the signal compute task if the source
# signal has been updated
cs.cancel()
cs = await n.start(fsp_compute)
# TODO: adopt an incremental update engine/approach
# where possible here eventually!
array = dst.array
last = array[-1:].copy()
# write new slot to the buffer
dst.push(last)
last_len = new_len

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@ -151,8 +151,8 @@ def wma(
return np.convolve(signal, weights, 'valid')
# @piker.fsp(
# aggregates=[60, 60*5, 60*60, '4H', '1D'],
# @piker.fsp.signal(
# timeframes=['1s', '5s', '15s', '1m', '5m', '1H'],
# )
async def _rsi(
source: 'QuoteStream[Dict[str, Any]]', # noqa

View File

@ -558,7 +558,9 @@ class ChartPlotWidget(pg.PlotWidget):
# TODO: see how this handles with custom ohlcv bars graphics
# and/or if we can implement something similar for OHLC graphics
clipToView=True,
# clipToView=True,
autoDownsample=True,
downsampleMethod='subsample',
**pdi_kwargs,
)
@ -1221,9 +1223,23 @@ async def update_signals(
# update chart graphics
async for value in stream:
# TODO: provide a read sync mechanism to avoid this polling.
# the underlying issue is that a backfill and subsequent shm
# array first/last index update could result in an empty array
# read here since the stream is never torn down on the
# re-compute steps.
read_tries = 2
while read_tries > 0:
try:
# read last
array = shm.array
value = array[-1][fsp_func_name]
break
except IndexError:
read_tries -= 1
continue
if last_val_sticky:
last_val_sticky.update_from_data(-1, value)