Validate Flask requests effortlessly with Pydantic
Project description
About
flask_typed_routes is a Python library designed to validate Flask requests effortlessly with Pydantic.
Documentation: https://rmoralespp.github.io/flask_typed_routes/
Features
- 🎯 Type Safety: Automatically validates requests based on standard Python type hints.
- 🔌 Easy Integration: Simple Flask extension for applying validation to Flask routes.
- ⚠️ Error Handling: Automatically returns meaningful error responses for validation failures.
- ✨ Autocomplete: Excellent editor integration, offering comprehensive completion across all contexts.
Requirements
- Python 3.10+
- Pydantic 2.0+
- Flask
Installation
To install flask_typed_routes using pip, run the following command:
pip install flask_typed_routes
Getting Started
This tool offers comprehensive validation for various types of request parameters, including Path, Query, JsonBody, Header, and Cookie parameters.
Example of a simple Flask application using flask_typed_routes:
Create a file items.py with:
import flask
import flask_typed_routes as flask_tpr
app = flask.Flask(__name__)
flask_tpr.FlaskTypeRoutes(app)
@app.get('/items/<user>/')
def get_items(user: str, skip: int = 0, limit: int = 10):
# Parameters not included in the "path" are automatically treated as "query" parameters.
data = {
'user': user,
'skip': skip,
'limit': limit,
}
return flask.jsonify(data)
Run the server with:
flask --app items run --debug
Open your browser and go to http://127.0.0.1:5000/items/myuser/?skip=20
You will see the JSON response as:
{
"limit": 10,
"skip": 20,
"user": "myuser"
}
Validation: Open your browser and go to http://127.0.0.1:5000/items/myuser/?skip=abc
You will see the JSON response with the error details because the skip parameter is not an integer:
{
"errors": [
{
"input": "abc",
"loc": [
"query",
"skip"
],
"msg": "Input should be a valid integer, unable to parse string as an integer",
"type": "int_parsing",
"url": "https://errors.pydantic.dev/2.9/v/int_parsing"
}
]
}
Example with Pydantic Models
You can also use Pydantic models to validate request data in Flask routes.
Now let's update the items.py file with:
import pydantic
import flask
import flask_typed_routes as flask_tpr
app = flask.Flask(__name__)
flask_tpr.FlaskTypeRoutes(app)
class Item(pydantic.BaseModel):
name: str
description: str = None
price: float
@app.post('/items/')
def create_item(item: Item):
return flask.jsonify(item.model_dump())
@app.put('/items/<item_id>/')
def update_item(item_id: int, item: Item):
return flask.jsonify({'item_id': item_id, **item.model_dump()})
Using Flask Blueprints
You can also use flask_typed_routes with Flask Blueprints.
Now let's update the items.py file with:
import flask
import flask_typed_routes as flask_tpr
app = flask.Flask(__name__)
flask_tpr.FlaskTypeRoutes(app)
app_v2 = flask.Blueprint('items', __name__, url_prefix='/v2')
@app_v2.get('/items/')
def get_items_v2(skip: int = 0, limit: int = 10, country: str = 'US'):
data = {'skip': skip, 'limit': limit, 'country': country}
return flask.jsonify(data)
app.register_blueprint(app_v2)
Using Flask Class-Based Views
You can also use flask_typed_routes with Flask Class-Based Views.
Now let's update the items.py file with:
import flask
import flask.views
import flask_typed_routes as flask_tpr
app = flask.Flask(__name__)
flask_tpr.FlaskTypeRoutes(app)
class UserProducts(flask.views.View):
def dispatch_request(self, user: str, skip: int = 0, limit: int = 10):
data = {'user': user, 'skip': skip, 'limit': limit}
return flask.jsonify(data)
class UserOrders(flask.views.MethodView):
def get(self, user: str, skip: int = 0, limit: int = 10):
data = {'user': user, 'skip': skip, 'limit': limit}
return flask.jsonify(data)
app.add_url_rule('/products/<user>/all/', view_func=UserProducts.as_view('user_products'))
app.add_url_rule('/orders/<user>/all/', view_func=UserOrders.as_view('user_orders'))
Documentation
For more detailed information and usage examples, refer to the project documentation
Development
To contribute to the project, you can run the following commands for testing and documentation:
Running Unit Tests
Install the development dependencies and run the tests:
(env)$ pip install -r requirements-dev.txt # Skip if already installed
(env)$ python -m pytest tests/
(env)$ python -m pytest --cov # Run tests with coverage
Building the Documentation
To build the documentation locally, use the following commands:
(env)$ pip install -r requirements-doc.txt # Skip if already installed
(env)$ mkdocs serve # Start live-reloading docs server
(env)$ mkdocs build # Build the documentation site
License
This project is licensed under the MIT license.
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