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Debugging & Profiling

6 Topics
1

pdb Debugger

Built-in Python debugger — interactive debugging with breakpoints, stepping, variable inspection, and post-mortem analysis.

Debugging skills — knowing how to use a debugger effectively is a fundamental development skill.
2

Logging

The logging module for structured event tracking — log levels, handlers, formatters, filters, and production-ready logging configuration.

Production debugging — proper logging is essential for diagnosing issues in deployed applications.
3

Profiling

Performance profiling with cProfile, pstats, and line_profiler — finding and fixing bottlenecks in Python code.

Performance optimization — profiling is essential for data-driven optimization decisions.
4

Memory Profiling

Tracking memory usage and finding leaks — tracemalloc, memory_profiler, objgraph, and sys.getsizeof for memory analysis.

Memory optimization — understanding memory usage is critical for long-running applications and data processing.
5

timeit Module

Accurately measuring small code snippets — timeit for micro-benchmarks, comparing approaches, and understanding Python performance characteristics.

Performance analysis — knowing how to benchmark code accurately is essential for optimization.
6

Traceback Analysis

Reading and understanding Python stack traces — traceback module, custom exception handling, and systematic error diagnosis.

Debugging fundamentals — reading tracebacks efficiently saves significant debugging time.
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