Exercises - Memory model

Exercises — Python Memory Model

References and Identity

Exercise 1 — 🟢 Beginner Predict the output of the following code before running it, then verify your answer.

a = [1, 2, 3]
b = a
c = [1, 2, 3]

print(a == b)       # ?
print(a is b)       # ?
print(a == c)       # ?
print(a is c)       # ?

b.append(4)
print(a)            # ?
print(c)            # ?

Exercise 2 — 🟢 Beginner Predict the output of the following code before running it, then verify your answer.

a = 42
b = a

print(a is b)       # ?

a += 1

print(a)            # ?
print(b)            # ?
print(a is b)       # ?

Exercise 3 — 🟡 Intermediate Predict the output of the following code before running it. Pay close attention to what is returns for integers inside and outside the CPython cache range.

a = 256
b = 256
print(a is b)       # ?

a = 257
b = 257
print(a is b)       # ?

a = -5
b = -5
print(a is b)       # ?

a = -6
b = -6
print(a is b)       # ?

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Shallow vs Deep Copy

Exercise 4 — 🟢 Beginner Predict the output of the following code before running it.

import copy

a = [1, 2, 3]
b = a.copy()

a.append(4)

print(a)            # ?
print(b)            # ?
print(a is b)       # ?

Exercise 5 — 🟡 Intermediate Predict the output of the following code before running it. Think carefully about what shallow copy means for nested structures.

import copy

original = [[1, 2], [3, 4]]
shallow  = original.copy()
deep     = copy.deepcopy(original)

original[0].append(99)
original.append([5, 6])

print(original)     # ?
print(shallow)      # ?
print(deep)         # ?

Exercise 6 — 🟡 Intermediate Fix this function so that modifying the returned list does not affect the original:

# ❌ broken — modifying result affects original
def get_items(cart):
    return cart

my_cart = ["apple", "banana", "cherry"]
result  = get_items(my_cart)
result.append("date")

print(my_cart)      # should be ["apple", "banana", "cherry"]
                    # but currently shows ["apple", "banana", "cherry", "date"]

Exercise 7 — 🔴 Advanced Predict the output of the following code, then explain why shallow behaves the way it does.

import copy

original = {"a": [1, 2, 3], "b": [4, 5, 6]}
shallow  = original.copy()
deep     = copy.deepcopy(original)

original["a"].append(99)
original["c"] = [7, 8, 9]

print(original)     # ?
print(shallow)      # ?
print(deep)         # ?

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Never Mutate — Functional Approach

Exercise 8 — 🟢 Beginner Rewrite this mutating function so it returns a new list instead of modifying the original:

# ❌ mutating
def double_all(numbers):
    for i in range(len(numbers)):
        numbers[i] *= 2
    return numbers

nums = [1, 2, 3, 4, 5]
result = double_all(nums)

# after fix:
# nums   should still be [1, 2, 3, 4, 5]
# result should be       [2, 4, 6, 8, 10]

Exercise 9 — 🟢 Beginner Rewrite this mutating function so it returns a new dict instead of modifying the original:

# ❌ mutating
def activate_user(user):
    user["active"] = True
    return user

u = {"name": "Alice", "active": False}
result = activate_user(u)

# after fix:
# u      should still be {"name": "Alice", "active": False}
# result should be       {"name": "Alice", "active": True}

Exercise 10 — 🟡 Intermediate Rewrite this mutating function that removes all negative numbers from a list, without modifying the original:

# ❌ mutating
def remove_negatives(numbers):
    for n in numbers[:]:
        if n < 0:
            numbers.remove(n)
    return numbers

nums   = [3, -1, 4, -2, 5, -3, 6]
result = remove_negatives(nums)

# after fix:
# nums   should still be [3, -1, 4, -2, 5, -3, 6]
# result should be       [3, 4, 5, 6]

Exercise 11 — 🟡 Intermediate Rewrite this mutating function that applies a discount to all items in a shopping cart, without modifying the original:

# ❌ mutating
def apply_discount(cart, discount):
    for item in cart:
        item["price"] *= (1 - discount)
    return cart

cart = [
    {"name": "apple",  "price": 1.0},
    {"name": "banana", "price": 0.5},
    {"name": "cherry", "price": 3.0},
]
result = apply_discount(cart, 0.10)

# after fix:
# cart   should still have original prices
# result should have discounted prices:
# [{"name": "apple",  "price": 0.9},
#  {"name": "banana", "price": 0.45},
#  {"name": "cherry", "price": 2.7}]

Exercise 12 — 🔴 Advanced Rewrite this mutating function that updates a nested configuration dict, without modifying the original at any level:

# ❌ mutating
def update_config(config, section, key, value):
    config[section][key] = value
    return config

config = {
    "server":   {"host": "localhost", "port": 8080},
    "database": {"host": "localhost", "port": 5432},
}
result = update_config(config, "server", "port", 3000)

# after fix:
# config["server"]["port"]  should still be 8080
# result["server"]["port"]  should be       3000
# config and result         should be different objects
# config["database"]        should be the same object in both
#                           (only the modified section needs a new object)

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Try solving each exercise without using copy.deepcopy where possible — the goal is to build the habit of constructing new objects naturally rather than copying and mutating.