https://github.com/arthurgousset/algorithms

✨ Algorithms cheat sheet
https://github.com/arthurgousset/algorithms

algorithms data-structures

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✨ Algorithms cheat sheet

• Host: GitHub
• URL: https://github.com/arthurgousset/algorithms
• Owner: arthurgousset
• License: mit
• Created: 2021-05-04T18:41:37.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-05-29T13:57:52.000Z (6 months ago)
• Last Synced: 2024-10-14T01:16:39.950Z (about 1 month ago)
• Topics: algorithms, data-structures
• Language: Python
• Homepage:
• Size: 11.7 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Algorithms and Data Structures (Cheat Sheet)

> [!NOTE]  

> This is a cheat sheet on algorithms and data structures (mostly notes-to-self). They are

> incomplete by default.

## Data structures

### Associative arrays (or dictionaries, maps, hash tables)

Source: ChatGPT

An associative array is a data structure that represents a collection of key-value pairs, where each

unique key is associated with a value. It allows for efficient retrieval, insertion, and deletion of

values based on their associated keys. This concept is fundamental in computer science and is

implemented in various programming languages under different names.

“Associative array” is often used interchangeably with “dictionary” (or “dict” in some languages

like Python), “map” (in Java, C++), or “hash table” (in several contexts). In essence, associative

arrays and dictionaries are conceptually the same. The difference is mostly semantic and contextual,

depending on the programming language or community.

Characteristics of an associative array:

1.  Keys and Values: Each element in an associative array consists of a unique key and a

    corresponding value.

1.  Key Lookup: The primary operation is the ability to quickly retrieve a value based on its key.

1.  Dynamic Size: Associative arrays can grow or shrink dynamically as key-value pairs are added or

    removed.

1.  Efficient Access: Optimized for average-case constant time complexity $O(1)$ for lookups,

    insertions, and deletions, assuming a good hash function.

For example:

1.  "Associative Array" (JavaScript Object)

    ```js

    let associativeArray = {

      name: "Alic",

      age: 30,

      job: "Software Engineer",

    };

    console.log(associativeArray["name"]); // Output: Alice

    ```

1.  "Dictionary" (Python)

    ```py

    dictionary = {

        "name": "Alice",

        "age": 30,

        "job": "Software Engineer"

    }

    print(dictionary["name"])  # Output: Alice

    ```