Flask-Pydantic

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

Installation

python3 -m pip install Flask-Pydantic

Basics

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

2. Using the decorated function argument parameters type hints

---

• 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,
• If validation fails, 400 response is returned with failure explanation.

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

Usage

Basic example

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 flask_pydantic import validate
from pydantic import BaseModel

app = Flask("flask_pydantic_app")


class QueryModel(BaseModel):
    age: int


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


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


@app.route("/", methods=["POST"])
@validate(body=BodyModel, query=QueryModel)
def post():
    # save model to DB
    id_ = ...

    return ResponseModel(
        id=id_,
        age=request.query_params.age,
        name=request.body_params.name,
        nickname=request.body_params.nickname,
    )

• age query parameter is a required int
  • 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)

    {
      "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 -XPOST http://localhost:5000/?age=20 --data '{"name": "John Doe"}' -H 'Content-Type: application/json'

-> {"id": 2, "age": 20, "name": "John Doe", "nickname": null}

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