PipeWire Stream Usage Guide for Snapcast

Overview

This implementation adds native PipeWire support to Snapcast server, allowing direct audio capture from PipeWire without going through ALSA or JACK compatibility layers.

It is the solution to issue 1371.

Building with PipeWire Support

1. Ensure PipeWire development packages are installed:

   bashCopy

   # Fedora/RHEL
   sudo dnf install pipewire-devel
   
   # Ubuntu/Debian
   sudo apt install libpipewire-0.3-dev
   

2. Build Snapcast with PipeWire support:

   bashCopy

   cmake .. -DBUILD_WITH_PIPEWIRE=ON
   make
   

Usage

Basic Usage

In your snapserver.conf, add a PipeWire stream:

[stream]
source = pipewire://?name=Snapcast&device=&auto_connect=true

URI Parameters

• name: The name of the PipeWire stream (default: "Snapcast")
• target: Target device/node to connect to (default: empty, auto-selects)
• capture_sink: Capture from sink outputs instead of sources (default: false)
• send_silence: Send silent chunks when idle (default: false)
• idle_threshold: Duration of silence before switching to idle state in ms (default: 100)

Examples

1. Capture from default source:

   iniCopy

   source = pipewire://?name=<your_stream_name>
   

2. Capture from specific application/device:

   iniCopy

   source = pipewire://?name=<your_stream_name>&target=Firefox
   

3. Capture sink output (like pw-record with stream.capture.sink=true):

   iniCopy

   source = pipewire://?name=<your_stream_name>&capture_sink=true&target=alsa_output.platform-snd_aloop.0.analog-stereo
   

4. Named stream with custom idle settings:

   iniCopy

   source = pipewire://?name=SnapcastCapture&idle_threshold=500&send_silence=true
   

PipeWire Graph Management

You can use PipeWire tools to manage connections:

# List all nodes
pw-cli list-objects Node

# View the PipeWire graph
pw-dot
qpwgraph  # GUI tool

# Connect manually if auto_connect=false
pw-link "Snapcast:input_FL" "Firefox:output_FL"
pw-link "Snapcast:input_FR" "Firefox:output_FR"

Pulseaudio clients like the pavucontrol UI can also be used.

Key Differences from ALSA Implementation

1. Callback-based: PipeWire uses callbacks instead of polling
2. Graph-based: Audio routing is handled through the PipeWire graph
3. Lower latency: Direct PipeWire integration can provide lower latency
4. Better integration: Works seamlessly with PipeWire's session management

Troubleshooting

1. No audio captured: Check PipeWire connections with pw-link -l
2. Permission issues: Ensure your user is in the audio group
3. High CPU usage: Adjust buffer sizes in PipeWire configuration

Replacing pw-record

If you're currently using pw-record to capture audio into a FIFO, like:

pw-record -P stream.capture.sink=true --target alsa_output.platform-snd_aloop.0.analog-stereo - >/tmp/snapfifo

You can replace it with a native PipeWire stream in snapserver:

source = pipewire://?capture_sink=true&target=alsa_output.platform-snd_aloop.0.analog-stereo

This eliminates the need for FIFOs and external processes, providing better performance and lower latency.

Using with sound loopback devices

It is possible (but not needed) to use pipewire-stream with sound loopback.

Load the loopback module temporarily with:

sudo modprobe snd-aloop

Or permanently by creating a file /etc/modules-load.d/snd_aloop.conf like this:

$ cat /etc/modules-load.d/snd_aloop.conf 
snd_aloop

Alternative: Use the libpipewire-module-snapcast-discover from PipeWire

An alternative to using the pipewire-stream source in Snapcast is to use the libpipewire-module-snapcast-discover module from PipeWire. This module allows PipeWire clients to automatically discover and connect to snapserver.

For details, see the PipeWire documentation and issue 1371.

Using libpipewire-module-snapcast-discover allows for discover snapserver on the (sub) network.

Using pipewire-stream is more direct, avoids loopback networking, but is restricted to snapserver on the local machine. It is - of course - better integrated with PipeWire and may feel more naturally because of that.

Acknowledgements

Research for this implementation was done with perplexity AI. Most of the inital code was written by Claude Code AI, including this documentation.

However, all tests, prompt directions, and the initial PR were done by aanno.