Pycon NL: from flask to fastapi - William Lacerda¶

Tags: python, pycon, django

(One of my summaries of the Pycon NL one-day conference in Utrecht, NL).

Full title: from flask to fastapi: why and how we made the switch.

He works at “polarsteps”, a travel app. Especially a travel app that will be used in areas with really bad internet connectivity. So performance is top of mind.

They used flask for a long time. Flask 2 added async, but it was still WSGI-bound. They really needed the async scaling possibility for their 4 million monthly users. Type hinting was also a big wish item for improved reliability.

They switched to fastapi:

• True async support. It is ASGI-native

• Typing and validation with pydantic. Pydantic validates requests and responses. Type hints help a lot.

• Native auto-generated docs (openapi). Built-in swagger helps for the frontend team.

This meant they gave up some things that Flask provided:

• Flask has a mature ecosystem. So they left a big community + handy heap of stackoverflow answers + lots of ready-made plugins behind.

• Integrated command-line dev tools. Flask is handy there.

• Simplicity, especially for new devs.

They did a gradual migration. So they needed to build a custom fastapi middleware that could support both worlds. And some api versioning to keep the two code bases apart. It took a lot of time to port everything over.

The middleware was key. Completely async in fastapi. Every request came through here. If needed, a request would be routed to Flask via wsgi, if possible it would go to the new fastapi part of the code.

For the migration, they made a dashboard of all the endpoints and the traffic volume. They migrated high-traffic APIs first: early infra validation. Attention to improvements by checking if the queries were faster. Lots of monitoring of both performance and errors.

Some lessons learned:

• Async adds complexity, but pays off at scale. They started the process with 4 million users, now they’re at 20.

• Pydantic typing catches errors early.

• Versioned middleware made incremental delivery safe.

• Data-driven prioritization (=the dashboard) beats a big-bang rewrite.

• AI helps, but hallucinates too much on complex APIs.

Unrelated photo from our 2025 holiday in Austria: the beautiful ‘große Mühl’ river valley.