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Downloading Python for Scientific Computing (for Mac)
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Python for Scientific Computing (for Mac)

Splunk Built
This add-on contains a Python interpreter bundled with the following scientific and machine learning libraries: numpy, scipy, pandas, scikit-learn, and statsmodels. With this add-on, you can import these powerful libraries in your own custom search commands, custom rest endpoints, modular inputs, and so forth.

This add-on is available for Linux (64-bit and 32-bit), Windows (64-bit) and Mac. Make sure you install the appropriate one for your Splunk deployment.


Python for Scientific Computing (PSC) Add-on is a requirement for some of the applications in Splunkbase such as:

  • Machine Learning Toolkit (MLTK Beta and Advisory apps as well)
  • Splunk Security Essentials for Fraud Detection
  • DGA App for Splunk
  • Suricata app for splunk

Splunk’s users have also used PSC and/or MLTK in combination with other applications such as:

  • Splunk Security Essentials
  • App for AWS Billing
  • Splunk ITSI Module for Application Performance Monitoring etc.


Please download and install the appropriate version here:


To install an app within Splunk Enterprise:

  1. Log into Splunk Enterprise.
  2. Next to the Apps menu, click the Manage Apps icon.
  3. Click Install app from file.
  4. In the Upload app dialog box, click Choose File.
  5. Locate the .tar.gz or .tar file you just downloaded, then click Open or Choose.
  6. Click Upload.

Release Notes

Version 4.0.0
May 25, 2022
Version 3.0.2
Jan. 12, 2022

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.

Version 3.0.1
Nov. 6, 2021

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.

Version 3.0.0
Sept. 14, 2021

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.

Version 2.0.2
July 23, 2020
Version 2.0.1
Feb. 25, 2020
Version 2.0.0
Oct. 18, 2019
Version 1.4
March 12, 2019
Version 1.3
July 23, 2018

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.

Version 1.2
May 23, 2016
  • Added statsmodels and patsy modules.
Version 1.1
March 29, 2016

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.

Version 1.0.0
Sept. 18, 2015

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