"In God we Trust, all others bring data."
– W. Edwards Deming
In the remaining chapters of this book, we will do a deep dive into the architecture of industry use cases, including the implementation of sample data pipelines, heavily applying the techniques we've learned so far. Before we start looking at the code, let's complete our toolbox with a few best practices and advanced PixieDust concepts that will be useful in the implementation of our sample applications:
Calling third-party Python libraries with
@captureOutput
decoratorIncreasing modularity and code reuse of your PixieApp
PixieDust support of streaming data
Adding dashboard drill-downs with PixieApp events
Extending PixieDust with a custom display renderer
Debugging:
Line-by-line Python code debugging running on the Jupyter Notebook using pdb
Visual debugging with PixieDebugger
Using the PixieDust logging framework to troubleshoot issues...