FastAPI vs. Flask: Comparing the Pros and Cons of Top Microframeworks for Building a REST API in Python

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • OpenAPI-Specification

    The OpenAPI Specification Repository

  • The most common standard for creating such documentation is OpenAPI and JSONSchema.

  • flasgger

    Easy OpenAPI specs and Swagger UI for your Flask API

  • Flask offers extensions, such as Flask-Swagger or Flasgger, which operate using the specification mentioned above. They require additional installation and knowledge of the format used by these standards.

  • 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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  • redoc

    📘 OpenAPI/Swagger-generated API Reference Documentation

  • FastAPI has documentation that is fully compatible with OpenAPI and JSONSchema, which is created automatically from Pydantic schemas and function parameters or GET variables. The user interface is provided by SwaggerUI and Redoc.

  • pydantic

    Data validation using Python type hints

  • FastAPI, on the other hand, gives us the Pydantic library to use, which makes data validation much simpler and faster than typing it by hand. It’s closely related to FastAPI itself, so we can be sure that Pydantic will be compatible with our framework at all times.

  • awesome-jsonschema

    A curated list of awesome JSON Schema resources, tutorials, tools, and more.

  • The most common standard for creating such documentation is OpenAPI and JSONSchema.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

    SaaSHub logo
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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