pyBigWig
A package for accessing bigWig files using libBigWig
Decision gist · record as of 2026-08-14
Yes, if you work with bigWig or bigBed genomic data files. The package is stable, actively maintained, and has no known vulnerabilities. Install friction is moderate due to C compilation and system library requirements, but these are standard in bioinformatics environments. MIT license poses no restrictions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- libcurl (with curl-config) and zlib headers and libraries must be installed on your system before pip install will succeed.
- Medium install friction due to C extension compilation requiring libcurl and zlib headers and libraries.
- Package is actively maintained with recent releases and has been stable since 2015.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute this package freely with minimal restrictions.
last release 2026-01-14 (212 days) · last repo commit 2026-07-22 · 250 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 164,324 downloads/mo, #10,553 on PyPI
Alternatives
Verify before relying
pip install pybigwig
import pyBigWig
bw = pyBigWig.open("file.bw")
stats = bw.stats("chr1", 0, 3)
bw.close()- Whether numpy integration (mentioned in description) is optional or required at runtime
- Performance characteristics for large-scale genomic queries or remote file streaming
What it is and what it does
pyBigWig is a Python wrapper around libBigWig that lets you read and write bigWig and bigBed files—standard formats for storing genomic coordinate data and associated numeric values. It handles both local files and remote access over HTTP, making it useful for working with public genome browser datasets. The package is implemented as a C extension for performance, so it compiles at install time and requires system libraries.
You use it to open files, query summary statistics (mean, max, min, coverage, standard deviation) over genomic ranges, retrieve individual base values, and access interval data. For writing, you create a new file, add a header with chromosome information, and append intervals with values. The package supports exact or approximate statistics via zoom levels, and integrates with numpy for efficient array operations.
Use it for
- Query mean coverage or peak values across genomic regions from public datasets
- Extract base-level signal data for a chromosome range to feed into downstream analysis
- Create bigWig files from interval-value data for visualization in genome browsers
- Compute summary statistics (min/max/std) over binned intervals for rapid region comparisons
- Access remote bigBed files without downloading entire files locally
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with bigWig or bigBed genomic data files.
The package is stable, actively maintained, and has no known vulnerabilities. Install friction is moderate due to C compilation and system library requirements, but these are standard in bioinformatics environments. MIT license poses no restrictions.
Install
pybigwig on PyPI
Before you install
Medium install friction due to C extension compilation requiring libcurl and zlib headers and libraries. Package is actively maintained with recent releases and has been stable since 2015.
libcurl (with curl-config) and zlib headers and libraries must be installed on your system before pip install will succeed.
License in practice
MIT license is permissive; you may use, modify, and distribute this package freely with minimal restrictions.
Quickstart
pip install pybigwig
import pyBigWig
bw = pyBigWig.open("file.bw")
stats = bw.stats("chr1", 0, 3)
bw.close()Verify before relying
- Whether numpy integration (mentioned in description) is optional or required at runtime
- Performance characteristics for large-scale genomic queries or remote file streaming
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 212 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 164,324 / month, #10,553 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI ApprovedOperating System :: MacOSOperating System :: POSIXOperating System :: UnixProgramming Language :: CProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPython |
Evidence: pybigwig-0.3.25-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pybigwig-0.3.25-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pybigwig-0.3.25-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pybigwig-0.3.25-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; pybigwig-0.3.25-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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