This project partially completes the requirements for datafun-05-spec.

The project uses these packages from the Python Standard Library:

• pathlib - to work with folders and files
• sqlite3 - to work with a Sqlite file-based database

If you want to avoid using a project virtual environment, it is possible to use the csv module from the Python Standard Library to read csv files.

To work with csv files using a bit cleaner code, we choose to use pandas, an external library, not part of the Python Standard Library. Therefore, this project requires a project virtual environment, which we recommend creating in the .venv folder.

This project organizes SQL scripts and Python scripts into separate folders to ensure a structured and maintainable workflow for database management.

• data/ – Stores the SQLite database (db.sqlite).
• sql_create/ – Contains SQL scripts for database setup:
  • 01_drop_tables.sql – Drops any existing tables
  • 02_create_tables.sql – Creates tables
  • 03_insert_records.sql – Inserts initial data
• sql_features/ – Contains SQL scripts for feature engineering and schema modifications.
• sql_analytics/ – Contains SQL scripts for analytics queries and aggregations.

First: Create a virtual environment, activate it, and install requirements.txt (see requirements.txt for commands).

1. Activate the .venv
2. Run the Python file

Windows Example

.\.venv\Scripts\activate
py db01_setup.py

Mac/Linux Example

source .venv/bin/activate
python3 db01_setup.py