pyloudnorm
Implementation of ITU-R BS.1770-4 loudness algorithm in Python.
Decision gist · record as of 2026-08-14
Yes. The package solves a specific, well-defined problem (ITU-R BS.1770-4 loudness measurement) with low install friction, permissive licensing, and active maintenance. It is suitable for audio production, streaming, and broadcast workflows where loudness standardization is required. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires audio data as a numpy array with shape (samples, channels); audio must be loaded separately using soundfile or similar.
- Low install friction with only scipy and numpy as dependencies.
- The package is aging (222 days since last release) but the repository remains active with recent commits and 780 GitHub stars.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for most audio processing workflows.
last release 2026-01-04 (222 days) · last repo commit 2026-01-04 · 780 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,030,269 downloads/mo, #2,396 on PyPI
Alternatives
Verify before relying
import pyloudnorm as pyln
import numpy as np
meter = pyln.Meter(rate) # create meter for sample rate
audio = np.random.randn(samples, channels)
loudness = meter.integrated_loudness(audio)
print(f"Loudness: {loudness}")- Whether the package handles edge cases like mono audio or very short audio files gracefully
- Performance characteristics when processing large audio files or real-time streams
- Compatibility with other audio libraries beyond soundfile
What it is and what it does
pyloudnorm is a Python implementation of the ITU-R BS.1770-4 loudness metering standard, used in broadcast and audio production to measure perceived loudness. It wraps scipy and numpy to perform frequency weighting and loudness analysis on audio arrays, supporting both measurement and normalization workflows.
The package provides a Meter class that analyzes audio at a given sample rate, offering integrated loudness measurement, loudness range calculation per EBU Tech 3342, and peak/loudness normalization functions. It includes multiple filter implementations (BS.1770 standard, DeMan, Fenton/Lee variants, and Dash et al.) and allows customization of block size and custom IIR filters for specialized use cases.
Use it for
- Normalize podcast or streaming audio to broadcast-standard loudness levels before distribution
- Measure loudness range in music production to assess dynamic variation across a track
- Batch-process audio files to ensure consistent perceived volume across a catalog
- Implement loudness metering in audio editing or DAW plugins
- Validate audio compliance with streaming platform loudness requirements
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package solves a specific, well-defined problem (ITU-R BS.1770-4 loudness measurement) with low install friction, permissive licensing, and active maintenance. It is suitable for audio production, streaming, and broadcast workflows where loudness standardization is required. No known vulnerabilities.
Install
pyloudnorm on PyPI
Before you install
Low install friction with only scipy and numpy as dependencies. The package is aging (222 days since last release) but the repository remains active with recent commits and 780 GitHub stars.
Requires audio data as a numpy array with shape (samples, channels); audio must be loaded separately using soundfile or similar.
License in practice
MIT license permits commercial and private use with minimal restrictions, making it suitable for most audio processing workflows.
Quickstart
import pyloudnorm as pyln
import numpy as np
meter = pyln.Meter(rate) # create meter for sample rate
audio = np.random.randn(samples, channels)
loudness = meter.integrated_loudness(audio)
print(f"Loudness: {loudness}")Verify before relying
- Whether the package handles edge cases like mono audio or very short audio files gracefully
- Performance characteristics when processing large audio files or real-time streams
- Compatibility with other audio libraries beyond soundfile
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesscipynumpy |
| Maintenance | Aging 222 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,030,269 / month, #2,396 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.9Topic :: Multimedia :: Sound/AudioTopic :: Scientific/Engineering |
Evidence: pyloudnorm-0.2.0-py3-none-any.whl
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