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When working with notebooks, it is very handy to easily generate a cell that reads the asset content (file, database) and puts the code to read that data. This is cool, and is a clear demonstration of the value of the platform against local notebook instances.
But that good idea can be enhanced with other common operations, specially to integrate notebooks with other Watson Data Platform components.
Candidate snippets would be:
- Save to a connection (creates a function to save a dataframe to a new asset into that connection, ej. new table)
- Save to COS (creates a function to save a file into COS / S3)
- Save to project (saves as project asset, using the project library)
- Deploy model to WML (creates the repetitive logic - maybe with a template with fields to fill - used to deploy to WML, using the wml-api)
- Put a record as an event into a Kafka topic (to create file readers that publish records as events and leverage stream analytics)
Also, it could be considered the option to customize and maintain your own snippets, for common repetitive routines.
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Yes, I know about project-lib, and it is good to have a notebook sample, but from a developer experience, it is better to have those snippets or easy way to add common repetitive operations as code in cells and not having to find the samples and copy-paste it....by the way, the new way of programming today!
Hey Juame, I think you would be happy to learn about `project-lib`
https://medium.com/ibm-data-science-experience/control-your-dsx-projects-using-python-c69e13880312
For customizing and saving your own snippets, there are a few ways we can handle this. We are considering solutions like a native file system for the project, and you can store your own packages with WML at this time, though this is not very well documented I believe.