The Secret Life of Python: The Silent Type (Type Casting)

Source: Dev.to

The Problem

Timothy wrote a simple guessing game, but even when he typed the correct number, the program told him he was wrong.

# Timothy's Guessing Game
secret_number = 7

guess = input("Guess the number (1-10): ")

if guess == secret_number:
    print("You won! Amazing!")
else:
    print(f"Sorry, you guessed {guess}, but the number was {secret_number}.")

Output

Guess the number (1-10): 7
Sorry, you guessed 7, but the number was 7.

Why It Happens: Strong Typing in Python

• input() always returns a string (str).
• secret_number is an integer (int).

Python does not perform implicit type conversion when comparing values of different types. The comparison guess == secret_number is therefore False because '7' (a string) is not the same as 7 (an integer).

Analogy: Comparing a photograph of a dog to the real dog—both look similar, but they are fundamentally different objects.

The Fix: Explicit Type Casting

Wrap the input() call with int() (or another appropriate cast) to convert the entered text to an integer.

# Timothy's Fixed Game
secret_number = 7

# Convert the input string to an integer
guess = int(input("Guess the number (1-10): "))

if guess == secret_number:
    print("You won! Amazing!")
else:
    print(f"Sorry, you guessed {guess}, but the number was {secret_number}.")

Output

Guess the number (1-10): 7
You won! Amazing!

Important Note

If the user types a non‑numeric word like "seven", int() will raise a ValueError. Handling such cases gracefully (e.g., with try/except or validation) is a topic for a later lesson.

Quick Reference: Common Casts

• int("5") → 5 (whole number)
• float("5") → 5.0 (decimal number)
• str(5) → "5" (useful for concatenation or printing)

Attempting int("hello") will raise a ValueError.

Takeaways

• Rule: input() returns a string, regardless of what the user types.
• Fix: Use explicit type casting (int(), float(), etc.) to match the expected data type.
• Benefit: Python’s strict typing prevents accidental operations on mismatched types, encouraging clearer, more reliable code.

Looking Ahead

In the next episode, Timothy will encounter “The Phantom Copy”, where copying a list leads to unexpected changes in the backup—a classic case of mutable object references.