IBM SPSS team is now sharing the extensions for IBM SPSS Modeler and IBM SPSS Statistics onGithub. The goal is to use it as a collaborative platform. We provide transparency and you have access to the source code of the extension so you can get inspiration and ideas to create new ones.
IBM SPSS welcomes contributions from anyone. You retain full ownership and control of your contribution subject. All you need to do is to create your own (free) Github account, upload the item with a description and your contact information, and send a note to the SPSS Community manager with the item url. Details are below. If the item is packaged as an extension command, you can take advantage of extra features available for that packaging as described below, but this is not a requirement. IBM does not test third-party submissions, but they are accepted for listing in the SPSS Community subject to its discretion. Once your extension is accepted if will appear in the “IBM SPSS Predictive Analytics Github” account tagged as ‘Community’ extension.
Please do not contribute code you did not write yourself unless you are certain you have the legal ability to do so. Also, ensure all code contributed can be licensed under the Apache License 2.0. For more details please see our guidelines for contributing.
Filling an issue
If you are just looking for help, you will probably attract the most attention if you post in SPSS dWAnswers forum.
If you want to connect to the developer of one of the SPSS extensions, you can use the ‘Issues‘ feature on Github. This helps to keep track of tasks, enhancements, and bugs for the extensions.
How can I contribute?
There are two options to contribute:
1. Create a new extension: If you would like to share a contribution (useful stream or extension), follow these steps:
- Create a Github Account.
- Upload your artifacts to your own repository. If you are not familiar with Github, we recommend the following 15 minutes training: Got 15 minutes and want to learn Git?
- In the Readme.md add a description and screenshots. If you share your extension is because you want it to be used by the community. The more attractive you repository is, the more attention it will get. You can get inspired by this one:
- The description has to include the following:
-Name: the name of the extension;
-Summary: A summary of the artifact, what it can do and how to install and use it;
-Author: Your name, your affiliation;
-MinimumModelerVersion: Version of Modeler in which the artifact was generated;
-Keywords: a list of keywords for searching
- Finally send a note to the Community Manager requesting to add your item to the IBM SPSS Predictive Analytics Github account. Include the url for the item.
To learn more about how to create extensions, check the Programmability Documentation for IBM SPSS Modeler and IBM SPSS Statistics.
2. Modify an existing extension:
We enforce a fork and pull model for contribution to existing repositories. There is an excellent resource to get more familiar with the general step of Contributing to Open Source on Github. Just fork the extension, modify it and do a pull request! The author will be notified and will check if the contribution makes sense, and if yes, the repository will be updated.
Remember to Star the project that you find interesting, even if you aren’t associated with the project! It is just one click away ! 🙂
In IBM SPSS Statistics version 22, we have added a feature to download and install extension bundles directly from the website from within the product. This will substantially increase the exposure and use of Python- and R-based extensions. The user will see a list of all files meeting certain criteria along with summary information and can just check off the ones they want.
Users of the older version will not be able to use this mechanism, but they can still download from the community. Check more information here.