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fastapi-events

An event dispatching/handling library for FastAPI, and Starlette.

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Installation

pip install fastapi-events

To use it with AWS handlers, install:

pip install fastapi-events[aws]

To use it with GCP handlers. install:

pip install fastapi-events[google]

To enable OpenTelemetry (OTEL) support, install:

pip install fastapi-events[otel]

Usage

fastapi-events supports both FastAPI and Starlette. To use it, simply configure it as middleware.

Dispatching events

Events can be dispatched anywhere in the code, provided that they are dispatched before a response is generated.

Option 1 - using dict

# anywhere in code

from fastapi_events.dispatcher import dispatch

dispatch(
    "cat-requested-a-fish",  # Event name, accepts any valid string
    payload={"cat_id": "fd375d23-b0c9-4271-a9e0-e028c4cd7230"}  # Event payload, accepts any arbitrary data
)

dispatch("a_cat_is_spotted")  # This works too!

Option 2 - using Pydantic model

New feature since version 0.10.0

It is now possible to dispatch pydantic model as events. A special thanks to @WilliamStam for introducing this remarkable idea.

# anywhere in code
import pydantic
from fastapi_events.dispatcher import dispatch


class CatRequestedAFishEvent(pydantic.BaseModel):
    __event_name__ = "cat-requested-a-fish"

    cat_id: pydantic.UUID4


# Option 2 - dispatching event with pydantic model
dispatch(CatRequestedAFishEvent(cat_id="fd375d23-b0c9-4271-a9e0-e028c4cd7230"))

# which is equivalent to:
dispatch("cat-requested-a-fish", payload={"cat_id": "fd375d23-b0c9-4271-a9e0-e028c4cd7230"})

Event Payload Validation With Pydantic

Since version 0.3.0, event payload validation is possible. To enable this feature, register a Pydantic model with the corresponding event name.

>=0.10.0: Event name can now be defined as a part of the payload schema as __event_name__

import uuid
from enum import Enum
from datetime import datetime

from pydantic import BaseModel
from fastapi_events.registry.payload_schema import registry as payload_schema


class UserEvents(Enum):
    SIGNED_UP = "USER_SIGNED_UP"
    ACTIVATED = "USER_ACTIVATED"


# Registering your event payload schema
@payload_schema.register(event_name=UserEvents.SIGNED_UP)
class SignUpPayload(BaseModel):
    user_id: uuid.UUID
    created_at: datetime

# which is also equivalent to
@payload_schema.register
class SignUpPayload(BaseModel):
    __event_name__ = "USER_SIGNED_UP"
    
    user_id: uuid.UUID
    created_at: datetime

Wildcard in event name is currently not supported

The payload will be validated automatically without any changes required when invoking the dispatcher.

# Events with payload schema registered
dispatch(UserEvents.SIGNED_UP)  # raises ValidationError, missing payload
dispatch(UserEvents.SIGNED_UP,
         {"user_id": "9e79cdbb-b216-40f7-9a05-20d223dee89a"})  # raises ValidationError, missing `created_at`
dispatch(UserEvents.SIGNED_UP,
         {"user_id": "9e79cdbb-b216-40f7-9a05-20d223dee89a", "created_at": datetime.utcnow()})  # OK!

# Events without payload schema -> No validation will be performed
dispatch(UserEvents.ACTIVATED,
         {"user_id": "9e79cdbb-b216-40f7-9a05-20d223dee89a"})  # OK! no validation will be performed

# Events dispatched with Pydantic model (>=0.10.0) -> Validation will be skipped since it would have been already validated
# If you choose to do this, you must ensure __event_name__ is defined in SignUpPayload
dispatch(SignUpPayload(user_id="9e79cdbb-b216-40f7-9a05-20d223dee89a", created_at=datetime.utcnow()))

Payload validation is optional. Payload of events without its schema registered will not be validated.

Handling Events

Handle events locally

The flexibility of fastapi-events enales customisation of how events should be handled. To begin, you may want to handle your events locally.

# ex: in handlers.py

from fastapi_events.handlers.local import local_handler
from fastapi_events.typing import Event


@local_handler.register(event_name="cat*")
def handle_all_cat_events(event: Event):
    """
    this handler will match with an events prefixed with `cat`.
    ex: "cat_eats_a_fish", "cat_is_cute", etc
    """
    # the `event` argument is nothing more than a tuple of event name and payload
    event_name, payload = event

    # TODO do anything you'd like with the event


@local_handler.register(event_name="cat*")  # Tip: You can register several handlers with the same event name
def handle_all_cat_events_another_way(event: Event):
    pass


@local_handler.register(event_name="*")
async def handle_all_events(event: Event):
    # event handlers can be coroutine function too (`async def`)
    pass

Using Dependencies in Local Handler

new feature in fastapi-events>=0.9.0

Dependencies can now be utilized with local handlers, and sub-dependencies are also supported.

As of now, dependencies utilizing a generator (with the yield keyword) are not yet supported.

# ex: in handlers.py
from fastapi import Depends

from fastapi_events.handlers.local import local_handler
from fastapi_events.typing import Event


async def get_db_conn():
    pass  # return a DB conn


async def get_db_session(
    db_conn=Depends(get_db_conn)
):
    pass  # return a DB session created from `db_conn`


@local_handler.register(event_name="*")
async def handle_all_events(
    event: Event,
    db_session=Depends(get_db_session)
):
    # use the `db_session` here
    pass

Piping Events To Remote Queues

In larger projects, it's common to have dedicated services for handling events separately. For example, fastapi-events includes an AWS SQS forwarder, allowing you to forward events to a remote queue.

  1. Register SQSForwardHandler as handlers:

    app = FastAPI()
app.add_middleware(EventHandlerASGIMiddleware, 
                   handlers=[SQSForwardHandler(queue_url="test-queue",
                                               region_name="eu-central-1")])   # registering handler(s)

  2. Start dispatching events! By default, events will be serialised into JSON format:

    ["event name", {"payload": "here is the payload"}]

Tip: to pipe events to multiple queues, provide multiple handlers while adding EventHandlerASGIMiddleware.

Built-in handlers

Here is a list of built-in event handlers:

Creating Custom Handlers

Creating your own handler is as simple as inheriting from the BaseEventHandler class in fastapi_events.handlers.base.

To handle events, fastapi_events calls one of these methods, following this priority order:

  1. handle_many(events): The coroutine function should expect the backlog of the events collected.

  2. handle(event): If handle_many() is not defined in your custom handler, handle() will be called by iterating through the events in the backlog.

from typing import Iterable

from fastapi_events.typing import Event
from fastapi_events.handlers.base import BaseEventHandler


class MyOwnEventHandler(BaseEventHandler):
    async def handle(self, event: Event) -> None:
        """
        Handle events one by one
        """
        pass

    async def handle_many(self, events: Iterable[Event]) -> None:
        """
        Handle events by batch
        """
        pass

OpenTelemetry (OTEL) support

Since version 0.7.0, OpenTelemetry support has been added as an optional feature.

To enable it, make sure you install the following optional modules:

pip install fastapi-events[otel]

Note that no instrumentation library is needed as fastapi_events supports OTEL natively

Spans will be created when:

Support for other handlers will be added in the future.

Cookbook

1) Suppressing Events / Disabling dispatch() Globally

If you wish to globally suppress events, especially during testing, you can achieve this without having to mock or patch the dispatch() function. Simply set the environment variable FASTAPI_EVENTS_DISABLE_DISPATCH to 1, True, or any truthy values.

2) Validating Event Payload During Dispatch

This feature requires Pydantic, which is included with FastAPI. If you're using Starlette, ensure that Pydantic is installed separately.

See Event Payload Validation With Pydantic

3) Dispatching events within handlers (Event Chaining)

It is now possible to dispatch events within another event handlers. You'll need version 0.4 or above.

Comparison between events dispatched within the request-response cycle and event handlers are:

dispatched within request-response cycledispatched within event handlers
processing of eventswill be handled after the response has been madewill be scheduled to the running event loop immediately
order of processingalways after the response is madenot guaranteed
supports payload schema validation with PydanticYesYes
can be disabled globally with FASTAPI_EVENTS_DISABLE_DISPATCHYesYes

4) Dispatching events outside of a request

One of the goals of fastapi-events is to dispatch events without the need to manage specific instance of EventHandlerASGIMiddleware. By default, this is handled using ContextVars. However, there are scenarios where users may want to dispatch events outside the standard request sequence. This can be achieved by generating a custom identifier for the middleware.

By default, the middleware identifier is generated from the object ID of the EventHandlerASGIMiddleware instance and is managed internally without user intervention. If a user needs to dispatch events outside of a request-response lifecycle, they can generate a custom middleware_id value and passed it to EventHandlerASGIMiddleware during its creation. This value can then be used with dispatch() to ensure the correct EventHandlerASGIMiddleware instance is selected.

It's important to note that dispatching events during a request does not require the middleware_id. The dispatcher will automatically discover the appropriate event handler.

In the following example, the ID is generated using the object ID of the FastAPI instance. The middleware identifier must be a unique int, but there are no other restrictions.

import asyncio

from fastapi import FastAPI
from fastapi.requests import Request
from fastapi.responses import JSONResponse

from fastapi_events.dispatcher import dispatch
from fastapi_events.middleware import EventHandlerASGIMiddleware
from fastapi_events.handlers.local import local_handler

app = FastAPI()
event_handler_id: int = id(app)
app.add_middleware(EventHandlerASGIMiddleware,
                   handlers=[local_handler],  # registering handler(s)
                   middleware_id=event_handler_id)  # register custom middleware id


async def dispatch_task() -> None:
    """ background task to dispatch autonomous events """

    for i in range(100):
        # without the middleware_id, this call would raise a LookupError
        dispatch("date", payload={"idx": i}, middleware_id=event_handler_id)
        await asyncio.sleep(1)


@app.on_event("startup")
async def startup_event() -> None:
    asyncio.create_task(dispatch_task())


@app.get("/")
def index(request: Request) -> JSONResponse:
    dispatch("hello", payload={"id": 1})  # Emit events anywhere in your code
    return JSONResponse({"detail": {"msg": "hello world"}})

FAQs:

  1. I'm getting LookupError when dispatch() is used:

        def dispatch(event_name: str, payload: Optional[Any] = None) -> None:
>       q: Deque[Event] = event_store.get()
E       LookupError: <ContextVar name='fastapi_context' at 0x400a1f12b0>

    Answer:

    The proper functioning of dispatch() relies on ContextVars. Various factors can lead to a LookupError, with a common cause being the invocation of dispatch() outside the request-response lifecycle of FastAPI/Starlette, such as calling dispatch() after a response has been returned.

    If you encounter this issue, a workaround is available by using a user-defined middleware_id. Refer to Dispatching Events Outside of a Request for details.

    If you're encountering this during testing, consider disabling dispatch() for testing purposes. Refer to Suppressing Events / Disabling dispatch() Globally for details.

  2. My event handlers are not registered / Local handlers are not being executed:

    Answer:

    To ensure that the module where your local event handlers are defined is loaded during runtime, make sure to import the module in your init.py. This straightforward fix guarantees the proper loading of modules during runtime.

Feedback, Questions?

Any form of feedback and questions are welcome! Please create an issue here.