Papers › EasySpider: A No-Code Visual System for Crawling the Web
EasySpider: A No-Code Visual System for Crawling the Web
Naibo Wang, Wenjie Feng, Jianwei Yin, See-Kiong Ng
The web is a treasure trove for data that is increasingly used by computer scientists for building large machine learning models as well as non-computer scientists for social studies or marketing analyses. As such, web-crawling is an essential tool for both computational and non-computational scientists to conduct research. However, most of the existing web crawler frameworks and software products either require professional coding skills without an easy-to-use graphic user interface or are expensive and limited in features. They are thus not friendly to newbies and inconvenient for complicated web-crawling tasks. In this paper, we present an easy-to-use visual web crawler system, EasySpider, for designing and executing web crawling tasks without coding. The workflow of a new web crawling task can be visually programmed by following EasySpider’s visual wizard on the target webpages using an intuitive point-and-click interface. The generated crawler task can then be easily invoked locally or as a web service. Our EasySpider is cross-platform and flexible to adapt to different web-resources. It also supports advanced configuration for complicated tasks and extension. The whole system is open-sourced and transparent for free-access at GitHub, which avoids possible privacy leakage.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Methods
1 archive method tag without a method page not shown.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections