😎
Templates
You don't have to be a data scientist, to use data science.
(aka the "awesome-notebooks")
The aim of the Naas templates is to be the largest aggregator of production-ready Jupyter Notebooks templates.
To do so, we have defined a framework that enables easy understanding and scaling of Notebooks: Each notebook is organized with the following sections:
- Title: "Tool - Action of the notebook"
- Description: a one-liner explaining the benefits of the notebooks for the user
- Tags: hashtags of the topics the notebook is about
- Input: list of all the variables, credentials, that needs to be setup
- Model: list the functions applied to the data
- Output: list the assets to be used by the user and its distribution channels if any.
The repository is organized by source/tools. Managed by Naas core-team and community ⭐️.
→ Feel free to use the Issues tab to add any templates you would like to see, or contribute to.
- Step 2: Clone awesome-notebooks repo
- Step 3: Change status of this Issue to “In progress” so we can know you are working on it
- Step 4: Create new branch with a short name of the issue (ex: “gsheet-notion”)
- Step 5: Create folder named with the source tool (if it does not already exist in the awesome-notebooks folder), and adapt notebook template to the current use case.
- Step 6: Once you are happy with the result, commit to the branch
- Step 7: Open a pull request and tag me as a reviewer with a little comment on what you have done, but most of the explanations should be in the notebook itself
- Step 8: Change status of this Issue to “Review” so we can know a review is pending
- Step 9: Link the PR to this issue for tracking in the backlog
- Step 10: Expect a feedback and merge in the next 48h-72h
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