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Downloading Python for Scientific Computing (for Windows 64-bit)
SHA256 checksum (python-for-scientific-computing-for-windows-64-bit_13.tgz) 631a6e9d78e7c0317c06a6393d38e6b967dd57c629d8c2601d66d86103aab3ae SHA256 checksum (python-for-scientific-computing-for-windows-64-bit_12.tgz) f2b48561ae83f89bf6bffeffb1db2ff4e2385bf0c0c10210576659f0490fdd9c SHA256 checksum (python-for-scientific-computing-for-windows-64-bit_11.tgz) 06c5354ef9baed1864bee491b8ce5cda6cfca509f95fbeb10ee677c0fe1ca18b SHA256 checksum (python-for-scientific-computing-for-windows-64-bit_101.tgz) 1a7497d5c0441cb1fcda80e8885b51fd22b39ccc2e592d10dad52513b8b3a49f SHA256 checksum (python-for-scientific-computing-for-windows-64-bit_100.tgz) 91b2d2425270babe74474745fa6ae98eb2cea799527521b370c59611d556d53a
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Python for Scientific Computing (for Windows 64-bit)

Splunk Built
Overview
Details
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.

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:

Installation

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 1.3
July 27, 2018

Upgraded numpy to 1.13.3, 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 1.0.1
Dec. 4, 2015

Bundles MSVCRT90.DLL.

Version 1.0.0
Sept. 18, 2015

969
Installs
11,752
Downloads
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