Optimal-Partition-Search


NameOptimal-Partition-Search JSON
Version 0.0.1 PyPI version JSON
download
home_pagehttps://github.com/fork123aniket/Optimal-Partition-Search
SummaryA function used to find the number of partitions required to speed up the array searching process
upload_time2022-12-02 18:24:09
maintainer
docs_urlNone
authorAniket Saxena
requires_python>=3.9
license
keywords optimal search array search optimal partition search searching algorithms
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bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Optimal Partition Search 

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.6](https://img.shields.io/badge/python-3.9-blue.svg)](https://www.python.org/downloads/release/python-395/)

## Overview and Functionality

- Official Implementation of the paper - ["***Optimal Partition Search***"](https://www.researchgate.net/publication/336638736_Optimal_Partition_Search)
- Searches for the optimal number of partitions required to speed up the search process
- Works for arrays having any data type (int, float, char, long, etc.)
- Independent of the order of the elements in the array, i.e. can work for both sorted and unsorted array settings

## Usage

- Make sure you have ***Python version 3.9 or greater*** installed on your system
- Run the following command on the terminal to install this package:
 ```
  pip install Optimal-Partition-Search
  ```

## Example

 ```
# test.py

from Optimal_Partition_Search import optimal_partition_search
import random
import numpy as np

# Example for array having integer values
array = random.sample(range(150), 100)
print(f'array: {array}')
element = int(input("Enter the item you want to search\n"))
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)

# Example for array having float values
array = np.random.uniform(low=600.5, high=705.2, size=(10,))
print(f'array: {array}')
element = float(np.random.choice(array, 1))
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)

# Example for array having character and string values
array = ['a', 'c', 'q', 'l', 'h', 's', 'tr', 'input']
print(f'array: {array}')
element = input("Enter the item you want to search\n")
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)
  ```

Use the following command to run the examples given in the `test.py` file above: 
 ```
  python test.py
 ```


            

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    "description": "# Optimal Partition Search \n\n[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 \n[![Python 3.6](https://img.shields.io/badge/python-3.9-blue.svg)](https://www.python.org/downloads/release/python-395/)\n\n## Overview and Functionality\n\n- Official Implementation of the paper - [\"***Optimal Partition Search***\"](https://www.researchgate.net/publication/336638736_Optimal_Partition_Search)\n- Searches for the optimal number of partitions required to speed up the search process\n- Works for arrays having any data type (int, float, char, long, etc.)\n- Independent of the order of the elements in the array, i.e. can work for both sorted and unsorted array settings\n\n## Usage\n\n- Make sure you have ***Python version 3.9 or greater*** installed on your system\n- Run the following command on the terminal to install this package:\n ```\n  pip install Optimal-Partition-Search\n  ```\n\n## Example\n\n ```\n# test.py\n\nfrom Optimal_Partition_Search import optimal_partition_search\nimport random\nimport numpy as np\n\n# Example for array having integer values\narray = random.sample(range(150), 100)\nprint(f'array: {array}')\nelement = int(input(\"Enter the item you want to search\\n\"))\noptimal_partition = optimal_partition_search(array, element)\nprint(\"Optimal no. of partitions\", optimal_partition)\n\n# Example for array having float values\narray = np.random.uniform(low=600.5, high=705.2, size=(10,))\nprint(f'array: {array}')\nelement = float(np.random.choice(array, 1))\noptimal_partition = optimal_partition_search(array, element)\nprint(\"Optimal no. of partitions\", optimal_partition)\n\n# Example for array having character and string values\narray = ['a', 'c', 'q', 'l', 'h', 's', 'tr', 'input']\nprint(f'array: {array}')\nelement = input(\"Enter the item you want to search\\n\")\noptimal_partition = optimal_partition_search(array, element)\nprint(\"Optimal no. of partitions\", optimal_partition)\n  ```\n\nUse the following command to run the examples given in the `test.py` file above: \n ```\n  python test.py\n ```\n\n",
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