fastapi 0.2.0

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

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Documentation: https://fastapi.tiangolo.com

Source Code: https://github.com/tiangolo/fastapi

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FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ 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% *.

• Less 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. Less 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.

Requirements

Python 3.6+

FastAPI stands on the shoulders of giants:

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

Installation

$ pip install fastapi

You will also need an ASGI server, for production such as uvicorn.

$ pip install uvicorn

Example

Create it

• Create a file main.py with:

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: str = None):
    return {"item_id": item_id, "q": q}

Or use async def...

If your code uses async / await, use async def:

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: str = 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 it

Run the server with:

uvicorn main:app --debug

About the command uvicorn main:app --debug...

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().
• --debug: make the server restart after code changes. Only do this for development.

Check it

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:

• 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

Now go to http://127.0.0.1:8000/docs.

You will see the automatic interactive API documentation (provided by Swagger UI):

Alternative API docs

And now, go to http://127.0.0.1:8000/redoc.

You will see the alternative automatic documentation (provided by ReDoc):

Example upgrade

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 fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = None


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}


@app.put("/items/{item_id}")
def create_item(item_id: int, item: Item):
    return {"item_name": item.name, "item_id": item_id}

The server should reload automatically (because you added --debug to the uvicorn command above).

Interactive API docs upgrade

Now go to http://127.0.0.1:8000/docs.

• 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

And now, go to http://127.0.0.1:8000/redoc.

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

Recap

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 3.6+.

For example, for an int:

item_id: int

or for a more complex Item model:

item: Item

...and with that single declaration you get:

• 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.

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Coming back to the previous code example, FastAPI will:

• 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 is 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.

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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:

• 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).
• Many extra features (thanks to Starlette) as:
  • WebSockets
  • GraphQL
  • extremely easy tests based on requests and pytest
  • CORS
  • Cookie Sessions
  • ...and more.

Performance

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.

Optional Dependencies

Used by Pydantic:

• ujson - for faster JSON "parsing".
• email_validator - for email validation.

Used by Starlette:

• requests - Required if you want to use the TestClient.
• aiofiles - Required if you want to use FileResponse or StaticFiles.
• 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 SchemaGenerator support.
• graphene - Required for GraphQLApp support.
• ujson - Required if you want to use UJSONResponse.

Used by FastAPI / Starlette:

• uvicorn - for the server that loads and serves your application.

You can install all of these with pip3 install fastapi[all].

License

This project is licensed under the terms of the MIT license.