Hey everyone! I recently built a website (https://www.privana.org/) that uses AI to summarize privacy policies for users, making it easier for them to understand what data apps are collecting. Right now, I'm manually collecting URLs for these privacy policies, which is pretty tedious. I want to switch to web scraping so users can quickly look up any app. I'm considering using either Scrapy or ParseHub, but I'm unsure if these tools can reliably fetch the correct URLs every time. Are there other tools I should consider?
2 Answers
Totally get where you're coming from! Those tools do have their pros and cons. You might think about running automated unit tests for your scraper to ensure you're pulling the right info. However, keep in mind that if the site's structure changes, it could throw off your tests. Regular updates to the scraper may be necessary to keep everything in check!
Both Scrapy and ParseHub are pretty solid options, but they cater to different needs. Scrapy is super powerful, especially if you're into Python; it’s great for big scraping projects and gives you a lot of flexibility. You can handle tricky situations like pagination and dynamic content easily.
On the flip side, ParseHub is more user-friendly with a visual interface, making it easier for those who don't want to dive deep into coding. It's decent for simple tasks and can deal with dynamic sites, but it might struggle if you're planning something more complex or large-scale.
For what you’re looking to do—scalable and reliable scraping—Scrapy is probably the way to go, especially since it lets you manage edge cases better. If you need something quick and easy, though, ParseHub could still fit the bill! Oh, and just a heads up: web scraping can be a bit unpredictable since websites change structures often, so building in error handling is essential!
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