new improved CallableMixin

[RootShinobi]

Description

new improved CallableMixin

Type of change

Please delete options that are not relevant.

• Documentation (typos, code examples or any documentation update)
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested?

all internal aiogram tests

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

[github-actions]

✔️ Changelog found.

Thank you for adding a description of the changes

[codecov]

Codecov Report

Merging #1357 (cb68bb2) into dev-3.x (a355dab) will not change coverage.
Report is 1 commits behind head on dev-3.x.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff            @@
##           dev-3.x     #1357   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
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  Files          369       369           
  Lines         9444      9447    +3     
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+ Hits          9444      9447    +3     

Flag	Coverage Δ
unittests	100.00% <100.00%> (ø)

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Files	Coverage Δ
aiogram/dispatcher/event/handler.py	100.00% <100.00%> (ø)

[JrooTJunior]

I know you have a performance test and comparison of results, so please post that test and results as a comment to this pull request.

This can help advanced users understand what has actually been changed.

[RootShinobi]

I know you have a performance test and comparison of results, so please post that test and results as a comment to this pull request.

This can help advanced users understand what has actually been changed.

from typing import Set, Dict, Any
import matplotlib.pyplot as plt
from aiogram.dispatcher.event.handler import CallableMixin, CallbackType
from dataclasses import field, dataclass
import inspect
from timeit import timeit


@dataclass
class CallableMixinEX:
    callback: CallbackType
    awaitable: bool = field(init=False)
    params: Set[str] = field(init=False)
    varkw: bool = field(init=False)

    def post_init(self) -> None:
        callback = inspect.unwrap(self.callback)
        self.awaitable = inspect.isawaitable(callback) or inspect.iscoroutinefunction(callback)
        spec = inspect.getfullargspec(callback)
        self.params = {*spec.args, *spec.kwonlyargs}
        self.varkw = spec.varkw is not None

    def _prepare_kwargs(self, kwargs: Dict[str, Any]) -> Dict[str, Any]:
        if self.varkw:
            return kwargs

        return {k: kwargs[k] for k in self.params if k in kwargs}


REPEAT = 1000000
MAX_FUNC_PARAMS = 10
MAX_MIDDLEWARE_DATA = MAX_FUNC_PARAMS + 5
KEYS = tuple(f"param_{i}" for i in range(MAX_MIDDLEWARE_DATA))
X = []
X_EX = []
Y = []

for FUNC_PARAMS_SIZE in range(1, MAX_FUNC_PARAMS):
    PARAMS = ", ".join(KEYS[:FUNC_PARAMS_SIZE])
    FUNC = eval(f"lambda {PARAMS}: 1")
    for MIDDLEWARE_SIZE in range(FUNC_PARAMS_SIZE, MAX_MIDDLEWARE_DATA):
        MIDDLEWARE_DATA = dict(zip(KEYS[:MIDDLEWARE_SIZE], range(MIDDLEWARE_SIZE)))
        X.append(timeit(
            stmt="call._prepare_kwargs(MIDDLEWARE_DATA)",
            setup="call = CallableMixin(FUNC)",
            globals={**globals(), **locals()},
            number=REPEAT
        ))

        X_EX.append(timeit(
            stmt="call._prepare_kwargs(MIDDLEWARE_DATA)",
            setup="call = CallableMixinEX(FUNC)",
            globals={**globals(), **locals()},
            number=REPEAT
        ))
        Y.append(f"{FUNC_PARAMS_SIZE}x{MIDDLEWARE_SIZE}")

plt.plot(Y, X)
plt.plot(Y, X_EX)
plt.xlabel('func param size x middleware data size')
plt.ylabel('time, [s]')
plt.grid()
plt.xticks(rotation=-90)
plt.legend(['old', 'new'])
plt.show()