Choosing the Best Python Web Framework

Stuck choosing between Django, Flask, and FastAPI? You’re in the right place. It’s no secret that Python has several great options for making web apps. Some folks have a framework they prefer over others, but you may be wondering how to choose between them!

In the next few minutes you’ll see how they compare in terms of performance, developer experience, and long-term scalability, so you can pick with confidence.

Start with the flowchart below for a quick answer, then read on for the deeper guide:

Performance and scalability

Your choice of Python web framework has performance implications for your app at scale. When comparing the common framework options for Python, we generally see that asynchronous frameworks tend to outperform synchronous ones at serious scale.

FastAPI is built and is designed for speed. Its asynchronous nature can handle many concurrent connections efficiently, making it ideal for high-traffic APIs. In fact, FastAPI is the framework of choice for the APIs behind ChatGPT! Its speed combined with high concurrency support means FastAPI can scale well horizontally to handle growing load, which is something we’ll get into later in the article.

By contrast, Django is the most heavyweight of the three major Python web frameworks. While it can handle plenty of traffic if used well, it often requires more resources. At enough scale, you’ll want to ensure you’re using caching and autoscaling to keep up with demand.

Flask sits between these two frameworks in terms of performance. It’s faster than Django but still slower than FastAPI. It’s an ASGI framework, so it supports concurrency well. While it has good concurrency support, it still has a synchronous architecture, so each request ties up one worker thread until the completion of the request.

In short, if raw performance is your top priority, FastAPI is likely your best bet, while Django trades some performance for rich features, and Flask strikes a middle ground. That said, any of these frameworks can handle significant scale with proper architecture and infrastructure.

Ease of use and extensibility

The most underrated category to consider when choosing a framework is ease of use. How quickly can developers get a new app off the ground? What about adding features? Is it straightforward for a new hire to get productive in a legacy project? While this might not affect your bottom line, it will affect your ability to ship.

The simplest option of the three major Python frameworks is Flask. It’s known for its simplicity - you can get a project off the ground in minutes. The core concepts like routing and templates are straightforward, and there isn’t a lot of framework magic to learn. (looking at you, Rails)

This makes Flask ideal for beginners or for projects you know will stay small like a simple CRUD API. Since Flask gives you so little to work with, you’ll find building more complex features means learning and integrating various extensions or libraries as you go.

The other side of this is Django. Django is more of a “batteries-included” framework. It has a bit steeper learning curve because it offers so much. Unlike Flask, getting a project started requires understanding the framework’s structure, the underlying ORM, and much more. Once you learn Django’s patterns, like the project architecture and the Django ORM, you can be very productive. Django may take longer to learn up front, but it can pay off by saving effort on repeatable tasks without you needing to choose a dependency or build it yourself.

FastAPI sits between Django and Flask in terms of a learning curve. Still, it’s designed with developer friendliness in mind. The syntax uses modern Python features like type hints, which enables automatic data validation and documentation that you’ll quickly grow to love. If you know Python’s basics and are familiar with web development standards, you can probably pick up FastAPI pretty fast. The interactive API docs it provides also make it straightforward to test and understand your API as you build it. All that said, it’s a tiny framework, and you’ll need to build or find your own essentials like an ORM or middleware.

Developer ecosystem

Since Django is one of the oldest and most popular Python frameworks, it has a vast and active community to support you. You’ll find documentation, many books and tutorials, and a rich ecosystem of packages. Django probably has the largest selection of third-party packages among the big three framework options.

Flask is a newer framework but still very popular. Like Django, it has a very active community and a wide range of options for extensions, most of which conform well to the really strong standards. In fact, because Flask includes less than Django out-of-the-box, it’s only natural that the ecosystem is filled with extensions out of necessity.

By contrast, FastAPI is a much newer Python framework. As such, it seems to have the smallest community and ecosystem. That said, its growth has been explosive. The community produces crazy quantities of articles and videos, especially in the context of building REST APIs and machine learning model serving, which shouldn’t be a surprise.

Deployment

Deployment is where the stakes get higher. Building a Python web app isn’t much use without actually being able to deploy it and support your users. While all three of the major frameworks have good production history, you’ll find each come with some tradeoffs.

Django has been used by some of the world’s most massive web applications. There’s good guidance for deployment and scale. You’ll notice Docker is common for Django app deployments but not strictly necessary.

It’s curious to me how many major websites started on Django but later moved to something else. YouTube, Instagram, and Pinterest are a few examples. That says something about Django as a choice for production apps at scale, but most people shouldn’t put too much weight here. The truth is that very few apps will exceed these thresholds where Django ceases to be a great choice! Combine this with a predictable release cycle and long-term support for older versions, and you’ll find Django a good fit for many projects.

Flask is also very popular for web apps - it’s seen use at Netflix and Reddit and many more web-scale companies. Flask forces less structure than Django, so you’ll face more choices on your path to production. You can use Docker, but it’s common to Gunicorn and possibly Nginx. Flask doesn’t automatically handle things like middleware, so you should be careful to include any additional dependencies your app needs.

FastAPI has quickly become a default choice for shipping microservices. The performance and concurrency model of the framework (more on that later) means that a single FastAPI worker can handle a lot of throughput, but you still might want to run multiple processes in case your service encounters CPU-bound work.

How each Python framework scales

Each of the major Python web frameworks scales well, but you may find Django’s heavier footprint coming with slightly higher latency or requiring more resources. Beyond that, keep in mind that the concurrency model of each framework affects how they scale 👇

The concurrency models matter!

One key difference in scalability between the frameworks is the concurrency model. Django and Flask use the WSGI (Web Server Gateway Interface) model, which is synchronous. That means each request is handled by one thread or process at a time, blocking that worker until the request completes. To handle many concurrent users, you often run multiple threads or worker processes, which increases resource usage linearly.

FastAPI is built on ASGI (Asynchronous Server Gateway Interface) and an async event loop. FastAPI endpoints can be defined with async def and leverage Python’s await syntax to handle many connections concurrently in one worker. When an async request in FastAPI needs to wait for something like I/O or a web request, the worker can pause that task and serve other requests in the meantime.

This non-blocking design lets a single FastAPI process handle a high number of simultaneous connections efficiently, giving the ability to serve large numbers of concurrent clients. Django and Flask will usually rely on spinning up more threads or processes for concurrency, by contrast.

Horizontal scaling is a big win

All three frameworks support horizontal scaling, which modulates the number of application instances behind a load balancer. Each instance can be a process or container and they all connect to shared resources like the database. Horizontal scaling is how large sites handle massive load variability without costs getting out of control. All three frameworks can be scaled out on modern cloud platforms to handle very high throughput.

Web service scalability is only one part of your app. If you have background tasks, you should probably scale those as well. In real-world workloads, memory-hungry or long-running tasks are often offloaded to task queues like Celery or RQ instead of being done during web requests. All three frameworks can integrate with such background job systems, but you must scale those workers separately from your web servers.

Choosing an autoscaler

Most platforms like Heroku and even cloud providers have an autoscaler option built-in. Still, they’re often too slow to make an impact for your users (and your bills!). Most rely on a host metric like CPU usage, which doesn’t actually give a direct insight into how long jobs take to process.

Robust autoscaling setups monitor the task queue depth and spin up workers when jobs begin to back up. This ensures background jobs complete in timely fashion and don’t become a bottleneck. Judoscale extends autoscaling to background workers scaling the job queue worker processes so that queues don’t get backed up.

Choosing a Python web framework

For small projects, it seems to me the framework choice isn’t extraordinarily high-stakes. Each major framework is enough to get you off the ground and scale well. It reminds me of a quote from the creator of Rails:

Still, it’s harder to change frameworks after a project has traction than it is to pick the right one up front, so you may as well put some thought into your decision. Here’s a simple framework to help you make your decision.

If you’re building a full-stack app and want lots of things out-of-the-box, Django is probably the best fit. If it’s just an API and performance (especially concurrency) is a top priority, FastAPI is a good bet. And if performance is less important than a strong community and huge content library on the web, Flask might be a better fit.

Regardless of your choice of framework, set up autoscaling (for your web service and workers!) early - and consider trying Judoscale!