meatie 0.1.28

Meatie is a Python library that simplifies the implementation of REST API clients. The library generates code for calling REST endpoints based on method signatures annotated with type hints. Meatie takes care of mechanics related to HTTP communication, such as building URLs, encoding query parameters, and serializing the body in the HTTP requests and responses. Rate limiting, retries, and caching are available with some modest extra setup.

Meatie works with all major HTTP client libraries (request, httpx, aiohttp) and offers seamless integration with Pydantic (v1 and v2). The minimum officially supported version is Python 3.9.

TL;DR

Generate HTTP clients using type annotations.

from typing import Annotated

from aiohttp import ClientSession
from meatie import api_ref, endpoint
from meatie_aiohttp import Client
from pydantic import BaseModel, Field


class Todo(BaseModel):
    user_id: int = Field(alias="userId")
    id: int
    title: str
    completed: bool


class JsonPlaceholderClient(Client):
    def __init__(self) -> None:
        super().__init__(ClientSession(base_url="https://jsonplaceholder.typicode.com"))

    @endpoint("/todos")
    async def get_todos(self, user_id: Annotated[int, api_ref("userId")] = None) -> list[Todo]: ...

    @endpoint("/users/{user_id}/todos")
    async def get_todos_by_user(self, user_id: int) -> list[Todo]: ...

    @endpoint("/todos")
    async def post_todo(self, todo: Annotated[Todo, api_ref("body")]) -> Todo: ...

Do you use a different HTTP client library in your project? See the example adapted for requests and httpx.

Documentation

https://meatie.readthedocs.io/

Installation

Meatie is available on pypi. You can install it with:

pip install meatie

Add Meatie to the Awesome Python list 📢

If you've had a positive experience with Meatie and would like to support the project, please consider helping us by approving our pull request in the Awesome Python repository. Your support is greatly appreciated!

Features

Caching

Cache result for a given TTL.

from typing import Annotated

from meatie import MINUTE, api_ref, cache, endpoint, Cache
from meatie_aiohttp import Client
from pydantic import BaseModel


class Todo(BaseModel):
    ...


class JsonPlaceholderClient(Client):
    def __init__(self) -> None:
        super().__init__(
            ClientSession(base_url="https://jsonplaceholder.typicode.com"),
            local_cache=Cache(max_size=100),
        )

    @endpoint("/todos", cache(ttl=MINUTE, shared=False))
    async def get_todos(self, user_id: Annotated[int, api_ref("userId")] = None) -> list[Todo]:
        ...

A cache key is built based on the URL path and query parameters. It does not include the scheme or the network location. By default, every HTTP client instance has an independent cache. The behavior can be changed in the endpoint definition to share cached results across all HTTP client class instances.

You can pass your custom cache to the local_cache parameter. The built-in cache provides a max_size parameter to limit its size.

Rate Limiting

Meatie can delay HTTP requests that exceed the predefined rate limit.

from typing import Annotated

from aiohttp import ClientSession
from meatie import Limiter, Rate, api_ref, endpoint, limit
from meatie_aiohttp import Client
from pydantic import BaseModel


class Todo(BaseModel):
    ...


class JsonPlaceholderClient(Client):
    def __init__(self) -> None:
        super().__init__(
            ClientSession(base_url="https://jsonplaceholder.typicode.com"),
            limiter=Limiter(Rate(tokens_per_sec=10), capacity=10),
        )

    @endpoint("/todos", limit(tokens=2))
    async def get_todos(self, user_id: Annotated[int, api_ref("userId")] = None) -> list[Todo]:
        ...

Retries

Meatie can retry failed HTTP requests following the strategy set in the endpoint definition. The retry strategy is controlled using third-party functions that specify when a retry should be attempted, how long to wait between consecutive attempts to call the endpoint, and whether to abort further retries.

from typing import Annotated

from aiohttp import ClientSession
from meatie import (
    HttpStatusError,
    RetryContext,
    after_attempt,
    api_ref,
    endpoint,
    fixed,
    jit,
    retry,
)
from meatie_aiohttp import Client
from pydantic import BaseModel


class Todo(BaseModel):
    ...


def should_retry(ctx: RetryContext) -> bool:
    if isinstance(ctx.error, HttpStatusError):
        return ctx.error.response.status >= 500
    return False


class JsonPlaceholderClient(Client):
    def __init__(self) -> None:
        super().__init__(
            ClientSession(base_url="https://jsonplaceholder.typicode.com", raise_for_status=True)
        )

    @endpoint("/todos", retry(on=should_retry, stop=after_attempt(3), wait=fixed(5) + jit(2)))
    async def get_todos(self, user_id: Annotated[int, api_ref("userId")] = None) -> list[Todo]:
        ...

Meatie comes with a built-in set of predefined functions for building retry strategies. See the meatie.retry option for more details.

Calling Private Endpoints

Meatie can inject additional information into the HTTP request. A typical example is adding the Authorization header with a token or signing the request using API keys.

from typing import Annotated, override

from aiohttp import ClientSession
from meatie import Request, api_ref, endpoint, private
from meatie_aiohttp import Client
from pydantic import BaseModel


class Todo(BaseModel):
    ...


class JsonPlaceholderClient(Client):
    def __init__(self) -> None:
        super().__init__(ClientSession(base_url="https://jsonplaceholder.typicode.com"))

    @endpoint("/todos", private)
    async def get_todos(self, user_id: Annotated[int, api_ref("userId")] = None) -> list[Todo]:
        ...

    @override
    async def authenticate(self, request: Request) -> None:
        request.headers["Authorization"] = "Bearer bWVhdGll"

More Examples

Need more control over processing the HTTP requests or responses? See the Meatie Cookbook with solutions to the most frequently asked questions by the community.