Assertions and Debugging in Python

Bugs are inevitable; finding them quickly is a skill. Python gives you assert statements to check assumptions while developing, a built-in debugger (pdb, started with breakpoint()), IDE debuggers with breakpoints and variable inspection, and helpful tools for tracing and timing code.

This lesson covers assertions and their limits, a systematic debugging process, pdb commands, IDE debugging, and quick diagnostic techniques.

The assert Statement

assert condition, "message" raises AssertionError if the condition is false. Use it for internal invariants that should never be false if the code is correct ("the discount is never above 100%") and in tests (pytest uses plain assert). Do not use assert to validate user input or enforce security: Python removes all asserts when run with -O (optimised mode).

A Debugging Process

Reproduce the bug reliably with the smallest input; read the full traceback; form a hypothesis; inspect actual values (print, logging or debugger) to confirm or reject it; fix the cause, not the symptom; then add a test so the bug never returns. Explaining the code to someone else (or a rubber duck) is surprisingly effective.

pdb and breakpoint()

Call breakpoint() anywhere to pause and open the interactive debugger. Useful commands: n (next line), s (step into), c (continue), l (list code), p expr (print), pp (pretty print), w (where — stack trace), u/d (move up/down the stack), b line (set breakpoint), q (quit). python -m pdb script.py starts a script under the debugger.

IDE Debuggers and Quick Tools

VS Code and PyCharm offer visual breakpoints, conditional breakpoints, watch expressions and step-through execution. For quick checks, print(f"{value=}") shows a variable with its name, pprint formats nested data, traceback.print_exc() prints the current exception, and time.perf_counter() measures slow sections.

Examples

def apply_discount(price, percent):
    assert 0 <= percent <= 100, f"invalid discount {percent}%"
    discounted = price * (100 - percent) / 100
    assert 0 <= discounted <= price, "discount produced an impossible price"
    return discounted

print(apply_discount(1000, 20))
try:
    apply_discount(1000, 150)
except AssertionError as e:
    print("AssertionError:", e)

800.0
AssertionError: invalid discount 150%

from pprint import pprint

def average_marks(students):
    total = 0
    for s in students:
        total += s["marks"]
    print(f"{total=} {len(students)=}")          # quick inspection
    return total / len(students)

students = [{"name": "Asha", "marks": 90}, {"name": "Ravi", "marks": 70}]
print(average_marks(students))

data = {"course": "Python", "students": students, "tags": ["beginner", "backend"]}
pprint(data, width=60)

total=160 len(students)=2
80.0
{'course': 'Python',
 'students': [{'marks': 90, 'name': 'Asha'},
              {'marks': 70, 'name': 'Ravi'}],
 'tags': ['beginner', 'backend']}

def calculate_total(items):
    total = 0
    for price, qty in items:
        breakpoint()            # execution pauses here
        total += price * qty
    return total

calculate_total([(100, 2), (50, 3)])

# In the (Pdb) prompt:
# (Pdb) p price, qty         -> (100, 2)
# (Pdb) p total              -> 0
# (Pdb) n                    -> runs the next line
# (Pdb) p total              -> 200
# (Pdb) c                    -> continue to the next breakpoint
# (Pdb) q                    -> quit

> main.py(5)calculate_total()
-> total += price * qty
(Pdb) p price, qty
(100, 2)

import time

start = time.perf_counter()
squares = [n * n for n in range(1_000_000)]
elapsed = time.perf_counter() - start
print(len(squares), "squares computed in under a second:", elapsed < 1)

1000000 squares computed in under a second: True