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FastAPI framework, high performance, easy to learn, fast to code, ready for production

Project description


FastAPI framework, high performance, easy to learn, fast to code, ready for production

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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.


Python 3.6+

FastAPI stands on the shoulders of giants:


$ pip install fastapi

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

$ pip install uvicorn


  • Create a file with:
from fastapi import FastAPI

app = FastAPI()

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 (the Python "module").
  • app: the object created inside of with the line app = FastAPI().
  • --debug: make the server restart after code changes. Only use for development.

Check it

Open your browser at

You will see the JSON response as:

{"hello": "world"}

Interactive API docs

Now go to

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

Swagger UI

Alternative API docs

And now, go to

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


Example upgrade

Now modify the file 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

async def read_root():
    return {'hello': 'world'}'/items/{item_id}')
async def create_item(item_id: int, item: Item, q: str = None):
    return {"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

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

Swagger UI

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

Swagger UI interaction

  • 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:

Swagger UI interaction

Alternative API docs upgrade

And now, go to

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



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.

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 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.

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_id": item_id, "query": q}


        ... "item_name": ...

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

...and see how your editor will auto-complete the attributes and know their types:

editor support

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:

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].


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

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