Skip to main content

generate OpenAPI document and validate request&response with Python annotations.

Project description

Flask Pydantic Spec

A library to make it easy to add OpenAPI documentation to your Flask app, and validate the requests using Pydantic.

This library began as a fork of Spectree, but as we made changes we thought other people might be interested in our approach.

Features

  • Less boilerplate code, only annotations, no need for YAML :sparkles:
  • Generate API document with Redoc UI or Swagger UI :yum:
  • Validate query, JSON data, response data with pydantic :wink:
  • Has support for request/response types other than JSON.

Quick Start

install with pip: pip install flask-pydantic-spec

Examples

Check the examples folder.

Step by Step

  1. Define your data structure used in (query, json, headers, cookies, resp) with pydantic.BaseModel
  2. create flask_pydantic_spec.Validator instance with the web framework name you are using, like api = Validator('flask')
  3. api.validate decorate the route with
    • query
    • body
    • headers
    • cookies
    • resp
    • tags
  4. access this data with context(query, body, headers, cookies) (of course, you can access these from the original place where the framework offered)
    • flask: request.context
  5. register to the web application api.register(app)
  6. check the document at URL location /apidoc/redoc or /apidoc/swagger

If the request doesn't pass the validation, it will return a 422 with JSON error message(ctx, loc, msg, type).

How To

How to add summary and description to endpoints?

Just add docs to the endpoint function. The 1st line is the summary, and the rest is the description for this endpoint.

How to add description to parameters?

Check the pydantic docs about description in Field.

Any config I can change?

Of course. Check the config document.

You can update the config when you init the validator like:

from flask_pydantic_spec import FlaskPydanticSpec
FlaskPydanticSpec("flask", title="Demo API", version="v1.0", path="doc")

What is a Response and how to use it?

To build a response for the endpoint, you need to declare the status code with format HTTP_{code} and corresponding data (optional).

from flask_pydantic_spec import Response
Response(HTTP_200=None, HTTP_403=ForbidModel)
Response('HTTP_200') # equals to Response(HTTP_200=None)

What should I return when I'm using the library?

No need to change anything. Just return what the framework required.

How to logging when the validation failed?

Validation errors are logged with INFO level. Details are passed into extra.

How can I change the response when there is a validation error? Can I record some metrics?

This library provides before and after hooks to do these. Check the doc or the test case. You can change the handlers for Flask-Pydantic-Spec or for a specific endpoint validation.

Demo

Try it with http post :8000/api/user name=alice age=18. (if you are using httpie)

Flask

from flask import Flask, request, jsonify
from pydantic import BaseModel, Field, constr
from flask_pydantic_spec import FlaskPydanticSpec, Response, Request


class Profile(BaseModel):
    name: constr(min_length=2, max_length=40) # Constrained Str
    age: int = Field(
        ...,
        gt=0,
        lt=150,
        description='user age(Human)'
    )

    class Config:
        schema_extra = {
            # provide an example
            'example': {
                'name': 'very_important_user',
                'age': 42,
            }
        }


class Message(BaseModel):
    text: str


app = Flask(__name__)
api = FlaskPydanticSpec('flask')


@app.route('/api/user', methods=['POST'])
@api.validate(body=Request(Profile), resp=Response(HTTP_200=Message, HTTP_403=None), tags=['api'])
def user_profile():
    """
    verify user profile (summary of this endpoint)

    user's name, user's age, ... (long description)
    """
    print(request.context.json) # or `request.json`
    return jsonify(text='it works')


if __name__ == "__main__":
    api.register(app) # if you don't register in api init step
    app.run(port=8000)

FAQ

ValidationError: missing field for headers

The HTTP headers' keys in Flask are capitalized. You can use pydantic.root_validators(pre=True) to change all the keys into lower cases or upper cases.

ValidationError: value is not a valid list for query

Since there is no standard for HTTP query with multiple values, it's hard to find the way to handle this for different web frameworks. So I suggest not to use list type in query until I find a suitable way to fix it.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

flask_pydantic_spec-0.1.5.tar.gz (20.7 kB view details)

Uploaded Source

Built Distribution

flask_pydantic_spec-0.1.5-py3-none-any.whl (20.5 kB view details)

Uploaded Python 3

File details

Details for the file flask_pydantic_spec-0.1.5.tar.gz.

File metadata

  • Download URL: flask_pydantic_spec-0.1.5.tar.gz
  • Upload date:
  • Size: 20.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for flask_pydantic_spec-0.1.5.tar.gz
Algorithm Hash digest
SHA256 2dbfa3538afc8dbe06fb14a92b0145d810cbddc4e6a563c419f6a0e07dfd1e7f
MD5 b9712a7b4d992d58cf822bb63373d22c
BLAKE2b-256 7ca04cf6a27b46e4810a253c6ba08b47d487a43833ac3936003b078896b1112c

See more details on using hashes here.

Provenance

File details

Details for the file flask_pydantic_spec-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: flask_pydantic_spec-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 20.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for flask_pydantic_spec-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 5afc7cf55589bb756a5e6ece3094aaedbbba5fbcdd98a177284619f1f1f350c4
MD5 37df43c5cf575c7f6968ffb847d3330e
BLAKE2b-256 e630bc52fb852bbb977468f5d0b012c3d767bfc2278a70423cc5fc3c3eac5c71

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page