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Fast Channels

PyPI Code Coverage Test Checked with mypy Checked with pyright Docstring

Fast Channels brings Django Channels–style consumers and channel layers to FastAPI, Starlette, and any ASGI-compatible framework for real-time apps.

What are Channel Layers?

Channel layers enhance WebSocket functionality by enabling advanced messaging patterns beyond simple request-response:

  • Group Messaging: Send messages to multiple WebSocket connections simultaneously
  • Cross-Instance Communication: Send messages from HTTP endpoints, background workers, or other processes
  • Task Distribution: Use as a basic task queue for offloading work to worker processes
  • Distributed Applications: Build scalable real-time apps without routing everything through a database

As the Django Channels documentation explains: "Channel layers allow you to talk between different instances of an application. They're a useful part of making a distributed realtime application if you don't want to have to shuttle all of your messages or events through a database."

Fast Channels ports this proven architecture from Django Channels, which has been battle-tested in production environments for years. By leveraging Redis for high-performance, reliable message delivery while maintaining the familiar consumer-based programming model, Fast Channels brings Django's mature WebSocket patterns to the entire ASGI ecosystem.

Features

  • Django Channels-Style Consumers: Familiar WebSocket consumer patterns with connect, receive, and disconnect methods
  • Channel Layers: Support for Redis-backed channel layers with group messaging
  • Redis Integration: Full Redis support with Redis Sentinel for high availability
  • Async/Await Support: Built from the ground up for modern Python async programming
  • ASGI Compatible: Seamless integration with FastAPI, Starlette, and any ASGI-compatible framework
  • Testing Framework: Comprehensive testing utilities for WebSocket consumers
  • Full Type Safety: Complete type hints with mypy and pyright support
  • Multiple Channel Layer Backends: In-memory for development, Redis for production

Installation

# Basic installation
pip install fast-channels

# Recommended: Install with Redis support for production use
pip install fast-channels[redis]

Optional Dependencies:

# For Redis channel layer support (recommended for production)
pip install fast-channels[redis]

Note: Additional channel layer backends (such as Kafka) may be supported in future releases.

Core Dependencies: Python 3.11+, compatible with any ASGI framework (FastAPI, Starlette, Quart, etc.)

Quick Start

  1. Set Up Channel Layers

Create a layers.py file to configure channel layers:

# layers.py
import os
from fast_channels.layers import (
    InMemoryChannelLayer,
    has_layers,
    register_channel_layer,
)
from fast_channels.layers.redis import RedisChannelLayer

def setup_channel_layers():
    """Set up and register channel layers for the application."""
    # Prevent duplicate registration
    if has_layers():
        return

    redis_url = os.getenv("REDIS_URL", "redis://localhost:6379")

    # Register the default channel layer
    register_channel_layer(
        "default",
        RedisChannelLayer(hosts=[redis_url])
    )

    # Optional: Register additional layers for specific purposes
    # register_channel_layer("memory", InMemoryChannelLayer())

For detailed setup options and advanced configurations, see the Channel Layer Setup Guide.

  1. Create WebSocket Consumer
# consumer.py
from fast_channels.consumer.websocket import AsyncWebsocketConsumer

class ChatConsumer(AsyncWebsocketConsumer):
    groups = ["chat_room"]
    channel_layer_alias = "default"  # Use registered layer

    async def connect(self):
        await self.accept()
        await self.channel_layer.group_send(
            "chat_room",
            {"type": "chat_message", "message": "Someone joined the chat"}
        )

    async def disconnect(self, close_code):
        await self.channel_layer.group_send(
            "chat_room",
            {"type": "chat_message", "message": "Someone left the chat"}
        )

    async def receive(self, text_data=None, bytes_data=None, **kwargs):
        await self.channel_layer.group_send(
            "chat_room",
            {"type": "chat_message", "message": f"Message: {text_data}"}
        )

    async def chat_message(self, event):
        # Send message to WebSocket
        await self.send(event["message"])
  1. Integrate with FastAPI
# main.py
from fastapi import FastAPI
from .layers import setup_channel_layers
from .consumer import ChatConsumer

# Setup layers BEFORE creating the app
setup_channel_layers()

app = FastAPI()

# Create WebSocket sub-app for better organization
ws_app = FastAPI()
ws_app.add_websocket_route("/chat", ChatConsumer.as_asgi())

# Mount WebSocket routes
app.mount("/ws", ws_app)

That's it! Your real-time WebSocket application with channel layers is ready to use.

Channel Layer Backends

In-Memory (Testing Only)
  • Fast and simple for unit tests
  • Single-process only - cannot send messages from workers or HTTP endpoints
  • No persistence
  • Use only for testing group chat functionality or running test suites
Redis Queue Layer (Production - Reliable)
  • Message persistence and guaranteed delivery
  • Scalable across multiple processes
  • Configurable expiry and capacity
  • Best for critical messaging
Redis Pub/Sub Layer (Production - Real-time)
  • Ultra-low latency messaging
  • Real-time broadcasting
  • No message persistence
  • Best for live chat and notifications

Configuration Examples:

# layers.py
import os
from fast_channels.layers import (
    InMemoryChannelLayer,
    has_layers,
    register_channel_layer,
)
from fast_channels.layers.redis import (
    RedisChannelLayer,
    RedisPubSubChannelLayer,
)

def setup_channel_layers():
    """Set up and register channel layers for the application."""
    if has_layers():
        return

    redis_url = os.getenv("REDIS_URL", "redis://localhost:6379")

    # In-memory for development/testing
    register_channel_layer("memory", InMemoryChannelLayer())

    # Redis Queue Layer for reliable messaging
    register_channel_layer("reliable", RedisChannelLayer(
        hosts=[redis_url],
        prefix="app_queue",
        capacity=1500,
        expiry=3600,  # 1 hour
    ))

    # Redis Pub/Sub for real-time chat
    register_channel_layer("chat", RedisPubSubChannelLayer(
        hosts=[redis_url],
        prefix="app_chat",
    ))

    # Redis Sentinel for high availability
    register_channel_layer("ha_queue", RedisChannelLayer(
        sentinels=[("localhost", 26379)],
        service_name="mymaster",
        sentinel_kwargs={"password": "sentinel_password"},
        connection_kwargs={"password": "redis_password"},
    ))

See the Channel Layer Setup Guide for detailed configuration options and best practices.

Testing

Fast Channels includes comprehensive testing utilities out of the box:

from fast_channels.testing import WebsocketCommunicator
import pytest

@pytest.mark.asyncio
async def test_chat_consumer():
    communicator = WebsocketCommunicator(ChatConsumer, "/ws/chat/")
    connected, subprotocol = await communicator.connect()
    assert connected

    # Test sending a message
    await communicator.send_json_to({
        "message": "hello world"
    })
    response = await communicator.receive_json_from()
    assert response == {"message": "hello world"}

    await communicator.disconnect()

Documentation

Please visit Fast Channels docs for complete documentation, including:

  • Detailed consumer patterns
  • Advanced channel layer configuration
  • Production deployment guides
  • Testing best practices
  • Migration guides from Django Channels

Comparison with Alternatives

Fast Channels vs. Native FastAPI/Starlette WebSockets

Native FastAPI WebSocket support provides basic connection handling but lacks advanced messaging capabilities:

# Native FastAPI - Limited to direct connections
@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    # Can only send/receive to this specific connection
    # No group messaging or cross-process communication

Fast Channels vs. Broadcaster

Broadcaster is a lightweight pub/sub library, but Fast Channels provides more comprehensive functionality:

Feature Native WS Broadcaster Fast Channels
Basic WebSocket
Simple Pub/Sub
Group Messaging
Consumer Pattern
Message Persistence ✅ (Redis Queue)
Testing Framework
Connection Management Manual Manual Automatic
Type Safety Manual Basic Full
Background Worker Msgs
Structured Event System

Contributing

Contributions are welcome! Please see our CONTRIBUTING.md for detailed development setup and guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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