abletonparsing 0.1.3

Python module for parsing Ableton Live ASD clip files containing warp markers.

AbletonParsing

Parse an Ableton ASD clip file and its warp markers in Python. This module has been tested with .asd files saved with Ableton 9 and Ableton 10.

Note: Ableton Live 12 uses a different binary format that is not yet supported by this library.

Install

pip install abletonparsing

Development Dependencies

To run the tests, you'll need to install additional dependencies:

# On macOS
brew install rubberband

# On Ubuntu/Debian
sudo apt-get install -y rubberband-cli

# Install Python test dependencies
pip install abletonparsing[test]
# or
pip install -e ".[test]"  # for development

API

Clip class:

• .loop_on - ( bool , READ/WRITE ) - Loop toggle is on
• .start_marker - ( float , READ/WRITE ) - Start marker in beats relative to 1.1.1
• .end_marker - ( float , READ/WRITE ) - End marker in beats relative to 1.1.1
• .loop_start - ( float , READ/WRITE ) - Loop start in beats relative to 1.1.1
• .loop_end - ( float , READ/WRITE ) - Loop end in beats relative to 1.1.1
• .hidden_loop_start - ( float , READ/WRITE ) - Hidden loop start in beats relative to 1.1.1
• .hidden_loop_end - ( float , READ/WRITE ) - Hidden loop end in beats relative to 1.1.1
• .warp_markers - ( list[WarpMarker] , READ/WRITE ) - List of warp markers
• .warp_on - ( bool , READ/WRITE ) - Warping is on
• .sr - ( float , READ/WRITE ) - Sample rate of audio data

WarpMarker class:

• .seconds - ( float , READ/WRITE ) - Position in seconds in the audio data.
• .beats - ( float , READ/WRITE ) - Position in "beats" (typically quarter note) relative to 1.1.1

If loop_on is false, then loop_start will equal the start_marker, and loop_end will equal the end_marker.

Example

import abletonparsing

import librosa
import soundfile as sf
import pyrubberband as pyrb

bpm = 130.
audio_path = 'drums.wav'
clip_path = audio_path + '.asd'

audio_data, sr = librosa.load(audio_path, sr=None, mono=False)
num_samples = audio_data.shape[1]

clip = abletonparsing.Clip(clip_path, sr, num_samples)

time_map = clip.get_time_map(bpm)

# Time-stretch the audio to the requested bpm.
output_audio = pyrb.timemap_stretch(audio_data.transpose(), sr, time_map)

with sf.SoundFile('output.wav', 'w', sr, 2, 'PCM_24') as f:
	f.write(output_audio)