{"id":36609,"date":"2025-11-17T07:27:16","date_gmt":"2025-11-17T06:27:16","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/whats-the-hardest-part-of-turning-scraped-data-into-something-reusable\/"},"modified":"2025-11-17T07:27:16","modified_gmt":"2025-11-17T06:27:16","slug":"whats-the-hardest-part-of-turning-scraped-data-into-something-reusable","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/whats-the-hardest-part-of-turning-scraped-data-into-something-reusable\/","title":{"rendered":"What\u2019s The Hardest Part Of Turning Scraped Data Into Something Reusable?"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>I\u2019ve been building datasets from retail and job sites for a while. The hardest part isn\u2019t crawling it\u2019s standardizing. Product specs, company names, job levels nothing matches cleanly. Even after cleaning, every new source breaks the schema again. For those who publish datasets: how do you maintain consistency without rewriting your schema every month?<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/Vivid_Stock5288\"> \/u\/Vivid_Stock5288 <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1oz8u6j\/whats_the_hardest_part_of_turning_scraped_data\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1oz8u6j\/whats_the_hardest_part_of_turning_scraped_data\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-36609 jlk' href='javascript:void(0)' data-task='like' data-post_id='36609' data-nonce='65e0e39b87' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-36609 lc'>0<\/span><\/a><\/div><\/div> <div class='status-36609 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>I\u2019ve been building datasets from retail and job sites for a while. The hardest part isn\u2019t crawling&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-36609","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/36609","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=36609"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/36609\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=36609"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=36609"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=36609"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}