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pybigtools

Python bindings to the Bigtools Rust library for high-performance BigWig and BigBed I/O

Worth itPyPI Bio-InformaticsReleased Jun 2026636.4K downloads / moMITPlatform wheel

Decision gist · record as of 2026-08-14

platform wheels — pybigtools-0.3.0-cp310-cp310-macosx_10_12_x86_64.whl · pybigtools-0.3.0-cp310-cp310-macosx_11_0_arm64.whl · pybigtools-0.3.0-cp310-cp310-manylinux_2_28_aarch64.whl
v0.3.0 · released 2026-06-04 · Python >=3.8 · 1 runtime deps: numpy

Yes. pybigtools is actively maintained, has no known vulnerabilities, and offers a performant, low-friction way to handle bigWig and bigBed files in Python. The MIT license and wide platform support make it suitable for research and production use. Install it if you work with genomic interval data in these formats.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python >=3.8; compiled wheels available for Python 3.10, 3.11, 3.12 on common platforms.
  • Medium install friction due to compiled wheels; pre-built binaries available for Python 3.10, 3.11, 3.12 across macOS, Linux, and Windows.
  • Active maintenance with a release 71 days ago and no known vulnerabilities.

License · maintenance · safety

MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; suitable for most projects without licensing concerns.

last release 2026-06-04 (71 days) · last repo commit 2026-08-14 · 120 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 636,421 downloads/mo, #5,627 on PyPI

Verify before relying

pip install pybigtools

import pybigtools

reader = pybigtools.BigWigRead('test.bigWig')
intervals = reader.get_interval('chr1', 0, 10000)
  • Exact performance improvements over UCSC tools and memory usage characteristics are not quantified in the fact sheet.
  • Whether async/await optimizations are exposed to Python callers or used only internally is unclear.
  • API stability and backward-compatibility guarantees for Beta-stage releases are not documented.
  • Support for Python 3.13 wheels is listed in friction evidence but not confirmed in requires_python metadata.
Same gist for agents: .md · .json

What it is and what it does

pybigtools is a Python binding to a Rust-based genomics library designed to read and write bigWig and bigBed files—standard formats for storing large-scale genomic interval data. It wraps the Rust bigtools crate using PyO3, inheriting Rust's performance and memory efficiency while exposing a Python API. The library depends only on numpy and is distributed as pre-compiled wheels for multiple Python versions on macOS, Linux, and Windows, reducing installation friction.

The package targets bioinformaticians and genomics researchers who need to parse or generate bigWig and bigBed files efficiently. It provides methods to read intervals from genomic coordinates, merge multiple bigWigs, and convert between formats (bigWig to bedGraph, bed to bigBed, etc.). The underlying Rust implementation uses async/await for multi-core computation where applicable, and the library is designed to minimize memory footprint—key constraints in genomics workflows that often process large datasets.

Use it for

  • Extract genomic intervals from a bigWig file over a set of genomic regions for statistical analysis.
  • Convert bedGraph files to bigWig format for efficient storage and sharing of genome-wide signal tracks.
  • Merge multiple bigWig files into a single file or bedGraph for comparative genomics studies.
  • Query bigBed files to retrieve annotated genomic features and their metadata.
  • Build bioinformatics pipelines that read/write UCSC-compatible bigWig and bigBed files.

Worth the install?

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

Worth it

Yes.

pybigtools is actively maintained, has no known vulnerabilities, and offers a performant, low-friction way to handle bigWig and bigBed files in Python. The MIT license and wide platform support make it suitable for research and production use. Install it if you work with genomic interval data in these formats.

Install

pybigtools on PyPI

Before you install

Medium install friction due to compiled wheels; pre-built binaries available for Python 3.10, 3.11, 3.12 across macOS, Linux, and Windows. Active maintenance with a release 71 days ago and no known vulnerabilities.

Requires Python >=3.8; compiled wheels available for Python 3.10, 3.11, 3.12 on common platforms.

License in practice

MIT license permits commercial and private use with minimal restrictions; suitable for most projects without licensing concerns.

Quickstart

pip install pybigtools

import pybigtools

reader = pybigtools.BigWigRead('test.bigWig')
intervals = reader.get_interval('chr1', 0, 10000)

Verify before relying

  • Exact performance improvements over UCSC tools and memory usage characteristics are not quantified in the fact sheet.
  • Whether async/await optimizations are exposed to Python callers or used only internally is unclear.
  • API stability and backward-compatibility guarantees for Beta-stage releases are not documented.
  • Support for Python 3.13 wheels is listed in friction evidence but not confirmed in requires_python metadata.

Package facts

LicenseMIT permissive
Python supportSupports the current Python release >=3.8
Install frictionMedium. Platform-specific wheel
Runtime dependencies
1 package
numpy
MaintenanceActively maintained 71 days since the last release
Last repo commit
First released
Downloads636,421 / month, #5,627 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: RustTopic :: Scientific/Engineering :: Bio-Informatics

Evidence: pybigtools-0.3.0-cp310-cp310-macosx_10_12_x86_64.whl; pybigtools-0.3.0-cp310-cp310-macosx_11_0_arm64.whl; pybigtools-0.3.0-cp310-cp310-manylinux_2_28_aarch64.whl; pybigtools-0.3.0-cp310-cp310-manylinux_2_28_x86_64.whl; pybigtools-0.3.0-cp310-cp310-win32.whl; pybigtools-0.3.0-cp310-cp310-win_amd64.whl; pybigtools-0.3.0-cp311-cp311-macosx_10_12_x86_64.whl; pybigtools-0.3.0-cp311-cp311-macosx_11_0_arm64.whl; pybigtools-0.3.0-cp311-cp311-manylinux_2_28_aarch64.whl; pybigtools-0.3.0-cp311-cp311-manylinux_2_28_x86_64.whl; pybigtools-0.3.0-cp311-cp311-win32.whl; pybigtools-0.3.0-cp311-cp311-win_amd64.whl; pybigtools-0.3.0-cp312-cp312-macosx_10_12_x86_64.whl; pybigtools-0.3.0-cp312-cp312-macosx_11_0_arm64.whl; pybigtools-0.3.0-cp312-cp312-manylinux_2_28_aarch64.whl; pybigtools-0.3.0-cp312-cp312-manylinux_2_28_x86_64.whl; pybigtools-0.3.0-cp312-cp312-win32.whl; pybigtools-0.3.0-cp312-cp312-win_amd64.whl; pybigtools-0.3.0-cp313-cp313-macosx_10_12_x86_64.whl; pybigtools-0.3.0-cp313-cp313-macosx_11_0_arm64.whl

Tags

Capabilities
bigwig bigbed file I/Ogenomic data format readerbioinformatics file handlinghigh-performance genomicsucsc bigwig parserrust-backed genomics librarybedgraph conversion tools
Topics
bioinformaticsgenomicsrust-backed
PyPI keywords
bigwigbigbedbbibioinformaticsgenomicskentucscrust

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See also pyBigWig · pybedtools · setuptools-rust · rustworkx · pysylph · deepbiop · pysam · py-bip39-bindings · pyranges · moviepilot-rust