8.17 Hands-on Exercises

User Input Converter

Build a function that safely converts input() text to int, float, or bool based on a requested target type, with sensible error handling.

def convert_input(value, target_type):
    try:
        if target_type == bool:
            return value.strip().lower() in ("true", "yes", "1")
        return target_type(value)
    except (ValueError, TypeError):
        return None

>>> convert_input("42", int)
42
>>> convert_input("yes", bool)
True
>>> convert_input("abc", int)
None

CSV Parser

Build a function that reads CSV rows and converts specified numeric columns, handling any row with bad data gracefully.

import csv, io

def parse_ages(csv_text):
    reader = csv.DictReader(io.StringIO(csv_text))
    result = []
    for row in reader:
        try:
            row["age"] = int(row["age"])
        except ValueError:
            row["age"] = None
        result.append(row)
    return result

>>> parse_ages("name,age\nAlice,30\nBob,N/A")
[{'name': 'Alice', 'age': 30}, {'name': 'Bob', 'age': None}]

Log Analyzer

Build a function that extracts and converts status codes from log lines, classifying each safely even if a line is malformed.

def classify_status_line(status_str):
    try:
        code = int(status_str)
    except ValueError:
        return "invalid"
    if 200 <= code < 300:
        return "success"
    elif 400 <= code < 500:
        return "client_error"
    elif code >= 500:
        return "server_error"
    return "other"

>>> classify_status_line("404")
'client_error'
>>> classify_status_line("N/A")
'invalid'

Mini Projects

• Config loader — reads a dict of raw string values and converts each to its declared type (int/float/bool), reporting any that fail.
• CLI calculator — safely converts two input() values to float and applies a chosen arithmetic operator, handling invalid input without crashing.
• Environment-variable validator — checks a list of required env vars exist and are convertible to their expected types before a script proceeds.

Quick Interview Answer

“These exercises reinforce the chapter’s core ideas hands-on: the input converter exercises try/except around a dynamic target type plus the boolean-string gotcha, the CSV parser exercises per-row resilience so one bad record doesn’t crash the whole import, and the log analyzer combines safe conversion with chained-comparison classification from 7.12 Chained Comparisons.”

Common Mistakes

• Letting one malformed CSV row crash the entire parse instead of catching the conversion failure per-row and continuing.
• Forgetting the boolean branch in convert_input needs its own logic — calling bool(value) directly on a string would always return True for any non-empty input.
• Not handling the case where target_type itself is invalid or unexpected, instead of assuming callers always pass one of the anticipated types.