Conditionals & Booleans

Real programs make decisions: flag an outlier, grade a score, route a customer. Everything hinges on questions that evaluate to True or False. In this lesson you'll master comparisons and boolean logic, then use if/elif/else to branch your code — plus the handful of pitfalls that account for most beginner bugs.

Comparison operators produce booleans

You met these briefly in the data-types lesson. Every comparison evaluates to a bool, and you can store that result in a well-named variable:

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score = 70 print(score >= 85) # greater than or equal print(score < 85) # less than print(score == 70) # equal - note the DOUBLE equals print(score != 70) # not equal good_score = score >= 85 print(good_score, type(good_score)) # "in" checks membership in a collection animals = ["cow", "fish", "cat"] print("cow" in animals) print("dog" in animals) print("dog" not in animals)

Combining conditions: and, or, not

Real rules usually involve several conditions at once. Python combines booleans with plain English words:

• a and b — True only if both are true
• a or b — True if at least one is true
• not a — flips the value

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score = 70 average_score = score >= 60 and score < 85 print(average_score) failed_or_flagged = score < 50 or score > 100 print(failed_or_flagged) print(not average_score) # Python bonus: comparisons can be CHAINED print(60 <= score < 85) # same as: score >= 60 and score < 85

That last line is a lovely Python idiom — 60 <= score < 85 reads exactly like the math notation and replaces an explicit and. Use it whenever you're checking that a value falls inside a range.

if / else: your first branch

An if statement runs its indented block only when the condition is True; the optional else block runs otherwise. Indentation isn't decoration in Python — it is the block structure:

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score = 70 if score >= 85: print("Good score") else: print("Not a good score") # The condition can be any expression that evaluates to a bool threshold = 60 if score >= threshold: print(f"{score} passes the threshold of {threshold}")

elif: many branches, first match wins

When there are more than two outcomes, chain conditions with elif ("else if"). Python checks each condition top to bottom and runs only the first block whose condition is true — the rest are skipped:

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def grade(score): if score >= 85: return "Good score" elif score >= 60: return "Average score" elif score >= 50: return "Bad score" else: return "Not passed" for s in [95, 70, 55, 30]: print(s, "->", grade(s))

Notice the second branch is just score >= 60, not score >= 60 and score < 85. It doesn't need the upper bound: if the score were 85 or more, the first branch would already have caught it. Ordering your conditions from strictest to loosest keeps each one simple — and getting that order wrong is a classic logic bug (put score >= 50 first and everything above 50 lands there).

Nested conditions

An if can live inside another if — just indent one level deeper. Use nesting when a second decision only makes sense after the first:

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def ticket_price(age, is_member): if age < 17: return 25000 # kids pay one flat price else: if is_member: # adults: membership matters return 40000 else: return 50000 print(ticket_price(12, False)) print(ticket_price(30, True)) print(ticket_price(30, False))

Nesting more than two levels deep gets hard to read. Often you can flatten it with and — if age >= 17 and is_member: — or by returning early. Prefer whichever version you can read aloud without stumbling.

Truthiness: non-booleans in conditions

Python lets any value stand in a condition. Empty things — 0, "", [], {}, None — count as False; everything else counts as True. This is called truthiness, and it makes "is there anything here?" checks very concise:

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print(bool(0), bool(42)) print(bool(""), bool("hi")) print(bool([]), bool([1, 2])) print(bool(None)) results = [] if results: print("Found", len(results), "results") else: print("No results - nothing to analyze") name = "Rama" if name: # idiomatic "is name non-empty?" print(f"Hello, {name}")

One caution: truthiness can't distinguish "missing" from "legitimately zero". If 0 is a valid value in your data, test explicitly with value is None instead of if value:.

Ternary expressions: if in one line

When each branch just picks a value, Python's conditional expression squeezes the whole decision into one line: value_if_true if condition else value_if_false.

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score = 70 status = "pass" if score >= 60 else "fail" print(status) # Great for labeling values inside f-strings and list operations ages = [15, 22, 17, 34] labels = ["adult" if age >= 18 else "minor" for age in ages] print(labels)

Keep ternaries for genuinely simple picks. The moment you're tempted to nest one inside another, switch back to a full if/elif block.

Check your understanding

5 questions · free

1. Q1.What is the difference between score = 85 and score == 85?

   ANone - they're interchangeableB= assigns the value 85 to score; == compares score against 85 and yields True/FalseC== assigns, = comparesD== only works on strings

2. Q2.score is 70. What does the chain if score >= 50: ... elif score >= 60: ... elif score >= 85: ... print?

   AThe score >= 85 branchBThe score >= 60 branchCThe score >= 50 branchDNothing - no branch matches

3. Q3.Which expression is equivalent to 60 <= score < 85?

   Ascore >= 60 or score < 85Bscore >= 60 and score < 85Cnot (score < 60)Dscore in [60, 85]

4. Q4.Which of these values is truthy?

   A0B"" (empty string)C[0] (a list containing zero)DNone

5. Q5.What does "pass" if score >= 60 else "fail" do when score is 59?

   ARaises a SyntaxErrorBEvaluates to "pass"CEvaluates to "fail"DPrints "fail"

Exercise: A shipping-cost calculator

Write shipping_cost(weight, is_member=False) for a delivery service. Rules: a weight of 0 or less is invalid — return None; up to 1 kg costs 10000; up to 5 kg costs 25000; above 5 kg costs 25000 plus 4000 for every kg over 5. Members always get 10% off the final price (use a ternary for the discount). Test it with weights 0.5, 3, 8, 8 with membership, and -2.

Next up: loops — running the same logic over every item in your data, automatically.