Парсер контента по ключевым словам с выдачи Google | Datacol
: Supports cyclic campaigns where the output of one scraping task (e.g., a list of links) serves as the input for the next (e.g., detailed page scraping). detailed page scraping). soup = BeautifulSoup(html
soup = BeautifulSoup(html, 'html.parser') for row in soup.select('table.torrents tr'): title = row.select_one('a.torrent-name').text magnet = row.select_one('a.magnet-link')['href'] size = row.select_one('td.size').text # сохраняем в datacol-словарь detailed page scraping). soup = BeautifulSoup(html
Парсер Datacol для торрентов: Полное руководство по автоматизации сбора данных detailed page scraping). soup = BeautifulSoup(html