flask extension for integration with the awesome pydantic package

Overview

Flask-Pydantic

Actions Status PyPI Language grade: Python License Code style

Flask extension for integration of the awesome pydantic package with Flask.

Installation

python3 -m pip install Flask-Pydantic

Basics

URL query and body parameters

validate decorator validates query and body request parameters and makes them accessible two ways:

  1. Using validate arguments, via flask's request variable
parameter type request attribute name
query query_params
body body_params
  1. Using the decorated function argument parameters type hints

URL path parameter

If you use annotated path URL path parameters as follows

@app.route("/users/<user_id>", methods=["GET"])
@validate()
def get_user(user_id: str):
    pass

flask_pydantic will parse and validate user_id variable in the same manner as for body and query parameters.


Additional validate arguments

  • Success response status code can be modified via on_success_status parameter of validate decorator.
  • response_many parameter set to True enables serialization of multiple models (route function should therefore return iterable of models).
  • request_body_many parameter set to False analogically enables serialization of multiple models inside of the root level of request body. If the request body doesn't contain an array of objects 400 response is returned,
  • get_json_params - parameters to be passed to flask.Request.get_json function
  • If validation fails, 400 response is returned with failure explanation.

For more details see in-code docstring or example app.

Usage

Example 1: Query parameters only

Simply use validate decorator on route function.

Be aware that @app.route decorator must precede @validate (i. e. @validate must be closer to the function declaration).

from typing import Optional
from flask import Flask, request
from pydantic import BaseModel

from flask_pydantic import validate

app = Flask("flask_pydantic_app")

class QueryModel(BaseModel):
  age: int

class ResponseModel(BaseModel):
  id: int
  age: int
  name: str
  nickname: Optional[str]

# Example 1: query parameters only
@app.route("/", methods=["GET"])
@validate()
def get(query: QueryModel):
  age = query.age
  return ResponseModel(
    age=age,
    id=0, name="abc", nickname="123"
    )
See the full example app here
  • age query parameter is a required int
    • curl --location --request GET 'http://127.0.0.1:5000/'
    • if none is provided the response contains:
      {
        "validation_error": {
          "query_params": [
            {
              "loc": ["age"],
              "msg": "field required",
              "type": "value_error.missing"
            }
          ]
        }
      }
    • for incompatible type (e. g. string /?age=not_a_number)
    • curl --location --request GET 'http://127.0.0.1:5000/?age=abc'
      {
        "validation_error": {
          "query_params": [
            {
              "loc": ["age"],
              "msg": "value is not a valid integer",
              "type": "type_error.integer"
            }
          ]
        }
      }
  • likewise for body parameters
  • example call with valid parameters: curl --location --request GET 'http://127.0.0.1:5000/?age=20'

-> {"id": 0, "age": 20, "name": "abc", "nickname": "123"}

Example 2: URL path parameter

@app.route("/character/<character_id>/", methods=["GET"])
@validate()
def get_character(character_id: int):
    characters = [
        ResponseModel(id=1, age=95, name="Geralt", nickname="White Wolf"),
        ResponseModel(id=2, age=45, name="Triss Merigold", nickname="sorceress"),
        ResponseModel(id=3, age=42, name="Julian Alfred Pankratz", nickname="Jaskier"),
        ResponseModel(id=4, age=101, name="Yennefer", nickname="Yenn"),
    ]
    try:
        return characters[character_id]
    except IndexError:
        return {"error": "Not found"}, 400

Example 3: Request body only

class RequestBodyModel(BaseModel):
  name: str
  nickname: Optional[str]

# Example2: request body only
@app.route("/", methods=["POST"])
@validate()
def post(body: RequestBodyModel): 
  name = body.name
  nickname = body.nickname
  return ResponseModel(
    name=name, nickname=nickname,id=0, age=1000
    )
See the full example app here

Example 4: BOTH query paramaters and request body

# Example 3: both query paramters and request body
@app.route("/both", methods=["POST"])
@validate()
def get_and_post(body: RequestBodyModel,query: QueryModel):
  name = body.name # From request body
  nickname = body.nickname # From request body
  age = query.age # from query parameters
  return ResponseModel(
    age=age, name=name, nickname=nickname,
    id=0
  )
See the full example app here

Modify response status code

The default success status code is 200. It can be modified in two ways

  • in return statement
# necessary imports, app and models definition
...

@app.route("/", methods=["POST"])
@validate(body=BodyModel, query=QueryModel)
def post():
    return ResponseModel(
            id=id_,
            age=request.query_params.age,
            name=request.body_params.name,
            nickname=request.body_params.nickname,
        ), 201
  • in validate decorator
@app.route("/", methods=["POST"])
@validate(body=BodyModel, query=QueryModel, on_success_status=201)
def post():
    ...

Status code in case of validation error can be modified using FLASK_PYDANTIC_VALIDATION_ERROR_STATUS_CODE flask configuration variable.

Using the decorated function kwargs

Instead of passing body and query to validate, it is possible to directly defined them by using type hinting in the decorated function.

# necessary imports, app and models definition
...

@app.route("/", methods=["POST"])
@validate()
def post(body: BodyModel, query: QueryModel):
    return ResponseModel(
            id=id_,
            age=query.age,
            name=body.name,
            nickname=body.nickname,
        )

This way, the parsed data will be directly available in body and query. Furthermore, your IDE will be able to correctly type them.

Model aliases

Pydantic's alias feature is natively supported for query and body models. To use aliases in response modify response model

def modify_key(text: str) -> str:
    # do whatever you want with model keys
    return text


class MyModel(BaseModel):
    ...
    class Config:
        alias_generator = modify_key
        allow_population_by_field_name = True

and set response_by_alias=True in validate decorator

@app.route(...)
@validate(response_by_alias=True)
def my_route():
    ...
    return MyModel(...)

Example app

For more complete examples see example application.

Configuration

The behaviour can be configured using flask's application config FLASK_PYDANTIC_VALIDATION_ERROR_STATUS_CODE - response status code after validation error (defaults to 400)

Contributing

Feature requests and pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

  • clone repository
    git clone https://github.com/bauerji/flask_pydantic.git
    cd flask_pydantic
  • create virtual environment and activate it
    python3 -m venv venv
    source venv/bin/activate
  • install development requirements
    python3 -m pip install -r requirements/test.pip
  • checkout new branch and make your desired changes (don't forget to update tests)
    git checkout -b <your_branch_name>
  • run tests
    python3 -m pytest
  • if tests fails on Black tests, make sure You have your code compliant with style of Black formatter
  • push your changes and create a pull request to master branch

TODOs:

  • header request parameters
  • cookie request parameters
Telegram bot + Flask API ( Make Introduction pages )

Introduction-Page-Maker Setup the api Upload the flask api on your host Setup requirements Make pages file on your host and upload the css and js and

Plugin 9 Feb 11, 2022
Cross Origin Resource Sharing ( CORS ) support for Flask

Flask-CORS A Flask extension for handling Cross Origin Resource Sharing (CORS), making cross-origin AJAX possible. This package has a simple philosoph

Cory Dolphin 803 Jan 01, 2023
Forum written for learning purposes in flask and sqlalchemy

Flask-forum forum written for learning purposes using SQLalchemy and flask How to install install requirements pip install sqlalchemy flask clone repo

Kamil 0 May 23, 2022
Rubik's cube assistant on Flask webapp

webcube Rubik's cube assistant on Flask webapp. This webapp accepts the six faces of your cube and gives you the voice instructions as a response. Req

Yash Indane 56 Nov 22, 2022
Alexa Skills Kit for Python

Program the Amazon Echo with Python Flask-Ask is a Flask extension that makes building Alexa skills for the Amazon Echo easier and much more fun. Flas

John Wheeler 1.9k Dec 30, 2022
Flask pre-setup architecture. This can be used in any flask project for a faster and better project code structure.

Flask pre-setup architecture. This can be used in any flask project for a faster and better project code structure. All the required libraries are already installed easily to use in any big project.

Ajay kumar sharma 5 Jun 14, 2022
Flask Sitemapper is a small Python 3 package that generates XML sitemaps for Flask applications.

Flask Sitemapper Flask Sitemapper is a small Python 3 package that generates XML sitemaps for Flask applications. This allows you to create a nice and

6 Jan 06, 2023
An extension to add support of Plugin in Flask.

An extension to add support of Plugin in Flask.

Doge Gui 31 May 19, 2022
RestApi_flask_sql.alchemy - Product REST API With Flask & SQL Alchemy

REST API With Flask & SQL Alchemy Products API using Python Flask, SQL Alchemy and Marshmallow Quick Start Using Pipenv # Activate venv $ pipenv shell

amirwahla 1 Jan 01, 2022
SQL Alchemy dialect for Neo4j

SQL Alchemy dialect for Neo4j This package provides the SQL dialect for Neo4j, using the official JDBC driver (the Neo4j "BI Connector" ) Installation

Beni Ben zikry 8 Jan 02, 2023
YAML-formatted plain-text file based models for Flask backed by Flask-SQLAlchemy

Flask-FileAlchemy Flask-FileAlchemy is a Flask extension that lets you use Markdown or YAML formatted plain-text files as the main data store for your

Siddhant Goel 20 Dec 14, 2022
Flask-Diamond is a batteries-included Flask framework.

Flask-Diamond Flask-Diamond is a batteries-included Python Flask framework, sortof like Django but radically decomposable. Flask-Diamond offers some o

Diamond Methods 173 Dec 22, 2022
A basic JSON-RPC implementation for your Flask-powered sites

Flask JSON-RPC A basic JSON-RPC implementation for your Flask-powered sites. Some reasons you might want to use: Simple, powerful, flexible and python

Cenobit Technologies 272 Jan 04, 2023
a flask profiler which watches endpoint calls and tries to make some analysis.

Flask-profiler version: 1.8 Flask-profiler measures endpoints defined in your flask application; and provides you fine-grained report through a web in

Mustafa Atik 718 Dec 20, 2022
An python flask app with webserver example

python-flask-example-keepalive How it works? Basically its just a python flask webserver which can be used to keep any repl/herokuapp or any other ser

KangersHub 2 Sep 28, 2022
A team blog based on Flask

A team blog based on Flask This project isn't supported at the moment, please see a newer pypress-tornado Thanks for flask_website and newsmeme at [ht

老秋 549 Nov 10, 2022
Neo4j Movies Example application with Flask backend using the neo4j-python-driver

Neo4j Movies Application: Quick Start This example application demonstrates how easy it is to get started with Neo4j in Python. It is a very simple we

Neo4j Examples 309 Dec 24, 2022
A clean and simple blog system based on Flask and MongoDB

CleanBlog A clean and simple blog system based on Flask and MongoDB You can access CleanBlog This is the source code of Flask Tutorial Pro,you can buy

shin 107 Oct 06, 2022
flask extension for integration with the awesome pydantic package

Flask-Pydantic Flask extension for integration of the awesome pydantic package with Flask. Installation python3 -m pip install Flask-Pydantic Basics v

249 Jan 06, 2023