Welcome to Dictionaries in Python
Dictionaries are one of Python’s most powerful and versatile data structures. At its core, a dictionary is an unordered collection of key-value pairs. Think of it like a real-world dictionary where you look up a word (the “key”) to find its definition (the “value”).
This mapping allows for incredibly fast data retrieval, making dictionaries the ideal choice for a wide range of tasks, from storing application settings to representing complex data objects like a user profile.
As of Python 3.7, dictionaries remember the order in which items were inserted. This feature makes them even more useful for tasks where order matters.
Why are Dictionaries so Important?
- Fast & Efficient: Dictionaries use a technique called hashing to provide near-instantaneous lookups, insertions, and deletions (average O(1) time complexity).
- Flexible & Expressive: Keys must be immutable (like strings, numbers, or tuples), but values can be any Python object—lists, other dictionaries, functions, you name it. This allows you to build complex, nested data structures.
- Human-Readable: They naturally represent structured data. When you work with formats like JSON (JavaScript Object Notation), you’ll find that they map directly to Python dictionaries.
Pyground
Create a simple dictionary to represent a book and then access its author.
Expected Output:
Douglas Adams
Output:
Explore the Dictionary Guide
This guide covers everything you need to know about Python dictionaries, from the basics of creation to advanced performance patterns.
Building Dictionaries
Learn all the ways to create a dictionary: using literals, the dict() constructor, comprehensions, and from other data structures.
Mastering dictionaries is a huge step towards becoming a proficient Python programmer. They are used everywhere, from web frameworks like Django and Flask to data science libraries like Pandas.