Inventory Management - CarFix

Problem

Mechanical workshops in Venezuela face critical challenges in the management of spare parts:

• Disorganized inventories with hundreds of parts.
• Difficulty prioritizing items by price, stock or demand
• Inefficient search times that affect customer service.

Objective

Develop a system that allows:

1. Sort spare parts by key criteria (price, stock, name) 2.
2. Optimize inventory and replenishment management
3. Compare the performance of algorithms for informed decision making.

Installation

1. Clone the repository

git clone git@github.com:MrTanuk/Testing-sorting-algorithms.git
cd Testing-sorting-algorithms

2. Install the dependencies

pip install numpy rich

3. Generate CSV File (if not already present):

python generate_csv.py

4. Run the program

python main.py

System Description

Spare Parts Data:

• Unique ID
• Part Name
• Compatibility (Toyota, Ford, Chevrolet, etc.)
• Price
• Stock on hand
• Days until expiration

Sorting Algorithms:

Criteria	Algorithm	Use Case
By Price	QuickSort	Identify Expensive Parts
By Stock	InsertionSort	Manage urgent replenishments
By Name	MergeSort	Quick Alphabet Search
By Compatibility	BubbleSort	Group parts by vehicle brand

Performance Comparison:

• All algorithms are tested on the same extended dataset.
• The run time for each algorithm is displayed.

Benefits

For the Shop Floor:

• 60% reduction in search times
• Intelligent inventory organization
• Proactive detection of critical stock
• Intelligent grouping: Quickly find all spare parts for a specific make

For the Customers:

• Increased speed of repair service
• Transparency in parts availability
• Competitive pricing through efficient management

Tools Used

• Python 3.10+
• Rich library for interactive tables (CLI)
• CSV for data management
• Custom sorting algorithms