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Python bindings for libsamplerate based on CFFI and NumPy

Project description

This is a wrapper around Erik de Castro Lopo’s libsamplerate (aka Secret Rabbit Code) for high-quality sample rate conversion.

It implements all three APIs available in libsamplerate:

  • Simple API: for resampling a large chunk of data with a single library call
  • Full API: for obtaining the resampled signal from successive chunks of data
  • Callback API: like Full API, but input samples are provided by a callback function

Library calls to libsamplerate are performed using CFFI.


$ pip install samplerate

Binaries of libsamplerate for macOS and Windows (32 and 64 bit) are included and used if not present on the system.


import numpy as np
import samplerate

# Synthesize data
fs = 1000.
t = np.arange(fs * 2) / fs
input_data = np.sin(2 * np.pi * 5 * t)

# Simple API
ratio = 1.5
converter = 'sinc_best'  # or 'sinc_fastest', ...
output_data_simple = samplerate.resample(input_data, ratio, converter)

# Full API
resampler = samplerate.Resampler(converter, channels=1)
output_data_full = resampler.process(input_data, ratio, end_of_input=True)

# The result is the same for both APIs.
assert np.allclose(output_data_simple, output_data_full)

# See `samplerate.CallbackResampler` for the Callback API, or
# `examples/` for an example.

See samplerate.resample, samplerate.Resampler, and samplerate.CallbackResampler in the API documentation for details.

See also

  • scikits.samplerate implements only the Simple API and uses Cython for extern calls. The resample function of scikits.samplerate and this package share the same function signature for compatiblity.
  • resampy: sample rate conversion in Python + Cython.


This project is licensed under the MIT license.

As of version 0.1.9, libsamplerate is licensed under the 2-clause BSD license.

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