wavtoolkit 1.0.3

File operations and other tools for working with .WAV files

wavtoolkit

wavtoolkit is a lightweight Python library for extracting and analyzing metadata from WAV files. Useful for inspecting audio files without diving into low-level byte handling. It uses wave_chunk_parser for parsing complex RIFF structures and pyloudnorm for loudness analysis.

Features

• Extracts key metadata:

  • Title, artist, category (from INFO and cart chunks)
  • Audio format (sample rate, channels, bit depth)
  • File properties (size, creation time, modification time)
  • Loudness metrics (Integrated LUFS, Peak)

• Lazy-loading design:

  • Metadata is parsed on-demand
  • Efficient and modular

• Simple API, ready for scripting

Installation

pip install wavtoolkit

Usage

import os
from wavtoolkit import WavFile

wavs = [WavFile(f) for f in os.listdir() if f.endswith(".wav")]

for wav in wavs:
  # Filename
  print('\n', wav.filename)
  
  # Title and duration
  print(f"    {wav}")
  
  # Loudness metrics (LUFS, Peak)
  for k, v in wav.loudness.items():
    print(f"    {k}: {v.item()}")
  
  # Metadata from INFO chunks
  for k, v in wav.metadata_info.items():
    v = v.decode() if isinstance(v, bytes) else v
    print(f"    [{k}] {v}")
  
  # Metadata from CART chunks
  print(f"    {wav.cart_metadata or ''}\n")
  

Example output:

Why wavtoolkit?

• Leverages existing libraries (wave_chunk_parser, pyloudnorm)
• No low-level hacks — just clean, high-level metadata access
• Modular design for integration into pipelines or tools

License

MIT

Credits

• wave_chunk_parser
• pyloudnorm

Coming Soon (?)

• Cue point parsing
• JSON metadata export