Expected errors are foreseeable boundary failures—missing input files, bad records, invalid parameters—that should produce clear messages or controlled recovery rather than cryptic tracebacks or silent corruption.
Expected errors are foreseeable boundary failures—missing input files, bad records, invalid parameters—that should produce clear messages or controlled recovery rather than cryptic tracebacks or silent corruption.
Learning goal: explain why Handle Expected Errors behaves this way, apply it to a small example, and verify the result independently. Begin by being able to justify this first step: Catch only specific exceptions you can handle, raise meaningful validation errors and leave unexpected programming failures visible.
Treat this as a sequence of observable decisions rather than one opaque command. Stage 1: Catch only specific exceptions you can handle, raise meaningful validation errors and leave unexpected programming failures visible. Stage 2: Keep the stage inside the same data/validation definitions used by the rest of the project. Stage 3: Save the evidence produced by this stage so the next stage can be audited.
Catch only specific exceptions you can handle, raise meaningful validation errors and leave unexpected programming failures visible.
Keep the stage inside the same data/validation definitions used by the rest of the project.
Save the evidence produced by this stage so the next stage can be audited.
Evidence: deliberate bad input triggers the intended message and does not generate a misleading output file.
The worked evidence makes the output of this project stage concrete and auditable.
For Handle Expected Errors, trace the specific input through the mechanism above and independently verify one returned value, state change or side effect.
InputObjects/values supplied to the operation.StateNames or mutable objects that may change during execution.OutputReturned value, side effect, file, plot or exception to inspect.Use Handle Expected Errors when it answers a defined question in Capstone: A Small Data Project and its inputs/assumptions match the current data or program state.
Reconsider Handle Expected Errors when the required information is unavailable, the operation would violate a validation/data boundary, or a simpler operation answers the question more transparently.
Construct a tiny example of Handle Expected Errors. First catch only specific exceptions you can handle, raise meaningful validation errors and leave unexpected programming failures visible. Then keep the stage inside the same data/validation definitions used by the rest of the project. Predict the result before execution and explain one boundary or failure case.
Which approach best demonstrates understanding of Handle Expected Errors?
Step 1Catch only specific exceptions you can handle, raise meaningful validation errors and leave unexpected programming failures visible.Step 2Keep the stage inside the same data/validation definitions used by the rest of the project.Step 3Save the evidence produced by this stage so the next stage can be audited.