pypcd4
Read and write PCL .pcd files in python
Decision gist · record as of 2026-08-14
Yes. pypcd4 is actively maintained, has no known vulnerabilities, installs with low friction, and is licensed permissively. It fills a clear need for point cloud I/O in Python with modern syntax and ROS integration. Suitable for robotics, 3D perception, and scientific computing workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction; pure Python wheel with three runtime dependencies (numpy, pydantic, python-neo-lzf).
- Active maintenance with recent commits and stable production status.
License · maintenance · safety
permissive license (permissive) — BSD 3-Clause permissive license allows commercial and private use with attribution; no viral copyleft restrictions.
last release 2026-01-07 (219 days) · last repo commit 2026-07-11 · 113 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 85,364 downloads/mo, #13,927 on PyPI
Alternatives
Verify before relying
pip install pypcd4
from pypcd4 import PointCloud
import numpy as np
pc = PointCloud.from_path("point_cloud.pcd")
array = pc.numpy()
pc_filtered = pc[pc.pc_data["x"] > 0.5]
pc_filtered.save("filtered.pcd")- Whether ROS integration requires ROS to be installed and sourced, or if rosbags library alone suffices for reading/writing
- Performance characteristics when concatenating or filtering large point clouds (thousands or millions of points)
What it is and what it does
pypcd4 is a modern Python library for reading, writing, and manipulating Point Cloud Data (PCD) files. It provides a PointCloud class that wraps point data and supports conversion to and from NumPy arrays, filtering by slicing or boolean masks, concatenation of multiple clouds, and integration with ROS PointCloud2 messages. The library depends on numpy for array operations, pydantic for data validation, and python-neo-lzf for compression support.
Typical workflows include loading PCD files from disk, extracting specific fields or subsets of points, transforming the data via NumPy, and saving results back to PCD format. It is designed for robotics and 3D perception applications where point cloud data is common, and offers convenience methods for common operations like field selection and point filtering without requiring manual NumPy indexing.
Use it for
- Load a PCD file, filter points by spatial coordinates, and save the result for downstream processing.
- Convert between PCD and NumPy array formats to integrate point cloud data with machine learning pipelines.
- Merge multiple PCD files into a single point cloud using concatenation for multi-sensor fusion.
- Convert ROS PointCloud2 messages to PCD files for offline analysis or archival.
- Extract specific fields (e.g., x, y, z, intensity) from a point cloud for visualization or analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
pypcd4 is actively maintained, has no known vulnerabilities, installs with low friction, and is licensed permissively. It fills a clear need for point cloud I/O in Python with modern syntax and ROS integration. Suitable for robotics, 3D perception, and scientific computing workflows.
Install
pypcd4 on PyPI
Before you install
Low install friction; pure Python wheel with three runtime dependencies (numpy, pydantic, python-neo-lzf). Active maintenance with recent commits and stable production status.
License in practice
BSD 3-Clause permissive license allows commercial and private use with attribution; no viral copyleft restrictions.
Quickstart
pip install pypcd4
from pypcd4 import PointCloud
import numpy as np
pc = PointCloud.from_path("point_cloud.pcd")
array = pc.numpy()
pc_filtered = pc[pc.pc_data["x"] > 0.5]
pc_filtered.save("filtered.pcd")Verify before relying
- Whether ROS integration requires ROS to be installed and sourced, or if rosbags library alone suffices for reading/writing
- Performance characteristics when concatenating or filtering large point clouds (thousands or millions of points)
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8.2 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesnumpypydanticpython-neo-lzf |
| Maintenance | Actively maintained 219 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 85,364 / month, #13,927 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 Approved :: BSD LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIXProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/EngineeringTopic :: Software Development :: LibrariesTopic :: Utilities |
Evidence: pypcd4-1.4.3-py3-none-any.whl
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See also pystac-ext-pointcloud · rosbags · netCDF4 · meshioplusplus · quadrilateral-fitter · mplib · fabio · fitsio · pylerc