Why dictionaries are used in Python - Performance Analysis

Time Complexity: Why dictionaries are used

O(1)

Understanding Time Complexity

We want to understand why dictionaries are chosen for certain tasks in Python.

How does using a dictionary affect the speed of finding or storing data?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

my_dict = {"apple": 3, "banana": 5, "orange": 2}

# Access a value by key
value = my_dict["banana"]

# Add a new key-value pair
my_dict["grape"] = 7

# Check if a key exists
exists = "apple" in my_dict

# Remove a key-value pair
del my_dict["orange"]

This code shows common dictionary operations: accessing, adding, checking, and deleting items by key.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Accessing or modifying items by key in the dictionary.
• How many times: Each operation happens once here, but in real use, these can happen many times.

How Execution Grows With Input

When the dictionary grows bigger, how does the time to find or add a key change?

Input Size (n)	Approx. Operations
10	About 1 step or less
100	About 1 step or less
1000	About 1 step or less

Pattern observation: The time to find or add a key stays almost the same even if the dictionary gets bigger.

Final Time Complexity

Time Complexity: O(1)

This means looking up or changing a value by key takes about the same short time no matter how many items are in the dictionary.

Common Mistake

[X] Wrong: "Finding a value in a dictionary takes longer as the dictionary gets bigger."

[OK] Correct: Dictionaries use a special method that lets them find keys quickly without checking every item, so size does not slow them down much.

Interview Connect

Knowing why dictionaries are fast helps you choose the right tool for storing and finding data quickly in real projects.

Self-Check

"What if we changed the dictionary keys to be lists instead of strings? How would the time complexity change?"

Practice

1. Why do programmers use dictionaries in Python?
my_dict = {'name': 'Alice', 'age': 25}

easy

A. To create loops automatically

B. To store data with unique keys for quick access

C. To perform mathematical calculations faster

D. To store data in a fixed order only

Solution

1. Step 1: Understand dictionary structure

   Dictionaries store data as key-value pairs, where each key is unique.

2. Step 2: Identify the main use

   This structure allows quick access to values using keys, unlike lists which use indexes.

3. Final Answer:

   To store data with unique keys for quick access -> Option B

4. Quick Check:

   Dictionaries = unique keys + fast access [OK]

Hint: Dictionaries use keys to find data fast [OK]

Common Mistakes:

• Thinking dictionaries store data in order only
• Confusing dictionaries with lists for calculations
• Believing dictionaries create loops automatically

2. Which of the following is the correct way to create a dictionary in Python?

easy

A. my_dict = ('key1', 'value1', 'key2', 'value2')

B. my_dict = ['key1', 'value1', 'key2', 'value2']

C. my_dict = {'key1': 'value1', 'key2': 'value2'}

D. my_dict = 'key1': 'value1', 'key2': 'value2'

Solution

1. Step 1: Recognize dictionary syntax

   Dictionaries use curly braces {} with key:value pairs separated by commas.

2. Step 2: Compare options

   my_dict = {'key1': 'value1', 'key2': 'value2'} uses correct syntax with braces and colons; others use lists, tuples, or invalid syntax.

3. Final Answer:

   my_dict = {'key1': 'value1', 'key2': 'value2'} -> Option C

4. Quick Check:

   Curly braces + key:value pairs = dictionary [OK]

Hint: Dictionaries use curly braces and colons [OK]

Common Mistakes:

• Using square brackets instead of curly braces
• Using tuples instead of dictionaries
• Missing curly braces or colons

3. What will be the output of this code?

phone_book = {'Alice': '1234', 'Bob': '5678'}
print(phone_book['Bob'])

medium

A. 5678

B. Bob

C. 1234

D. KeyError

Solution

1. Step 1: Understand dictionary key access

   Accessing phone_book['Bob'] retrieves the value for key 'Bob'.

2. Step 2: Find the value for 'Bob'

   In the dictionary, 'Bob' maps to '5678'.

3. Final Answer:

   5678 -> Option A

4. Quick Check:

   phone_book['Bob'] = '5678' [OK]

Hint: Access value by key inside brackets [OK]

Common Mistakes:

• Confusing keys and values
• Expecting the key name as output
• Mistyping key causing KeyError

4. Find the error in this code that tries to add a new entry to a dictionary:

contacts = {'John': '1111'}
contacts.add('Mary', '2222')

medium

A. Missing parentheses in dictionary creation

B. Dictionary keys cannot be names

C. Keys must be integers, not strings

D. Using .add() method which does not exist for dictionaries

Solution

1. Step 1: Check method used to add items

   Dictionaries do not have an .add() method; items are added by assignment.

2. Step 2: Correct way to add entry

   Use contacts['Mary'] = '2222' to add a new key-value pair.

3. Final Answer:

   Using .add() method which does not exist for dictionaries -> Option D

4. Quick Check:

   Add items by assignment, not .add() [OK]

Hint: Add dict items with assignment, not .add() [OK]

Common Mistakes:

• Trying to use set methods on dictionaries
• Confusing dictionary syntax with list methods
• Assuming keys must be numbers

5. You have a list of students and their scores:

students = [('Anna', 85), ('Ben', 90), ('Anna', 95)]

How can you create a dictionary that stores the highest score for each student?

hard

A. Use a loop to update the dictionary only if the new score is higher

B. Use a dictionary comprehension without conditions

C. Store all scores in a list as dictionary values

D. Use a set instead of a dictionary

Solution

1. Step 1: Understand the problem

   We want one highest score per student, so duplicates must be checked.

2. Step 2: Use a loop to update scores

   Loop through the list, and for each student, update the dictionary only if the new score is higher than the current stored score.

3. Final Answer:

   Use a loop to update the dictionary only if the new score is higher -> Option A

4. Quick Check:

   Update dict with max score per key [OK]

Hint: Update dict values only if new value is higher [OK]

Common Mistakes:

• Using comprehension without checking scores
• Storing multiple scores instead of highest
• Using sets which don't map keys to values