lasio
Read/write well data from Log ASCII Standard (LAS) files
Decision gist · record as of 2026-08-14
Yes, if you work with LAS well-log data. The package is stable, permissively licensed, has low install friction, and carries no known vulnerabilities. The aging maintenance status (378 days since last release) is a minor concern for a mature I/O library but worth monitoring if you depend on active development. Consider welly if you need higher-level well-data abstractions beyond reading and writing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later; numpy must be installed.
- Low install friction with a single runtime dependency on numpy.
- Package is aging (378 days since last release) but maintains broad Python version support from 3.9 through 3.13 and carries Beta stability classification.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions—you may use, modify, and distribute lasio freely provided you include the license notice.
last release 2025-08-01 (378 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 291,039 downloads/mo, #7,975 on PyPI
Alternatives
Verify before relying
pip install lasio
import lasio
las = lasio.read("sample.las")
data = las['DEPT'] # access curve as numpy array
metadata = las.curves # access CurveItem objects with units and descriptions- Performance characteristics for large LAS files (documentation notes lasio is not particularly fast).
- Current status of LAS 3 support mentioned as 'being worked on' in the description.
What it is and what it does
lasio is a Python library that reads and writes Log ASCII Standard (LAS) files, a format used to store borehole data such as geophysical, geological, and petrophysical logs. It implements support for LAS versions 1.2 and 2.0 as published by the Canadian Well Logging Society and is designed to handle real-world LAS files that may contain common errors and non-compliant formatting. The package exposes data both as raw numpy arrays and as CurveItem objects with associated metadata (units, descriptions, mnemonics), and provides access to header sections (version, well information, parameters) as HeaderItem objects.
The library is primarily for I/O operations—reading LAS files from disk, file-like objects, or URLs, and writing them back. It does not provide higher-level curve analysis or well project management; the documentation explicitly recommends considering welly for broader well-data workflows. lasio stopped supporting Python 2.7 in August 2020 and currently requires Python 3.9 or later with numpy as its sole required dependency.
Use it for
- Import borehole geophysical log data from LAS files into numpy arrays for numerical analysis and visualization.
- Parse well logging metadata (depths, units, curve descriptions) from LAS headers for data cataloging and validation.
- Convert LAS files to pandas DataFrames or export to Excel for spreadsheet-based workflows.
- Build LAS files programmatically from well data and write them back to disk in compliant format.
- Handle non-standard or malformed LAS files that strict parsers may reject.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with LAS well-log data.
The package is stable, permissively licensed, has low install friction, and carries no known vulnerabilities. The aging maintenance status (378 days since last release) is a minor concern for a mature I/O library but worth monitoring if you depend on active development. Consider welly if you need higher-level well-data abstractions beyond reading and writing.
Install
lasio on PyPI
Before you install
Low install friction with a single runtime dependency on numpy. Package is aging (378 days since last release) but maintains broad Python version support from 3.9 through 3.13 and carries Beta stability classification.
Requires Python 3.9 or later; numpy must be installed.
License in practice
MIT license permits commercial and private use with minimal restrictions—you may use, modify, and distribute lasio freely provided you include the license notice.
Quickstart
pip install lasio
import lasio
las = lasio.read("sample.las")
data = las['DEPT'] # access curve as numpy array
metadata = las.curves # access CurveItem objects with units and descriptionsVerify before relying
- Performance characteristics for large LAS files (documentation notes lasio is not particularly fast).
- Current status of LAS 3 support mentioned as 'being worked on' in the description.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Aging 378 days since the last release |
| First released | |
| Downloads | 291,039 / month, #7,975 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: Customer ServiceIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: End Users/DesktopIntended Audience :: Other AudienceIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: System :: Filesystems |
Evidence: lasio-0.32-py3-none-any.whl
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See also laspy · laszip · RoffIO · fitsio · plyfile · pyshp · aiofile · geoh5py · texttable · pylightxl