This serves as the repository for all the source code to generate all the example data for the Collaboration Data lightning talk at IBM Interconnect
API scripts are written in python 3.5.x, specifically using the anaconda distribution.
Third party dependencies are defined in the requirements.txt file in root directory.
The script (gh-reports.py) is run with command line arguments. The arguments are as follows:
-r - Specify the repository name (Required)
-o - Specify the organization name (If not specified, will use the user's repositories)
-u - User account (Required)
-t [1-8] - Which report you want to run (Required)
- 1 : "Languages committed per User",
- 2 : "Ratio of Merged/Unmerged Pull Requests (Status=All)",
- 3 : "Ratio of Merged/Unmerged Pull Requests (Status=Closed)",
- 4 : "Contribution Count of last 100 Pull Requests",
- 5 : "Repository Maintenance (Documentation submission vs Code Submission",
- 6 : "Issues open by Assignee",
- 7 : "Number of Comments on Closed Issues",
- 8 : "Analyze sentiment of conversations in last 100 Pull Requests"
-e [True|False] - Specify GitHub Enterprise instance. False by default
-p - Public repo vs org repo. Not currently used.
-s - Search Unused arg for later reports forthcoming
Example usage:
./gh-reports.py -r hubot -o github -u webdog -t 1
You will then be prompted for a personal access token which you can generate in your GitHub Profile.
Reports are then dropped in the ./reports/ directory as pipe-delimited csvs. Note: CSVs are not generated in any specific column order. So you may experience different column positions after each run.
Example usage is then shown in ipython notebooks under the reports directory.
Note: This software is in a very alpha state. Happy hacking!