NOTE: This is a fork of (https://github.com/long2ice/fastapi-limiter), currently because the original maintainer @long2ice has not published the latest version which supports FastAPI middleware.

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Table of Contents

• Introduction
• Quick Start
• Installation
• Usage
• Formatting and linting
• CICD

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Introduction

FastAPI-Limiter is a rate limiting tool for fastapi routes, powered by pyrate-limiter.

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Quick Start

Since this is just a package, and not a service, there is no real "run" action. But you can run the tests immediately.

Here are a list of available commands via make.

Bare Metal (i.e. your machine)

1. make install - install the required dependencies.
2. make test - runs the tests.

Docker

1. make build-docker - build the docker image.
2. make run-docker - run the docker compose services.
3. make test-docker - run the tests in docker.
4. make clean-docker - remove all docker containers etc.

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Installation

For Dev work on the repo

Install uv, (if you haven't already) https://docs.astral.sh/uv/getting-started/installation/#installation-methods

brew install uv

Initialise pre-commit (validates ruff on commit.)

uv run pre-commit install

Install dependencies (including dev dependencies)

uv sync

If you are adding a new dev dependency, please run:

uv add --dev {your-new-package}

Namespaces

Packages all share the same namespace ab_core. To import this package into your project:

from ab_core.template import placeholder_func

We encourage you to make your package available to all of ab via this ab_core namespace. The goal is to streamline development, POCs and overall collaboration.

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Usage

Adding the dependency to your project

The library is available on PyPI. You can install it using the following command:

Using pip:

pip install ab-fastapi-limiter

Using UV

Note: there is currently no nice way like poetry, hence we still needd to provide the full url. https://github.com/astral-sh/uv/issues/10140

Add the dependency

uv add ab-fastapi-limiter

Using poetry:

Then run the following command to install the package:

poetry add ab-fastapi-limiter

How tos

Quick Start

FastAPI-Limiter is simple to use, which just provides a dependency RateLimiter. The following example allows 2 requests per 5 seconds on route /.

import uvicorn
from fastapi import Depends, FastAPI
from pyrate_limiter import Duration, Limiter, Rate

from ab_core.fastapi_limiter.depends import RateLimiter

app = FastAPI()

@app.get(
    "/",
    dependencies=[Depends(RateLimiter(limiter=Limiter(Rate(2, Duration.SECOND * 5))))],
)
async def index():
    return {"msg": "Hello World"}


if __name__ == "__main__":
    uvicorn.run("main:app", reload=True)

Usage

RateLimiter

RateLimiter accepts the following parameters:

• limiter: A pyrate_limiter.Limiter instance that defines the rate limiting rules.
• identifier: A callable to identify the request source, default is by IP + path.
• callback: A callable invoked when the rate limit is exceeded, default raises HTTPException with 429 status code.
• blocking: Whether to block the request when the rate limit is exceeded, default is False.
• skip: An async callable that takes a request and returns True to skip rate limiting, default is None.

Identifier

Identifier of route limit, default is ip + path, you can override it such as userid and so on.

async def default_identifier(request: Union[Request, WebSocket]):
    forwarded = request.headers.get("X-Forwarded-For")
    if forwarded:
        ip = forwarded.split(",")[0]
    elif request.client:
        ip = request.client.host
    else:
        ip = "127.0.0.1"
    return ip + ":" + request.scope["path"]

Callback

Callback when rate limit is exceeded, default raises HTTPException with 429 status code.

def default_callback(*args, **kwargs):
    raise HTTPException(
        HTTP_429_TOO_MANY_REQUESTS,
        "Too Many Requests",
    )

Multiple limiters

You can use multiple limiters in one route.

@app.get(
    "/multiple",
    dependencies=[
        Depends(RateLimiter(limiter=Limiter(Rate(1, Duration.SECOND * 5)))),
        Depends(RateLimiter(limiter=Limiter(Rate(2, Duration.SECOND * 15)))),
    ],
)
async def multiple():
    return {"msg": "Hello World"}

Note that you should keep the stricter limiter (lower seconds/times ratio) first.

Skip rate limiting

You can pass a skip callable to RateLimiter to conditionally skip rate limiting for a specific route. The callable receives the request and should return True to skip.

from fastapi.requests import Request

async def skip(request: Request):
    return request.scope["path"] == "/skip"

@app.get(
    "/skip",
    dependencies=[
        Depends(RateLimiter(limiter=Limiter(Rate(1, Duration.SECOND * 5)), skip=skip))
    ],
)
async def skip_route():
    return {"msg": "This route skips rate limiting"}

Middleware

You can also use RateLimiterMiddleware to apply rate limiting globally to all routes without adding dependencies to each route individually.

from fastapi import FastAPI
from pyrate_limiter import Duration, Limiter, Rate

from ab_core.fastapi_limiter.middleware import RateLimiterMiddleware

app = FastAPI()

app.add_middleware(
    RateLimiterMiddleware,
    limiter=Limiter(Rate(2, Duration.SECOND * 5)),
)


@app.get("/")
async def index():
    return {"msg": "Hello World"}

RateLimiterMiddleware accepts the same identifier, callback, blocking, and skip parameters as RateLimiter.

Path-based middleware

Use PathBasedRateLimiterMiddleware when you only want middleware rate limiting to apply to routes under a specific prefix.

from fastapi import FastAPI
from pyrate_limiter import Duration, Limiter, Rate

from ab_core.fastapi_limiter.middleware import PathBasedRateLimiterMiddleware

app = FastAPI()

app.add_middleware(
    PathBasedRateLimiterMiddleware,
    limiter=Limiter(Rate(2, Duration.SECOND * 5)),
    path_prefix="/path/based",
)


@app.get("/")
async def index():
    return {"msg": "Not rate limited by this middleware"}


@app.get("/path/based/1")
async def path_based_route_1():
    return {"msg": "Rate limited"}


@app.get("/path/based/2")
async def path_based_route_2():
    return {"msg": "Rate limited"}

PathBasedRateLimiterMiddleware accepts:

• limiter: Required pyrate_limiter.Limiter instance.
• path_prefix: Required string prefix used to decide which request paths are rate limited.
• identifier: Optional identifier callable (defaults to default_identifier).
• callback: Optional callback callable when the limit is exceeded (defaults to default_middleware_callback).
• blocking: Optional bool passed to try_acquire_async (defaults to False).

Routes not starting with path_prefix are skipped by this middleware.

Rate limiting within a websocket

While the above examples work with REST requests, FastAPI also allows easy usage of websockets, which require a slightly different approach.

Because websockets are likely to be long lived, you may want to rate limit in response to data sent over the socket.

You can do this by rate limiting within the body of the websocket handler:

from ab_core.fastapi_limiter.depends import WebSocketRateLimiter

@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    ratelimit = WebSocketRateLimiter(limiter=Limiter(Rate(1, Duration.SECOND * 5)))
    while True:
        try:
            data = await websocket.receive_text()
            await ratelimit(websocket, context_key=data)  # NB: context_key is optional
            await websocket.send_text("Hello, world")
        except HTTPException:
            await websocket.send_text("Hello again")

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Formatting and linting

We use Ruff as the formatter and linter. The pre-commit has hooks which runs checking and applies linting automatically. The CI validates the linting, ensuring main is always looking clean.

You can manually use these commands too:

1. make lint - check for linting issues.
2. make format - fix linting issues.

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CICD

Publishing to PyPI

We publish to PyPI using Github releases. Steps are as follows:

1. Manually update the version in pyproject.toml file using a PR and merge to main. Use uv version --bump {patch/minor/major} to update the version.
2. Create a new release in Github with the tag name as the version number. This will trigger the publish workflow. In the Release window, type in the version number and it will prompt to create a new tag.
3. Verify the release in PyPI