Dictionaries in Python

In this article, we'll explore dictionaries (dict) — one of the most powerful and flexible data types in Python.

What is a Dictionary?

A dictionary in Python is a collection of key-value pairs. You can think of a dictionary as a phone book, where people's names (keys) are associated with their phone numbers (values).

Main properties of dictionaries:

• Keys must be unique — you cannot have two identical keys in one dictionary
• Keys must be immutable — you can use strings, numbers, tuples as keys, but not lists or dictionaries
• Values can be of any type — numbers, strings, lists, other dictionaries, etc.
• Starting from Python 3.7, dictionaries preserve the order of adding elements (previously order was not guaranteed)

Creating Dictionaries

There are several ways to create a dictionary in Python:

1. Using curly braces

Python 3.13
123456
# Empty dictionary
empty_dict = {}

# Dictionary with data
person = {"name": "John", "age": 30, "city": "New York"}
print(person)
{'name': 'John', 'age': 30, 'city': 'New York'}
789101112
# Nested dictionaries
nested = {
    "person": {"name": "Mary", "age": 25},
    "contacts": {"email": "mary@example.com", "phone": "+1234567890"}
}
print(nested["person"])
{'name': 'Mary', 'age': 25}

2. Using the dict() constructor

Python 3.13
1234567
# Empty dictionary
empty_dict = dict()

# From a list of tuples (key-value pairs)
pairs = [("name", "Anna"), ("age", 28), ("city", "Berlin")]
person = dict(pairs)
print(person)
{'name': 'Anna', 'age': 28, 'city': 'Berlin'}
8910
# Using keyword arguments (only for string keys)
settings = dict(theme="dark", font_size=12, notifications=True)
print(settings)
{'theme': 'dark', 'font_size': 12, 'notifications': True}

3. Dictionary comprehensions

Python 3.13
123
# Dictionary of squares (number: square of number)
squares = {x: x**2 for x in range(1, 6)}
print(squares)
{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}

4. The fromkeys() method for creating a dictionary with identical values

Python 3.13
1234
# Creating a dictionary with given keys and the same value for all
keys = ["name", "age", "city"]
defaults = dict.fromkeys(keys, None)
print(defaults)
{'name': None, 'age': None, 'city': None}

Accessing Dictionary Elements

Access to values in a dictionary is done through keys:

Accessing by key

Python 3.13
12345
person = {"name": "John", "age": 30, "city": "New York"}

# Getting a value by key
name = person["name"]
print(name)
John
678
# Safe way using the get() method
phone = person.get("phone")  # Returns None if the key doesn't exist
print(phone)
None
91011
# The get() method with a default value
phone = person.get("phone", "Not specified")
print(phone)
Not specified

Checking if a key exists

Python 3.13
1234
person = {"name": "John", "age": 30, "city": "New York"}

# Checking if a key exists
print("name" in person)
True
5
print("phone" not in person)
True

Accessing nested dictionaries

Python 3.13
12345678
nested = {
    "person": {"name": "Mary", "age": 25},
    "contacts": {"email": "mary@example.com", "phone": "+1234567890"}
}

# Accessing values in nested dictionaries
name = nested["person"]["name"]
print(name)
Mary
91011
# Safe access using get()
email = nested.get("contacts", {}).get("email")
print(email)
mary@example.com
121314
# If the path doesn't exist, None or a default value is returned
website = nested.get("contacts", {}).get("website", "Not specified")
print(website)
Not specified

Modifying Dictionaries

Dictionaries in Python are mutable, so they can be easily modified:

Adding and changing elements

Python 3.13
123456
# Creating a dictionary
person = {"name": "John", "age": 30}

# Adding a new key and value
person["city"] = "New York"
print(person)
{'name': 'John', 'age': 30, 'city': 'New York'}
789
# Changing the value of an existing key
person["age"] = 31
print(person)
{'name': 'John', 'age': 31, 'city': 'New York'}
101112
# Using the update() method for bulk updates
person.update({"age": 32, "job": "developer", "language": "Python"})
print(person)
{'name': 'John', 'age': 32, 'city': 'New York', 'job': 'developer', 'language': 'Python'}

Removing elements

Python 3.13
12345
person = {"name": "John", "age": 30, "city": "New York", "job": "developer"}

# Removing an element by key using del
del person["job"]
print(person)
{'name': 'John', 'age': 30, 'city': 'New York'}
678
# Removing and returning an element using pop()
age = person.pop("age")
print(age)
30
9
print(person)
{'name': 'John', 'city': 'New York'}
101112
# pop() with a default value (doesn't raise an error if the key doesn't exist)
job = person.pop("job", "Not specified")
print(job)
Not specified
13141516
# Removing and returning an arbitrary element using popitem()
# In Python 3.7+ returns the last added element
item = person.popitem()
print(item)
('city', 'New York')
17
print(person)
{'name': 'John'}
181920
# Removing all elements
person.clear()
print(person)
{}

Dictionary Methods

Python provides many useful methods for working with dictionaries:

Getting keys, values, and key-value pairs

Python 3.13
12345
person = {"name": "John", "age": 30, "city": "New York"}

# Getting all keys
keys = person.keys()
print(keys)
dict_keys(['name', 'age', 'city'])
678
# Getting all values
values = person.values()
print(values)
dict_values(['John', 30, 'New York'])
91011
# Getting all key-value pairs
items = person.items()
print(items)
dict_items([('name', 'John'), ('age', 30), ('city', 'New York')])
12131415
# The objects dict_keys, dict_values and dict_items are dictionary views
# They dynamically reflect changes in the dictionary
person["job"] = "developer"
print(keys)
dict_keys(['name', 'age', 'city', 'job'])
161718
# Converting views to lists
keys_list = list(keys)
print(keys_list)
['name', 'age', 'city', 'job']

Copying dictionaries

Python 3.13
12345678910111213
import copy

# Dictionary with a nested structure
original = {"name": "John", "settings": {"theme": "dark"}}

# Shallow and deep copies
shallow_copy = original.copy()
deep_copy = copy.deepcopy(original)

# Changing a simple key works the same in both cases
shallow_copy["name"] = "Peter"
deep_copy["name"] = "Alice"
print(f"original['name']: {original['name']}")  # Remains John
original['name']: John
141516
# Differences appear when changing nested structures
shallow_copy["settings"]["theme"] = "light"
print(f"After shallow copy - original['settings']['theme']: {original['settings']['theme']}")  # Changes!
After shallow copy - original['settings']['theme']: light
1718192021
# Create a new original to demonstrate deep copy
original = {"name": "John", "settings": {"theme": "dark"}}
deep_copy = copy.deepcopy(original)
deep_copy["settings"]["theme"] = "light"
print(f"After deep copy - original['settings']['theme']: {original['settings']['theme']}")  # Doesn't change
After deep copy - original['settings']['theme']: dark

Merging dictionaries

Python 3.13
12345678
# Merging dictionaries with update
dict1 = {"a": 1, "b": 2}
dict2 = {"b": 3, "c": 4}

# Create a copy of dict1 and update it with data from dict2
merged = dict1.copy()
merged.update(dict2)
print(merged)
{'a': 1, 'b': 3, 'c': 4}
910
# In Python 3.9+ you can use the | operator
# merged = dict1 | dict2

Setting a default value

Python 3.13
123456789101112
# Counting word frequency
counts = {}
text = "one two one two three"
words = text.split()

# Method 1: checking if the key exists
for word in words:
    if word in counts:
        counts[word] += 1
    else:
        counts[word] = 1
print(counts)
{'one': 2, 'two': 2, 'three': 1}
1314151617
# Method 2: using get()
counts = {}
for word in words:
    counts[word] = counts.get(word, 0) + 1
print(counts)
{'one': 2, 'two': 2, 'three': 1}

Iterating Through Dictionaries

There are several ways to iterate through dictionary elements:

Python 3.13
123456
person = {"name": "John", "age": 30, "city": "New York"}

# Iterating through keys (default method)
print("Iterating through keys:")
for key in person:
    print(key, ":", person[key])
Iterating through keys:
name : John
age : 30
city : New York
78910
# Iterating through values
print("Iterating through values:")
for value in person.values():
    print(value)
Iterating through values:
John
30
New York
11121314
# Iterating through key-value pairs
print("Iterating through key-value pairs:")
for key, value in person.items():
    print(key, ":", value)
Iterating through key-value pairs:
name : John
age : 30
city : New York