About this talk

Jira is known as a task management tool, but for Glasswall it is a graphing database allowing us to mark and map anything we wish to. Combined with the power of Jupyter notebooks, we have stunning new ways to organize and visualize our data. Utlizing Jira’s API, secure authentication ensures that data doesn’t get into the wrong hands, and all the same flexible privilege options that we set in Jira will apply in Jupyter. In this session, you will see how with Python’s automation abilities, entire reports and dashboards can be built in clean and scalable ways, right from a simple notebook. You’ll see how graphs help visualize your workflow, and easily find what needs changing/improving. These changes can be implemented, and new nodes and edges can be added to our “map”, on a huge scale. We can neatly graph all of these Issues however we’d like - by their type, or by the link types they share with other issues, for example - or even store it in a clean Pandas dataframe. The consistency in Jira’s structure translates over seamlessly to code.