# Sorting Module in Python
This Python module provides implementations of several sorting algorithms. The current version includes the following sorting algorithms:
- Bubble Sort
- Merge Sort
- Quick Sort
- Insertion Sort
- Heap Sort
- Shell Sort
- Partial Sort
# How to install and import module
To install the module, you need to write in the terminal.
```
pip install easiest_sort
```
To import the module, you need to write in your Python file
```
from easiest_sort import *
```
## Bubble Sort
Use Case: Simplicity and ease of understanding. Suitable for small data sets or educational purposes. Inefficient for large data sets due to quadratic complexity.
```python
from easiest_sort import bubble_sort
my_list = []
bubble_sort(my_list)
```
## Merge Sort
Use Case: Efficient sorting for large data sets. Relatively stable and well-suited for lists that do not fit entirely in memory
```python
from easiest_sort import merge_sort
my_list = []
merge_sort(my_list)
```
## Quick Sort
Use Case: High efficiency on average and large data sets. Demonstrates good practical performance. Used in various domains, including programming languages and databases.
```python
from easiest_sort import quick_sort
my_list = []
quick_sort(my_list)
```
## Insertion Sort
Use Case: Effective for small or partially ordered data. Convenient when adding new elements to an already sorted part of an array.
```python
from easiest_sort import insertion_sort
my_list = []
insertion_sort(my_list)
```
## Heap Sort
Use Case: Efficient for sorting large data sets. Utilizes the "heap" data structure. Possesses predictable worst-case performance.
```python
from easiest_sort import heap_sort
my_list = []
heap_sort(my_list)
```
## Shell Sort
Use Case: Balances implementation simplicity with good performance. Often applied in scenarios where a trade-off between efficiency and implementation simplicity is desired.
```python
from easiest_sort import shell_sort
my_list = []
shell_sort(my_list)
```
## Ascending and Descending order
If you want to use descending order sorting, you should use the second argument 'order' with a value of False. Its works with every sort algorithm
```python
from easiest_sort import *
my_list = []
bubble_sort(my_array, order=False)
```
# Partial Sort
This module provides a partial_sort function, allowing you to perform partial sorting on a list. With this function, you can sort only the top or bottom k elements of the list, leaving the rest of the elements in their original order.
## Usage
```python
from easiest_sort import partial_sort
my_array = [5, 2, 8, 1, 9, 4, 7, 3, 6]
x1 = partial_sort(my_array, 3, top=True)
x2 = partial_sort(my_array, 3, top=False)
```
Also you can use Reverse Order for Partial Sort
```python
from easiest_sort import partial_sort
my_list = [5, 2, 8, 1, 9, 4, 7, 3, 6]
x = partial_sort(my_array, 3, top=True, reverse=True)
```
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"description": "# Sorting Module in Python\r\n\r\nThis Python module provides implementations of several sorting algorithms. The current version includes the following sorting algorithms:\r\n\r\n- Bubble Sort\r\n- Merge Sort\r\n- Quick Sort\r\n- Insertion Sort\r\n- Heap Sort\r\n- Shell Sort\r\n- Partial Sort\r\n\r\n# How to install and import module \r\n\r\nTo install the module, you need to write in the terminal.\r\n\r\n```\r\npip install easiest_sort\r\n```\r\n\r\nTo import the module, you need to write in your Python file\r\n\r\n```\r\nfrom easiest_sort import *\r\n```\r\n\r\n\r\n## Bubble Sort\r\n\r\nUse Case: Simplicity and ease of understanding. Suitable for small data sets or educational purposes. Inefficient for large data sets due to quadratic complexity.\r\n\r\n```python\r\nfrom easiest_sort import bubble_sort\r\n\r\nmy_list = []\r\nbubble_sort(my_list)\r\n```\r\n\r\n## Merge Sort\r\n\r\nUse Case: Efficient sorting for large data sets. Relatively stable and well-suited for lists that do not fit entirely in memory\r\n\r\n```python\r\nfrom easiest_sort import merge_sort\r\n\r\nmy_list = []\r\nmerge_sort(my_list)\r\n```\r\n\r\n## Quick Sort\r\n\r\nUse Case: High efficiency on average and large data sets. Demonstrates good practical performance. Used in various domains, including programming languages and databases.\r\n\r\n```python\r\nfrom easiest_sort import quick_sort\r\n\r\nmy_list = []\r\nquick_sort(my_list)\r\n```\r\n## Insertion Sort\r\n\r\nUse Case: Effective for small or partially ordered data. Convenient when adding new elements to an already sorted part of an array.\r\n\r\n```python\r\nfrom easiest_sort import insertion_sort\r\n\r\nmy_list = []\r\ninsertion_sort(my_list)\r\n```\r\n\r\n## Heap Sort\r\n\r\nUse Case: Efficient for sorting large data sets. Utilizes the \"heap\" data structure. Possesses predictable worst-case performance.\r\n\r\n```python\r\nfrom easiest_sort import heap_sort\r\n\r\nmy_list = []\r\nheap_sort(my_list)\r\n```\r\n\r\n## Shell Sort\r\n\r\nUse Case: Balances implementation simplicity with good performance. Often applied in scenarios where a trade-off between efficiency and implementation simplicity is desired.\r\n\r\n```python\r\nfrom easiest_sort import shell_sort\r\n\r\nmy_list = []\r\nshell_sort(my_list)\r\n```\r\n\r\n\r\n## Ascending and Descending order\r\n\r\nIf you want to use descending order sorting, you should use the second argument 'order' with a value of False. Its works with every sort algorithm\r\n\r\n\r\n```python\r\nfrom easiest_sort import *\r\n\r\nmy_list = []\r\nbubble_sort(my_array, order=False)\r\n```\r\n\r\n\r\n\r\n# Partial Sort \r\n\r\nThis module provides a partial_sort function, allowing you to perform partial sorting on a list. With this function, you can sort only the top or bottom k elements of the list, leaving the rest of the elements in their original order.\r\n\r\n## Usage\r\n\r\n```python\r\nfrom easiest_sort import partial_sort\r\n\r\nmy_array = [5, 2, 8, 1, 9, 4, 7, 3, 6]\r\n\r\nx1 = partial_sort(my_array, 3, top=True)\r\n\r\nx2 = partial_sort(my_array, 3, top=False)\r\n```\r\n\r\nAlso you can use Reverse Order for Partial Sort\r\n\r\n```python\r\nfrom easiest_sort import partial_sort\r\n\r\nmy_list = [5, 2, 8, 1, 9, 4, 7, 3, 6]\r\n\r\nx = partial_sort(my_array, 3, top=True, reverse=True)\r\n```\r\n\r\n\r\n\r\n",
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