FastAPI

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 3.7+ based on standard Python type hints.

The key features are:

• Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). One of the fastest Python frameworks available.
• Fast to code: Increase the speed to develop features by about 200% to 300%. *
• Fewer bugs: Reduce about 40% of human (developer) induced errors. *
• Intuitive: Great editor support. Completion everywhere. Less time debugging.
• Easy: Designed to be easy to use and learn. Less time reading docs.
• Short: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
• Robust: Get production-ready code. With automatic interactive documentation.
• Standards-based: Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema.

* estimation based on tests on an internal development team, building production applications.

Opinions

Typer, the FastAPI of CLIs

Requirements

• Starlette for the web parts.
• Pydantic for the data parts.

Installation

$ pip install fastapi

---> 100%

$ pip install "uvicorn[standard]"

---> 100%

Example

Create it

• Create a file 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}

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}

Run it

$ 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.

Check it

{"item_id": 5, "q": "somequery"}

• Receives HTTP requests in the paths / and /items/{item_id}.
• Both paths take GET operations (also known as HTTP methods).
• The path /items/{item_id} has a path parameter item_id that should be an int.
• The path /items/{item_id} has an optional str query parameter q.

Interactive API docs

Alternative API docs

Example upgrade

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}

Interactive API docs upgrade

• The interactive API documentation will be automatically updated, including the new body:

• Click on the button "Try it out", it allows you to fill the parameters and directly interact with the API:

• Then click on the "Execute" button, the user interface will communicate with your API, send the parameters, get the results and show them on the screen:

Alternative API docs upgrade

• The alternative documentation will also reflect the new query parameter and body:

Recap

item_id: int

item: Item

• Editor support, including:
  • Completion.
  • Type checks.
• Validation of data:
  • Automatic and clear errors when the data is invalid.
  • Validation even for deeply nested JSON objects.
• Conversion of input data: coming from the network to Python data and types. Reading from:
  • JSON.
  • Path parameters.
  • Query parameters.
  • Cookies.
  • Headers.
  • Forms.
  • Files.
• Conversion of output data: converting from Python data and types to network data (as JSON):
  • Convert Python types (str, int, float, bool, list, etc).
  • datetime objects.
  • UUID objects.
  • Database models.
  • ...and many more.
• Automatic interactive API documentation, including 2 alternative user interfaces:
  • Swagger UI.
  • ReDoc.

• Validate that there is an item_id in the path for GET and PUT requests.
• Validate that the item_id is of type int for GET and PUT requests.
  • If it is not, the client will see a useful, clear error.
• Check if there is an optional query parameter named q (as in http://127.0.0.1:8000/items/foo?q=somequery) for GET requests.
  • As the q parameter is declared with = None, it is optional.
  • Without the None it would be required (as is the body in the case with PUT).
• For PUT requests to /items/{item_id}, Read the body as JSON:
  • Check that it has a required attribute name that should be a str.
  • Check that it has a required attribute price that has to be a float.
  • Check that it has an optional attribute is_offer, that should be a bool, if present.
  • All this would also work for deeply nested JSON objects.
• Convert from and to JSON automatically.
• Document everything with OpenAPI, that can be used by:
  • Interactive documentation systems.
  • Automatic client code generation systems, for many languages.
• Provide 2 interactive documentation web interfaces directly.

    return {"item_name": item.name, "item_id": item_id}

        ... "item_name": item.name ...

        ... "item_price": item.price ...

• Declaration of parameters from other different places as: headers, cookies, form fields and files.
• How to set validation constraints as maximum_length or regex.
• A very powerful and easy to use Dependency Injection system.
• Security and authentication, including support for OAuth2 with JWT tokens and HTTP Basic auth.
• More advanced (but equally easy) techniques for declaring deeply nested JSON models (thanks to Pydantic).
• GraphQL integration with Strawberry and other libraries.
• Many extra features (thanks to Starlette) as:
  • WebSockets
  • extremely easy tests based on HTTPX and pytest
  • CORS
  • Cookie Sessions
  • ...and more.

Performance

Optional Dependencies

• email_validator - for email validation.
• pydantic-settings - for settings management.
• pydantic-extra-types - for extra types to be used with Pydantic.

• 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.

• uvicorn - for the server that loads and serves your application.
• orjson - Required if you want to use ORJSONResponse.

License