A concise and comprehensive cheat sheet covering time complexities of Python's built-in data structures like Lists, Dictionaries, Sets, Tuples, and Strings. This resource is designed to help developers write efficient and optimized Python code.
- Understand the average and worst-case complexities of common operations.
- Make informed decisions while working with Python's data structures.
- Write optimized, faster programs with confidence.
- Lists: Dynamic arrays with flexible operations.
- Dictionaries: Hash-based key-value pairs for ultra-fast lookups.
- Sets: Hash-based collections for unique items and efficient membership tests.
- Tuples: Immutable, lightweight sequences.
- Strings: Immutable text sequences optimized for searching and slicing.
Want to help us make this cheat sheet even better? Check out our CONTRIBUTING.md file to get started!
This project is licensed under the MIT License.
Here’s a quick look at time complexities for Lists:
| Operation | Examples | Average Case | Worst Case |
|---|---|---|---|
| Append | l.append(item) |
O(1) | O(1) (resize) |
| Indexing | l[i] |
O(1) | O(1) |
| Containment | item in l |
O(N) | O(N) |
For more details, visit our dedicated cheat sheets! 🚀