If you could choose any Python web framework to build APIs for a startup, which one would you choose and why?

This page summarizes the projects mentioned and recommended in the original post on /r/Python

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  • sos-django-template

    SOS Django Template is a starter template for new Django projects with modern defaults, power cable included.

  • You can even start fast with this Django starter template, which includes probably all the things you want. You can check out what it includes here.

  • flask-mvc-boilerplate

    Flask boilerlate in MVC format

  • flask 100% as long as u adhere to MVC: https://github.com/esteininger/flask-mvc-boilerplate

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • fastapi

    FastAPI framework, high performance, easy to learn, fast to code, ready for production

  • Do yourself a favor and go with FastAPI. It is for APIs what Python is for programming. Starlette (the backbone of FastAPI) is the fastest Python webframework. You use Pydantic-powered type system do build serialization and validation. You also get autogenerated docs. Plus it's async. What else do you need?

  • aiosql

    Simple SQL in Python

  • I tend to do a lot of data-heavy projects, so I tend to eschew ORM-style code and use a project called aiosql to bind raw SQL to python methods, and offload as much expensive computation to the DB as possible. If I'm prototyping an endpoint (e.g. calculating percentiles for some midsized time-series data), and just need a non-performant working placeholder, it's extremely easy to dump a SQL table to pandas and yeet something together in a few lines - then smoothly replace it with a more performant SQL query down the road. Highly contextual move, but I find it to be an awesome balancing point between flexibility, scalability, performance, productivity, etc.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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