🐍FastAPI vs Flask 🌶️v⚡

🐍FastAPI vs Flask 🌶️v⚡

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It is built on top of Starlette for the web parts and Pydantic for the data parts.

Flask is a lightweight Python web framework that provides useful tools and features for creating web applications. It is built on top of the Werkzeug WSGI toolkit and Jinja2 template engine.

One key difference between FastAPI and Flask is the speed at which they can handle requests. FastAPI is built on top of Starlette and is, therefore, capable of handling a large number of concurrent requests efficiently. This makes it a good choice for building highly-scalable, performance-critical APIs. Flask, on the other hand, is not designed for high-performance and may struggle to handle a large number of concurrent requests.

Another difference is the way in which the two frameworks handle data validation. FastAPI uses Pydantic, a powerful data validation and parsing library, to validate the data sent to the API. This allows developers to define the data schemas using Python 3.6+ type hints and ensures that the data sent to the API is always valid. Flask, on the other hand, does not have a built-in data validation system and developers must manually validate the data sent to the API.

Here is a simple example of how to create a GET endpoint in FastAPI:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

And here is the same example in Flask:

from flask import Flask

app = Flask(__name__)

@app.route("/", methods=["GET"])
def read_root():
    return {"Hello": "World"}

As you can see, FastAPI provides a more concise and user-friendly syntax for creating endpoints compared to Flask. Additionally, FastAPI automatically generates an OpenAPI schema for your API, allowing users to easily interact with it using tools like Postman or Swagger UI. Flask does not have this built-in functionality and developers must manually create the OpenAPI schema for their API.

One of the advantages of using FastAPI is its built-in support for asynchronous programming. Asynchronous programming allows you to write non-blocking code that can improve the performance of your application. FastAPI uses the asyncio library from the Python standard library to support asynchronous programming. This means that you can write async code in FastAPI simply by adding the async keyword to your functions.

Here is an example of how to use asynchronous programming in FastAPI:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def read_root():
    return {"Hello": "World"}

Flask, on the other hand, does not have built-in support for asynchronous programming. If you want to use asyncio in Flask, you must use a separate extension like Flask-Aiohttp or Flask-SocketIO. This can make it more difficult to use asynchronous programming in Flask compared to FastAPI.

Another advantage of FastAPI is its support for automatic documentation and code generation. FastAPI automatically generates an OpenAPI schema for your API, which can be used to generate interactive documentation using tools like Swagger UI. This makes it easy for developers to understand and use your API. FastAPI also provides a command-line interface (CLI) that can be used to generate code for your API based on the OpenAPI schema. This can save you a lot of time and effort when building your API. Flask does not have these features built-in and developers must create the documentation and code manually.

Despite the advantages of FastAPI, Flask is still a popular choice for building APIs in Python. One of the reasons for this is its simplicity and lightweight design. Flask is easy to learn and use, making it a good choice for developers who are new to building APIs. Flask is also highly customizable, allowing you to choose the right tools and libraries for your project. This flexibility can be useful if you have specific requirements for your API that are not supported by FastAPI. Additionally, Flask has a large and active community, with many third-party extensions and libraries that can be used to add extra features to your API. This can make it easier to find solutions to common problems when building your API with Flask.

Conclusion

In conclusion, FastAPI and Flask are both popular choices for building APIs with Python. FastAPI is a modern, high-performance web framework that makes it easy to build efficient and scalable APIs. It has built-in support for data validation, asynchronous programming, and automatic documentation and code generation. Flask, on the other hand, is a simple and lightweight framework that is easy to learn and customize. It is a good choice for developers who are new to building APIs and need a flexible framework that can be adapted to their specific requirements. Ultimately, the choice between FastAPI and Flask will depend on your specific needs and preferences.

In my opinion if you're using a python web server just as a webhook/other kind of glue to connect different processes, Flask will do the job and is a bit faster to get up and running, and for me is easier to debug, However FastAPI is arguably a straight upgrade of Flask and is still a fairly new framework that will probably continue to improve at a fast rate.

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