BSc IT Project Guide: CSV to Database Converter
1. Introduction
The 'CSV to Database Converter' project is a tool designed to simplify the process of importing CSV files into structured relational databases. This project is particularly useful for data analysts, developers, and administrative users who regularly work with CSV files and need a streamlined method to ingest data into a database system.
2. Objectives
- Develop a web-based or desktop-based tool for converting CSV files to database tables.
- Automate schema detection and table creation.
- Ensure data integrity and handle exceptions during import.
- Support multiple database backends (e.g., MySQL, PostgreSQL, SQLite).
3. Tools and Technologies
- Frontend: HTML, CSS, JavaScript (optional)
- Backend: Python (with Flask or Django)
- Database: MySQL, SQLite, PostgreSQL
- Libraries: pandas, SQLAlchemy, csv, sqlite3
4. System Requirements
Minimum requirements for development and deployment:
- Python 3.8+
- Database server (MySQL/PostgreSQL/SQLite)
- Web browser (if web-based)
5. System Design
The tool consists of three main components:
1. CSV Upload Interface
2. CSV Parser and Schema Generator
3. Database Interface for Table Creation and Data Insertion
6. Implementation Steps
1. Create a file upload interface.
2. Parse the CSV and preview its contents.
3. Detect column types and prepare SQL schema.
4. Insert data into the database.
5. Display success/failure messages.
7. Testing
- Test CSV uploads with different formats.
- Test for duplicate rows, empty values, invalid characters.
- Perform backend unit testing and integration testing.
8. Conclusion
The 'CSV to Database Converter' project provides a reliable and user-friendly solution for importing CSV data into relational databases. It simplifies data management tasks and ensures data integrity through automated conversion and schema mapping.