semvec/pypi-packages huggingface dataset:
pyds-fundamental 0.1.5
Production-ready implementation of fundamental data structures implemented in Python
License: MIT
Requires Python: >=3.10

# `pyds-fundamental`: An Implementation of Data Structures

`pyds-fundamental` / `data_structures` contains implementations of various data structures. 

Currently trying to make this a fully functioning library where you can basically use implemented data structures as-intended.

To see all the functionalities, check out the [document here.](https://999-juicewrld.github.io/data_structures/data_structures.html)

Current data structures are:
- Linked Lists
    - Singly Linked List
    - Doubly Linked List
- Stacks
    - Array Stack
    - Linked Stack (Using Linked List)
- Queues
    - Array Queue
    - Linked Queue (Using Linked List)
    - Circular Queue
    - Priority Qeueue (Using Linked List)
- Binary Search Tree
- AVL Tree
- Red-Black Tree

To download this package, go to terminal:
```sh
pip install pyds-fundamental
```

Example usage:
```py
from data_structures import BinarySearchTree, AVLTree

bst = BinarySearchTree()
bst.insert(12)
bst.insert(8)
bst.insert(16)

for node in bst.inorder_traversal():
    print(node)

# 8
# 12
# 16

import random

avl = AVLTree()
for _ in range(20):
    avl.insert(random.randint(0, 100))
avl.pretty_print()

# Output:

           ________59___________     
          /                     \    
   ______15___           ______88_   
  /           \         /         \  
 _9___       20_       66___     95_ 
/     \     /   \     /     \       \
3    13_   19  41_   64    70_     98
 \  /   \         \       /   \      
 8 11  13        46      68  75 
```
pure-validator 0.3.0
Purity validator for Python code.
License: MIT
Requires Python: >=3.12

# Pure validator

Purity validator for Python code.

[![GitHub](https://img.shields.io/github/stars/jdahlin/pure?style=social)](https://github.com/jdahlin/pure)

## Overview

Pure validator is a static analysis tool for checking the purity of Python functions and modules. It analyzes Python source code and reports on side effects, global state usage, and other purity-related concerns.

Suppose you have the following code:

```python
def impure_function(): # pragma: pure
    print("This is impure!")
```

Running the purity checker, will report an error similar to:

```
example.py:3: Function 'impure_function' is marked as pure but has side effects (print statement)
```

There is also a [flake8](https://flake8.pycqa.org/) plugin available that can be used to check purity violations in your codebase.

```bash
$ flake8 --select PURE file-or-directory
```

For more information on using flake8, you can refer to the official [flake8](https://flake8.pycqa.org/) documentation.

## Features
- Recursively analyzes Python files in directories
- Reports purity violations and messages
- CLI and module entry point (`python -mpure_validator`)
- Easy integration with CI/CD

## Installation

You can install Pure via pip:

```bash
$ pip install pure-validator
```

## Usage

### Command Line


```bash
$ pure-validator file-or-directory
```

## Contributing

Contributions are welcome! Please open issues or pull requests on [GitHub](https://github.com/jdahlin/pure).

## License

This project is licensed under the terms of the license found in the `LICENSE` file.