As I mentioned in my previous blog article, we at SAP Cloud ALM for implementation are really excited about the APIs we recently released.
In order to help you get started, and to see what possibilities the APIs offer, we created a github.com repository with samples for you to explore.
In particular, I'd like to highlight a Jupyter notebook we created to demonstrate the project and task APIs:
If you are not familiar with Jupyter notebooks, they combine documentation sections, written in markdown, with independently executable code cells, typically written in Python.
In the notebook, we use pandas data frames to analyze and process the data from the APIs. Pandas is a Python library generally used by data scientists for such purposes.
Since Jupyter so effectively combines documentation with code cells, you don't even have to download and run the notebook. Just use GitHub's notebook display feature to view the nicely formatted documentation along with the results printed from the last run (my run) of the code. Take a look at the notebook here:
If you do want to try running and adapting the notebook on your own, we've included everything you need to know. This includes
There are a few steps you have to go through to provide authentication data. That's probably the most difficult part, as it always is, and for good reason: security. Please exercise caution and appropriately protect your data.
We hope the examples we provide in the notebook, such as creating interactive Gantt charts of tasks, inspire you to create your own analyses and automation. Please send us feedback - we're always interested in improving our offerings.
Take a look at the sample Kanban board in our repository:
This is a Node.js application which showcases another use case: building your own UIs for SAP Cloud ALM.
See the master blog post for Project and Task Management in SAP Cloud ALM for a list of all our articles: Project and Task Management capabilities-Master List
In order to help you get started, and to see what possibilities the APIs offer, we created a github.com repository with samples for you to explore.
In particular, I'd like to highlight a Jupyter notebook we created to demonstrate the project and task APIs:
If you are not familiar with Jupyter notebooks, they combine documentation sections, written in markdown, with independently executable code cells, typically written in Python.
In the notebook, we use pandas data frames to analyze and process the data from the APIs. Pandas is a Python library generally used by data scientists for such purposes.
Since Jupyter so effectively combines documentation with code cells, you don't even have to download and run the notebook. Just use GitHub's notebook display feature to view the nicely formatted documentation along with the results printed from the last run (my run) of the code. Take a look at the notebook here:
The notebook as it appears in GitHub
If you do want to try running and adapting the notebook on your own, we've included everything you need to know. This includes
- Visual Studio (VS) Code as the development environment
- The notebooks extension for VS Code
- Python and related dependencies, such as pandas as mentioned above and Plotly for nice interactive charts
There are a few steps you have to go through to provide authentication data. That's probably the most difficult part, as it always is, and for good reason: security. Please exercise caution and appropriately protect your data.
We hope the examples we provide in the notebook, such as creating interactive Gantt charts of tasks, inspire you to create your own analyses and automation. Please send us feedback - we're always interested in improving our offerings.
Further Reading
Take a look at the sample Kanban board in our repository:
This is a Node.js application which showcases another use case: building your own UIs for SAP Cloud ALM.
See the master blog post for Project and Task Management in SAP Cloud ALM for a list of all our articles: Project and Task Management capabilities-Master List
- SAP Managed Tags:
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