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Pait is a Python api tool. Pait enables your Python web framework to have type checking, parameter type conversion, interface document generation and can display your documents through Redoc or Swagger (power by inspect, pydantic)

Project description

Pait(π tool) - Python Modern API Tools, easier to use web frameworks/write API routing

Coverage

PyPI - Python Version PyPI

GitHub Workflow Status GitHub release (release name instead of tag name) Test

Support framework


Documentation: https://so1n.me/pait/

中文文档: https://so1n.me/pait-zh-doc/


Warning

There are changes between the current version and the 0.8 version of the API, For more information, please refer to 1.0.0version change

pait

Pait is an api tool that can be used in any python web framework, the features provided are as follows:

  • Parameter checksum automatic conversion (parameter check depends on Pydantic)
  • Parameter dependency verification
  • Automatically generate openapi files
  • Swagger, Redoc, Rapidoc, Elements, OpenAPI route
  • gRPC Gateway route(After version 1.0, this feature has been migrated to grpc-gateway)
  • TestClient support, support response result verification
  • Support for plugin extensions, such as the Mock plugin, CheckResponse Plugin, Cache Response Plugin
  • Support Pydantic V1 and V2
  • WebSocket support
  • SSE support
  • Auto API Test support

Note:

  • mypy check 100%

  • python version >= 3.7 (support postponed annotations)

Installation

pip install pait --pre

Simple Example

from typing import Type
import uvicorn  # type: ignore
from starlette.applications import Starlette
from starlette.responses import JSONResponse
from starlette.routing import Route

from pait.app.starlette import pait
from pait.field import Body
from pait.openapi.doc_route import add_doc_route
from pait.model.response import JsonResponseModel
from pydantic import BaseModel, Field


class DemoResponseModel(JsonResponseModel):
    """demo post api response model"""
    class ResponseModel(BaseModel):
        uid: int = Field()
        user_name: str = Field()

    description: str = "demo response"
    response_data: Type[BaseModel] = ResponseModel


@pait(response_model_list=[DemoResponseModel])
async def demo_post(
    uid: int = Body.i(description="user id", gt=10, lt=1000),
    user_name: str = Body.i(description="user name", min_length=2, max_length=4)
) -> JSONResponse:
    return JSONResponse({'uid': uid, 'user_name': user_name})


app = Starlette(routes=[Route('/api', demo_post, methods=['POST'])])
add_doc_route(app)
uvicorn.run(app)

See documentation for more features

Support Web framework

Framework Description
Flask All features supported
Sanic All features supported
Starlette All features supported
Tornado All features supported
Django Coming soon

If the web framework is not supported(which you are using).

Can be modified sync web framework according to pait.app.flask

Can be modified async web framework according to pait.app.starlette

Performance

For the parameter validation and transformation feature, Pait is mainly responsible for injecting the request data dependency into the Pydantic model, and then the Pydanitc verifies and transforms the data.

The time consumed by this process <= 0.00005(s), for benchmarks data and subsequent optimization, see #27

Full example

For more complete examples, please refer to example

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