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https://github.com/vokimon/python-wavefile
Pythonic access to audio files
https://github.com/vokimon/python-wavefile
Last synced: 13 days ago
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Pythonic access to audio files
- Host: GitHub
- URL: https://github.com/vokimon/python-wavefile
- Owner: vokimon
- Created: 2012-10-11T15:44:58.000Z (about 12 years ago)
- Default Branch: master
- Last Pushed: 2023-11-13T21:40:41.000Z (about 1 year ago)
- Last Synced: 2024-04-16T06:50:17.250Z (7 months ago)
- Language: Python
- Size: 1.12 MB
- Stars: 57
- Watchers: 10
- Forks: 14
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGES.md
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README
# ![python-wavefile](docs/python-wavefile-banner.svg)
[![CI](https://github.com/vokimon/python-wavefile/actions/workflows/main.yml/badge.svg)](https://github.com/vokimon/python-wavefile/actions/workflows/main.yml)
[![Coverage Status](https://coveralls.io/repos/vokimon/python-wavefile/badge.png?branch=master)](https://coveralls.io/r/vokimon/python-wavefile?branch=master)
[![PyPi Downloads](https://img.shields.io/pypi/dm/wavefile.svg)](https://pypi.python.org/pypi/wavefile)
[![PyPi Version](https://img.shields.io/pypi/v/wavefile.svg)](https://pypi.python.org/pypi/wavefile)Pythonic libsndfile wrapper to read and write audio files.
## Features
- Wave file resources open and close as context managers (`with`)
- Property accessors for format, channels, length, sample rate... and metadata (ID3...)
- Real multichannel (not just mono/stereo, but also surround, ambisonics and virtually any number of channels)
- All libsndfile formats supported, floating point encodings used by default
- Numpy based interface
- Generators for efficient block-by-block access
- Alternative Matlab-like whole-file interface. Less efficient, but convenient for quick and dirty scripts.
- Shortened constant names for formats (Using namespaces instead of prefixes)
- Tools for listing available formats
- Transparent Unicode handling for filenames and text strings
- No module compilation required (wraps the dll using ctypes)
- Compatible with Python >= 3.8You can find the latest version at:
https://github.com/vokimon/python-wavefile- [Version history](CHANGES.md)
- [Wish list](TODO.md)
- [Installation](#installation)
- [Examples](#examples)
- [Writing example](#writing-example)
- [Playback example (using PyAudio)](#playback-example-using-pyaudio)
- [Processing example](#processing-example)
- [Whole file (slow) processing](#whole-file-slow-processing)## Installation
[![Latest Version](https://img.shields.io/pypi/v/wavefile.svg)](https://pypi.python.org/pypi/wavefile/)
[![Supported Python Versions](https://img.shields.io/pypi/pyversions/wavefile.svg)](https://pypi.python.org/pypi/wavefile/)### Binary dependencies
Python dependencies are managed by the setup.py script.
But still there are a couple of binary dependencies.
In Debian/Ubuntu, you can install them by casting:```bash
sudo apt-get install -y libsndfile1 portaudio19-dev
```
PortAudio and its Python wrapper, PyAudio, are just required in order to run the examples.### Using PyPi
```bash
pip install wavefile
```### From sources
If you want to develop, installing editable is recomended. From the source directory:
```bash
pip install -e .
```## Examples
### Whole file (slow) processing
Writing and reading whole audio files (like Mathlab primitives do)
is not as efficient than block based processing to process long audios.
But it could be quite convenient on occassions to have quickly something working.```python
import wavefile
import numpy as npdef sinusoid(samples, f, samplerate=44100):
return np.sin( np.linspace(0, 2*np.pi*f*samples/samplerate, samples))[:,np.newaxis]def channels(*args):
return np.hstack(args).Taudio = channels(
sinusoid(100000, 440),
sinusoid(100000, 880),
sinusoid(100000, 1760),
)wavefile.save("sinusoid.wav", audio, 44100)
loadedsamplerate, loaded = wavefile.load("sinusoid.wav")
loaded.shape() # 3, 100000
```
### Block writing example
```python
from wavefile import WaveWriter, Format
import numpy as npBUFFERSIZE = 512
NCHANNELS = 2with WaveWriter(
'synth.ogg',
channels=NCHANNELS,
format=Format.OGG|Format.VORBIS,
) as w:
w.metadata.title = "Some Noise"
w.metadata.artist = "The Artists"
data = np.zeros((NCHANNELS,BUFFERSIZE), np.float32)
for x in range(256):
# First channel: Saw wave sweep
data[0,:] = (x*np.arange(BUFFERSIZE, dtype=np.float32)%BUFFERSIZE/BUFFERSIZE)
# Second channel: Modulated square wave
data[1,BUFFERSIZE-x*2:] = 1
data[1,:BUFFERSIZE-x*2] = -1# Write it down
w.write(data)
```### Block playback example (using pyaudio)
```python
import pyaudio, sys
from wavefile import WaveReaderp = pyaudio.PyAudio()
with WaveReader(sys.argv[1]) as r:# Print info
print("Title: {r.metadata.title}")
print("Artist: {r.metadata.artist}")
print(f"Channels: {r.channels}")
print(f"Format: 0x{r.format:x}")
print(f"Sample Rate: {r.samplerate}")# open pyaudio stream
stream = p.open(
format = pyaudio.paFloat32,
channels = r.channels,
rate = r.samplerate,
frames_per_buffer = 512,
output = True,
)# iterator interface (reuses one array)
# beware of the frame size, not always 512, but 512 at least
for frame in r.read_iter(size=512):
stream.write(frame.flatten(), frame.shape[1])
sys.stdout.write("."); sys.stdout.flush()stream.close()
```### Block processing example
```python
import sys
from wavefile import WaveReader, WaveWriterwith WaveReader(sys.argv[1]) as r:
with WaveWriter(
'output.wav',
channels=r.channels,
samplerate=r.samplerate,
) as w:
w.metadata.title = r.metadata.title + " II"
w.metadata.artist = r.metadata.artistfor data in r.read_iter(size=512):
sys.stdout.write("."); sys.stdout.flush()
w.write(.8*data)
``````read_iter``` simplifies the code by transparently:
- allocating the data block for you,
- reusing it for each block, and
- slicing it when the last incomplete block arrives.## Arquitecture
The library consists of two layers
- `libsndfile.py`: a plain ctypes based wrapper that provides 1:1 access to the functions of the sndlib library
- `wavefile.py`: an interface layer that provides the Pythonic sugar calling the former one.## Existing alternatives (what i like and dislike)
This is 'yet another' wrapper for sndfile.
A lot of them appeared just because the standard
'wave' module is quite limited on what and how it does.
But none of the wrappers I found around fully suit my
needs and that's because I wrote this small and incomplete one,
to fit my needs.
So this is a summary of what I found, just in case it is useful to anyone.- Standard 'wave' module:
- http://docs.python.org/library/wave.html
- I think this is the main reason why there are many
wrappers around. The standard module to do wave file
loading is crap.
- Based on sndfile but it just writes .wav files.
- It lacks support for floating point samples, patch provided
but ignored see http://bugs.python.org/issue1144504
- unreadable getX() methods instead of properties.
- no numpy integration
- generators, context managers... what?
- no whole-file shortcuts provided- scikits.audiolab
- git clone https://github.com/cournape/audiolab
- Cython based + python layer
- Dual interface: matlab like and OO
- Property accessors to samplerate...
- Numpy integration
- Inplace processing
- Not in Ubuntu
- Within a big library- pysndfile
- http://savannah.nongnu.org/projects/pysndfile/
- Swig based wrapper.
- Direct lib library + python object wrappers
- Unusable because it is not finished (empty read/write methods in wrapper!)- libsndfile-python
- http://code.google.com/p/libsndfile-python/
- svn checkout http://libsndfile-python.googlecode.com/svn/trunk/ libsndfile-python-read-only
- Implemented in CPython
- numpy support
- cpython purely wraps the library
- wrappers build the interface
- double layered lib and pythonic interface (not that pythonic but supports numpy)
- Implements 'command' sndfile interface- libsndfilectypes
- http://code.google.com/p/pyzic/wiki/LibSndFilectypes
- ctypes based wrapper: no compilation required
- numpy supported
- Windows only setup (fixable)
- Long access to constants
- Not inplace read (creates an array every time)python-wavefile reuses most of the libsndfilectypes ctypes wrapper,
as not requiring module compilation was seen as a good point.
A pythonic layer was added on the top of it.