Python for Scientific Computing (for Mac)
Overview
Details
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.
Requirements
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.
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/
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Windows 64-bit: https://splunkbase.splunk.com/app/2883/
Installation
To install an app within Splunk Enterprise:
- Log into Splunk Enterprise.
- Next to the Apps menu, click the Manage Apps icon.
- Click Install app from file.
- In the Upload app dialog box, click Choose File.
- Locate the .tar.gz or .tar file you just downloaded, then click Open or Choose.
- Click Upload.
Release Notes
Version 3.0.2
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
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
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
Version 2.0.1
Version 2.0.0
Version 1.4
Version 1.3
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
- Added statsmodels and patsy modules.
Version 1.1
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.