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.. _installation:
============
Installation
============
Short Instructions
==================
Pip
____
.. code-block:: shell
# Install _without_ LAZ support
pip install laspy
# Install with LAZ support via lazrs
pip install laspy[lazrs]
# Install with LAZ support via laszip
pip install laspy[laszip]
# Install with LAZ support via both lazrs & laszip
pip install laspy[lazrs,laszip]
Conda
_____
A conda build of laspy is available and maintained (but not by laspy)
.. code-block:: shell
conda install -c conda-forge laspy
``lazrs`` is also available on conda
.. code-block:: shell
conda install -c conda-forge lazrs-python
However, ``laszip`` [#f1]_ is not available via conda.
Optional dependencies / features
=================================
LAZ support
___________
laspy does not support LAZ (.laz) file by itself but can use one of two optional dependencies
to support compressed LAZ files.
The 2 supported options are:
1) `lazrs`_ `[lazrs PyPi]`_
2) `laszip-python`_ (bindings to `laszip`_)
When encountering LAZ data, laspy will try to use one of the backend in the order described above.
(Example: if lazrs is not installed or if it fails during, the process, laspy will try laszip)
`lazrs`_ is a Rust port of the laszip compression and decompression.
Its main advantage is that it is able to compress/decompress using multiple threads which can
greatly speed up things. However it does not supports points with waveforms.
`laszip`_ is the official and original LAZ implementation by Martin Isenburg.
The advantage of the `laszip` backend is that its the official implementation, it supports points
with waveform but does not offer multi-threaded compression/decompression.
Both the laszip bindings and lazrs are available on pip.
To install laspy with one of its supported backend use one of the commands
show in the section above.
.. _lazrs: https://github.com/tmontaigu/laz-rs
.. _laszip-python: https://github.com/tmontaigu/laszip-python
.. _laszip: https://github.com/LASzip/LASzip
.. _[lazrs PyPi]: https://pypi.org/project/lazrs/
CRS / SRS
_________
LAS files allows to define the CRS / SRS in which the points coordinates are.
When `pyproj`_ is installed, you can use the :meth:`.LasHeader.add_crs` to add
CRS information to a file, or you can use :meth:`.LasHeader.parse_crs` to get
`pyproj.CRS`.
.. _pyproj: https://pypi.org/project/pyproj/
Cloud Optimized Point Cloud (COPC)
__________________________________
`laspy` supports `COPC`_ files via its :class:`.CopcReader` class.
This features **requires** the optional dependency ``lazrs`` to be installed.
Optionaly, when python package `requests`_ is installed the :class:`.CopcReader`
can handle COPC that are in a HTTP server.
.. _COPC: https://github.com/copcio/copcio.github.io
.. _requests: https://docs.python-requests.org/en/latest
.. rubric:: Footnotes.
.. [#f1] A ``laszip`` package exists on conda-forge, but it only includes the C++ library, not the the Python
bindings, which means that installing it won't give you a LAZ capable laspy installation.
CLI
---
laspy has an optional command line interface (CLI) with the following commands:
* ``laspy info`` to print informations about a LAS/LAZ file
* ``laspy compress`` / ``laspy decompress`` to compress/decompress one or many file
* ``laspy convert`` to convert file(s) between version and point format
* ``laspy copc query`` to download to a LAS/LAZ file some points from a COPC ressource.
As the cli requires etra dependencies, it has to be installed using
``pip install laspy[cli]``.
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