Dictionaries in Python

A dictionary in Python is a collection of key-value pairs. It allows you to store and retrieve data based on a unique key. Dictionaries are mutable, meaning they can be changed after creation, and they offer fast lookup for retrieving values.

Dictionaries are one of the most versatile and widely used data structures in Python, especially useful when you want to associate one piece of data (the key) with another (the value).

Key Characteristics of Dictionaries

Key-value mapping: Each item is stored as a key and a corresponding value.
Mutable: You can add, update, or remove key-value pairs.
Unordered (prior to Python 3.7): From Python 3.7+, insertion order is preserved.
Keys must be immutable: e.g., strings, numbers, tuples.
Values can be any data type.

Creating Dictionaries

dict_create.py

# Creating a dictionary
empty_dict = {}
person = {"name": "Alice", "age": 30, "city": "New York"}
scores = dict(math=95, science=88)

Explanation:

Dictionaries can be created using {} with key-value pairs, or with the dict() constructor.
Keys are unique within a dictionary.
Values can be of any type.

Example 1: Accessing Values

dict_access.py

person = {"name": "Alice", "age": 30, "city": "New York"}
print(person["name"])
print(person.get("city"))

output.txt

Alice
New York

Explanation:

You can access values by referencing the key inside square brackets [].
Alternatively, get() can be used which returns None if the key is not found (instead of raising an error).

Example 2: Adding and Updating Entries

dict_update.py

person = {"name": "Alice", "age": 30}
 
# Adding a new key-value pair
person["city"] = "New York"
 
# Updating an existing key
person["age"] = 31
 
print(person)

output.txt

{'name': 'Alice', 'age': 31, 'city': 'New York'}

Explanation:

You can add or update dictionary entries by assigning a value to a key.
If the key already exists, its value is updated.

Example 3: Removing Items

dict_remove.py

person = {"name": "Alice", "age": 30, "city": "New York"}
 
# Remove key and return its value
age = person.pop("age")
 
# Remove an arbitrary item
person.popitem()
 
# Clear the dictionary
person.clear()
 
print(person)

output.txt

{}

Explanation:

pop(key) removes a specified key and returns its value.
popitem() removes the last inserted key-value pair.
clear() removes all items.

Example 4: Iterating Over a Dictionary

dict_loop.py

person = {"name": "Alice", "age": 30, "city": "New York"}
 
for key, value in person.items():
    print(f"{key}: {value}")

output.txt

name: Alice
age: 30
city: New York

Explanation:

items() returns a view of key-value pairs, which can be unpacked in a for loop.

Example 5: Dictionary Comprehension

dict_comprehension.py

squares = {x: x**2 for x in range(5)}
print(squares)

output.txt

{0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

Explanation:

Dictionary comprehensions provide a concise way to create dictionaries using loops.

Common Dictionary Methods

Method	Description
`get(key)`	Returns the value for a key
`keys()`	Returns a view of dictionary keys
`values()`	Returns a view of dictionary values
`items()`	Returns a view of key-value pairs
`update(other)`	Updates dictionary with key-value pairs
`pop(key)`	Removes key and returns its value
`popitem()`	Removes and returns the last inserted pair
`clear()`	Removes all items from the dictionary
`copy()`	Returns a shallow copy of the dictionary

Summary

Dictionaries store data as key-value pairs and provide fast lookups.
Keys must be unique and immutable.
Values can be of any type and can even be other dictionaries or lists.
Dictionaries support flexible operations for insertion, updating, deletion, and iteration.

In the next topic, we’ll explore Functions in Python, covering how to define and use reusable blocks of code.

Set Data type Boolean Data type