The lightning-fast ASGI server.
Introduction
Uvicorn is a lightning-fast ASGI server, built on uvloop and httptools.
Until recently Python has lacked a minimal low-level server/application interface for asyncio frameworks. The ASGI specification fills this gap, and means we're now able to start building a common set of tooling usable across all asyncio frameworks.
ASGI should help enable an ecosystem of Python web frameworks that are highly competitive against Node and Go in terms of achieving high throughput in IO-bound contexts. It also provides support for HTTP/2 and WebSockets, which cannot be handled by WSGI.
Uvicorn currently supports HTTP/1.1 and WebSockets. Support for HTTP/2 is planned.
Quickstart
Requirements: Python 3.5, 3.6, 3.7
Install using pip
:
$ pip install uvicorn
Create an application, in app.py
:
class App():
def __init__(self, scope):
assert scope['type'] == 'http'
self.scope = scope
async def __call__(self, receive, send):
await send({
'type': 'http.response.start',
'status': 200,
'headers': [
[b'content-type', b'text/plain'],
]
})
await send({
'type': 'http.response.body',
'body': b'Hello, world!',
})
Run the server:
$ uvicorn app:App
Usage
The uvicorn command line tool is the easiest way to run your application...
Command line options
$ uvicorn --help
Usage: uvicorn [OPTIONS] APP
Options:
--host TEXT Bind socket to this host. [default:
127.0.0.1]
--port INTEGER Bind socket to this port. [default: 8000]
--uds TEXT Bind to a UNIX domain socket.
--fd INTEGER Bind to socket from this file descriptor.
--loop [auto|asyncio|uvloop] Event loop implementation. [default: auto]
--http [auto|h11|httptools] HTTP parser implementation. [default: auto]
--ws [none|auto|websockets|wsproto]
WebSocket protocol implementation.
[default: auto]
--wsgi Use WSGI as the application interface,
instead of ASGI.
--debug Enable debug mode.
--log-level [critical|error|warning|info|debug]
Log level. [default: info]
--no-access-log Disable access log.
--proxy-headers Use X-Forwarded-Proto, X-Forwarded-For,
X-Forwarded-Port to populate remote address
info.
--root-path TEXT Set the ASGI 'root_path' for applications
submounted below a given URL path.
--limit-concurrency INTEGER Maximum number of concurrent connections or
tasks to allow, before issuing HTTP 503
responses.
--limit-max-requests INTEGER Maximum number of requests to service before
terminating the process.
--timeout-keep-alive INTEGER Close Keep-Alive connections if no new data
is received within this timeout. [default:
5]
--help Show this message and exit.
For more information, see the settings documentation.
Running programmatically
To run uvicorn directly from your application...
import uvicorn
class App:
...
if __name__ == "__main__":
uvicorn.run(App, "127.0.0.1", 5000, log_level="info")
Running with Gunicorn
Gunicorn is a mature, fully featured server and process manager.
Uvicorn includes a Gunicorn worker class allowing you to run ASGI applications, with all of Uvicorn's performance benefits, while also giving you Gunicorn's fully-featured process management.
This allows you to increase or decrease the number of worker processes on the fly, restart worker processes gracefully, or perform server upgrades without downtime.
For production deployments we recommend using gunicorn with the uvicorn worker class.
gunicorn app:App -w 4 -k uvicorn.workers.UvicornWorker
For a PyPy compatible configuration use uvicorn.workers.UvicornH11Worker
.
For more information, see the deployment documentation.
The ASGI interface
Uvicorn uses the ASGI specification for interacting with an application.
The application should expose a callable which takes one argument, scope
.
This callable is used to create a new instance of the application for each incoming connection.
It must return a coroutine which the server can then call into.
The application instance coroutine takes two arguments, (receive, send)
,
which are the channels by which messages are sent between the web server and client application.
One style of implementation is to use a class with an __init__()
method to handle
application instantiation, and a __call__()
coroutine to provide the application implementation.
class App():
def __init__(self, scope):
self.scope = scope
async def __call__(self, receive, send):
...
The content of the scope
argument, and the messages expected by receive
and send
depend on
the protocol being used.
The format for HTTP messages is described in the ASGI HTTP Message format.
HTTP Scope
An incoming HTTP request might instantiate an application with the following scope
:
{
'type': 'http.request',
'scheme': 'http',
'root_path': '',
'server': ('127.0.0.1', 8000),
'http_version': '1.1',
'method': 'GET',
'path': '/',
'headers': [
[b'host', b'127.0.0.1:8000'],
[b'user-agent', b'curl/7.51.0'],
[b'accept', b'*/*']
]
}
HTTP Messages
The instance coroutine communicates back to the server by sending messages to the send
coroutine.
await send({
'type': 'http.request.start',
'status': 200,
'headers': [
[b'content-type', b'text/plain'],
]
})
await send({
'type': 'http.request.body',
'body': b'Hello, world!',
})
Requests & responses
Here's an example that displays the method and path used in the incoming request:
class EchoMethodAndPath():
def __init__(self, scope):
self.scope = scope
async def __call__(self, receive, send):
body = 'Received %s request to %s' % (self.scope['method'], self.scope['path'])
await send({
'type': 'http.response.start',
'status': 200,
'headers': [
[b'content-type', b'text/plain'],
]
})
await send({
'type': 'http.response.body',
'body': body.encode('utf-8'),
})
Reading the request body
You can stream the request body without blocking the asyncio task pool,
by fetching messages from the receive
coroutine.
class EchoBody():
def __init__(self, scope):
self.scope = scope
async def read_body(self, receive):
"""
Read and return the entire body from an incoming ASGI message.
"""
body = b''
more_body = True
while more_body:
message = await receive()
body += message.get('body', b'')
more_body = message.get('more_body', False)
return body
async def __call__(self, receive, send):
body = await self.read_body(receive)
await send({
'type': 'http.response.start',
'status': 200,
'headers': [
[b'content-type', b'text/plain'],
]
})
await send({
'type': 'http.response.body',
'body': body,
})
Streaming responses
You can stream responses by sending multiple http.response.body
messages to
the send
coroutine.
class StreamResponse():
def __init__(self, scope):
self.scope = scope
async def __call__(self, receive, send):
body = await self.read_body(receive)
await send({
'type': 'http.response.start',
'status': 200,
'headers': [
[b'content-type', b'text/plain'],
]
})
for chunk in [b'Hello', b', ', b'world!']
await send({
'type': 'http.response.body',
'body': chunk,
'more_body': True
})
await send({
'type': 'http.response.body',
'body': b'',
})
Alternative ASGI servers
Daphne
The first ASGI server implementation, originally developed to power Django Channels, is the Daphne webserver.
It is run widely in production, and supports HTTP/1.1, HTTP/2, and WebSockets.
Any of the example applications given here can equally well be run using daphne
instead.
$ pip install daphne
$ daphne app:App
Hypercorn
Hypercorn was initially part of the Quart web framework, before being separated out into a standalone ASGI server.
Hypercorn supports HTTP/1.1, HTTP/2, and WebSockets.
$ pip install hypercorn
$ hypercorn app:App
ASGI frameworks
You can use Uvicorn, Daphne, or Hypercorn to run any ASGI framework.
For small services you can also write ASGI applications directly.
Starlette
Starlette is a lightweight ASGI framework/toolkit.
It is ideal for building high performance asyncio services, and supports both HTTP and WebSockets.
Django Channels
The ASGI specification was originally designed for use with Django Channels.
Channels is a little different to other ASGI frameworks in that it provides an asynchronous frontend onto a threaded-framework backend. It allows Django to support WebSockets, background tasks, and long-running connections, with application code still running in a standard threaded context.
Quart
Quart is a Flask-like ASGI web framework.
FastAPI
FastAPI is an API framework based on Starlette and Pydantic, heavily inspired by previous server versions of APIStar.
You write your API function parameters with Python 3.6+ type declarations and get automatic data conversion, data validation, OpenAPI schemas (with JSON Schemas) and interactive API documentation UIs.