fastapi 0.1.10

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

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

The key features are:

• Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic).
• 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.
• Robust: Get production-ready code. With automatic interactive documentation.
• Standards-based: Based on (and fully compatible with) the open standards for APIs: OpenAPI and JSON Schema.

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 a file main.py with:

from fastapi import FastAPI

app = FastAPI()

@app.get('/')
async def read_root():
    return {'hello': 'world'}

• Run the server with:

uvicorn main:app --debug

Note: 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 use for development.

Check it

Open your browser at http://127.0.0.1:8000.

You will see the JSON response as:

{"hello": "world"}

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 include:

• a path parameter item_id.
• a body, declared using standard Python types (thanks to Pydantic).
• an optional query parameter q.

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.get('/')
async def read_root():
    return {'hello': 'world'}


@app.post('/items/{item_id}')
async def create_item(item_id: int, item: Item, q: str = None):
    return {"item_name": item.name, "item_id": item_id, "query": q}

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 query, and 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 don't have to learn a new syntax, use a specific library, class or object to declare fields, you just type standard Python types.

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.
• Serialization of input data: from the network to Python, reading from:
  • JSON.
  • Forms.
  • Files.
  • Path parameters.
  • Query parameters.
  • Cookies.
  • Headers.
• Serialization of output data: from Python to network (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.
• Validate that the item_id is of type int. If it is not, the client will see a useful error.
• Check if there is an optional query parameter named q (as in http://127.0.0.1:8000/items/foo?q=somequery). As the q parameter is declared with = None, it is optional. Without the None it would be required (as is the body).
• 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 as OpenAPI, so the interactive documentation is created and updated automatically.
• Provide the interactive documentation web interfaces.

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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, "query": q}

...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.

Spoiler alert: the tutorial, although very short, includes:

• Declaration of parameters from different places as: headers, cookies, form data and files.
• How to set validation constrains as maximum_length or regex.
• A very powerful and easy to use Dependency Injection system (also known as "components", "resources", "providers", "services").
• Security and authentication, including support for OAuth2 with JWT tokens and HTTP Basic auth.
• More advanced (but equally easy) techniques for declaring deeply nested models (JSON body, Form and Files) (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.

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.

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

License

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