| Name | pcodec JSON |
| Version |
0.3.2
JSON |
| download |
| home_page | None |
| Summary | Good compression for numerical sequences |
| upload_time | 2024-11-23 18:00:16 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | None |
| license | Apache-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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