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When releasing new versions of JWQL, we constantly run into issues with Bokeh plotting issues in production because of constant changes and improvements to their project/api. These issues are not caught in our CI/CD tests and are outside of the scope of whether the data that is being displayed is correct.
I would like to see JWQL implement a way to represent "dummy datasets" to test our plotting algorithms (a dummy data factory).
If bokeh plots are used in a monitor, there doesn't need to be an excessive amount of data points (it could even be one row in a pandas dataframe with all necessary columns of correct dtype) that are then passed to our plotting routines as part of the CI/CD to make sure if there are deprecation warnings or implementations that they are caught before merging code into production.
The text was updated successfully, but these errors were encountered:
When releasing new versions of JWQL, we constantly run into issues with Bokeh plotting issues in production because of constant changes and improvements to their project/api. These issues are not caught in our CI/CD tests and are outside of the scope of whether the data that is being displayed is correct.
I would like to see JWQL implement a way to represent "dummy datasets" to test our plotting algorithms (a dummy data factory).
If bokeh plots are used in a monitor, there doesn't need to be an excessive amount of data points (it could even be one row in a pandas dataframe with all necessary columns of correct dtype) that are then passed to our plotting routines as part of the CI/CD to make sure if there are deprecation warnings or implementations that they are caught before merging code into production.
The text was updated successfully, but these errors were encountered: