Web scraping pagination in R lacks browser automation support
R users struggle to scrape paginated websites requiring JavaScript clicks, with limited tooling options between rvest and broken rSelenium.
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Similar Problems
surfaced semanticallySelenium Cannot Click Elements in Dynamically Rendered Menus
Developers automating web interactions with Selenium cannot reliably click elements inside dropdown menus that appear after a button click. The stale element reference and timing issues between click events and DOM updates cause the automation script to fail. This blocks price scraping and similar automation workflows.
Web crawlers fail on JS-rendered dynamic team/leadership pages
Developers scraping company websites for team and leadership data find that dynamically rendered card components break standard HTTP crawlers. The problem recurs daily across hundreds of sites and requires either headless browsers or smart rendering detection. This creates friction for anyone building people-data pipelines or lead-enrichment tools.
BeautifulSoup find_all returns empty results when combined with Selenium
Developers combining Selenium for dynamic page rendering with BeautifulSoup for HTML parsing encounter find_all returning no results despite valid data being present. The root cause is passing the wrong page source to BeautifulSoup after Selenium manipulates the DOM. Widespread confusion among scraping beginners.
Unreliable Click-Success Detection in Generic Web Test Automation
Builders of no-code Selenium-based test runners cannot reliably confirm that a click actually affected the target web application, since apps may attach event handlers asynchronously and a successful click() call only means the event fired, not that it was handled. This causes false test failures and makes generic, app-agnostic retry logic risky to implement without duplicating actions.
No Reliable Way to Automate Multi-Step Bulk File Downloads From a Website
A user needs to manually download over 400 files from a website, each requiring several clicks through nested viewers (external window, Google Drive preview, open original, download) with no direct link. Existing automation tools like macOS Automator cannot reliably reproduce the multi-step sequence across many different pages, forcing tedious manual repetition.
Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.