Validating Input

Session 22 handled the happy path and basic type errors. Real input has more edge cases: empty strings, whitespace, out-of-range values, and wrong types entirely.

1. Learning Objective

2. Pre-Coding Quiz

Answer these before reading the concept explanation or writing any code. It is fine to get these wrong — that is the point. You need 4/5 to proceed to the lab.

3. The Concept — Thorough Input Validation

Whitespace-only input is not empty

A naive if not text: check misses whitespace-only strings, since they have nonzero length and are therefore truthy. Always .strip() before checking emptiness.

name = "   "
print(bool(name))          # True! Not empty by length
print(bool(name.strip()))  # False — after stripping, it really is empty

def validate_name(raw):
    cleaned = raw.strip()
    if not cleaned:
        raise ValueError("name cannot be empty or whitespace-only")
    return cleaned

Parsing success is not the same as business validity

A number can parse just fine and still be unacceptable for your specific rules. Both checks are needed, and they check different things.

def validate_population(raw):
    raw = raw.strip()
    try:
        value = int(raw)
    except ValueError:
        raise ValueError(f"'{raw}' is not a valid whole number")

    if value < 0:
        raise ValueError(f"population cannot be negative, got {value}")
    if value > 2_000_000_000:
        raise ValueError(f"population {value} exceeds a plausible maximum")

    return value

One shared validation function, used everywhere

Rather than repeating a range check inline in the menu, in a data importer, and in a test, define it once and call it from every path that needs it — connecting back to Session 10's module discipline.

# validators.py
def validate_population(raw):
    raw = raw.strip()
    try:
        value = int(raw)
    except ValueError:
        raise ValueError(f"'{raw}' is not a valid whole number")
    if value < 0:
        raise ValueError(f"population cannot be negative, got {value}")
    return value

# input_lab.py (Session 22) can now import and reuse this directly
from validators import validate_population

def prompt_set_population(country):
    raw = input(f"New population for {country.name}: ")
    try:
        value = validate_population(raw)
        country.set_population(value)
    except ValueError as e:
        print("Rejected:", e)

User error vs a program bug

A user typing bad input is expected and must be handled gracefully with a clear message — this is not a bug. A genuine bug is the program itself doing something it should never do, like a typo'd variable name raising NameError. Session 11's "catch narrowly" advice is exactly why we only catch the specific exceptions we expect from user input.

4. Lab

What you will build

Two files: validators.py and an updated menu.py.

Step-by-step instructions

# validators.py
def validate_name(raw):
    cleaned = raw.strip()
    if not cleaned:
        raise ValueError("name cannot be empty or whitespace-only")
    return cleaned

def validate_population(raw):
    raw = raw.strip()
    try:
        value = int(raw)
    except ValueError:
        raise ValueError(f"'{raw}' is not a valid whole number")
    if value < 0:
        raise ValueError(f"population cannot be negative, got {value}")
    if value > 2_000_000_000:
        raise ValueError(f"population {value} exceeds a plausible maximum")
    return value

test_cases = ["", "   ", "abc", "-5", "54000000"]
for case in test_cases:
    try:
        print(f"'{case}' ->", validate_population(case))
    except ValueError as e:
        print(f"'{case}' -> rejected:", e)

# menu.py
from validators import validate_name, validate_population

class Country:
    def __init__(self, name, region, population):
        self.name = name
        self.region = region
        self.population = population

    def summary(self):
        return f"{self.name} ({self.region}): pop. {self.population:,}"

    def set_population(self, value):
        if value < 0:
            raise ValueError(f"population must be non-negative, got {value}")
        self.population = value

def prompt_set_population(country):
    raw = input(f"New population for {country.name}: ")
    try:
        value = validate_population(raw)
    except ValueError as e:
        print("Invalid input:", e)
        return
    country.set_population(value)
    print("Updated:", country.summary())

if __name__ == "__main__":
    kenya = Country(name="Kenya", region="Africa", population=54000000)
    while True:
        choice = input("(s)et population, (v)iew, (q)uit: ").strip().lower()
        if choice == "q":
            break
        elif choice == "s":
            prompt_set_population(kenya)
        elif choice == "v":
            print(kenya.summary())

5. Expected Files Changed

6. Commit Checkpoint

Once the lab is complete and you can explain every line, make this exact commit:

git add validators.py menu.py docs/sessions/session-24/index.html
git commit -m "session-24: add thorough, reusable input validation for name and population"

7. Code Review Checklist

Go through your code line by line and check each item:

8. Post-Coding Quiz

Same 5 questions. Take it again now that you have written and run the code. You need 4/5 to mark this session complete.

9. Reflection Questions

Think through these after the post-quiz. No right answer — they are for discussion.

10. What Breaks If This Knowledge Is Missing?

11. What We Learned