AD141 Python Programming with Red Hat — Lesson 3: Files, JSON, Regular Expressions, Exceptions, Logging, and Debugging

Learning Objectives

• Explain the structures, services, data, settings, roles, and dependencies governing file handling and JSON.
• Implement and validate regular expressions, exceptions, and logging and debugging using reviewable evidence.
• Evaluate the condition where operators cannot explain the outcome because logs, commands, settings, and acceptance evidence were not captured consistently and select a proportionate corrective response.

Detailed Topics

• file handling applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• JSON applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• regular expressions applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• exceptions applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• logging and debugging applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.

Instructor Demonstration

The instructor traces a systems professional building maintainable Python utilities for data handling and operational automation. The walkthrough connects navigation, commands, configuration logic, system messages, and evidence captured in the Python utility repository, test evidence, code-review checklist, and automation implementation guide. It also tests the exception where operators cannot explain the outcome because logs, commands, settings, and acceptance evidence were not captured consistently.

Hands-On Exercise

Complete a controlled Red Hat exercise covering Files, JSON, Regular Expressions, Exceptions, Logging, and Debugging and preserve the verified result in the Python utility repository, test evidence, code-review checklist, and automation implementation guide.

1. Confirm scope, prerequisites, versions, identities, dependencies, and acceptance criteria.
2. Execute the workflow while recording commands, settings, outputs, events, and system messages.
3. Test normal behavior, one boundary condition, and the stated exception.
4. Document corrections, evidence, ownership, retest criteria, rollback, and handover actions.

Scenario Analysis

• Identify which object, service, policy, setting, or sequence most strongly influences file handling.
• Compare two defensible responses and explain technical, security, operational, and support trade-offs.
• Determine how the Python utility repository, test evidence, code-review checklist, and automation implementation guide should be approved, retained, retested, and updated.

Troubleshooting Guidance

Start where expected behavior first differs from the observed result. Check prerequisites, identity, configuration order, version compatibility, connectivity, status, resource limits, and evidence separately. Treat “operators cannot explain the outcome because logs, commands, settings, and acceptance evidence were not captured consistently” as a hypothesis until commands, logs, settings, and retest outcomes confirm the cause.

Validation Checklist

• Required platform components, identities, permissions, settings, and dependencies are present.
• The Python utility repository, test evidence, code-review checklist, and automation implementation guide connects each conclusion to objective, reviewable evidence.
• Normal processing, a boundary condition, dependency behavior, and the stated exception were tested.
• Corrections, ownership, retest criteria, rollback, documentation, and operational handover are complete.

Lesson Outcome

Learners can apply Files, JSON, Regular Expressions, Exceptions, Logging, and Debugging, explain the resulting platform behavior, and defend the outcome through the Python utility repository, test evidence, code-review checklist, and automation implementation guide.