A Python script to scrape grocery flyer deals from Flipp. This project collects current deals from major grocery stores including No Frills, FreshCo, Walmart, and Loblaws.

• Scrapes current flyer deals from multiple grocery stores
• Filters for grocery-specific flyers
• Exports data to CSV format
• Handles multiple categories and store types
• Includes deal validity dates

• Python 3.9 or higher
• pip (Python package installer)

1. Clone the repository:

git clone https://github.com/Kiizon/flippscrape.git
cd flippscrape

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate

3. Install required packages:

pip install requests pandas

1. Run the script:

python app.py

2. Enter your postal code when prompted (format: A1A1A1)

3. The script will:

   • Fetch current flyer data for your postal code
   • Filter for grocery store flyers
   • Extract deal information
   • Save results to flyer_items_[POSTAL_CODE].csv

The script generates a CSV file with the following columns:

• merchant: Store name
• flyer_id: Unique identifier for the flyer
• name: Item name
• price: Item price
• valid_from: Deal start date
• valid_to: Deal end date

1. Flyer Collection:

   • Generates a session ID for API access
   • Fetches flyer data for the specified postal code
   • Filters for grocery store flyers

2. Data Processing:

   • Extracts relevant deal information
   • Handles multiple categories
   • Associates items with their respective stores

3. Data Export:

   • Formats data into a structured CSV
   • Includes all relevant deal information
   • Maintains store and validity information

The script uses the following default settings:

• Supported stores: No Frills, FreshCo, Walmart, Loblaws

To modify these settings, edit the relevant variables in app.py.

Note that some stores have duplicate flyers, each has its own category. Sometimes two flyers share the same category like Groceries so you'll have to find a way to differenciate which one to parse .

Feel free to submit issues and enhancement requests!

This project is for educational purposes only. Please note:

• This is an unofficial tool and is not affiliated with Flipp
• Use responsibly and respect Flipp's terms of service
• Consider rate limiting and server load when using the script
• The data is owned by Flipp and their partners