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laspy

Native Python ASPRS LAS read/write library

laspy v2.7.0 1.9M downloads/30d#3,417 on PyPI505
Permissive license BSD-2-Clause Active released

What it is and what it does

Laspy is a native Python library for working with ASPRS LAS and LAZ LiDAR point cloud files. It handles the full lifecycle of LAS data: reading files into memory, filtering and modifying point records, and writing results back to disk. The library supports both complete file operations and streamed/chunked processing for handling large datasets that may not fit in memory at once. It can read file headers and metadata without loading all points, and supports COPC (Cloud Optimized Point Cloud) format both from local files and over HTTPS.

The package depends only on numpy for its core functionality, keeping installation simple and lightweight. Optional features like LAZ compression and CRS coordinate transformation require additional packages (lazrs/laszip and pyproj respectively) that can be installed separately. The library is actively maintained, marked as Production/Stable, and widely used in geospatial and LiDAR processing workflows.

Use it for:

  • Filter and extract specific point classes (e.g., ground, vegetation) from large LAS/LAZ files for analysis.
  • Convert between LAS and LAZ formats or reproject point cloud coordinates using CRS support.
  • Process multi-gigabyte LiDAR datasets in chunks to avoid loading entire files into memory.
  • Read LAS file headers and metadata to inspect point formats and record counts before full processing.
  • Build geospatial data pipelines that read, transform, and write LiDAR point clouds programmatically.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Laspy reads, modifies, and writes LAS and LAZ LiDAR point cloud files, with support for streamed/chunked processing, COPC format, and optional CRS transformation via pyproj.

Yes. Laspy is the standard Python library for LAS/LAZ file handling, actively maintained, Production/Stable, with minimal dependencies and no known vulnerabilities. Install it if you work with LiDAR data or ASPRS point cloud formats. The only consideration is the Python 3.10+ requirement; if you're on an older version, you'll need to upgrade.

Install

laspy on PyPI

pip

pip install laspy

uv

uv add laspy

poetry

poetry add laspy

Installing laspy

Before you install

Low friction: pure Python wheel with only numpy as a runtime dependency. Active maintenance (last commit 2026-05-30), marked Production/Stable, and in the top 5000 PyPI packages by download volume.

License in practice

BSD-2-Clause permissive license allows commercial and private use with minimal restrictions; suitable for most projects.

Quickstart

pip install laspy

import laspy

las = laspy.read('filename.las')
las.points = las.points[las.classification == 2]
las.write('ground.laz')

Requires Python 3.10 or later. LAZ support requires optional lazrs or laszip backend installation.

Verify before relying

  • Performance characteristics and memory footprint when processing very large point clouds.
  • Compatibility details with specific LAS/LAZ versions and COPC implementations.
  • Whether COPC over HTTPS requires requests to be installed as a runtime dependency or only when that feature is used.

Package facts

License BSD-2-Clause (permissive)
Python support supports the current Python release (>=3.10)
Install friction low — pure-Python wheel
Runtime dependencies 1 — numpy
Maintenance actively maintained — 212 days since the last release
Last repo commit
First released
Downloads 1,941,539/month — #3,417 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: laspy-2.7.0-py3-none-any.whl

Keywords: gis, las, lidar

Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: BSD LicenseOperating System :: OS IndependentProgramming Language :: PythonTopic :: Scientific/Engineering :: GIS

Tags

lidar las laz file readerpoint cloud processing pythonlas file manipulationlidar data formatlas laz conversionstreamed lidar readingpoint cloud filtering
lidargeospatialpoint-cloud

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