Debugging Python Models

The debugger allows you to:

• Set and clear breakpoints.
• Set conditional breakpoints.
• Step over the next program statement.
• Step into a subroutine call at the current statement.
• Step out of the current subroutine call.
• View the current call stack and navigate through it.
• View the values of local variables within the current subroutine call.
• View the values of global variables in the current model.
• View the values of global variables defined in each Python module.
• Evaluate expressions via a new input field above the Output pane as you step through the program.

Note: You must have an Xpress Insight project to debug Python models. The debugging inspection tools do not currently support full traversal of object hierarchies. Objects like pandas DataFrames have a default textual representation showing the data in a tabular format. Data can be viewed as static text, in contrast to Mosel's live Inspect In Table option. As with Mosel, the Python debugger does not support editing the source during debugging. Only single-threaded debugging is currently supported. For example, debugging the sklearn module's multithreaded cross_validate method may lead to the debug process freezing.

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