Technical Explanation
For: Me, Myself and I
Project Goal
The main goal of this project was to develop an automated web scraper that extracts data from the Apify Store category pages, so I could analyze the data (gap analysis) for potential new scraper opportunities (to monetize). This involved programmatically navigating through multiple pages, identifying specific elements containing the desired information, and extracting this data in a structured format. The scraper was designed to be robust, handling potential errors gracefully and logging relevant details for debugging.
The scraper is deployed on Apify, check it out here!
How it was built
The scraper was built using Python and Selenium, a powerful browser automation tool. It starts by launching a Chrome WebDriver, which can operate in headless mode for server-side execution. The code iterates through specified pages of the Apify Store, using CSS selectors to locate elements like actor cards, titles, creators, descriptions, and user/star statistics. The data is then extracted using Selenium’s methods, and stored in a structured dictionary. Error handling is implemented using try-except blocks to catch issues during page processing. The extracted data is then pushed to an Apify dataset for further processing or storage.
Technologies used
- Python: The primary programming language for the scraper.
- Selenium: Used to automate browser interactions and data extraction.
- Chrome WebDriver: Used to control the Chrome browser.
- Apify SDK: Used for managing the scraping process and data storage.
- CSS Selectors: Used to precisely target HTML elements for data extraction.