Requirements
Python for Scientific Computing (PSC) Add-on is a requirement for some of the applications in Splunkbase such as:
Splunk’s users have also used PSC and/or MLTK in combination with other applications such as:
Download
Please download and install the appropriate version here:
Linux 64-bit: https://splunkbase.splunk.com/app/2882/
Linux 32-bit: https://splunkbase.splunk.com/app/2884/
Windows 64-bit: https://splunkbase.splunk.com/app/2883/
Installation
To install an app within Splunk Enterprise:
This release of Python for Scientific Computing (PSC) does not bring any major updates, only bug fixes.
Everything remains the same as in PSC 3.0.1 except MLTK 5.3.1 will be compatible with PSC 3.0.0 and above which includes PSC 3.0.1 and PSC 3.0.2.
Note that the streaming_apply feature has been deprecated and PSC should no longer be installed on indexers.
This release of the Python for Scientific Computing (PSC) add-on is limited to configuration updates for deployment on Splunk Cloud Platform.
MLTK versions 5.2.2 or lower are not compatible with this version of PSC. If you are upgrading to this version of PSC, you must also upgrade your installation of MLTK to version 5.3.0 or higher.
This release of Python for Scientific Computing (PSC) brings updates to several libraries in the package. In particular, Numpy, Scipy, scikit-learn, Statsmodels, and Networkx are upgraded to their latest available versions.
MLTK versions earlier than 5.3.0 are not compatible with this version of PSC. Therefore, if you are upgrading to this version of PSC, you must also upgrade your installation of MLTK to version 5.3.0 or later.
Upgraded numpy to 1.13.1, pandas to 0.22.0, scikit-learn to 0.19.0, scipy to 0.19.1, statsmodels to 0.8.0.
This version of Python for Scientific Computing is compatible with Splunk Machine Learning Toolkit 3.2 and above.
Upgraded numpy to 1.10.4, scipy to 0.17.0, pandas to 0.17.1, scikit-learn to 0.17.0. Removed statsmodels and patsy.
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