Dictionaries in Python

Master Python dictionaries (maps): creation, access, mutation, traversal, comparison, copying, merging, dictionary comprehension, and practical usage patterns.

Introduction to Dictionaries

A dictionary is a key-value data structure used to map unique keys to values.

1. What is a Dictionary?

Key-value mapping.

Creating Dictionaries

Dictionaries can be created using literals or the dict() constructor.

1. Dictionary Literal

Recommended way.

2. dict() Constructor

Using keyword arguments.

Accessing & Updating Values

Dictionary values can be accessed using keys.

1. Access by Key

Use square brackets or get().

2. Updating Values

Modify existing keys.

Adding & Deleting Keys

Dictionaries are dynamic and can grow or shrink.

1. Adding Key

Assign new key.

2. Deleting Key

Use del or pop().

Traversing Dictionaries

Loop through keys, values, or key-value pairs.

1. Loop Through Keys

Iterate keys only.

2. Loop Through Key-Value Pairs

Use items().

Comparing Dictionaries

Dictionaries compare by value, not reference.

1. Value Comparison

Use == operator.

Copying Dictionaries

Understand shallow vs deep copy.

1. Shallow Copy

Use copy().

2. Deep Copy

Use copy module.

Merging Dictionaries

Combine multiple dictionaries.

1. Using | Operator (Python 3.9+)

Merge two dicts.

Dictionary Comprehension

Create dictionaries dynamically using comprehension.

1. Basic Transformation

Create key-value pairs.

2. Conditional Dictionary

Filter inside comprehension.

Dictionary Unpacking

Unpacking allows extracting and spreading key-value pairs into new dictionaries, function calls, and assignments.

1. Basic ** Unpacking

Expand dictionary into another dictionary.

2. Overriding Keys During Unpacking

Later values overwrite earlier keys.

3. Creating a Shallow Copy

Using unpacking to copy.

4. Unpacking into Function Arguments

Pass dictionary as named parameters.

5. Mixing Fixed Keys and Unpacked Keys

Combine manual keys with unpacked dictionary.

Dictionary Pattern Matching (Python 3.10+)

Pattern matching allows structural destructuring of dictionaries in a safe and expressive way.

1. Basic Dictionary Pattern

Extract values directly from structure.

2. Partial Matching

Match only some keys.

3. Pattern with Guard Condition

Add extra validation.

4. Nested Dictionary Matching

Match deep structures.

5. Using Wildcards (_)

Ignore values you do not care about.

Additional Dictionary Operations

These are important built-in dictionary methods commonly used in real applications.

1. keys(), values(), items()

Retrieve dictionary views.

2. pop() and popitem()

Remove and return values.

3. setdefault()

Insert key only if missing.

4. update()

Modify dictionary in-place.

5. fromkeys()

Create dictionary from keys.

Sorting Dictionaries

Dictionaries themselves are not sorted automatically, but can be sorted using sorted().

1. Sort by Keys

Use sorted() on keys.

2. Sort by Values

Use sorted() with key parameter.

Specialized Dictionary Types

Python provides advanced dictionary-like data structures for special use cases.

1. defaultdict

Automatic default values.

2. Counter

Count occurrences easily.

Hashing Rules for Dictionary Keys

Understanding why some objects cannot be dictionary keys is critical.

1. Why Keys Must Be Immutable

Hashable requirement.