FastAPI
| Developer(s) | Sebastián Ramírez |
|---|---|
| Initial release | December 5, 2018[1] |
| Stable release | 0.91.0[2] 
/ 10 February 2023 |
| Repository | github |
| Written in | Python |
| Type | Web framework |
| License | MIT |
| Website | fastapi |
FastAPI is a Web framework for developing RESTful APIs in Python. FastAPI is based on Pydantic and type hints to validate, serialize, and deserialize data and automatically auto-generate OpenAPI documents.[3]
It fully supports asynchronous programming and can run with Gunicorn and ASGI servers for production, such as Uvicorn and Hypercorn.[4] To improve developer-friendliness, editor support was considered since the project's earliest days.[5]
Adoption and real-world usage
FastAPI was the third most loved web framework in Stack Overflow 2021 Developer Survey.[6]
T. Danka stressed its value for data science applications.[7]
Large companies like Uber and Netflix use it to develop some of their applications.[8][9]
Example
The following code shows a simple web application that displays "Hello World!" when visited:[10]
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
def read_root():
return "Hello World!"
See also
- Django (web framework)
- Flask (web framework)
- Pylons project
- Web2py
- Tornado
- Comparison of web frameworks
- Representational state transfer
- Python (programming language)
External links
References
- ^ "fastapi repo". GitHub. 2018-12-05.
- ^ "Release 0.91.0". 10 February 2023. Retrieved 11 February 2023.
- ^ Lubanovic, Bill (2019-11-06). Introducing Python: Modern Computing in Simple Packages (2nd ed.). O'Reilly Media, Inc. pp. 397, 418. ISBN 9781492051367.
- ^ Philipp Kats; David Katz (2019-08-30). Learn Python by Building Data Science Applications. Packt Publishing Ltd. pp. 435, 365. ISBN 9781789535365.
- ^ "History, Design and Future - FastAPI". Retrieved 4 November 2020.
- ^ "Stack Overflow Developer Survey 2021". Stack Overflow. Retrieved 2021-08-25.
- ^ Danka, Tivadar (2021-08-17). "You Should Start Using FastAPI Now". Towards Data Science. Retrieved 2021-08-25.
- ^ "Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox". Uber Engineering. 2019-07-24. Retrieved 4 November 2020.
- ^ "Introducing Dispatch". Netflix Technology Blog. 2020-02-25. Retrieved 4 November 2020.
- ^ "Example". Retrieved 2022-09-14.