How to Install and Uninstall python39-Rtree Package on openSuSE Tumbleweed
Last updated: November 14,2024
1. Install "python39-Rtree" package
Please follow the instructions below to install python39-Rtree on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python39-Rtree
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2. Uninstall "python39-Rtree" package
This guide covers the steps necessary to uninstall python39-Rtree on openSuSE Tumbleweed:
$
sudo zypper remove
python39-Rtree
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3. Information about the python39-Rtree package on openSuSE Tumbleweed
Information for package python39-Rtree:
---------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-Rtree
Version : 0.9.7-1.11
Arch : noarch
Vendor : openSUSE
Installed Size : 270.3 KiB
Installed : No
Status : not installed
Source package : python-Rtree-0.9.7-1.11.src
Upstream URL : https://github.com/Toblerity/rtree
Summary : R-Tree spatial index for Python GIS
Description :
A ctypes Python wrapper of libspatialindex that provides a number of advanced
spatial indexing features for the spatially curious Python user.
* Nearest neighbor search
* Intersection search
* Multi-dimensional indexes
* Clustered indexes (store Python pickles directly with index entries)
* Bulk loading
* Deletion
* Disk serialization
* Custom storage implementation (to implement spatial indexing in ZODB,
for example)
---------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-Rtree
Version : 0.9.7-1.11
Arch : noarch
Vendor : openSUSE
Installed Size : 270.3 KiB
Installed : No
Status : not installed
Source package : python-Rtree-0.9.7-1.11.src
Upstream URL : https://github.com/Toblerity/rtree
Summary : R-Tree spatial index for Python GIS
Description :
A ctypes Python wrapper of libspatialindex that provides a number of advanced
spatial indexing features for the spatially curious Python user.
* Nearest neighbor search
* Intersection search
* Multi-dimensional indexes
* Clustered indexes (store Python pickles directly with index entries)
* Bulk loading
* Deletion
* Disk serialization
* Custom storage implementation (to implement spatial indexing in ZODB,
for example)