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FastAPI

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

Test Coverage Package version Supported Python versions


Documentation: https://fastapi.tiangolo.com

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


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

Sponsors

Other sponsors

Opinions

"[...] I'm using FastAPI a ton these days. [...] I'm actually planning to use it for all of my team's ML services at Microsoft. Some of them are getting integrated into the core Windows product and some Office products."

Kabir Khan - Microsoft (ref)

"We adopted the FastAPI library to spawn a REST server that can be queried to obtain predictions. [for Ludwig]"

Piero Molino, Yaroslav Dudin, and Sai Sumanth Miryala - Uber (ref)

"Netflix is pleased to announce the open-source release of our crisis management orchestration framework: Dispatch! [built with FastAPI]"

Kevin Glisson, Marc Vilanova, Forest Monsen - Netflix (ref)

"I’m over the moon excited about FastAPI. It’s so fun!"

Brian Okken - Python Bytes podcast host (ref)

"Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted Hug to be - it's really inspiring to see someone build that."

Timothy Crosley - Hug creator (ref)

"If you're looking to learn one modern framework for building REST APIs, check out FastAPI [...] It's fast, easy to use and easy to learn [...]"

"We've switched over to FastAPI for our APIs [...] I think you'll like it [...]"

Ines Montani - Matthew Honnibal - Explosion AI founders - spaCy creators (ref) - (ref)

"If anyone is looking to build a production Python API, I would highly recommend FastAPI. It is beautifully designed, simple to use and highly scalable, it has become a key component in our API first development strategy and is driving many automations and services such as our Virtual TAC Engineer."

Deon Pillsbury - Cisco (ref)

Typer, the FastAPI of CLIs

If you are building a CLI app to be used in the terminal instead of a web API, check out Typer.

Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. ⌨️ 🚀

Requirements

FastAPI stands on the shoulders of giants:

Installation

Create and activate a virtual environment and then install FastAPI:

$ pip install "fastapi[standard]"

---> 100%

Note: Make sure you put "fastapi[standard]" in quotes to ensure it works in all terminals.

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}
Or use async def...

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

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}

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:

$ fastapi dev main.py

 ╭────────── FastAPI CLI - Development mode ───────────╮
 │                                                     │
 │  Serving at: http://127.0.0.1:8000                  │
 │                                                     │
 │  API docs: http://127.0.0.1:8000/docs               │
 │                                                     │
 │  Running in development mode, for production use:   │
 │                                                     │
 │  fastapi run                                        │
 │                                                     │
 ╰─────────────────────────────────────────────────────╯

INFO:     Will watch for changes in these directories: ['/home/user/code/awesomeapp']
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [2248755] using WatchFiles
INFO:     Started server process [2248757]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
About the command fastapi dev main.py...

The command fastapi dev reads your main.py file, detects the FastAPI app in it, and starts a server using Uvicorn.

By default, fastapi dev will start with auto-reload enabled for local development.

You can read more about it in the FastAPI CLI docs.

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):

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):

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 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}

The fastapi dev server should reload automatically.

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:

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 http://127.0.0.1:8000/redoc.

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

ReDoc

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.

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 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.

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:

editor support

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).
  • 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

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.

Dependencies

FastAPI depends on Pydantic and Starlette.

standard Dependencies

When you install FastAPI with pip install "fastapi[standard]" it comes the standard group of optional dependencies:

Used by Pydantic:

Used by Starlette:

  • 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().

Used by FastAPI / Starlette:

  • uvicorn - for the server that loads and serves your application. This includes uvicorn[standard], which includes some dependencies (e.g. uvloop) needed for high performance serving.
  • fastapi-cli - to provide the fastapi command.

Without standard Dependencies

If you don't want to include the standard optional dependencies, you can install with pip install fastapi instead of pip install "fastapi[standard]".

Additional Optional Dependencies

There are some additional dependencies you might want to install.

Additional optional Pydantic dependencies:

Additional optional FastAPI dependencies:

  • orjson - Required if you want to use ORJSONResponse.
  • ujson - Required if you want to use UJSONResponse.

License

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

asyncer's People

Contributors

dependabot[bot] avatar estebanx64 avatar giladsheffer avatar gowee avatar jonasks avatar khiemdoan avatar kludex avatar markparker5 avatar michaeloliverx avatar pre-commit-ci[bot] avatar realfranco avatar sanders41 avatar svlandeg avatar tiangolo avatar vrslev avatar windson avatar zhymabekroman avatar

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asyncer's Issues

Discussion on function naming

First Check

  • I added a very descriptive title to this issue.
  • I used the GitHub search to find a similar issue and didn't find it.
  • I searched the Asyncer documentation, with the integrated search.
  • I already searched in Google "How to X in Asyncer" and didn't find any information.
  • I already read and followed all the tutorial in the docs and didn't find an answer.
  • I already checked if it is not related to Asyncer but to AnyIO.
  • I already checked if it is not related to Asyncer but to Trio.

Commit to Help

  • I commit to help with one of those options 👆

Example Code

import anyio
import asyncer

def sync_work(name: str):
    time.sleep(1)
    return f"Hello, {name}"

async def do_async_work(name: str):
    message = asyncer.run_sync(sync_work)(name=name)
    return message

async def main():
    message = await do_async_work(name="World")
    print(message)

asyncer.run(main)

Description

It's strange to name the three main functions, Why not use regular name?

  • asyncify
  • syncify
  • runnify

The first two unified can be understood, but runnify is always weird.

Why not

  • run_async
  • run_sync
  • run

Operating System

Windows

Operating System Details

No response

asyncer Version

0.0.1

Python Version

3.X

Additional Context

No response

🚀 Roadmap

Description

This is a tentative roadmap, I will update it as things evolve. Some things might be discarded, others might be added later. I didn't want to make it fully public as it could raise expectations, but it seems it would be more beneficial for the community to know all the ideas and objectives.

Work on this is alternated (and sometimes mixed) with work on FastAPI, Typer, SQLModel, and others.

Answering questions, issues, and PRs is also intermixed with this, but as in some cases one of these features would solve several issues or questions, or potentially solve something done by one or more PRs, in many cases I focus on this a bit more than on answering specific issues, questions, PRs.

Maintenance

The word "maintenance" or "maintainer" doesn't have a very strict definition, and it probably varies a lot from perspective.

A lot of the work related to maintaining FastAPI is done by contributors by answering questions, reviewing PRs, etc.

You can help me ensure each existing PR is in shape (has tests, solves the problem, etc.). Make sure you filter out the translation PRs (most of them) unless you speak the language and can review them.

Security

When there are security issues, those are handled with the highest priority. Those are normally not handled in issues and PRs but in emails, it's not public until the security disclosure is made, in most cases (always, up to now) with the version that fixes them.

Roadmap

Now, here's the current high-level tentative roadmap:

  • Support for the latest AnyIO.
  • Docs for handling concurrency.
  • Docs in FastAPI.

All this is intermixed with reviews for PRs, issues, and discussions.

Invalid images path in tutorial directory

First Check

  • I added a very descriptive title to this issue.
  • I used the GitHub search to find a similar issue and didn't find it.
  • I searched the Asyncer documentation, with the integrated search.
  • I already searched in Google "How to X in Asyncer" and didn't find any information.
  • I already read and followed all the tutorial in the docs and didn't find an answer.
  • I already checked if it is not related to Asyncer but to AnyIO.
  • I already checked if it is not related to Asyncer but to Trio.

Commit to Help

  • I commit to help with one of those options 👆

Example Code

-

Description

Hi @tiangolo.
Images path in tutorial directory is invalid. It seems all of them need a /doc in the beginning of their path.
In #7, I've fixed one of them in asyncify section of the tutorial page. Do you think other cases need to be resolved in the same PR?
Thanks for this awesome library. 🥳

Operating System

Linux

Operating System Details

No response

asyncer Version

Python Version

Additional Context

No response

Autocompletion doesn't seem to work for PyCharm

First Check

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  • I used the GitHub search to find a similar issue and didn't find it.
  • I searched the Asyncer documentation, with the integrated search.
  • I already searched in Google "How to X in Asyncer" and didn't find any information.
  • I already read and followed all the tutorial in the docs and didn't find an answer.
  • I already checked if it is not related to Asyncer but to AnyIO.
  • I already checked if it is not related to Asyncer but to Trio.

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Example Code

from datetime import datetime

from asyncer import asyncify


def foobar(x: int, y: 'str') -> datetime:
    return datetime(int(y), x, 1)


async def main():
    x = await asyncify(foobar)()

Description

asyncer looks awesome yet again. 🎉

Unless I'm missing something(?), I don't seem to get auto-completion help on pycharm.

image

Might be worth:

  • putting a note in the docs about "auto-completion on vscode"
  • thinking about a way to get this to work on pycharm - I assume it would require a plugin?
  • bugging @pauleveritt about whether pycharm have a plan to add support for stuff like this? - It wouldn't just be for this library, if pycharm could do clever inspection of type hints in decorators, it would open up lots of interesting applications to those of us wedded to pycharm

Operating System

Linux

Operating System Details

Ubuntu 21.04

asyncer Version

0.0.1

Python Version

3.9.5

Additional Context

No response

How to handle exceptions ?

First Check

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  • I used the GitHub search to find a similar issue and didn't find it.
  • I searched the Asyncer documentation, with the integrated search.
  • I already searched in Google "How to X in Asyncer" and didn't find any information.
  • I already read and followed all the tutorial in the docs and didn't find an answer.
  • I already checked if it is not related to Asyncer but to AnyIO.
  • I already checked if it is not related to Asyncer but to Trio.

Commit to Help

  • I commit to help with one of those options 👆

Example Code

import asyncer
import logging
from typing import Union

from fastapi import FastAPI

async def func1(name: str):
    return {"message": f"Hello {name} form func1"}


async def func2():
    return {"message": f"Hello {name} form func2"}


@app.get("/test")
async def knowledge_panel(name_str: str):
    async with asyncer.create_task_group() as task_group:
        try:
            soon_value1 = task_group.soonify(func1)(name=name_str)
        except Exception:
            logging.exception()
        try:
            soon_value2 = task_group.soonify(func2)(name=name_str)
        except Exception:
            logging.exception()
    data = [soon_value1.value, soon_value2.value]
    return data

Description

  • How to handle an exception like here soon_value2 will throw an error, then how could I catch the exceptions and return user only single data rather than crashing the whole program?

Operating System

Windows

Operating System Details

No response

asyncer Version

0.0.1

Python Version

Python 3.10.5

Additional Context

No response

how do you get mypy working with paramspec... I cannot

First Check

  • I added a very descriptive title to this issue.
  • I used the GitHub search to find a similar issue and didn't find it.
  • I searched the Asyncer documentation, with the integrated search.
  • I already searched in Google "How to X in Asyncer" and didn't find any information.
  • I already read and followed all the tutorial in the docs and didn't find an answer.
  • I already checked if it is not related to Asyncer but to AnyIO.
  • I already checked if it is not related to Asyncer but to Trio.

Commit to Help

  • I commit to help with one of those options 👆

Example Code

n/a

Description

Hi tiangolo!

Looks like a nice lib. I have a lib called asyncify (https://github.com/dynamic-graphics-inc/dgpy-libs/tree/master/libs/asyncify) pip install asyncify that has an asyncify function. I cannot get my asyncify function to work with mypy and paramspec. do you have any suggestions.

Operating System

Linux, Windows, macOS

Operating System Details

No response

asyncer Version

n/a

Python Version

36+

Additional Context

This is a random question and I thought you might be interested. DM me if you are interested in taking over the asyncify name as it is imo a better name.

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