FastAPI vs Flask: what's better for Python app development? (2024)

What is Flask

Flask is a web framework and a Python module that allows you to create web applications easily. It has a small and simple core: a microframework without an ORM (Object Relational Manager) or similar features.

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Flask is also known as a microframework since it does not offer an extensive set of features like a full stack framework. However, this allows the intuitive framework to use for many applications. The Flask framework is built on the Werkzeug toolkit and Jinja2 templating engine, which helps to create a lightweight web application with lower resource consumption.

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Among its cool features are URL routing and template engines. Moreover, Flask is deployed on WSGI (Python Web Server Gateway Interface). It is easily extensible with the help of third-party libraries and has a simple structure.

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Uber, Microsoft, Explosion AI, and others are currently using it.

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Flask Advantages

• Easy to understand and start with
  The jargon and syntax associated with Flask are easier to grasp than in other frameworks.
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• Flask supports unit testing
  If you are a person who values code readability and efficiency, then you'll surely appreciate unit testing. With Flask, you can simulate various conditions and test your application's functionality to ensure it runs smoothly under all conditions.
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• It comes with a built-in development server
  The best way to test your application is by setting up a development environment where you can simulate the production environment. The development server with the Flask framework makes this process even simpler by letting you test your application without putting it into production.
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• Easy to extend functionality
  If you don't want to start from scratch and want to enhance the functionality of an existing application, then it is much easier to do it with Flask. Just for kicks, let's say you want to add a comment section to your application. Well, you won't have to go through the lengthy process of starting from scratch. Instead, you'll be able to easily add the desired functionality to your existing application by making a few changes in the code.
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• No need to worry about scalability
  If you plan on making your application available on a larger scale, then you shouldn't worry about the scalability of your application. Flask is highly scalable and lets you create a large application with minimum effort.

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Flask Disadvantages

• Flask is single threaded and synchronous by default
  This means that each request is handled in turn while waiting for the previous task to complete.
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• No out-of-the-box support for session management
  The lack of session management in Flask is a major drawback because it means you have to implement the feature yourself. You'll have a hard time dealing with requests and responses that are linked to one user's interactions of your service or application if you don't have this functionality. The process isn't too complicated but still takes some time when implementing into an app.
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• It uses Modules
  And they are shared by the framework and the developer. These are vulnerable to security flaws.
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• Flask is a web framework that is HTML-oriented
  It is not necessarily designed to create APIs. Of course, it is possible, but it is not Flask's primary goal. Because there is no standard way of writing in Flask, it is preferable to become more familiar with the framework before embarking on a larger project.
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• No built-in support for database migrations
  Data migration is the process of moving information from source to target databases. Users who accessed the source databases will now use the target databases. So, migrating your database and keeping track of different versions can be challenging, but it's necessary. Luckily, third-party libraries let you create a migration manager and track different database versions. But each database type will require its own library (PostgreSQL, MySQL, etc.).

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What is FastAPI

To construct serverless APIs quickly and easily, you can use FastAPI a microframework for Python web development. It provides a slew of features that make creating and managing APIs a snap. The standard web server-web application interface of the framework is ASGI (Asynchronous Server Gateway Interface). Even though Jinja2 isn't required, it is the template engine of choice. FastAPI will work with any database and any library style for databases.

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Netflix, Lyft, and Zillow are currently using Flask. It is the most popular Python development framework for newcomers.

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FastAPI Advantages

• Great performance
  FastAPI surpasses Flask in terms of performance, and it is one of the fastest Python web frameworks. Only Starlette and Uvicorn are faster. Because of ASGI, FastAPI supports concurrency and asynchronous code by declaring the endpoints.
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• Built-in concurrency
  For concurrent programming, Python 3.4 introduced Async I/O. FastAPI simplifies concurrency by eliminating the need for an event loop or async/await management. The initial path function can then be specified as coroutines using async def and await specific locations by developers.
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• Dependency injection support
  FastAPI supports a dependency injection solution that is simple and easy to use. This method ensures that different classes are not directly dependent on one another. It makes it easier to make changes to your code, which can be helpful. This technique increases the modularity of the code and the scalability of the system by achieving inversion of control. FastAPI's path operation functions enable developers to declare relevant dependencies.
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• Built-in docs
  The documentation generated by FastAPI is useful. The documentation assists developers in explaining the software to others, simplifies the use of your backend by front-end engineers, and simplifies API endpoint testing.
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• Validation built-in
  Built-in data validation enables developers to omit proof and write more compact code. It detects incorrect data types and returns the underlying reasoning in JSON. FastAPI uses the Pydantic module to simplify validation and speed up typing. According to FastAPI's authors, it reduces developer errors by 40%.

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FastAPI Disadvantages

• Insufficient security
  FastAPI isn't secure. Instead, fastapi.security handles security. At the same time, it supports OAuth2.0.
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• Small developers group
  FastAPI is eight years younger than Flask. Thus its community and educational materials are still modest. Searching reveals few books, guidelines, or lessons. Growing popularity may change this in the future.

Python FastAPI vs Flask Comparison

When deciding between FastAPI and Flask for Python application development, it's essential to understand how they compare across various aspects. Both frameworks have their strengths and application areas, making them suitable for different project requirements. Let's dive into a detailed comparison based on key factors:

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1. HTTP Methods

• Flask is a micro web framework known for its simplicity and flexibility. It supports all HTTP methods (GET, POST, PUT, DELETE, etc.) through decorators that make route handling straightforward. Flask allows developers to create RESTful web applications with minimal boilerplate code.
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• FastAPI, on the other hand, is built with modern Python features like type hints and asynchronous support. It also supports all HTTP methods but encourages using async functions, making it more efficient for handling asynchronous operations and I/O-bound tasks.

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2. Passing Parameters and Data Validation

• Flask allows parameters to be passed through URLs and forms, supporting basic data validation via WTForms or similar libraries. However, Flask does not provide built-in validation and relies on external libraries for more complex validation needs.
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• FastAPI excels in this area by integrating Pydantic models, which use Python type annotations for request and response data validation. This approach simplifies data parsing and validation, providing automatic request body validation, query parameter validation, and more with detailed error messages.

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3. Displaying Error Messages

• Flask relies on custom error handlers that developers must define for displaying custom error messages. It provides flexibility but requires extra work to ensure consistency across different types of errors.
• FastAPI, integrating Pydantic models, automatically generates detailed and developer-friendly error messages for data validation issues. This feature significantly improves debugging and development efficiency, especially in API-centric applications.

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4. Asynchronous Tasks

• Flask supports asynchronous tasks via extensions like Flask-AsyncIO, but it's not inherently designed for async programming. As a result, achieving optimal performance in I/O-bound or high-concurrency environments requires more effort.
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• FastAPI is built from the ground up with async/await syntax, making it inherently suited for asynchronous programming. This design allows FastAPI to handle large volumes of concurrent connections efficiently, making it ideal for real-time web applications and high-performance APIs.

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5. FastAPI and Flask Performance

• FastAPI generally outperforms Flask, especially in applications that benefit from asynchronous I/O operations. FastAPI's design allows it to handle more requests per second than Flask, making it a better choice for high-load applications.
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• Flask can still perform adequately for many types of applications, especially those that are not I/O-bound or do not require handling large numbers of concurrent connections. Its simplicity and ease of use make it an excellent choice for small to medium sized projects and for learning web development with Python.

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6. Documentation Support

• FastAPI boasts extensive and well-structured documentation that covers its features comprehensively. The documentation includes interactive API documentation with Swagger/UI, automatically generated from the code, enhancing developer experience and API testing.
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• Flask also has good documentation but lacks the automatic API documentation generation feature. Developers often use external tools like Swagger to document their Flask APIs, adding an extra step to the process.

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7. Community Support

• Flask has been around longer than FastAPI and has a larger community. It has many resources, from tutorials and guides to third-party extensions and plugins. This extensive community support makes finding solutions to common problems easier.
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• FastAPI, while newer, has quickly gained popularity due to its performance and ease of use for building modern web applications. Its community is growing rapidly, with increasing contributions to documentation, third-party tools, and extensions.

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Choosing between FastAPI and Flask depends on the specific needs of your project. FastAPI offers superior performance, especially for asynchronous tasks and applications requiring high concurrency. Its automatic validation and documentation generation features make it appealing for rapidly developing robust APIs.

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On the other hand, Flask's simplicity, flexibility, and large community make it an excellent choice for beginners and projects where advanced features provided by FastAPI are unnecessary. Ultimately, both frameworks have their place in Python web development, and the best option depends on the project requirements and developer preference.

Conclusion

A Python application is an excellent way to bring new features and solutions to the table. However, before diving into the development process, you must decide on the framework that will power it.

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Flask and FastAPI can put up Python web servers and data science programs rapidly. They deploy with the same effort. So how do you choose a web framework?

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FastAPI is superior for speed and performance. Choose this latest framework if you're constructing your content delivery network and expect traffic. FastAPI's cutting-edge framework and project template will save you time. It’s also superior to Flask for creating APIs, especially microservices. Flask would only be a good choice if your company already uses it extensively.

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Flask is better for simple microservices with a few API endpoints. It's excellent for constructing machine learning models and data-backed web app prototypes. It’s a good choice if you want to develop a simple app that can grow quickly and in ways you haven't considered. It's easy to use and scales well with few dependencies.

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When it comes down to which one is better, it comes down to your application requirements. So, before deciding on a framework, ensure you thoroughly understand your project and its scope.

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