🧪 Laboratory Management System

📌 Project Overview

The Laboratory Management System is a Python and MySQL-based application developed to manage laboratory operations efficiently. It provides modules for managing laboratory samples, scientists, equipment, experiments, and results. The system also generates reports by retrieving data from multiple tables using SQL queries.

🚀 Features

• Sample Management

  • Add Sample
  • View Samples
  • Search Sample
  • Update Sample
  • Delete Sample

• Scientist Management

  • Add Scientist
  • View Scientists
  • Search Scientist
  • Update Scientist
  • Delete Scientist

• Equipment Management

  • Add Equipment
  • View Equipment
  • Search Equipment
  • Update Equipment
  • Delete Equipment

• Experiment Management

  • Add Experiment
  • View Experiments
  • Search Experiment
  • Update Experiment
  • Delete Experiment

• Result Management

  • Add Result
  • View Results
  • Search Result
  • Update Result
  • Delete Result

• Reports

  • Laboratory Report
  • Sample Status Report
  • Scientist Report
  • Equipment Report
  • Dashboard Summary

🛠 Technologies Used

• Python
• MySQL
• MySQL Workbench
• mysql-connector-python

🗄 Database Tables

• samples
• scientists
• equipment
• experiments
• results

📁 Project Structure

Laboratory_Management_System/
│
├── main.py
├── database.py
├── sample.py
├── scientist.py
├── equipment.py
├── experiment.py
├── results.py
├── reports.py
├── laboratory_management.sql
├── requirements.txt
└── README.md

▶️ How to Run

1. Clone or download the project.
2. Import laboratory_management.sql into MySQL Workbench.
3. Install the required package:

pip install -r requirements.txt

4. Open database.py and update:

   • Host
   • Username
   • Password
   • Database name

5. Run the project:

python main.py

📊 Database Concepts Used

• CREATE TABLE
• INSERT
• SELECT
• UPDATE
• DELETE
• Primary Keys
• Foreign Keys
• SQL JOINs
• Aggregate Functions (COUNT)

🎯 Learning Outcomes

Through this project, I learned:

• Python programming
• MySQL database connectivity
• CRUD operations
• Modular programming
• SQL queries and JOIN operations
• Database design using relationships

🔮 Future Improvements

• User authentication (Admin Login)
• Graphical User Interface (GUI)
• Export reports to PDF or Excel
• Search and filter options
• Better exception handling and input validation

👩‍💻 Developed By

Renuka Rapolu