
Adding Python 3 libraries
Version 5.0.0 and higher of the Machine Learning Toolkit (MLTK) requires version 2.0 of the Python for Scientific Computing add-on, version 8.0 of Splunk Enterprise, and Python 3.
Users on this version or above of the Machine Learning Toolkit have the option to add Python 3 libraries as a means to enhance their machine learning efforts.
Support is not offered on the use of or upgrade of any Python 3 libraries added to your Splunk platform instance. Any upgrade to MLTK or the PSC add-on will overwrite any Python library changes.
Follow these steps to add a Python 3 library to your instance of the MLTK:
- Clone the GitHub repo for the Python for Scientific Computing add-on: https://github.com/splunk/Splunk-python-for-scientific-computing.git
- Navigate to https://repo.anaconda.com/pkgs/ to check the list of packages supported through Anaconda. You can only add packages listed on this site.
- In GitHub, choose the package you need and add it in
package.txt
. - Specify the version of the package in
package.txt
. The latest version is selected by default. - Run
bash repack.sh
to create the environment and install the package within the environment. - When the repacking in complete, run the
bash build.sh
script which creates a .tgz file for the PSC add-on. On Windows, run abuild.psl
script. - In your Splunk platform instance (not in the Splunk CLI or web installer) extract the .tgz file.
The final .tgz app stores in the build directory.
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This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 5.0.0, 5.1.0, 5.2.0, 5.2.1, 5.2.2, 5.3.0, 5.3.1, 5.3.3, 5.4.0, 5.4.1
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