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
- Specify the version of the package in
package.txt. The latest version is selected by default.
bash repack.shto create the environment and install the package within the environment.
- When the repacking in complete, run the
bash build.shscript which creates a .tgz file for the PSC add-on. On Windows, run a
- 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.
Use custom logging
Support for the ML-SPL API
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