Introducing FastAPI

Sebastián Ramírez
6 min readFeb 4, 2019


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

This article lives in:


I have been avoiding the creation of a new framework for several years. First I tried to solve all the features covered by FastAPI using many different frameworks, plug-ins, and tools.

But at some point, there was no other option than creating something that provided all these features, taking the best ideas from previous tools, and combining them in the best way possible, using language features that weren’t even available before (Python 3.6+ type hints).

Key Features

  • 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.


$ pip install fastapi

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

$ pip install uvicorn


Create it

  • Create a file with:
from fastapi import FastAPIapp = FastAPI()
def read_root():
return {"Hello": "World"}
def read_item(item_id: int, q: str = None):
return {"item_id": item_id, "q": q}

Or use async def...

Check it

Open your browser at

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

You will see the automatic interactive API documentation (provided by 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 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
def read_root():
return {"Hello": "World"}
def read_item(item_id: int, q: str = None):
return {"item_id": item_id, "q": q}
def create_item(item_id: int, item: Item):
return {"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

  • 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

  • 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 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.

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 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.

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}


... "item_name": ...


... "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.


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.

Learn more


Source Code:

About me

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Sebastián Ramírez

Creator of FastAPI and Typer. Dev at Exposion AI. APIs, Deep Learning/Machine Learning, full-stack distributed systems, SQL/NoSQL, Python, Docker, JS, TS, etc.