beginnerPython Framework • Core Concepts

Dictionaries: Key-Value Pairs

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Introduction to Dictionaries

A dictionary is a fast, flexible container that maps unique keys to values. Unlike lists, which are indexed by numbers (0, 1, 2...), dictionaries are indexed by keys, which can be strings, numbers, or even tuples. They are the backbone of data representation in Python.

Python
# A simple contact book
contacts = {
    "Alice": "555-1234",
    "Bob": "555-9876"
}

# Lookup by name (key)
print(contacts["Alice"])  # "555-1234"

Dictionary Visualization

Key (Name) → Value (Phone)
{
"Alice":"555-1234",
"Bob":"555-9876"
}
💡 Access values using Key (Name) → Value (Phone)["key"] — hover over entries to see access syntax

Creating Dictionaries

You can create dictionaries using the literal syntax {} or the dict() constructor. The literal syntax is faster and more common.

Python
# Literal syntax (Recommended)
student = {"name": "Alice", "age": 25}

# dict() constructor
car = dict(brand="Toyota", model="Corolla")

# Empty dictionary
empty = {}

Dictionary Visualization

student = {...}
{
"name":"Alice",
"age":25
}
💡 Access values using student = {...}["key"] — hover over entries to see access syntax

Accessing Values

Access values using square brackets [key]. If you're unsure if a key exists, use .get(key) to avoid errors. .get() returns None (or a default) if the key is missing.

Python
student = {"name": "Alice", "age": 25}

# Direct access
print(student["name"])  # "Alice"
# print(student["grade"])  # KeyError!

# Safe access with .get()
grade = student.get("grade")  # None
score = student.get("score", 0)  # 0 (default)

Dictionary Visualization

student.get("name") → "Alice"
{
"name":"Alice",
"age":25
}
💡 Access values using student.get("name") → "Alice"["key"] — hover over entries to see access syntax

Updating & Adding

Dictionaries are mutable. Assign a value to a key to add it (if new) or update it (if it exists).

Python
student = {"name": "Alice", "age": 25}

# Add new key
student["grade"] = "A"

# Update existing key
student["age"] = 26

print(student)
# {'name': 'Alice', 'age': 26, 'grade': 'A'}

Dictionary Visualization

Modified age, added grade
{
"name":"Alice",
"age":26,Modified age, added grade["age"] → 26
"grade":"A"Modified age, added grade["grade"] → "A"
}
💡 Access values using Modified age, added grade["key"] — hover over entries to see access syntax

Removing Items

Use .pop(key) to remove a key and return its value. 'del' deletes a key without returning. .popitem() removes the last inserted item (LIFO). .clear() wipes the dictionary.

Python
student = {"name": "Alice", "age": 26, "grade": "A"}

# Remove and get value
grade = student.pop("grade")  # "A"

# Delete specific key
del student["age"]

# Remove last item
item = student.popitem()  # ('name', 'Alice')

print(student)  # {}

Dictionary Visualization

After popping 'grade'
{
"name":"Alice",
"age":26
}
💡 Access values using After popping 'grade'["key"] — hover over entries to see access syntax

Iteration

You can loop over a dictionary's keys, values, or both. Looping over the dictionary directly yields keys.

Python
data = {"a": 1, "b": 2}

# Loop over keys (default)
for key in data:
    print(key)  # "a", "b"

# Loop over keys and values
for key, val in data.items():
    print(f"{key}: {val}")

Dictionary Visualization

for k, v in data.items()
{
"a":1,
"b":2
}
💡 Access values using for k, v in data.items()["key"] — hover over entries to see access syntax

Dictionary Methods

.keys(), .values(), and .items() return view objects. These views update dynamically if the dictionary changes.

Python
d = {"x": 10, "y": 20}

keys = d.keys()    # dict_keys(['x', 'y'])
vals = d.values()  # dict_values([10, 20])
items = d.items()  # dict_items([('x', 10), ('y', 20)])

Dictionary Visualization

.keys(), .values(), .items()
{
"x":10,
"y":20
}
💡 Access values using .keys(), .values(), .items()["key"] — hover over entries to see access syntax

Nested Dictionaries

Dictionaries can contain other dictionaries. This is great for representing complex hierarchical data like JSON responses or database records.

Python
students = {
    "Alice": {"age": 25, "grade": "A"},
    "Bob": {"age": 22, "grade": "B"}
}

# Access nested value
print(students["Alice"]["grade"])  # "A"

Real-World Examples

Dictionaries are everywhere: user profiles, configuration settings, counting frequencies, and caching results.

Python
# 1. Frequency Counter
text = "apple banana apple"
counts = {}
for word in text.split():
    counts[word] = counts.get(word, 0) + 1
# {'apple': 2, 'banana': 1}

# 2. Config Settings
config = {
    "theme": "dark",
    "notifications": True,
    "volume": 80
}

Dictionary Visualization

Word frequency count
{
"apple":2,
"banana":1
}
💡 Access values using Word frequency count["key"] — hover over entries to see access syntax

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Visual Lab

Dictionary Visualization

student = {'name': 'Alice', ...}
{
"name":"Alice",
"age":25,
"city":"NYC"
}
💡 Access values using student = {'name': 'Alice', ...}["key"] — hover over entries to see access syntax

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