"""Shared setup keeping CodSpeed measurements hermetic.

CodSpeed's callgrind instrumentation counts instructions from every thread while
a measurement window is open, and valgrind serializes all threads onto one
virtual CPU. Work deferred to litellm's shared logging executor would therefore
be attributed to whichever benchmark the valgrind scheduler resumes it under,
flipping results between runs. Running the executor inline keeps each
benchmark's cost self-contained and deterministic.
"""

from collections.abc import Callable, Iterator
from concurrent.futures import Future
from typing import ParamSpec, TypeVar

import pytest

from litellm.litellm_core_utils.thread_pool_executor import executor

P = ParamSpec("P")
R = TypeVar("R")


def _submit_inline(fn: Callable[P, R], /, *args: P.args, **kwargs: P.kwargs) -> Future[R]:
    future: Future[R] = Future()
    try:
        future.set_result(fn(*args, **kwargs))
    except BaseException as exc:
        future.set_exception(exc)
    return future


@pytest.fixture(autouse=True, scope="session")
def inline_logging_executor() -> Iterator[None]:
    executor.submit = _submit_inline
    yield
    del executor.submit