Looking for advice on ThreadPool separation for middleware and actual event, looking for ContextVars to be passed

Looking for advice on ThreadPool separation for middleware and actual event, looking for ContextVars to be passed

Reproducible in:

pip freeze | grep slack
python --version
sw_vers && uname -v # or `ver`

The slack_bolt version

slack_bolt==1.20.1
slack_sdk==3.34.0
slackclient==2.9.4

Python runtime version

Python 3.11.10

OS info

ProductName: macOS
ProductVersion: 15.3.1
BuildVersion: 24D70
Darwin Kernel Version 24.3.0: Thu Jan 2 20:24:16 PST 2025; root:xnu-11215.81.4~3/RELEASE_ARM64_T6000

Steps to reproduce:

I am attempting to create a trace_id/correlation_id for all slack events/actions/views etc to help with tracking in our structured logs.

1. Create Global middleware, contextvar, and LogFilter

Context

from contextvars import ContextVar
from typing import Optional

from slack_bolt import BoltContext

# Middleware
correlation_id: ContextVar[Optional[str]] = ContextVar("correlation_id", default=None)

LogFilter

from logging import Filter, LogRecord
from typing import Optional

from.modules.logging import correlation_id


def _trim_string(string: Optional[str], string_length: Optional[int]) -> Optional[str]:
    return string[:string_length] if string_length is not None and string else string


class CorrelationIdFilter(Filter):
    """Logging filter to attached correlation IDs to log records"""

    def __init__(
        self,
        name: str = "",
        uuid_length: int | None = None,
        default_value: str | None = None,
    ):
        super().__init__(name=name)
        self.uuid_length = uuid_length
        self.default_value = default_value

    def filter(self, record: "LogRecord") -> bool:
        """
        Attach a correlation ID to the log record.

        Since the correlation ID is defined in the middleware layer, any
        log generated from a request after this point can easily be searched
        for, if the correlation ID is added to the message, or included as
        metadata.
        """
        cid = correlation_id.get(self.default_value)
        record.correlation_id = _trim_string(cid, self.uuid_length)
        return True

Middleware

    from.modules.logging import correlation_id

    def call(context: BoltContext, logger: Logger, next: Callable[[], None]) -> None:
        # Capture the current context
        current_context = copy_context()
        current_thread = threading.current_thread()

        id_value: str | None = correlation_id.get()
        if id_value is not None:
            logger.info(
                f"{__name__} {id_value=} found id in contextvar {current_thread=}"
            )
        elif context.get("correlation_id", None) is not None:
            id_value = context["correlation_id"]
            token = correlation_id.set(id_value)
            logger.info(f"{__name__} {id_value=} found id in context {current_thread=}")
        else:
            id_value = uuid4().hex
            context["correlation_id"] = id_value
            token = correlation_id.set(id_value)
            logger.info(f"{__name__} {id_value=} generated new id {current_thread=}")

        try:
            current_context.run(next)
        finally:
            if token:
                correlation_id.reset(token)

3. Since middleware is ran in a separate threadpool worker as the action/event/view, the contextvar isn't shared between them.
4. Log filter always print None from the ContextVar due to this...

Expected result:

{"levelname": "INFO", "correlation_id": "34a110e2ba6d4100a099e18fd2fb4c74", "name": "module_name", "message": "log message here", "lineno": 44, "asctime": "2025-03-07 13:47:16,182", "exc_info": null}

Actual result:

{"levelname": "INFO", "correlation_id": null, "name": "module_name", "message": "log message here", "lineno": 44, "asctime": "2025-03-07 13:47:16,182", "exc_info": null}

Requirements

Please read the Contributing guidelines and Code of Conduct before creating this issue or pull request. By submitting, you are agreeing to those rules.

El issue no menciona archivos ni tests del repositorio; empieza rastreando cómo se distribuyen los handlers de middleware y de eventos/acciones/vistas entre los workers del thread pool. Compara las rutas de ejecución relevantes con el comportamiento de Python ContextVar y determina cuál es el límite de propagación previsto. El trabajo estaría terminado cuando hubiera un diseño acordado y la cobertura correspondiente para los IDs de correlación en el middleware y los handlers.