Add signal backfilling via trio task respawn
Tyler Goodlet
parent
e89d3f9560
commit
c01382294e
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@ -20,6 +20,7 @@ Financial signal processing for the peeps.
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from typing import AsyncIterator, Callable, Tuple
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import trio
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from trio_typing import TaskStatus
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import tractor
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import numpy as np
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@ -75,6 +76,7 @@ async def increment_signals(
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# write new slot to the buffer
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dst_shm.push(last)
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len(dst_shm.array)
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@tractor.stream
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@ -99,60 +101,107 @@ async def cascade(
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async with data.open_feed(brokername, [symbol]) as feed:
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assert src.token == feed.shm.token
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# TODO: load appropriate fsp with input args
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async def filter_by_sym(sym, stream):
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async for quotes in stream:
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for symbol, quotes in quotes.items():
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if symbol == sym:
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yield quotes
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async def fsp_compute(
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task_status: TaskStatus[None] = trio.TASK_STATUS_IGNORED,
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) -> None:
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out_stream = func(
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filter_by_sym(symbol, feed.stream),
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feed.shm,
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)
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# TODO: load appropriate fsp with input args
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# TODO: XXX:
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# THERE'S A BIG BUG HERE WITH THE `index` field since we're
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# prepending a copy of the first value a few times to make
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# sub-curves align with the parent bar chart.
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# This likely needs to be fixed either by,
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# - manually assigning the index and historical data
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# seperately to the shm array (i.e. not using .push())
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# - developing some system on top of the shared mem array that
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# is `index` aware such that historical data can be indexed
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# relative to the true first datum? Not sure if this is sane
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# for derivatives.
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async def filter_by_sym(
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sym: str,
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stream,
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):
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# task cancellation won't kill the channel
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async with stream.shield():
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async for quotes in stream:
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for symbol, quotes in quotes.items():
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if symbol == sym:
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yield quotes
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# Conduct a single iteration of fsp with historical bars input
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# and get historical output
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history_output = await out_stream.__anext__()
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out_stream = func(
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filter_by_sym(symbol, feed.stream),
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feed.shm,
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)
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# build a struct array which includes an 'index' field to push
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# as history
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history = np.array(
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np.arange(len(history_output)),
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dtype=dst.array.dtype
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)
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history[fsp_func_name] = history_output
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# TODO: XXX:
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# THERE'S A BIG BUG HERE WITH THE `index` field since we're
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# prepending a copy of the first value a few times to make
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# sub-curves align with the parent bar chart.
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# This likely needs to be fixed either by,
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# - manually assigning the index and historical data
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# seperately to the shm array (i.e. not using .push())
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# - developing some system on top of the shared mem array that
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# is `index` aware such that historical data can be indexed
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# relative to the true first datum? Not sure if this is sane
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# for incremental compuations.
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dst._first.value = src._first.value
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dst._last.value = src._first.value
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# check for data length mis-allignment and fill missing values
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diff = len(src.array) - len(history)
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if diff >= 0:
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print(f"WTF DIFF SIGNAL to HISTORY {diff}")
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for _ in range(diff):
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dst.push(history[:1])
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# Conduct a single iteration of fsp with historical bars input
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# and get historical output
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history_output = await out_stream.__anext__()
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# compare with source signal and time align
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index = dst.push(history)
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# build a struct array which includes an 'index' field to push
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# as history
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history = np.array(
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np.arange(len(history_output)),
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dtype=dst.array.dtype
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)
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history[fsp_func_name] = history_output
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yield index
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# check for data length mis-allignment and fill missing values
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diff = len(src.array) - len(history)
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if diff >= 0:
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print(f"WTF DIFF SIGNAL to HISTORY {diff}")
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for _ in range(diff):
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dst.push(history[:1])
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# compare with source signal and time align
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index = dst.push(history)
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await ctx.send_yield(index)
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# setup a respawn handle
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with trio.CancelScope() as cs:
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task_status.started(cs)
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# rt stream
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async for processed in out_stream:
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log.debug(f"{fsp_func_name}: {processed}")
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index = src.index
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dst.array[-1][fsp_func_name] = processed
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# stream latest shm array index entry
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await ctx.send_yield(index)
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last_len = new_len = len(src.array)
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async with trio.open_nursery() as n:
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n.start_soon(increment_signals, feed, dst)
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async for processed in out_stream:
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log.debug(f"{fsp_func_name}: {processed}")
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index = src.index
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dst.array[-1][fsp_func_name] = processed
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await ctx.send_yield(index)
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cs = await n.start(fsp_compute)
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# Increment the underlying shared memory buffer on every "increment"
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# msg received from the underlying data feed.
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async for msg in await feed.index_stream():
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new_len = len(src.array)
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if new_len > last_len + 1:
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# respawn the signal compute task if the source
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# signal has been updated
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cs.cancel()
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cs = await n.start(fsp_compute)
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# TODO: adopt an incremental update engine/approach
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# where possible here eventually!
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array = dst.array
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last = array[-1:].copy()
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# write new slot to the buffer
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dst.push(last)
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last_len = new_len
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@ -151,8 +151,8 @@ def wma(
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return np.convolve(signal, weights, 'valid')
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# @piker.fsp(
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# aggregates=[60, 60*5, 60*60, '4H', '1D'],
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# @piker.fsp.signal(
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# timeframes=['1s', '5s', '15s', '1m', '5m', '1H'],
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# )
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async def _rsi(
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source: 'QuoteStream[Dict[str, Any]]', # noqa
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@ -171,8 +171,8 @@ async def _rsi(
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# TODO: the emas here should be seeded with a period SMA as per
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# wilder's original formula..
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rsi_h, last_up_ema_close, last_down_ema_close = rsi(sig, period, seed, seed)
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up_ema_last = last_up_ema_close
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down_ema_last = last_down_ema_close
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up_ema_last = last_up_ema_close
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down_ema_last = last_down_ema_close
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# deliver history
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yield rsi_h
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@ -558,7 +558,9 @@ class ChartPlotWidget(pg.PlotWidget):
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# TODO: see how this handles with custom ohlcv bars graphics
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# and/or if we can implement something similar for OHLC graphics
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clipToView=True,
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# clipToView=True,
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autoDownsample=True,
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downsampleMethod='subsample',
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**pdi_kwargs,
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)
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@ -1221,9 +1223,23 @@ async def update_signals(
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# update chart graphics
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async for value in stream:
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# read last
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array = shm.array
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value = array[-1][fsp_func_name]
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# TODO: provide a read sync mechanism to avoid this polling.
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# the underlying issue is that a backfill and subsequent shm
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# array first/last index update could result in an empty array
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# read here since the stream is never torn down on the
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# re-compute steps.
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read_tries = 2
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while read_tries > 0:
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try:
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# read last
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array = shm.array
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value = array[-1][fsp_func_name]
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break
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except IndexError:
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read_tries -= 1
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continue
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if last_val_sticky:
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last_val_sticky.update_from_data(-1, value)
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