I’m building a chat bot using JavaScript and need help with web scraping functionality. The goal is to make the bot fetch content from Wikipedia pages when users type a command with an article name. For example, if someone types !wiki Python programming, the bot should grab the opening paragraph from that Wikipedia page and send it back to the channel.
I’ve tried looking up tutorials but most examples I find are outdated or don’t cover the scraping part specifically. What libraries or methods would work best for this? I’m open to using other programming languages if JavaScript isn’t the best option for web scraping tasks.
Has anyone implemented something similar before? Any code examples or guidance on how to extract specific text content from web pages would be really helpful.
Python’s probably better for this than JavaScript. I’ve built similar stuff using requests + BeautifulSoup for HTML parsing. But honestly? Skip the HTML scraping and use Wikipedia’s API instead - you get clean JSON data back, no parsing nightmares. Just hit their REST endpoint with the page title and you’re done. No worrying about DOM changes breaking everything.
If you’re stuck on JavaScript, node-fetch + jsdom works fine. Heads up though - Wikipedia’s mobile and desktop versions have different content structures, so pick one and stick with it. Also, add rate limiting once people start using your bot. Wikipedia’s cool about it but they’ll throttle you if you go crazy with requests.
Been there with scraping projects. Usually you’re stuck dealing with Puppeteer or Cheerio, building API endpoints, handling rate limits, and fixing everything when sites change their structure.
Skip all that infrastructure coding. Just automate the whole workflow - set up a system that catches your chat commands, scrapes Wikipedia, formats it, and sends it back.
No scraping code to write or servers to manage. Connect your chat platform as a trigger, add a web scraping step for Wikipedia, then format and send the response. 20 minutes setup instead of days coding.
I’ve built similar bots for Slack and Discord this way. No maintenance headaches when Wikipedia changes their HTML either - just update the scraping logic in the visual interface.
For your Wikipedia bot: workflow triggers on chat messages, checks for !wiki, scrapes the Wikipedia page, grabs the opening paragraph, posts it back to your channel.
Built something just like this last year for a Discord server. Use Cheerio for HTML parsing and Axios for HTTP requests - they work great together for Wikipedia scraping since their HTML stays pretty consistent. Error handling is crucial though. Wikipedia redirects will break your scraping logic if you’re not careful. Respect their robots.txt and add delays between requests or you’ll get blocked. Wikipedia’s got an API, but if you want the actual HTML content, Cheerio lets you grab specific paragraph elements. The hardest part? Handling disambiguation pages and redirects. Always check the page title after scraping to confirm you got the right article. Pro tip: add character limits for responses since Wikipedia’s opening paragraphs can get way too long for chat.
Wikipedia’s rate limiting blindsided me when I first tried this. My basic Node.js setup with Axios and Cheerio worked great in testing but crashed hard after deployment. Wikipedia kills aggressive scrapers fast, even legit ones. I had to add exponential backoff and request queuing or I’d get blacklisted. The parsing part’s pretty straightforward since Wikipedia keeps their HTML structure consistent, but disambiguation pages will break your logic. Also watch for pages with multiple redirects - your bot might scrape totally different content than you wanted. Cache responses for popular articles to cut down API calls. If you’re scraping HTML, use CSS selectors to target just the first paragraph instead of grabbing everything.
You’ll spend way more time debugging scraping code than building your actual bot.
I’ve built this for multiple work teams. The scraping isn’t the hard part - it’s handling Wikipedia redirects, different page layouts, rate limits, and broken HTML when they update stuff.
Skip writing all that parsing logic. Set up an automated workflow instead. Someone types !wiki, it grabs the Wikipedia content and posts it back to your channel.
No scraping libraries to maintain or getting blocked by Wikipedia. The workflow handles requests, extracts content, and formats responses.
I built one for our Slack that pulls Wikipedia summaries, news articles, and GitHub repo info. 30 minutes to set up vs weeks of coding and testing.
Best part? When Wikipedia changes their layout, you adjust the workflow visually instead of debugging code at 2 AM.
skip the html scraping - just use wikipedia’s api. hit https://en.wikipedia.org/api/rest_v1/page/summary/{title} and you’ll get the intro paragraph as clean json. no risk of getting banned, and you can ditch cheerio/beautifulsoup completely.