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pcodec

Good compression for numerical sequences

With conditionsPyPI Scientific/EngineeringReleased Aug 2026120.4K downloads / moPlatform wheel

Decision gist · record as of 2026-08-14

platform wheels — pcodec-1.0.3-cp310-cp310-macosx_10_12_x86_64.whl · pcodec-1.0.3-cp310-cp310-macosx_11_0_arm64.whl · pcodec-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
v1.0.3 · released 2026-08-01 · 1 runtime deps: numpy

Yes, with conditions. Install if you need specialized compression for numerical sequences and can verify the license terms in the repository. The package is actively maintained, has no known vulnerabilities, and offers a clean API. However, the undeclared license is a blocker for any project with legal compliance requirements; resolve that first. Also confirm that Python 3.10–3.12 wheels cover your deployment targets.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires numpy; compiled extension wheels are provided for Python 3.10–3.12 only.
  • Medium install friction due to compiled wheels; prebuilt binaries available for Python 3.10–3.12 across macOS, Linux (x86_64, ARM, ARMv7, i686), and Windows.
  • Active maintenance with a release 13 days old and recent commits.

License · maintenance · safety

(unclear) — License status is unclear—no SPDX identifier or raw license text is declared in package metadata. Verify the actual license terms in the repository before adopting in proprietary or copyleft-sensitive projects.

last release 2026-08-01 (13 days) · last repo commit 2026-08-08 · 495 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 120,385 downloads/mo, #12,027 on PyPI

Verify before relying

import numpy as np
from pcodec import standalone, ChunkConfig

nums = np.random.normal(size=1000000)
compressed = standalone.simple_compress(nums, ChunkConfig())
recovered = standalone.simple_decompress(compressed)
  • Actual license terms and conditions—metadata declares neither SPDX nor raw license text.
  • Python version support beyond 3.10–3.12 (wheels not listed for 3.9 or 3.13+).
  • Compression ratio and speed benchmarks relative to standard codecs (zlib, lz4, etc.).
  • Whether lossless recovery is guaranteed for all numerical types or only specific dtypes.
Same gist for agents: .md · .json

What it is and what it does

Pcodec is a Python binding to a Rust-based codec designed specifically for compressing numerical sequences. It takes numpy arrays, applies a specialized compression algorithm tuned for numerical data patterns, and produces a byte string that can be decompressed back to the original array. The package exposes a minimal API: `simple_compress()` and `simple_decompress()` functions that handle the core workflow, plus configuration options via `ChunkConfig`.

The package depends only on numpy and is distributed as precompiled wheels for modern Python versions (3.10–3.12) across common platforms. Maintenance is active, with recent releases and repository commits. However, the license status is undeclared in the package metadata, which is a significant gap for adoption in commercial or legally sensitive contexts.

Use it for

  • Compress large numpy arrays of floating-point or integer data for storage or transmission.
  • Reduce memory footprint of time-series or sensor data in data pipelines.
  • Archive numerical datasets with better compression than generic algorithms.
  • Embed numerical compression in scientific computing workflows that already use numpy.
  • Benchmark or compare specialized numerical codecs against standard compression libraries.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, with conditions.

Install if you need specialized compression for numerical sequences and can verify the license terms in the repository. The package is actively maintained, has no known vulnerabilities, and offers a clean API. However, the undeclared license is a blocker for any project with legal compliance requirements; resolve that first. Also confirm that Python 3.10–3.12 wheels cover your deployment targets.

Install

pcodec on PyPI

Before you install

Medium install friction due to compiled wheels; prebuilt binaries available for Python 3.10–3.12 across macOS, Linux (x86_64, ARM, ARMv7, i686), and Windows. Active maintenance with a release 13 days old and recent commits.

Requires numpy; compiled extension wheels are provided for Python 3.10–3.12 only.

License in practice

License status is unclear—no SPDX identifier or raw license text is declared in package metadata. Verify the actual license terms in the repository before adopting in proprietary or copyleft-sensitive projects.

Quickstart

import numpy as np
from pcodec import standalone, ChunkConfig

nums = np.random.normal(size=1000000)
compressed = standalone.simple_compress(nums, ChunkConfig())
recovered = standalone.simple_decompress(compressed)

Verify before relying

  • Actual license terms and conditions—metadata declares neither SPDX nor raw license text.
  • Python version support beyond 3.10–3.12 (wheels not listed for 3.9 or 3.13+).
  • Compression ratio and speed benchmarks relative to standard codecs (zlib, lz4, etc.).
  • Whether lossless recovery is guaranteed for all numerical types or only specific dtypes.

Package facts

LicenseNot declared unclear
Python supportNot specified
Install frictionMedium. Platform-specific wheel
Runtime dependencies
1 package
numpy
MaintenanceActively maintained 13 days since the last release
Last repo commit
First released
Downloads120,385 / month, #12,027 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14

Evidence: pcodec-1.0.3-cp310-cp310-macosx_10_12_x86_64.whl; pcodec-1.0.3-cp310-cp310-macosx_11_0_arm64.whl; pcodec-1.0.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; pcodec-1.0.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; pcodec-1.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pcodec-1.0.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl; pcodec-1.0.3-cp310-cp310-win_amd64.whl; pcodec-1.0.3-cp311-cp311-macosx_10_12_x86_64.whl; pcodec-1.0.3-cp311-cp311-macosx_11_0_arm64.whl; pcodec-1.0.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; pcodec-1.0.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; pcodec-1.0.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pcodec-1.0.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl; pcodec-1.0.3-cp311-cp311-win_amd64.whl; pcodec-1.0.3-cp312-cp312-macosx_10_12_x86_64.whl; pcodec-1.0.3-cp312-cp312-macosx_11_0_arm64.whl; pcodec-1.0.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; pcodec-1.0.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; pcodec-1.0.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pcodec-1.0.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl

Tags

Capabilities
numerical data compressioncompress numpy arrayscodec for time serieslossless numerical compressionsequence compression libraryfast array compressionnumpy compression codec
Topics
compressionnumerical-datarust-binding
PyPI keywords
compressionnumerical

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See also listcrunch · python-neo-lzf · ncompress · lilcom · descript-audio-codec · numcodecs · encodec · texture2ddecoder · astc-encoder-py · blosc