A Scrum burndown chart for Jira that also keeps track of hours spent on a separate fixed-size budget
Jira burn-up-and-down is a python application that talks to the Jira REST API to display a Scrum burndown chart combined with a burnup chart that shows how much of a fixed-size budget has been spent.
Combining these two charts will help you realize how much additional points of sprint work should be completed when not all of the fixed-size budget has been used up, in order to keep sprint velocity constant.
Another difference with the built-in Jira burndown chart is that this one does not mix sprint progress with sprint scope changes. Sprint progress is plotted as usual, while sprint scope changes are shown as a change in the baseline of the chart.
All in all this chart gives a much clearer view of what is expected of the team in order to maintain their velocity.
python3 -m pip install jiraburnupanddown
Note: when using the above command make sure you are running a python version for which PyQt5 wheels are available.
This section describes two things to keep in mind when you plan to use this application.
I believe that sprint progress must be measured in points, not in estimated remaining time. I also think that it's valuable to see progress when tasks are completed instead of only when user stories are completed.
For this reason I distribute the points of a story over the sub-tasks and, lacking a points field for sub-tasks in Jira, fill in the number of points in the original estimate field. Jira may see that field as hours, but I consider it to be points.
This application follows the same approach and tracks the completion of sub-tasks in Jira. It uses the original estimate field as the size (in points) of a sub-task.
The point of this application is to show you if there is going to be a conflict between finishing sprint content and spending time on a separate activity counted in hours.
This only works if the query for burnup tasks (specified in the connection dialog) does not return any of the sub-tasks that are part of the sprint.
- numpy
- PyQt5
- pyqtgraph
- python-dateutil
- pytz
- requests
- tzlocal