Automated CSV-to-SQL Converter

This project focuses on data transformation and database automation. I built a Python tool that reads large CSV files (in this case, translated scuba diving locations) and automatically converts them into SQL table creation and insert statements.

The program doesn’t just dump raw data—it applies smart type mapping:

• Integers → INT

• Floats → FLOAT

• Text fields → VARCHAR(255) or TEXT (depending on max length)

It also includes performance optimizations:

• Dynamically scans data to determine the right schema.

• Escapes strings safely to prevent SQL errors.

• Batches inserts (100 rows per statement) for faster database loading.

Finally, everything is exported into a single .sql file that can be run directly to recreate the dataset in a relational database.

This project shows how Python can bridge the gap between messy raw data and clean, structured SQL databases, enabling seamless integration with production systems, analytics pipelines, or web backends.