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io-and-debugging

I/O and Debugging — robust interaction and finding bugs​

Safe I/O patterns, parsing, and practical debugging workflows.

Console input and output​

Use input() for simple interactive programs and format output with f-strings for clarity.

name = input("Enter your name: ")
print(f"Hello, {name}")

For scripts intended to be used non-interactively, prefer command-line arguments (e.g., argparse) so the program can be automated.

File I/O (text and CSV)​

Use context managers to ensure files are closed correctly.

with open("data.txt", "r", encoding="utf-8") as f:
    text = f.read()

with open("out.txt", "w", encoding="utf-8") as f:
    f.write(text.upper())

Parsing CSV (simple):

import csv

with open("students.csv", newline='', encoding='utf-8') as csvfile:
    reader = csv.reader(csvfile)
    for row in reader:
        name, score = row[0], float(row[1])

Robust parsing patterns​

  • Validate input and use try/except to report meaningful errors (don't catch Exception blindly).
  • Use strip() to remove extra whitespace before conversion.

Logging vs print​

  • Use logging instead of print for anything but the simplest scripts; logging levels (DEBUG, INFO, WARNING, ERROR) let you control verbosity.
import logging
logging.basicConfig(level=logging.INFO)
logging.debug("This is a debug message")
logging.info("Started processing")

Debugging workflow​

  1. Read the error message and the stack trace — it often points directly to the cause.
  2. Reproduce the bug with the smallest possible input.
  3. Insert assertions or temporary prints to inspect values.
  4. Use an interactive debugger (e.g., pdb or your IDE's debugger) to step through and inspect variables.
  5. Once fixed, add a unit test that reproduces the bug to prevent regressions.

Example using pdb:

import pdb

def buggy(v):
    pdb.set_trace()
    return v + 1

buggy('x')

Common errors and how to fix them​

  • SyntaxError: check the line and preceding lines for missing :, unmatched parentheses or indent problems.
  • NameError: a variable is used before it has been assigned — check scope and spelling.
  • ValueError/TypeError: ensure you are passing values of the correct type; validate and coerce if necessary.

Testing and quick checks​

  • Use assert for small checks during development: assert x >= 0, "x must be non-negative".
  • For structured tests use pytest or unittest and keep tests in a tests/ folder.

Example: reading numbers until blank and reporting sum (robust)​

def read_numbers_and_sum():
    total = 0
    while True:
        s = input("Enter a number (blank to finish): ")
        if not s.strip():
            break
        try:
            total += int(s)
        except ValueError:
            print("Invalid number, try again")
    return total

if __name__ == '__main__':
    print('Total:', read_numbers_and_sum())

See functions.md for exhibiting I/O in small testable functions and exercises.md for practice problems that require file and console I/O.