Step-by-Step: Moving Scraped Products to an Offline DB

If you are building custom price comparison apps, automated inventory managers, or running advanced e-commerce analytics, you need to store data in a database. Storing raw CSV files can be difficult to scale. Moving scraped Shopify data to an offline DB (like SQLite, PostgreSQL, or MongoDB) provides a more robust structure for your applications.

Setting Up Your Database Schema

To import product catalogs, create a database schema that maps typical Shopify attributes:

CREATE TABLE products (
  id VARCHAR(255) PRIMARY KEY,
  title VARCHAR(255),
  handle VARCHAR(255),
  vendor VARCHAR(255),
  price DECIMAL(10, 2),
  compare_at_price DECIMAL(10, 2),
  sku VARCHAR(100),
  weight DECIMAL(10, 2)
);

Running Python Import Pipelines

You can write a simple Python script to read your exported CSV files using the `pandas` library, clean up formatting anomalies, and write the data directly to your local SQL database.