Debugging in Python and VSCode Cheat Sheet

Updated 2026-04-27

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Debugging is the process of identifying and fixing errors in Python code, essential for both development and production environments. Python offers built-in debugging tools like pdb and the breakpoint() function, while Visual Studio Code provides a powerful graphical debugger with features like breakpoints, watch expressions, and call stack inspection. Understanding debugging techniques—from simple print statements to advanced post-mortem analysis—enables developers to efficiently troubleshoot issues, profile performance, and ensure code quality. The key mental model: debugging is an iterative investigation where you form hypotheses, test them with breakpoints and inspection, and refine your understanding until the bug is isolated and fixed.

What This Cheat Sheet Covers

This topic spans 12 focused tables and 145 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Core Debugging TechniquesTable 2: Python pdb Debugger CommandsTable 3: VSCode Debugging FeaturesTable 4: VSCode launch.json ConfigurationTable 5: Breakpoint TypesTable 6: Advanced Python DebuggingTable 7: Debugging Best PracticesTable 8: Debugging Web FrameworksTable 9: VSCode Keyboard ShortcutsTable 10: Profiling and PerformanceTable 11: Debugging Specific IssuesTable 12: Alternative Debuggers

Table 1: Core Debugging Techniques

Technique	Example	Description
print() debugging	`print(f"x = {x}, y = {y}")`	• Outputs variable values to console • simple but clutters code and requires manual removal.
icecream / ic()	`from icecream import ic` `ic(x, result)`	• Drop-in `print()` upgrade: prints both expression name and value automatically • includes file/line context; `pip install icecream`.
breakpoint() built-in	`breakpoint()`	• Pauses execution and drops into pdb debugger (Python 3.7+) • replaces legacy `import pdb; pdb.set_trace()`.
logging module	`logging.debug(f"Processing {item}")`	• Structured output with severity levels (DEBUG, INFO, WARNING, ERROR, CRITICAL) • persists to files and can be filtered.
assert statements	`assert x > 0, "x must be positive"`	• Raises `AssertionError` if condition is `False` • disabled with `-O` flag (not for production validation).

Table 1: Core Debugging Techniques

Technique	Example	Description
print() debugging	`print(f"x = {x}, y = {y}")`	• Outputs variable values to console • simple but clutters code and requires manual removal.
icecream / ic()	`from icecream import ic` `ic(x, result)`	• Drop-in `print()` upgrade: prints both expression name and value automatically • includes file/line context; `pip install icecream`.
breakpoint() built-in	`breakpoint()`	• Pauses execution and drops into pdb debugger (Python 3.7+) • replaces legacy `import pdb; pdb.set_trace()`.
logging module	`logging.debug(f"Processing {item}")`	• Structured output with severity levels (DEBUG, INFO, WARNING, ERROR, CRITICAL) • persists to files and can be filtered.
assert statements	`assert x > 0, "x must be positive"`	• Raises `AssertionError` if condition is `False` • disabled with `-O` flag (not for production validation).