piker/piker/fsp/_api.py

200 lines
5.0 KiB
Python

# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship of pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
FSP (financial signal processing) apis.
'''
# TODO: things to figure the heck out:
# - how to handle non-plottable values (pyqtgraph has facility for this
# now in `arrayToQPath()`)
# - composition of fsps / implicit chaining syntax (we need an issue)
from __future__ import annotations
from functools import partial
from typing import (
Any,
Callable,
Awaitable,
Optional,
)
import numpy as np
import tractor
from tractor.msg import NamespacePath
from ..data._sharedmem import (
ShmArray,
maybe_open_shm_array,
attach_shm_array,
_Token,
)
from ..log import get_logger
log = get_logger(__name__)
# global fsp registry filled out by @fsp decorator below
_fsp_registry = {}
def _load_builtins() -> dict[tuple, Callable]:
# import to implicity trigger registration via ``@fsp``
from . import _momo # noqa
from . import _volume # noqa
return _fsp_registry
class Fsp:
'''
"Financial signal processor" decorator wrapped async function.
'''
# TODO: checkout the advanced features from ``wrapt``:
# - dynamic enable toggling,
# https://wrapt.readthedocs.io/en/latest/decorators.html#dynamically-disabling-decorators
# - custom object proxies, might be useful for implementing n-compose
# https://wrapt.readthedocs.io/en/latest/wrappers.html#custom-object-proxies
# - custom function wrappers,
# https://wrapt.readthedocs.io/en/latest/wrappers.html#custom-function-wrappers
# actor-local map of source flow shm tokens
# + the consuming fsp *to* the consumers output
# shm flow.
_flow_registry: dict[
tuple[_Token, str], _Token,
] = {}
def __init__(
self,
func: Callable[..., Awaitable],
*,
outputs: tuple[str] = (),
display_name: Optional[str] = None,
**config,
) -> None:
# TODO (maybe):
# - type introspection?
# - should we make this a wrapt object proxy?
self.func = func
self.__name__ = func.__name__ # XXX: must have func-object name
self.ns_path: tuple[str, str] = NamespacePath.from_ref(func)
self.outputs = outputs
self.config: dict[str, Any] = config
# register with declared set.
_fsp_registry[self.ns_path] = self
@property
def name(self) -> str:
return self.__name__
def __call__(
self,
# TODO: when we settle on py3.10 we should probably use the new
# type annots from pep 612:
# https://www.python.org/dev/peps/pep-0612/
# instance,
*args,
**kwargs
):
return self.func(*args, **kwargs)
# TODO: lru_cache this? prettty sure it'll work?
def get_shm(
self,
src_shm: ShmArray,
) -> ShmArray:
'''
Provide access to allocated shared mem array
for this "instance" of a signal processor for
the given ``key``.
'''
dst_token = self._flow_registry[
(src_shm._token, self.name)
]
shm = attach_shm_array(dst_token)
return shm
def fsp(
wrapped=None,
*,
outputs: tuple[str] = (),
display_name: Optional[str] = None,
**config,
) -> Fsp:
if wrapped is None:
return partial(
Fsp,
outputs=outputs,
display_name=display_name,
**config,
)
return Fsp(wrapped, outputs=(wrapped.__name__,))
def mk_fsp_shm_key(
sym: str,
target: Fsp
) -> str:
uid = tractor.current_actor().uid
return f'{sym}.fsp.{target.name}.{".".join(uid)}'
def maybe_mk_fsp_shm(
sym: str,
target: Fsp,
readonly: bool = True,
) -> (str, ShmArray, bool):
'''
Allocate a single row shm array for an symbol-fsp pair if none
exists, otherwise load the shm already existing for that token.
'''
assert isinstance(sym, str), '`sym` should be file-name-friendly `str`'
# TODO: load output types from `Fsp`
# - should `index` be a required internal field?
fsp_dtype = np.dtype(
[('index', int)] +
[(field_name, float) for field_name in target.outputs]
)
key = mk_fsp_shm_key(sym, target)
shm, opened = maybe_open_shm_array(
key,
# TODO: create entry for each time frame
dtype=fsp_dtype,
readonly=True,
)
return key, shm, opened