Merge pull request #304 from pikers/offline_history_loading
Offline history loadingno_orderid_in_error
commit
67cec4bc54
piker
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@ -37,7 +37,6 @@ import asyncio
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from pprint import pformat
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import inspect
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import logging
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import platform
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from random import randint
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import time
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@ -1583,7 +1582,7 @@ async def backfill_bars(
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# on that until we have the `marketstore` daemon in place in which
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# case the shm size will be driven by user config and available sys
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# memory.
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count: int = 100,
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count: int = 16,
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task_status: TaskStatus[trio.CancelScope] = trio.TASK_STATUS_IGNORED,
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@ -1603,11 +1602,6 @@ async def backfill_bars(
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# async with open_history_client(fqsn) as proxy:
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async with open_client_proxy() as proxy:
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if platform.system() == 'Windows':
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log.warning(
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'Decreasing history query count to 4 since, windows...')
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count = 4
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out, fails = await get_bars(proxy, fqsn)
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if out is None:
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@ -76,7 +76,6 @@ async def filter_quotes_by_sym(
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async def fsp_compute(
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ctx: tractor.Context,
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symbol: Symbol,
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feed: Feed,
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quote_stream: trio.abc.ReceiveChannel,
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@ -86,7 +85,7 @@ async def fsp_compute(
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func: Callable,
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attach_stream: bool = False,
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# attach_stream: bool = False,
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task_status: TaskStatus[None] = trio.TASK_STATUS_IGNORED,
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) -> None:
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@ -127,8 +126,8 @@ async def fsp_compute(
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# each respective field.
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fields = getattr(dst.array.dtype, 'fields', None).copy()
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fields.pop('index')
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# TODO: nptyping here!
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history: Optional[np.ndarray] = None
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history: Optional[np.ndarray] = None # TODO: nptyping here!
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if fields and len(fields) > 1 and fields:
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if not isinstance(history_output, dict):
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raise ValueError(
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@ -193,40 +192,47 @@ async def fsp_compute(
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profiler(f'{func_name} pushed history')
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profiler.finish()
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# TODO: UGH, what is the right way to do something like this?
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if not ctx._started_called:
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await ctx.started(index)
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# setup a respawn handle
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with trio.CancelScope() as cs:
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# TODO: might be better to just make a "restart" method where
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# the target task is spawned implicitly and then the event is
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# set via some higher level api? At that poing we might as well
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# be writing a one-cancels-one nursery though right?
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tracker = TaskTracker(trio.Event(), cs)
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task_status.started((tracker, index))
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profiler(f'{func_name} yield last index')
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# import time
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# last = time.time()
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try:
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# rt stream
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async with ctx.open_stream() as stream:
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async for processed in out_stream:
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log.debug(f"{func_name}: {processed}")
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key, output = processed
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index = src.index
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dst.array[-1][key] = output
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async for processed in out_stream:
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# NOTE: for now we aren't streaming this to the consumer
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# stream latest array index entry which basically just acts
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# as trigger msg to tell the consumer to read from shm
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if attach_stream:
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await stream.send(index)
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log.debug(f"{func_name}: {processed}")
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key, output = processed
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index = src.index
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dst.array[-1][key] = output
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# period = time.time() - last
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# hz = 1/period if period else float('nan')
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# if hz > 60:
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# log.info(f'FSP quote too fast: {hz}')
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# last = time.time()
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# NOTE: for now we aren't streaming this to the consumer
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# stream latest array index entry which basically just acts
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# as trigger msg to tell the consumer to read from shm
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# TODO: further this should likely be implemented much
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# like our `Feed` api where there is one background
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# "service" task which computes output and then sends to
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# N-consumers who subscribe for the real-time output,
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# which we'll likely want to implement using local-mem
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# chans for the fan out?
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# if attach_stream:
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# await client_stream.send(index)
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# period = time.time() - last
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# hz = 1/period if period else float('nan')
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# if hz > 60:
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# log.info(f'FSP quote too fast: {hz}')
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# last = time.time()
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finally:
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tracker.complete.set()
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@ -314,7 +320,6 @@ async def cascade(
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fsp_target = partial(
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fsp_compute,
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ctx=ctx,
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symbol=symbol,
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feed=feed,
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quote_stream=quote_stream,
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@ -323,7 +328,7 @@ async def cascade(
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src=src,
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dst=dst,
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# func_name=func_name,
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# target
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func=func
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)
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@ -335,90 +340,113 @@ async def cascade(
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profiler(f'{func_name}: fsp up')
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async def resync(tracker: TaskTracker) -> tuple[TaskTracker, int]:
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# TODO: adopt an incremental update engine/approach
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# where possible here eventually!
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log.warning(f're-syncing fsp {func_name} to source')
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tracker.cs.cancel()
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await tracker.complete.wait()
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return await n.start(fsp_target)
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# sync client
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await ctx.started(index)
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def is_synced(
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src: ShmArray,
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dst: ShmArray
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) -> tuple[bool, int, int]:
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'''Predicate to dertmine if a destination FSP
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output array is aligned to its source array.
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# XXX: rt stream with client which we MUST
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# open here (and keep it open) in order to make
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# incremental "updates" as history prepends take
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# place.
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async with ctx.open_stream() as client_stream:
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'''
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step_diff = src.index - dst.index
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len_diff = abs(len(src.array) - len(dst.array))
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return not (
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# the source is likely backfilling and we must
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# sync history calculations
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len_diff > 2 or
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# TODO: these likely should all become
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# methods of this ``TaskLifetime`` or wtv
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# abstraction..
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async def resync(
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tracker: TaskTracker,
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# we aren't step synced to the source and may be
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# leading/lagging by a step
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step_diff > 1 or
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step_diff < 0
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), step_diff, len_diff
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) -> tuple[TaskTracker, int]:
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# TODO: adopt an incremental update engine/approach
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# where possible here eventually!
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log.warning(f're-syncing fsp {func_name} to source')
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tracker.cs.cancel()
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await tracker.complete.wait()
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tracker, index = await n.start(fsp_target)
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async def poll_and_sync_to_step(
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# always trigger UI refresh after history update,
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# see ``piker.ui._fsp.FspAdmin.open_chain()`` and
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# ``piker.ui._display.trigger_update()``.
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await client_stream.send('update')
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return tracker, index
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tracker: TaskTracker,
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src: ShmArray,
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dst: ShmArray,
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def is_synced(
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src: ShmArray,
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dst: ShmArray
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) -> tuple[bool, int, int]:
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'''Predicate to dertmine if a destination FSP
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output array is aligned to its source array.
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) -> tuple[TaskTracker, int]:
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'''
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step_diff = src.index - dst.index
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len_diff = abs(len(src.array) - len(dst.array))
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return not (
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# the source is likely backfilling and we must
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# sync history calculations
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len_diff > 2 or
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# we aren't step synced to the source and may be
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# leading/lagging by a step
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step_diff > 1 or
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step_diff < 0
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), step_diff, len_diff
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async def poll_and_sync_to_step(
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tracker: TaskTracker,
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src: ShmArray,
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dst: ShmArray,
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) -> tuple[TaskTracker, int]:
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synced, step_diff, _ = is_synced(src, dst)
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while not synced:
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tracker, index = await resync(tracker)
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synced, step_diff, _ = is_synced(src, dst)
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while not synced:
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tracker, index = await resync(tracker)
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synced, step_diff, _ = is_synced(src, dst)
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return tracker, step_diff
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return tracker, step_diff
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s, step, ld = is_synced(src, dst)
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s, step, ld = is_synced(src, dst)
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# detect sample period step for subscription to increment
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# signal
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times = src.array['time']
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delay_s = times[-1] - times[times != times[-1]][-1]
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# detect sample period step for subscription to increment
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# signal
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times = src.array['time']
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delay_s = times[-1] - times[times != times[-1]][-1]
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# Increment the underlying shared memory buffer on every
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# "increment" msg received from the underlying data feed.
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async with feed.index_stream(int(delay_s)) as istream:
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# Increment the underlying shared memory buffer on every
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# "increment" msg received from the underlying data feed.
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async with feed.index_stream(
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int(delay_s)
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) as istream:
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profiler(f'{func_name}: sample stream up')
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profiler.finish()
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profiler(f'{func_name}: sample stream up')
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profiler.finish()
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async for _ in istream:
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async for _ in istream:
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# respawn the compute task if the source
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# array has been updated such that we compute
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# new history from the (prepended) source.
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synced, step_diff, _ = is_synced(src, dst)
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if not synced:
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tracker, step_diff = await poll_and_sync_to_step(
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tracker,
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src,
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dst,
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)
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# respawn the compute task if the source
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# array has been updated such that we compute
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# new history from the (prepended) source.
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synced, step_diff, _ = is_synced(src, dst)
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if not synced:
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tracker, step_diff = await poll_and_sync_to_step(
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tracker,
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src,
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dst,
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)
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# skip adding a last bar since we should already
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# be step alinged
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if step_diff == 0:
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continue
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# skip adding a last bar since we should already
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# be step alinged
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if step_diff == 0:
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continue
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# read out last shm row, copy and write new row
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array = dst.array
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# read out last shm row, copy and write new row
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array = dst.array
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# some metrics like vlm should be reset
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# to zero every step.
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if zero_on_step:
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last = zeroed
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else:
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last = array[-1:].copy()
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# some metrics like vlm should be reset
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# to zero every step.
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if zero_on_step:
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last = zeroed
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else:
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last = array[-1:].copy()
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dst.push(last)
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dst.push(last)
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@ -19,7 +19,7 @@ High level chart-widget apis.
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'''
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from __future__ import annotations
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from typing import Optional
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from typing import Optional, TYPE_CHECKING
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from PyQt5 import QtCore, QtWidgets
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from PyQt5.QtCore import Qt
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@ -63,6 +63,8 @@ from ._interaction import ChartView
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from ._forms import FieldsForm
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from ._overlay import PlotItemOverlay
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if TYPE_CHECKING:
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from ._display import DisplayState
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log = get_logger(__name__)
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@ -230,6 +232,7 @@ class GodWidget(QWidget):
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# chart is already in memory so just focus it
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linkedsplits.show()
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linkedsplits.focus()
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linkedsplits.graphics_cycle()
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await trio.sleep(0)
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# resume feeds *after* rendering chart view asap
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@ -346,8 +349,19 @@ class LinkedSplits(QWidget):
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self.layout.setContentsMargins(0, 0, 0, 0)
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self.layout.addWidget(self.splitter)
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# chart-local graphics state that can be passed to
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# a ``graphic_update_cycle()`` call by any task wishing to
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# update the UI for a given "chart instance".
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self.display_state: Optional[DisplayState] = None
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self._symbol: Symbol = None
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def graphics_cycle(self, **kwargs) -> None:
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from . import _display
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ds = self.display_state
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if ds:
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return _display.graphics_update_cycle(ds, **kwargs)
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@property
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def symbol(self) -> Symbol:
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return self._symbol
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@ -21,9 +21,10 @@ this module ties together quote and computational (fsp) streams with
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graphics update methods via our custom ``pyqtgraph`` charting api.
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'''
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from dataclasses import dataclass
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from functools import partial
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import time
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from typing import Optional
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from typing import Optional, Any, Callable
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import numpy as np
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import tractor
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@ -31,6 +32,7 @@ import trio
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from .. import brokers
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from ..data.feed import open_feed
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from ._axes import YAxisLabel
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from ._chart import (
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ChartPlotWidget,
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LinkedSplits,
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@ -109,6 +111,33 @@ def chart_maxmin(
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return last_bars_range, mx, max(mn, 0), mx_vlm_in_view
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@dataclass
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class DisplayState:
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'''
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Chart-local real-time graphics state container.
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'''
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quotes: dict[str, Any]
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maxmin: Callable
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ohlcv: ShmArray
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# high level chart handles
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linked: LinkedSplits
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chart: ChartPlotWidget
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vlm_chart: ChartPlotWidget
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# axis labels
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l1: L1Labels
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last_price_sticky: YAxisLabel
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vlm_sticky: YAxisLabel
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# misc state tracking
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vars: dict[str, Any]
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wap_in_history: bool = False
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async def graphics_update_loop(
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linked: LinkedSplits,
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|
@ -147,7 +176,6 @@ async def graphics_update_loop(
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if vlm_chart:
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vlm_sticky = vlm_chart._ysticks['volume']
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vlm_view = vlm_chart.view
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maxmin = partial(chart_maxmin, chart, vlm_chart)
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chart.default_view()
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|
@ -183,7 +211,7 @@ async def graphics_update_loop(
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tick_margin = 3 * tick_size
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chart.show()
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view = chart.view
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# view = chart.view
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last_quote = time.time()
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i_last = ohlcv.index
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|
@ -210,7 +238,29 @@ async def graphics_update_loop(
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# async for quotes in iter_drain_quotes():
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ds = linked.display_state = DisplayState(**{
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'quotes': {},
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'linked': linked,
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'maxmin': maxmin,
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'ohlcv': ohlcv,
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'chart': chart,
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'last_price_sticky': last_price_sticky,
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'vlm_chart': vlm_chart,
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'vlm_sticky': vlm_sticky,
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'l1': l1,
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'vars': {
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'tick_margin': tick_margin,
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'i_last': i_last,
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'last_mx_vlm': last_mx_vlm,
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'last_mx': last_mx,
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'last_mn': last_mn,
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}
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})
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# main loop
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async for quotes in stream:
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ds.quotes = quotes
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quote_period = time.time() - last_quote
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quote_rate = round(
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1/quote_period, 1) if quote_period > 0 else float('inf')
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|
@ -231,222 +281,263 @@ async def graphics_update_loop(
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chart.pause_all_feeds()
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continue
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for sym, quote in quotes.items():
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# sync call to update all graphics/UX components.
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graphics_update_cycle(ds)
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|
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def graphics_update_cycle(
|
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ds: DisplayState,
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wap_in_history: bool = False,
|
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trigger_all: bool = False, # flag used by prepend history updates
|
||||
|
||||
) -> None:
|
||||
|
||||
# TODO: eventually optimize this whole graphics stack with ``numba``
|
||||
# hopefully XD
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||||
|
||||
# unpack multi-referenced components
|
||||
chart = ds.chart
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vlm_chart = ds.vlm_chart
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l1 = ds.l1
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ohlcv = ds.ohlcv
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array = ohlcv.array
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vars = ds.vars
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tick_margin = vars['tick_margin']
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||||
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||||
for sym, quote in ds.quotes.items():
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|
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# NOTE: vlm may be written by the ``brokerd`` backend
|
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# event though a tick sample is not emitted.
|
||||
# TODO: show dark trades differently
|
||||
# https://github.com/pikers/piker/issues/116
|
||||
|
||||
# NOTE: this used to be implemented in a dedicated
|
||||
# "increment tas": ``check_for_new_bars()`` but it doesn't
|
||||
# make sense to do a whole task switch when we can just do
|
||||
# this simple index-diff and all the fsp sub-curve graphics
|
||||
# are diffed on each draw cycle anyway; so updates to the
|
||||
# "curve" length is already automatic.
|
||||
|
||||
# increment the view position by the sample offset.
|
||||
i_step = ohlcv.index
|
||||
i_diff = i_step - vars['i_last']
|
||||
if i_diff > 0:
|
||||
chart.increment_view(
|
||||
steps=i_diff,
|
||||
)
|
||||
vars['i_last'] = i_step
|
||||
|
||||
(
|
||||
brange,
|
||||
mx_in_view,
|
||||
mn_in_view,
|
||||
mx_vlm_in_view,
|
||||
) = ds.maxmin()
|
||||
|
||||
l, lbar, rbar, r = brange
|
||||
mx = mx_in_view + tick_margin
|
||||
mn = mn_in_view - tick_margin
|
||||
liv = r > i_step # the last datum is in view
|
||||
|
||||
# don't real-time "shift" the curve to the
|
||||
# left under the following conditions:
|
||||
if (
|
||||
(
|
||||
brange,
|
||||
mx_in_view,
|
||||
mn_in_view,
|
||||
mx_vlm_in_view,
|
||||
) = maxmin()
|
||||
l, lbar, rbar, r = brange
|
||||
mx = mx_in_view + tick_margin
|
||||
mn = mn_in_view - tick_margin
|
||||
i_diff > 0 # no new sample step
|
||||
and liv
|
||||
)
|
||||
or trigger_all
|
||||
):
|
||||
# TODO: we should track and compute whether the last
|
||||
# pixel in a curve should show new data based on uppx
|
||||
# and then iff update curves and shift?
|
||||
chart.increment_view(steps=i_diff)
|
||||
|
||||
# NOTE: vlm may be written by the ``brokerd`` backend
|
||||
# event though a tick sample is not emitted.
|
||||
# TODO: show dark trades differently
|
||||
# https://github.com/pikers/piker/issues/116
|
||||
array = ohlcv.array
|
||||
if vlm_chart:
|
||||
vlm_chart.update_curve_from_array('volume', array)
|
||||
ds.vlm_sticky.update_from_data(*array[-1][['index', 'volume']])
|
||||
|
||||
# NOTE: this used to be implemented in a dedicated
|
||||
# "increment tas": ``check_for_new_bars()`` but it doesn't
|
||||
# make sense to do a whole task switch when we can just do
|
||||
# this simple index-diff and all the fsp sub-curve graphics
|
||||
# are diffed on each draw cycle anyway; so updates to the
|
||||
# "curve" length is already automatic.
|
||||
|
||||
# increment the view position by the sample offset.
|
||||
i_step = ohlcv.index
|
||||
i_diff = i_step - i_last
|
||||
if i_diff > 0:
|
||||
chart.increment_view(
|
||||
steps=i_diff,
|
||||
)
|
||||
i_last = i_step
|
||||
|
||||
if vlm_chart:
|
||||
vlm_chart.update_curve_from_array('volume', array)
|
||||
vlm_sticky.update_from_data(*array[-1][['index', 'volume']])
|
||||
|
||||
if (
|
||||
mx_vlm_in_view != last_mx_vlm or
|
||||
mx_vlm_in_view > last_mx_vlm
|
||||
):
|
||||
# print(f'mx vlm: {last_mx_vlm} -> {mx_vlm_in_view}')
|
||||
vlm_view._set_yrange(
|
||||
yrange=(0, mx_vlm_in_view * 1.375)
|
||||
)
|
||||
last_mx_vlm = mx_vlm_in_view
|
||||
|
||||
for curve_name, flow in vlm_chart._flows.items():
|
||||
update_fsp_chart(
|
||||
vlm_chart,
|
||||
flow.shm,
|
||||
curve_name,
|
||||
array_key=curve_name,
|
||||
)
|
||||
# is this even doing anything?
|
||||
flow.plot.vb._set_yrange(
|
||||
autoscale_linked_plots=False,
|
||||
name=curve_name,
|
||||
)
|
||||
|
||||
ticks_frame = quote.get('ticks', ())
|
||||
|
||||
frames_by_type: dict[str, dict] = {}
|
||||
lasts = {}
|
||||
|
||||
# build tick-type "frames" of tick sequences since
|
||||
# likely the tick arrival rate is higher then our
|
||||
# (throttled) quote stream rate.
|
||||
for tick in ticks_frame:
|
||||
price = tick.get('price')
|
||||
ticktype = tick.get('type')
|
||||
|
||||
if ticktype == 'n/a' or price == -1:
|
||||
# okkk..
|
||||
continue
|
||||
|
||||
# keys are entered in olded-event-inserted-first order
|
||||
# since we iterate ``ticks_frame`` in standard order
|
||||
# above. in other words the order of the keys is the order
|
||||
# of tick events by type from the provider feed.
|
||||
frames_by_type.setdefault(ticktype, []).append(tick)
|
||||
|
||||
# overwrites so the last tick per type is the entry
|
||||
lasts[ticktype] = tick
|
||||
|
||||
# from pprint import pformat
|
||||
# frame_counts = {
|
||||
# typ: len(frame) for typ, frame in frames_by_type.items()
|
||||
# }
|
||||
# print(f'{pformat(frame_counts)}')
|
||||
# print(f'framed: {pformat(frames_by_type)}')
|
||||
# print(f'lasts: {pformat(lasts)}')
|
||||
|
||||
# TODO: eventually we want to separate out the utrade (aka
|
||||
# dark vlm prices) here and show them as an additional
|
||||
# graphic.
|
||||
clear_types = _tick_groups['clears']
|
||||
|
||||
# XXX: if we wanted to iterate in "latest" (i.e. most
|
||||
# current) tick first order as an optimization where we only
|
||||
# update from the last tick from each type class.
|
||||
# last_clear_updated: bool = False
|
||||
# for typ, tick in reversed(lasts.items()):
|
||||
|
||||
# iterate in FIFO order per frame
|
||||
for typ, tick in lasts.items():
|
||||
|
||||
price = tick.get('price')
|
||||
size = tick.get('size')
|
||||
|
||||
# compute max and min prices (including bid/ask) from
|
||||
# tick frames to determine the y-range for chart
|
||||
# auto-scaling.
|
||||
# TODO: we need a streaming minmax algo here, see def above.
|
||||
mx = max(price + tick_margin, mx)
|
||||
mn = min(price - tick_margin, mn)
|
||||
|
||||
if typ in clear_types:
|
||||
|
||||
# XXX: if we only wanted to update graphics from the
|
||||
# "current"/"latest received" clearing price tick
|
||||
# once (see alt iteration order above).
|
||||
# if last_clear_updated:
|
||||
# continue
|
||||
|
||||
# last_clear_updated = True
|
||||
# we only want to update grahpics from the *last*
|
||||
# tick event that falls under the "clearing price"
|
||||
# set.
|
||||
|
||||
# update price sticky(s)
|
||||
end = array[-1]
|
||||
last_price_sticky.update_from_data(
|
||||
*end[['index', 'close']]
|
||||
)
|
||||
|
||||
# update ohlc sampled price bars
|
||||
chart.update_ohlc_from_array(
|
||||
chart.name,
|
||||
array,
|
||||
)
|
||||
|
||||
if wap_in_history:
|
||||
# update vwap overlay line
|
||||
chart.update_curve_from_array('bar_wap', ohlcv.array)
|
||||
|
||||
# L1 book label-line updates
|
||||
# XXX: is this correct for ib?
|
||||
# if ticktype in ('trade', 'last'):
|
||||
# if ticktype in ('last',): # 'size'):
|
||||
if typ in ('last',): # 'size'):
|
||||
|
||||
label = {
|
||||
l1.ask_label.fields['level']: l1.ask_label,
|
||||
l1.bid_label.fields['level']: l1.bid_label,
|
||||
}.get(price)
|
||||
|
||||
if label is not None:
|
||||
label.update_fields({'level': price, 'size': size})
|
||||
|
||||
# TODO: on trades should we be knocking down
|
||||
# the relevant L1 queue?
|
||||
# label.size -= size
|
||||
|
||||
# elif ticktype in ('ask', 'asize'):
|
||||
elif typ in _tick_groups['asks']:
|
||||
l1.ask_label.update_fields({'level': price, 'size': size})
|
||||
|
||||
# elif ticktype in ('bid', 'bsize'):
|
||||
elif typ in _tick_groups['bids']:
|
||||
l1.bid_label.update_fields({'level': price, 'size': size})
|
||||
|
||||
# check for y-range re-size
|
||||
if (
|
||||
(mx > last_mx) or (mn < last_mn)
|
||||
and not chart._static_yrange == 'axis'
|
||||
mx_vlm_in_view > vars['last_mx_vlm']
|
||||
or trigger_all
|
||||
):
|
||||
# print(f'new y range: {(mn, mx)}')
|
||||
view._set_yrange(
|
||||
yrange=(mn, mx),
|
||||
# TODO: we should probably scale
|
||||
# the view margin based on the size
|
||||
# of the true range? This way you can
|
||||
# slap in orders outside the current
|
||||
# L1 (only) book range.
|
||||
# range_margin=0.1,
|
||||
# print(f'mx vlm: {last_mx_vlm} -> {mx_vlm_in_view}')
|
||||
vlm_chart.view._set_yrange(
|
||||
yrange=(0, mx_vlm_in_view * 1.375)
|
||||
)
|
||||
vars['last_mx_vlm'] = mx_vlm_in_view
|
||||
|
||||
last_mx, last_mn = mx, mn
|
||||
|
||||
# run synchronous update on all derived fsp subplots
|
||||
for name, subchart in linked.subplots.items():
|
||||
for curve_name, flow in vlm_chart._flows.items():
|
||||
update_fsp_chart(
|
||||
subchart,
|
||||
subchart._shm,
|
||||
|
||||
# XXX: do we really needs seperate names here?
|
||||
name,
|
||||
array_key=name,
|
||||
)
|
||||
subchart.cv._set_yrange()
|
||||
|
||||
# TODO: all overlays on all subplots..
|
||||
|
||||
# run synchronous update on all derived overlays
|
||||
for curve_name, flow in chart._flows.items():
|
||||
update_fsp_chart(
|
||||
chart,
|
||||
vlm_chart,
|
||||
flow.shm,
|
||||
curve_name,
|
||||
array_key=curve_name,
|
||||
)
|
||||
# chart.view._set_yrange()
|
||||
# is this even doing anything?
|
||||
flow.plot.vb._set_yrange(
|
||||
autoscale_linked_plots=False,
|
||||
name=curve_name,
|
||||
)
|
||||
|
||||
# loop end
|
||||
ticks_frame = quote.get('ticks', ())
|
||||
|
||||
frames_by_type: dict[str, dict] = {}
|
||||
lasts = {}
|
||||
|
||||
# build tick-type "frames" of tick sequences since
|
||||
# likely the tick arrival rate is higher then our
|
||||
# (throttled) quote stream rate.
|
||||
for tick in ticks_frame:
|
||||
price = tick.get('price')
|
||||
ticktype = tick.get('type')
|
||||
|
||||
if ticktype == 'n/a' or price == -1:
|
||||
# okkk..
|
||||
continue
|
||||
|
||||
# keys are entered in olded-event-inserted-first order
|
||||
# since we iterate ``ticks_frame`` in standard order
|
||||
# above. in other words the order of the keys is the order
|
||||
# of tick events by type from the provider feed.
|
||||
frames_by_type.setdefault(ticktype, []).append(tick)
|
||||
|
||||
# overwrites so the last tick per type is the entry
|
||||
lasts[ticktype] = tick
|
||||
|
||||
# from pprint import pformat
|
||||
# frame_counts = {
|
||||
# typ: len(frame) for typ, frame in frames_by_type.items()
|
||||
# }
|
||||
# print(f'{pformat(frame_counts)}')
|
||||
# print(f'framed: {pformat(frames_by_type)}')
|
||||
# print(f'lasts: {pformat(lasts)}')
|
||||
|
||||
# TODO: eventually we want to separate out the utrade (aka
|
||||
# dark vlm prices) here and show them as an additional
|
||||
# graphic.
|
||||
clear_types = _tick_groups['clears']
|
||||
|
||||
# XXX: if we wanted to iterate in "latest" (i.e. most
|
||||
# current) tick first order as an optimization where we only
|
||||
# update from the last tick from each type class.
|
||||
# last_clear_updated: bool = False
|
||||
# for typ, tick in reversed(lasts.items()):
|
||||
|
||||
# update ohlc sampled price bars
|
||||
chart.update_ohlc_from_array(
|
||||
chart.name,
|
||||
array,
|
||||
)
|
||||
|
||||
# iterate in FIFO order per frame
|
||||
for typ, tick in lasts.items():
|
||||
|
||||
price = tick.get('price')
|
||||
size = tick.get('size')
|
||||
|
||||
# compute max and min prices (including bid/ask) from
|
||||
# tick frames to determine the y-range for chart
|
||||
# auto-scaling.
|
||||
# TODO: we need a streaming minmax algo here, see def above.
|
||||
mx = max(price + tick_margin, mx)
|
||||
mn = min(price - tick_margin, mn)
|
||||
|
||||
if typ in clear_types:
|
||||
|
||||
# XXX: if we only wanted to update graphics from the
|
||||
# "current"/"latest received" clearing price tick
|
||||
# once (see alt iteration order above).
|
||||
# if last_clear_updated:
|
||||
# continue
|
||||
|
||||
# last_clear_updated = True
|
||||
# we only want to update grahpics from the *last*
|
||||
# tick event that falls under the "clearing price"
|
||||
# set.
|
||||
|
||||
# update price sticky(s)
|
||||
end = array[-1]
|
||||
ds.last_price_sticky.update_from_data(
|
||||
*end[['index', 'close']]
|
||||
)
|
||||
|
||||
if wap_in_history:
|
||||
# update vwap overlay line
|
||||
chart.update_curve_from_array(
|
||||
'bar_wap',
|
||||
array,
|
||||
)
|
||||
|
||||
# L1 book label-line updates
|
||||
# XXX: is this correct for ib?
|
||||
# if ticktype in ('trade', 'last'):
|
||||
# if ticktype in ('last',): # 'size'):
|
||||
if typ in ('last',): # 'size'):
|
||||
|
||||
label = {
|
||||
l1.ask_label.fields['level']: l1.ask_label,
|
||||
l1.bid_label.fields['level']: l1.bid_label,
|
||||
}.get(price)
|
||||
|
||||
if label is not None:
|
||||
label.update_fields(
|
||||
{'level': price, 'size': size}
|
||||
)
|
||||
|
||||
# TODO: on trades should we be knocking down
|
||||
# the relevant L1 queue?
|
||||
# label.size -= size
|
||||
|
||||
# elif ticktype in ('ask', 'asize'):
|
||||
elif typ in _tick_groups['asks']:
|
||||
l1.ask_label.update_fields({'level': price, 'size': size})
|
||||
|
||||
# elif ticktype in ('bid', 'bsize'):
|
||||
elif typ in _tick_groups['bids']:
|
||||
l1.bid_label.update_fields({'level': price, 'size': size})
|
||||
|
||||
# check for y-range re-size
|
||||
if (
|
||||
(mx > vars['last_mx']) or (mn < vars['last_mn'])
|
||||
and not chart._static_yrange == 'axis'
|
||||
):
|
||||
# print(f'new y range: {(mn, mx)}')
|
||||
chart.view._set_yrange(
|
||||
yrange=(mn, mx),
|
||||
# TODO: we should probably scale
|
||||
# the view margin based on the size
|
||||
# of the true range? This way you can
|
||||
# slap in orders outside the current
|
||||
# L1 (only) book range.
|
||||
# range_margin=0.1,
|
||||
)
|
||||
|
||||
vars['last_mx'], vars['last_mn'] = mx, mn
|
||||
|
||||
# run synchronous update on all derived fsp subplots
|
||||
for name, subchart in ds.linked.subplots.items():
|
||||
update_fsp_chart(
|
||||
subchart,
|
||||
subchart._shm,
|
||||
|
||||
# XXX: do we really needs seperate names here?
|
||||
name,
|
||||
array_key=name,
|
||||
)
|
||||
subchart.cv._set_yrange()
|
||||
|
||||
# TODO: all overlays on all subplots..
|
||||
|
||||
# run synchronous update on all derived overlays
|
||||
for curve_name, flow in chart._flows.items():
|
||||
update_fsp_chart(
|
||||
chart,
|
||||
flow.shm,
|
||||
curve_name,
|
||||
array_key=curve_name,
|
||||
)
|
||||
|
||||
|
||||
async def display_symbol_data(
|
||||
|
@ -479,8 +570,10 @@ async def display_symbol_data(
|
|||
# clear_on_next=True,
|
||||
# group_key=loading_sym_key,
|
||||
# )
|
||||
fqsn = '.'.join((sym, provider))
|
||||
|
||||
async with open_feed(
|
||||
['.'.join((sym, provider))],
|
||||
[fqsn],
|
||||
loglevel=loglevel,
|
||||
|
||||
# limit to at least display's FPS
|
||||
|
|
|
@ -438,6 +438,17 @@ class FspAdmin:
|
|||
started.set()
|
||||
|
||||
# wait for graceful shutdown signal
|
||||
async with stream.subscribe() as stream:
|
||||
async for msg in stream:
|
||||
if msg == 'update':
|
||||
# if the chart isn't hidden try to update
|
||||
# the data on screen.
|
||||
if not self.linked.isHidden():
|
||||
log.info(f'Re-syncing graphics for fsp: {ns_path}')
|
||||
self.linked.graphics_cycle(trigger_all=True)
|
||||
else:
|
||||
log.info(f'recved unexpected fsp engine msg: {msg}')
|
||||
|
||||
await complete.wait()
|
||||
|
||||
async def start_engine_task(
|
||||
|
|
Loading…
Reference in New Issue