App Listing Integrations Analysis

This project analyzes integration information from Shopify app listings to create a standardized taxonomy of integrations.

Project Structure

.
├── README.md           # This file
├── context.md         # Project context and planning
├── requirements.txt   # Python dependencies
├── data/             # Data directory for CSV files
└── src/              # Source code
    ├── fetch_apps.py           # Script to fetch top apps from BigQuery
    ├── scrape_integrations.py  # Script to scrape integration info
    └── analyze_integrations.py # Script to analyze using GPT-4

Setup

1. Install dependencies:

pip install -r requirements.txt

Usage

The analysis is done in three steps:

1. Fetch top apps from BigQuery:

python src/fetch_apps.py

This will provide instructions to run a BigQuery query through MCP and save results.

2. Scrape integration information:

python src/scrape_integrations.py

This will process the app list and scrape integration information from each app's page.

3. Analyze integrations:

python src/analyze_integrations.py

This will use GPT-4 via Shopify's proxy to analyze and categorize the integrations.

Data Files

• data/top_apps_raw.csv: Raw app data from BigQuery
• data/app_integrations_*.csv: Scraped integration data
• data/integration_analysis_*.json: Analysis results

Notes

• The scraper includes a delay between requests to avoid overwhelming the app store
• Integration data is stored as comma-separated strings in the CSV
• Analysis results include categorization and standardization recommendations