Skip to main content

compressbench

Benchmark compression algorithms on Parquet datasets.

Why

Compression settings affect performance, storage cost, and latency — but most data engineers inherit defaults without testing.
compressbench lets you benchmark compression ratio, compression speed, and decompression speed across algorithms using your own Parquet files.

Features

  • Accepts local Parquet files as input.
  • Supports gzip and snappy.
  • Outputs:
    • Compression ratio.
    • Compression time.
    • Decompression time.
  • CLI built with Typer.
  • Unit tests with pytest.

Installation

pip install compressbench

Usage

compressbench input.parquet --algorithms gzip snappy If --algorithms is omitted, runs benchmarks for all available algorithms.

Example Output Algorithm: gzip Compression ratio: 2.91 Compression time: 0.43s Decompression time: 0.12s

Algorithm: snappy Compression ratio: 1.67 Compression time: 0.12s Decompression time: 0.05s

CLI Options

input.parquet Path to the Parquet file to benchmark. --algorithms List of algorithms to test (gzip, snappy). --level Not supported in v0.1.0. Reserved for future versions.

Roadmap

See ROADMAP.md for planned features.

License

MIT

Metadata

Release files for compressbench 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for compressbench 0.1.0
File Size Uploaded Provenance
compressbench-0.1.0.tar.gz 5.1 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for compressbench 0.1.0
File Interpreter ABI Platform
compressbench-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 10.4 kB

Release files / compressbench-0.1.0.tar.gz

Download URL compressbench-0.1.0.tar.gz
Size 5.1 kB
Tags Source
SHA-256 checksum
How to use checksums
41204ae22615ca25d59b68c65074fefc632270bd0c849690f34335ec23e9905f
BLAKE2b-256 checksum
How to use checksums
4555f6dc3b34a296c84f97f765aff73e3b1c20751555300b7d07a8521c1235ad
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.3

Release files / compressbench-0.1.0-py3-none-any.whl

Download URL compressbench-0.1.0-py3-none-any.whl
Size 5.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a9bc5fb5baa4494d2c611f9032d653b44279eaec398d4dd7f3cfcbd6ebb009a3
BLAKE2b-256 checksum
How to use checksums
234eef948c448b1103a800487c11d1e38c0e3485ff3c831b100f0c3a1d4c7d90
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.3

Security for compressbench 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page