pcodec


Namepcodec JSON
Version 0.3.3 PyPI version JSON
download
home_pageNone
SummaryGood compression for numerical sequences
upload_time2025-02-13 22:37:30
maintainerNone
docs_urlNone
authorNone
requires_pythonNone
licenseApache-2.0
keywords compression numerical
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            <div style="text-align:center">
  <img alt="Pco logo: a pico-scale, compressed version of the Pyramid of Khafre in the palm of your hand" src="https://raw.githubusercontent.com/mwlon/pcodec/cac902e714077426d915f4fc397508b187c72380/images/logo.svg" width="160px">
</div>

[![pypi.org][pypi-badge]][pypi-url]

[pypi-badge]: https://img.shields.io/pypi/v/pcodec.svg

[pypi-url]: https://pypi.org/project/pcodec/

# Pcodec Python API

Pcodec is a codec for numerical sequences. Example usage:

```python
>>> from pcodec import standalone, ChunkConfig
>>> import numpy as np
>>> 
>>> np.random.seed(0)
>>> nums = np.random.normal(size=1000000)
>>> 
>>> # compress
>>> compressed = standalone.simple_compress(nums, ChunkConfig())
>>> print(f'compressed to {len(compressed)} bytes')
compressed to 6946258 bytes
>>> 
>>> # decompress
>>> recovered = standalone.simple_decompress(compressed)
>>> 
>>> np.testing.assert_array_equal(recovered, nums)

```

For pcodec's uses, design, and benchmarks, [see the main repo](https://github.com/mwlon/pcodec).

At the moment, we don't have sphinx + a website set up, so run `help(pcodec)`
(or whatever module name) in Python to read pcodec's documentation.


            

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