Release v0.1.1 (What’s new?).
Welcome to compress Documentation#
compress provides a unified interface for various mature data compression algorithms. It supports algorithms from both the Python Standard Library and the community, offering a range of options for different compression needs.
Supported Algorithms
From Python Standard library
From Community (Additional Library Required)
snappy, from Google, lower compression ratio but super fast! (on MacOS, you need to install it via
brew install snappy, on Ubuntu, you needsudo apt-get install libsnappy-dev.lz4, lower ratio, super fast!
pyzstd, very fast!
Note: Community libraries are not installed by default with compress. To include them, use:
pip install compress[lz4,snappy,zstd]
These libraries require a C compiler. If you encounter issues installing the C compiler for your OS, refer to this tutorial.
Usage Example
import sys
import compress.api as compress
data = ("hello world" * 1000).encode("utf-8")
print(f"before: {sys.getsizeof(data)}")
data_compressed = compress.compress(
algo=compress.Algorithm.gzip,
data=data,
kwargs={"compresslevel": 9},
)
print(f"after: {sys.getsizeof(data_compressed)}")
Benchmark
This website provides comprehensive comparison and visualization. But how do you know how it works on your own production environment?.
compress comes with a tool to run benchmark test for All test case, All algorithm, All parameters, and you will get informative stats about ratio, compress/decompress speed in ascii table format. Then You are able to visualize it in the way you preferred.
To run benchmark test, just do:
pip install -r requirements-benchmark.txt
python ./benchmark/run_benchmark.py
Then you can find the result at benchmark/result.txt.
Install#
compress is released on PyPI, so all you need is to:
$ pip install compress
To upgrade to latest version:
$ pip install --upgrade compress