Easy Spider Guide

EasySpider Guide

Overview

EasySpider is a visual, no-code web crawler tool with over 44K stars on GitHub. It provides a graphical interface where users design web scraping tasks by interacting directly with target web pages, clicking on elements to extract, and defining navigation flows visually. No programming knowledge is required to build functional scrapers, making it accessible to researchers across all disciplines.

For academic researchers, data collection from web sources is a frequent need but often a technical barrier. Whether gathering publication metadata from journal websites, collecting survey responses from public forums, extracting pricing data for economic research, or archiving web content for digital humanities projects, EasySpider enables researchers to build custom scrapers without writing Python or JavaScript code. The visual approach also makes scrapers easier to maintain and modify when target websites change their structure.

EasySpider runs as a desktop application on Windows, macOS, and Linux. It uses a built-in Chromium browser for rendering, which means it can handle JavaScript-heavy websites, single-page applications, and sites that require user interaction such as clicking buttons, scrolling, or filling forms. Scraped data can be exported as CSV, JSON, or directly to databases.

Installation

Download and Setup

# Download the latest release for your platform from GitHub releases
# https://github.com/NaiboWang/EasySpider/releases

# macOS - download the .dmg file and drag to Applications

# Linux - download the AppImage
chmod +x EasySpider-linux-x86_64.AppImage
./EasySpider-linux-x86_64.AppImage

# Or run from source
git clone https://github.com/NaiboWang/EasySpider.git
cd EasySpider
npm install
npm start

System Requirements

• Operating system: Windows 10+, macOS 10.15+, or Linux (Ubuntu 18.04+)
• RAM: 4 GB minimum, 8 GB recommended for complex scraping tasks
• Disk space: 500 MB for the application plus storage for scraped data
• Network: stable internet connection for web scraping

Core Concepts

Task Design Workflow

EasySpider follows a visual task design approach with these steps:

1. Open target page - Enter the URL in EasySpider's built-in browser
2. Select elements - Click on the data elements you want to extract
3. Define fields - Name each extracted element (title, author, date, etc.)
4. Configure pagination - Click the "next page" button to set up pagination
5. Set extraction rules - Define how to handle lists, tables, and nested pages
6. Test and run - Preview results, then execute the full scraping task

Element Selection Modes

• Single element - Click one element to extract that specific item
• Similar elements - Click two similar items and EasySpider detects the pattern for all matching elements on the page
• Table mode - Select a table header row to extract entire structured tables
• Input mode - Define form fields to fill before extracting (useful for search-based data collection)

Research Use Cases

Collecting Publication Metadata

Researchers can use EasySpider to gather publication information from journal websites, conference proceedings pages, or institutional repositories.

Example workflow for scraping a conference proceedings page:

1. Navigate to the proceedings listing page
2. Click on the first paper title to mark it as a "title" field
3. Click on the second paper title; EasySpider recognizes the pattern and selects all titles
4. Similarly select author names, abstract snippets, and publication dates
5. If papers span multiple pages, click the "Next" pagination button
6. Configure "click into each paper" to follow links and extract full abstracts
7. Run the task and export as CSV

Monitoring Research Funding Opportunities

Task: Daily scan of funding agency websites for new opportunities

Steps configured in EasySpider:
1. Navigate to funding agency announcement page
2. Extract: opportunity title, deadline, funding amount, eligibility
3. Filter: only new announcements (since last check)
4. Schedule: run daily at 8:00 AM
5. Export: append to CSV file, send notification email