Scrape Today's Top 13 Trending GitHub Repositories
This workflow automatically scrapes the information of the top 13 trending code repositories from GitHub's trending page for today, including data such as author, name, description, programming language, and links, generating a structured list in real-time. By automating the process, it addresses the cumbersome task of manually organizing data, improving the speed and accuracy of information retrieval. This helps developers, product managers, and content creators quickly grasp the latest dynamics of open-source projects, supporting industry technology trend tracking and data analysis.
Workflow Name
Scrape Today's Top 13 Trending GitHub Repositories
Key Features and Highlights
This workflow automatically scrapes the top 13 trending repositories from GitHub's daily trending page. It extracts detailed information including repository author, repository name, description, programming language, and corresponding links, generating a structured list in real-time for easy analysis and presentation.
Core Problem Addressed
Manually browsing and organizing GitHub trending repository data is tedious and inefficient. This workflow significantly improves data acquisition speed and accuracy through automated scraping and data cleaning, enabling users to quickly stay updated on the latest open-source project trends.
Use Cases
- Developers and technical teams obtaining daily references to popular open-source projects
- Product managers tracking industry technology trends
- Technical content creators compiling trending project information
- Automated data collection and scheduled report generation
Main Workflow Steps
- Manual trigger to start the workflow;
- Send an HTTP request to access the GitHub Trending page;
- Extract the main “Box” section containing the repository list from the returned HTML;
- Further extract the HTML list of each repository;
- Split the repository list into individual repository entries;
- Parse detailed information for each repository including author, title, description, and programming language;
- Assemble and save structured repository data, including generating corresponding GitHub links and capture timestamps.
Involved Systems or Services
- GitHub Trending webpage (scraped via HTTP requests)
- Built-in n8n nodes: Manual Trigger, HTTP Request, HTML Extract, Split Out, Set (for data processing)
Target Audience and Value
- Software developers and tech enthusiasts needing quick access to current popular open-source projects
- Data analysts and product managers requiring automated industry trend data acquisition
- Content creators aiming to efficiently gather technical news and materials
- Automation enthusiasts and operations personnel building scheduled reports and data monitoring systems
This workflow empowers users to effortlessly automate the scraping and organization of GitHub trending repositories, enhancing information retrieval efficiency and keeping pace with cutting-edge technology developments.