Exercises - closures

Basic Closures

Exercise 1 — 🟢 Beginner Create a closure that generates a greeting function for a specific language.

# expected:
# greet_en = make_greeter("Hello")
# greet_es = make_greeter("Hola")
# greet_fr = make_greeter("Bonjour")

# greet_en("Alice")   → "Hello, Alice!"
# greet_es("Alice")   → "Hola, Alice!"
# greet_fr("Alice")   → "Bonjour, Alice!"

Exercise 2 — 🟢 Beginner Create a closure that keeps track of how many times a function has been called.

# expected:
# counter = make_call_counter()
# counter()   → "Called 1 time"
# counter()   → "Called 2 times"
# counter()   → "Called 3 times"

Exercise 3 — 🟢 Beginner Create a closure that applies a fixed discount to any price.

# expected:
# ten_percent_off  = make_discount(10)
# twenty_percent_off = make_discount(20)

# ten_percent_off(100)    → 90.0
# twenty_percent_off(100) → 80.0
# ten_percent_off(50)     → 45.0

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Function Factories

Exercise 4 — 🟡 Intermediate Create a closure that generates a multiplier function for a given factor, then use it with map() to transform a list.

numbers = [1, 2, 3, 4, 5]

# expected:
# double = make_multiplier(2)
# triple = make_multiplier(3)

# double(5)                      → 10
# list(map(double, numbers))     → [2, 4, 6, 8, 10]
# list(map(triple, numbers))     → [3, 6, 9, 12, 15]

Exercise 5 — 🟡 Intermediate Create a closure that generates a power function for a given exponent, then use it with map() and filter().

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# expected:
# square = make_power(2)
# cube   = make_power(3)

# square(4)                                          → 16
# list(map(square, numbers))                         → [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
# list(map(cube, filter(lambda x: x % 2 == 0, numbers))) → [8, 64, 216, 512, 1000]

Exercise 6 — 🟡 Intermediate Create a closure that builds a logger with a fixed prefix and log level.

# expected:
# db_info    = make_logger("DATABASE", "INFO")
# api_error  = make_logger("API", "ERROR")

# db_info("Connection established")   → "[INFO]  [DATABASE] Connection established"
# api_error("Timeout after 30s")      → "[ERROR] [API]      Timeout after 30s"

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Stateful Closures

Exercise 7 — 🟡 Intermediate Create a closure that accumulates values and returns the running total each time it is called.

# expected:
# accumulator = make_accumulator()
# accumulator(10)   → 10
# accumulator(20)   → 30
# accumulator(5)    → 35
# accumulator(100)  → 135

Exercise 8 — 🟡 Intermediate Create a closure that implements a simple stack with push and pop operations, returning both functions.

# expected:
# push, pop = make_stack()
# push(1)
# push(2)
# push(3)
# pop()   → 3
# pop()   → 2
# pop()   → 1
# pop()   → None   ← empty stack

Exercise 9 — 🔴 Advanced Create a closure that implements a rate limiter — it allows a function to be called at most n times, then raises an error.

# expected:
# limited = make_rate_limiter(3)
# limited()   → "Call 1 of 3"
# limited()   → "Call 2 of 3"
# limited()   → "Call 3 of 3"
# limited()   → ❌ RuntimeError: Rate limit exceeded — max 3 calls allowed

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Late Binding Gotcha

Exercise 10 — 🟢 Beginner Fix this broken code so each function returns its own index value:

# ❌ broken
funcs = [lambda: i for i in range(5)]
print([f() for f in funcs])     # [4, 4, 4, 4, 4]

# ✅ fix it so the output is:
# [0, 1, 2, 3, 4]

Exercise 11 — 🟡 Intermediate Fix this broken code that tries to create a list of multiplier functions:

# ❌ broken
multipliers = [lambda x: x * i for i in range(1, 6)]
print([f(10) for f in multipliers])    # [50, 50, 50, 50, 50]

# ✅ fix it so the output is:
# [10, 20, 30, 40, 50]

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Combined Exercises

Exercise 12 — 🔴 Advanced Create a closure that memoizes a function manually — without using functools.lru_cache. It should cache results and return them on repeated calls.

# expected:
# memoized_square = memoize(lambda x: x ** 2)
# memoized_square(4)   → 16  (computed)
# memoized_square(4)   → 16  (from cache)
# memoized_square(5)   → 25  (computed)
# memoized_square(5)   → 25  (from cache)

Exercise 13 — 🔴 Advanced Create a closure that composes two functions together — the output of the first becomes the input of the second. Then use it to build a text processing pipeline.

# expected:
# strip_and_upper = compose(str.upper, str.strip)
# strip_and_upper("  hello  ")    → "HELLO"

# Build a pipeline:
# clean = compose(str.strip, str.lower)
# clean("  HELLO WORLD  ")        → "hello world"

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Try implementing each solution as a pure closure first — no classes, no functools. The goal is to understand how captured state and returned functions can replace objects entirely.