FastAPI framework, high performance, easy to learn, fast to code, ready for production
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Documentation: https://fastapi.tiangolo.com
Source Code: https://github.com/tiangolo/fastapi
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.8+ based on standard Python type hints.
The key features are:
* estimation based on tests on an internal development team, building production applications.
"[...] I'm using FastAPI a ton these days. [...] I'm actually planning to use it for all of my team's ML services at Microsoft. Some of them are getting integrated into the core Windows product and some Office products."
"We adopted the FastAPI library to spawn a REST server that can be queried to obtain predictions. [for Ludwig]"
"Netflix is pleased to announce the open-source release of our crisis management orchestration framework: Dispatch! [built with FastAPI]"
"I’m over the moon excited about FastAPI. It’s so fun!"
"Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted Hug to be - it's really inspiring to see someone build that."
"If you're looking to learn one modern framework for building REST APIs, check out FastAPI [...] It's fast, easy to use and easy to learn [...]"
"We've switched over to FastAPI for our APIs [...] I think you'll like it [...]"
"If anyone is looking to build a production Python API, I would highly recommend FastAPI. It is beautifully designed, simple to use and highly scalable, it has become a key component in our API first development strategy and is driving many automations and services such as our Virtual TAC Engineer."
If you are building a CLI app to be used in the terminal instead of a web API, check out Typer.
Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. ⌨️ 🚀
Python 3.8+
FastAPI stands on the shoulders of giants:
$ pip install fastapi
---> 100%
You will also need an ASGI server, for production such as Uvicorn or Hypercorn.
$ pip install "uvicorn[standard]"
---> 100%
main.py
with:from typing import Union
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
def read_root():
return {"Hello": "World"}
@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
return {"item_id": item_id, "q": q}
async def
...If your code uses async
/ await
, use async def
:
from typing import Union
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
async def read_root():
return {"Hello": "World"}
@app.get("/items/{item_id}")
async def read_item(item_id: int, q: Union[str, None] = None):
return {"item_id": item_id, "q": q}
Note:
If you don't know, check the "In a hurry?" section about async
and await
in the docs.
Run the server with:
$ uvicorn main:app --reload
INFO: Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO: Started reloader process [28720]
INFO: Started server process [28722]
INFO: Waiting for application startup.
INFO: Application startup complete.
uvicorn main:app --reload
...The command uvicorn main:app
refers to:
main
: the file main.py
(the Python "module").app
: the object created inside of main.py
with the line app = FastAPI()
.--reload
: make the server restart after code changes. Only do this for development.Open your browser at http://127.0.0.1:8000/items/5?q=somequery.
You will see the JSON response as:
{"item_id": 5, "q": "somequery"}
You already created an API that:
/
and /items/{item_id}
.GET
operations (also known as HTTP methods)./items/{item_id}
has a path parameter item_id
that should be an int
./items/{item_id}
has an optional str
query parameter q
.Now go to http://127.0.0.1:8000/docs.
You will see the automatic interactive API documentation (provided by Swagger UI):
And now, go to http://127.0.0.1:8000/redoc.
You will see the alternative automatic documentation (provided by ReDoc):
Now modify the file main.py
to receive a body from a PUT
request.
Declare the body using standard Python types, thanks to Pydantic.
from typing import Union
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
price: float
is_offer: Union[bool, None] = None
@app.get("/")
def read_root():
return {"Hello": "World"}
@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
return {"item_id": item_id, "q": q}
@app.put("/items/{item_id}")
def update_item(item_id: int, item: Item):
return {"item_name": item.name, "item_id": item_id}
The server should reload automatically (because you added --reload
to the uvicorn
command above).
Now go to http://127.0.0.1:8000/docs.
And now, go to http://127.0.0.1:8000/redoc.
In summary, you declare once the types of parameters, body, etc. as function parameters.
You do that with standard modern Python types.
You don't have to learn a new syntax, the methods or classes of a specific library, etc.
Just standard Python 3.8+.
For example, for an int
:
item_id: int
or for a more complex Item
model:
item: Item
...and with that single declaration you get:
str
, int
, float
, bool
, list
, etc).datetime
objects.UUID
objects.Coming back to the previous code example, FastAPI will:
item_id
in the path for GET
and PUT
requests.item_id
is of type int
for GET
and PUT
requests.
q
(as in http://127.0.0.1:8000/items/foo?q=somequery
) for GET
requests.
q
parameter is declared with = None
, it is optional.None
it would be required (as is the body in the case with PUT
).PUT
requests to /items/{item_id}
, Read the body as JSON:
name
that should be a str
.price
that has to be a float
.is_offer
, that should be a bool
, if present.We just scratched the surface, but you already get the idea of how it all works.
Try changing the line with:
return {"item_name": item.name, "item_id": item_id}
...from:
... "item_name": item.name ...
...to:
... "item_price": item.price ...
...and see how your editor will auto-complete the attributes and know their types:
For a more complete example including more features, see the Tutorial - User Guide.
Spoiler alert: the tutorial - user guide includes:
maximum_length
or regex
.pytest
Independent TechEmpower benchmarks show FastAPI applications running under Uvicorn as one of the fastest Python frameworks available, only below Starlette and Uvicorn themselves (used internally by FastAPI). (*)
To understand more about it, see the section Benchmarks.
Used by Pydantic:
email_validator
- for email validation.pydantic-settings
- for settings management.pydantic-extra-types
- for extra types to be used with Pydantic.Used by Starlette:
httpx
- Required if you want to use the TestClient
.jinja2
- Required if you want to use the default template configuration.python-multipart
- Required if you want to support form "parsing", with request.form()
.itsdangerous
- Required for SessionMiddleware
support.pyyaml
- Required for Starlette's SchemaGenerator
support (you probably don't need it with FastAPI).ujson
- Required if you want to use UJSONResponse
.Used by FastAPI / Starlette:
uvicorn
- for the server that loads and serves your application.orjson
- Required if you want to use ORJSONResponse
.You can install all of these with pip install "fastapi[all]"
.
This project is licensed under the terms of the MIT license.