200 lines
5.0 KiB
Python
200 lines
5.0 KiB
Python
# piker: trading gear for hackers
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# Copyright (C) Tyler Goodlet (in stewardship of pikers)
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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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FSP (financial signal processing) apis.
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'''
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# TODO: things to figure the heck out:
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# - how to handle non-plottable values (pyqtgraph has facility for this
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# now in `arrayToQPath()`)
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# - composition of fsps / implicit chaining syntax (we need an issue)
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from __future__ import annotations
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from functools import partial
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from typing import (
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Any,
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Callable,
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Awaitable,
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Optional,
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)
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import numpy as np
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import tractor
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from tractor.msg import NamespacePath
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from ..data._sharedmem import (
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ShmArray,
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maybe_open_shm_array,
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attach_shm_array,
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_Token,
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)
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from ..log import get_logger
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log = get_logger(__name__)
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# global fsp registry filled out by @fsp decorator below
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_fsp_registry = {}
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def _load_builtins() -> dict[tuple, Callable]:
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# import to implicity trigger registration via ``@fsp``
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from . import _momo # noqa
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from . import _volume # noqa
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return _fsp_registry
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class Fsp:
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'''
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"Financial signal processor" decorator wrapped async function.
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'''
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# TODO: checkout the advanced features from ``wrapt``:
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# - dynamic enable toggling,
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# https://wrapt.readthedocs.io/en/latest/decorators.html#dynamically-disabling-decorators
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# - custom object proxies, might be useful for implementing n-compose
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# https://wrapt.readthedocs.io/en/latest/wrappers.html#custom-object-proxies
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# - custom function wrappers,
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# https://wrapt.readthedocs.io/en/latest/wrappers.html#custom-function-wrappers
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# actor-local map of source flow shm tokens
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# + the consuming fsp *to* the consumers output
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# shm flow.
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_flow_registry: dict[
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tuple[_Token, str], _Token,
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] = {}
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def __init__(
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self,
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func: Callable[..., Awaitable],
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*,
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outputs: tuple[str] = (),
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display_name: Optional[str] = None,
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**config,
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) -> None:
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# TODO (maybe):
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# - type introspection?
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# - should we make this a wrapt object proxy?
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self.func = func
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self.__name__ = func.__name__ # XXX: must have func-object name
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self.ns_path: tuple[str, str] = NamespacePath.from_ref(func)
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self.outputs = outputs
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self.config: dict[str, Any] = config
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# register with declared set.
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_fsp_registry[self.ns_path] = self
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@property
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def name(self) -> str:
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return self.__name__
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def __call__(
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self,
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# TODO: when we settle on py3.10 we should probably use the new
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# type annots from pep 612:
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# https://www.python.org/dev/peps/pep-0612/
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# instance,
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*args,
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**kwargs
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):
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return self.func(*args, **kwargs)
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# TODO: lru_cache this? prettty sure it'll work?
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def get_shm(
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self,
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src_shm: ShmArray,
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) -> ShmArray:
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'''
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Provide access to allocated shared mem array
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for this "instance" of a signal processor for
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the given ``key``.
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'''
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dst_token = self._flow_registry[
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(src_shm._token, self.name)
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]
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shm = attach_shm_array(dst_token)
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return shm
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def fsp(
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wrapped=None,
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*,
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outputs: tuple[str] = (),
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display_name: Optional[str] = None,
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**config,
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) -> Fsp:
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if wrapped is None:
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return partial(
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Fsp,
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outputs=outputs,
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display_name=display_name,
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**config,
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)
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return Fsp(wrapped, outputs=(wrapped.__name__,))
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def mk_fsp_shm_key(
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sym: str,
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target: Fsp
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) -> str:
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uid = tractor.current_actor().uid
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return f'{sym}.fsp.{target.name}.{".".join(uid)}'
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def maybe_mk_fsp_shm(
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sym: str,
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target: Fsp,
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readonly: bool = True,
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) -> (str, ShmArray, bool):
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'''
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Allocate a single row shm array for an symbol-fsp pair if none
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exists, otherwise load the shm already existing for that token.
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'''
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assert isinstance(sym, str), '`sym` should be file-name-friendly `str`'
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# TODO: load output types from `Fsp`
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# - should `index` be a required internal field?
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fsp_dtype = np.dtype(
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[('index', int)] +
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[(field_name, float) for field_name in target.outputs]
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)
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key = mk_fsp_shm_key(sym, target)
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shm, opened = maybe_open_shm_array(
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key,
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# TODO: create entry for each time frame
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dtype=fsp_dtype,
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readonly=True,
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)
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return key, shm, opened
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