mercury-parser/dist/mercury.js.map

{"version":3,"file":null,"sources":["../src/utils/text/normalize-spaces.js","../src/utils/text/extract-from-url.js","../src/utils/text/constants.js","../src/utils/text/page-num-from-url.js","../src/utils/text/remove-anchor.js","../src/utils/text/article-base-url.js","../src/utils/text/has-sentence-end.js","../src/utils/text/excerpt-content.js","../src/utils/text/get-encoding.js","../src/utils/range.js","../src/utils/validate-url.js","../src/utils/errors.js","../src/resource/utils/constants.js","../src/resource/utils/fetch-resource.js","../src/resource/utils/dom/normalize-meta-tags.js","../src/utils/dom/constants.js","../src/utils/dom/strip-unlikely-candidates.js","../src/utils/dom/brs-to-ps.js","../src/utils/dom/paragraphize.js","../src/utils/dom/convert-to-paragraphs.js","../src/utils/dom/convert-node-to.js","../src/utils/dom/clean-images.js","../src/utils/dom/mark-to-keep.js","../src/utils/dom/strip-junk-tags.js","../src/utils/dom/clean-h-ones.js","../src/utils/dom/clean-attributes.js","../src/utils/dom/remove-empty.js","../src/extractors/generic/content/scoring/constants.js","../src/extractors/generic/content/scoring/get-weight.js","../src/extractors/generic/content/scoring/get-score.js","../src/extractors/generic/content/scoring/score-commas.js","../src/extractors/generic/content/scoring/score-length.js","../src/extractors/generic/content/scoring/score-paragraph.js","../src/extractors/generic/content/scoring/set-score.js","../src/extractors/generic/content/scoring/add-score.js","../src/extractors/generic/content/scoring/add-to-parent.js","../src/extractors/generic/content/scoring/get-or-init-score.js","../src/extractors/generic/content/scoring/score-node.js","../src/extractors/generic/content/scoring/score-content.js","../src/extractors/generic/content/scoring/merge-siblings.js","../src/extractors/generic/content/scoring/find-top-candidate.js","../src/extractors/generic/content/scoring/index.js","../src/utils/dom/clean-tags.js","../src/utils/dom/clean-headers.js","../src/utils/dom/rewrite-top-level.js","../src/utils/dom/make-links-absolute.js","../src/utils/dom/link-density.js","../src/utils/dom/extract-from-meta.js","../src/utils/dom/extract-from-selectors.js","../src/utils/dom/strip-tags.js","../src/utils/dom/within-comment.js","../src/utils/dom/node-is-sufficient.js","../src/utils/dom/is-wordpress.js","../src/utils/dom/get-attrs.js","../src/utils/dom/set-attr.js","../src/utils/dom/set-attrs.js","../src/utils/dom/index.js","../src/resource/utils/dom/constants.js","../src/resource/utils/dom/convert-lazy-loaded-images.js","../src/resource/utils/dom/clean.js","../src/resource/index.js","../src/utils/merge-supported-domains.js","../src/extractors/custom/blogspot.com/index.js","../src/extractors/custom/nymag.com/index.js","../src/extractors/custom/wikipedia.org/index.js","../src/extractors/custom/twitter.com/index.js","../src/extractors/custom/www.nytimes.com/index.js","../src/extractors/custom/www.theatlantic.com/index.js","../src/extractors/custom/www.newyorker.com/index.js","../src/extractors/custom/www.wired.com/index.js","../src/extractors/custom/www.msn.com/index.js","../src/extractors/custom/www.yahoo.com/index.js","../src/extractors/custom/www.buzzfeed.com/index.js","../src/extractors/custom/fandom.wikia.com/index.js","../src/extractors/custom/www.littlethings.com/index.js","../src/extractors/custom/www.politico.com/index.js","../src/extractors/custom/deadspin.com/index.js","../src/extractors/custom/www.broadwayworld.com/index.js","../src/extractors/custom/www.apartmenttherapy.com/index.js","../src/extractors/custom/medium.com/index.js","../src/extractors/custom/www.tmz.com/index.js","../src/extractors/custom/www.washingtonpost.com/index.js","../src/extractors/custom/www.huffingtonpost.com/index.js","../src/extractors/custom/newrepublic.com/index.js","../src/extractors/custom/money.cnn.com/index.js","../src/extractors/custom/www.theverge.com/index.js","../src/extractors/custom/www.cnn.com/index.js","../src/extractors/custom/www.aol.com/index.js","../src/extractors/custom/www.youtube.com/index.js","../src/extractors/custom/www.theguardian.com/index.js","../src/extractors/custom/www.sbnation.com/index.js","../src/extractors/custom/www.bloomberg.com/index.js","../src/extractors/custom/www.bustle.com/index.js","../src/extractors/custom/www.npr.org/index.js","../src/extractors/custom/www.recode.net/index.js","../src/extractors/custom/qz.com/index.js","../src/extractors/custom/www.dmagazine.com/index.js","../src/extractors/custom/www.reuters.com/index.js","../src/extractors/custom/mashable.com/index.js","../src/extractors/custom/www.chicagotribune.com/index.js","../src/extractors/custom/www.vox.com/index.js","../src/extractors/custom/news.nationalgeographic.com/index.js","../src/extractors/custom/www.nationalgeographic.com/index.js","../src/extractors/custom/www.latimes.com/index.js","../src/extractors/custom/pagesix.com/index.js","../src/extractors/custom/thefederalistpapers.org/index.js","../src/extrac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NORMALIZE_RE = /\\s{2,}/g;\n\nexport default function normalizeSpaces(text) {\n  return text.replace(NORMALIZE_RE, ' ').trim();\n}\n","// Given a node type to search for, and a list of regular expressions,\n// look to see if this extraction can be found in the URL. Expects\n// that each expression in r_list will return group(1) as the proper\n// string to be cleaned.\n// Only used for date_published currently.\nexport default function extractFromUrl(url, regexList) {\n  const matchRe = regexList.find(re => re.test(url));\n  if (matchRe) {\n    return matchRe.exec(url)[1];\n  }\n\n  return null;\n}\n","// An expression that looks to try to find the page digit within a URL, if\n// it exists.\n// Matches:\n//  page=1\n//  pg=1\n//  p=1\n//  paging=12\n//  pag=7\n//  pagination/1\n//  paging/88\n//  pa/83\n//  p/11\n//\n// Does not match:\n//  pg=102\n//  page:2\nexport const PAGE_IN_HREF_RE = new RegExp('(page|paging|(p(a|g|ag)?(e|enum|ewanted|ing|ination)))?(=|/)([0-9]{1,3})', 'i');\n\nexport const HAS_ALPHA_RE = /[a-z]/i;\n\nexport const IS_ALPHA_RE = /^[a-z]+$/i;\nexport const IS_DIGIT_RE = /^[0-9]+$/i;\n\nexport const ENCODING_RE = /charset=([\\w-]+)\\b/;\nexport const DEFAULT_ENCODING = 'utf-8';\n","import { PAGE_IN_HREF_RE } from './constants';\n\nexport default function pageNumFromUrl(url) {\n  const matches = url.match(PAGE_IN_HREF_RE);\n  if (!matches) return null;\n\n  const pageNum = parseInt(matches[6], 10);\n\n  // Return pageNum < 100, otherwise\n  // return null\n  return pageNum < 100 ? pageNum : null;\n}\n","export default function removeAnchor(url) {\n  return url.split('#')[0].replace(/\\/$/, '');\n}\n","import URL from 'url';\n\nimport {\n  HAS_ALPHA_RE,\n  IS_ALPHA_RE,\n  IS_DIGIT_RE,\n  PAGE_IN_HREF_RE,\n} from './constants';\n\nfunction isGoodSegment(segment, index, firstSegmentHasLetters) {\n  let goodSegment = true;\n\n  // If this is purely a number, and it's the first or second\n  // url_segment, it's probably a page number. Remove it.\n  if (index < 2 && IS_DIGIT_RE.test(segment) && segment.length < 3) {\n    goodSegment = true;\n  }\n\n  // If this is the first url_segment and it's just \"index\",\n  // remove it\n  if (index === 0 && segment.toLowerCase() === 'index') {\n    goodSegment = false;\n  }\n\n  // If our first or second url_segment is smaller than 3 characters,\n  // and the first url_segment had no alphas, remove it.\n  if (index < 2 && segment.length < 3 && !firstSegmentHasLetters) {\n    goodSegment = false;\n  }\n\n  return goodSegment;\n}\n\n// Take a URL, and return the article base of said URL. That is, no\n// pagination data exists in it. Useful for comparing to other links\n// that might have pagination data within them.\nexport default function articleBaseUrl(url, parsed) {\n  const parsedUrl = parsed || URL.parse(url);\n  const { protocol, host, path } = parsedUrl;\n\n  let firstSegmentHasLetters = false;\n  const cleanedSegments = path.split('/')\n  .reverse()\n  .reduce((acc, rawSegment, index) => {\n    let segment = rawSegment;\n\n    // Split off and save anything that looks like a file type.\n    if (segment.includes('.')) {\n      const [possibleSegment, fileExt] = segment.split('.');\n      if (IS_ALPHA_RE.test(fileExt)) {\n        segment = possibleSegment;\n      }\n    }\n\n    // If our first or second segment has anything looking like a page\n    // number, remove it.\n    if (PAGE_IN_HREF_RE.test(segment) && index < 2) {\n      segment = segment.replace(PAGE_IN_HREF_RE, '');\n    }\n\n    // If we're on the first segment, check to see if we have any\n    // characters in it. The first segment is actually the last bit of\n    // the URL, and this will be helpful to determine if we're on a URL\n    // segment that looks like \"/2/\" for example.\n    if (index === 0) {\n      firstSegmentHasLetters = HAS_ALPHA_RE.test(segment);\n    }\n\n    // If it's not marked for deletion, push it to cleaned_segments.\n    if (isGoodSegment(segment, index, firstSegmentHasLetters)) {\n      acc.push(segment);\n    }\n\n    return acc;\n  }, []);\n\n  return `${protocol}//${host}${cleanedSegments.reverse().join('/')}`;\n}\n","// Given a string, return True if it appears to have an ending sentence\n// within it, false otherwise.\nconst SENTENCE_END_RE = new RegExp('.( |$)');\nexport default function hasSentenceEnd(text) {\n  return SENTENCE_END_RE.test(text);\n}\n","export default function excerptContent(content, words = 10) {\n  return content.trim()\n                .split(/\\s+/)\n                .slice(0, words)\n                .join(' ');\n}\n","import iconv from 'iconv-lite';\nimport { DEFAULT_ENCODING, ENCODING_RE } from './constants';\n\n// check a string for encoding; this is\n// used in our fetchResource function to\n// ensure correctly encoded responses\nexport default function getEncoding(str) {\n  let encoding = DEFAULT_ENCODING;\n  if (ENCODING_RE.test(str)) {\n    const testEncode = ENCODING_RE.exec(str)[1];\n    if (iconv.encodingExists(testEncode)) {\n      encoding = testEncode;\n    }\n  }\n  return encoding;\n}\n","export default function* range(start = 1, end = 1) {\n  while (start <= end) {\n    yield start += 1;\n  }\n}\n","// extremely simple url validation as a first step\nexport default function validateUrl({ hostname }) {\n  // If this isn't a valid url, return an error message\n  return !!hostname;\n}\n","const Errors = {\n  badUrl: {\n    error: true,\n    messages: 'The url parameter passed does not look like a valid URL. Please check your data and try again.',\n  },\n};\n\nexport default Errors;\n","import cheerio from 'cheerio';\n\n// Browser does not like us setting user agent\nexport const REQUEST_HEADERS = cheerio.browser ? {} : {\n  'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36',\n};\n\n// The number of milliseconds to attempt to fetch a resource before timing out.\nexport const FETCH_TIMEOUT = 10000;\n\n// Content types that we do not extract content from\nconst BAD_CONTENT_TYPES = [\n  'audio/mpeg',\n  'image/gif',\n  'image/jpeg',\n  'image/jpg',\n];\n\nexport const BAD_CONTENT_TYPES_RE = new RegExp(`^(${BAD_CONTENT_TYPES.join('|')})$`, 'i');\n\n// Use this setting as the maximum size an article can be\n// for us to attempt parsing. Defaults to 5 MB.\nexport const MAX_CONTENT_LENGTH = 5242880;\n\n// Turn the global proxy on or off\n// Proxying is not currently enabled in Python source\n// so not implementing logic in port.\nexport const PROXY_DOMAINS = false;\nexport const REQUESTS_PROXIES = {\n  http: 'http://38.98.105.139:33333',\n  https: 'http://38.98.105.139:33333',\n};\n\nexport const DOMAINS_TO_PROXY = [\n  'nih.gov',\n  'gutenberg.org',\n];\n","import URL from 'url';\nimport request from 'request';\nimport { Errors } from 'utils';\n\nimport {\n  REQUEST_HEADERS,\n  FETCH_TIMEOUT,\n  BAD_CONTENT_TYPES_RE,\n  MAX_CONTENT_LENGTH,\n} from './constants';\n\nfunction get(options) {\n  return new Promise((resolve, reject) => {\n    request(options, (err, response, body) => {\n      if (err) {\n        reject(err);\n      } else {\n        resolve({ body, response });\n      }\n    });\n  });\n}\n\n// Evaluate a response to ensure it's something we should be keeping.\n// This does not validate in the sense of a response being 200 level or\n// not. Validation here means that we haven't found reason to bail from\n// further processing of this url.\n\nexport function validateResponse(response, parseNon2xx = false) {\n  // Check if we got a valid status code\n  // This isn't great, but I'm requiring a statusMessage to be set\n  // before short circuiting b/c nock doesn't set it in tests\n  // statusMessage only not set in nock response, in which case\n  // I check statusCode, which is currently only 200 for OK responses\n  // in tests\n  if (\n    (response.statusMessage && response.statusMessage !== 'OK') ||\n      response.statusCode !== 200\n  ) {\n    if (!response.statusCode) {\n      throw new Error(\n        `Unable to fetch content. Original exception was ${response.error}`\n      );\n    } else if (!parseNon2xx) {\n      throw new Error(\n        `Resource returned a response status code of ${response.statusCode} and resource was instructed to reject non-2xx level status codes.`\n      );\n    }\n  }\n\n  const {\n    'content-type': contentType,\n    'content-length': contentLength,\n  } = response.headers;\n\n  // Check that the content is not in BAD_CONTENT_TYPES\n  if (BAD_CONTENT_TYPES_RE.test(contentType)) {\n    throw new Error(\n      `Content-type for this resource was ${contentType} and is not allowed.`\n    );\n  }\n\n  // Check that the content length is below maximum\n  if (contentLength > MAX_CONTENT_LENGTH) {\n    throw new Error(\n      `Content for this resource was too large. Maximum content length is ${MAX_CONTENT_LENGTH}.`\n    );\n  }\n\n  return true;\n}\n\n// Grabs the last two pieces of the URL and joins them back together\n// This is to get the 'livejournal.com' from 'erotictrains.livejournal.com'\nexport function baseDomain({ host }) {\n  return host.split('.').slice(-2).join('.');\n}\n\n// Set our response attribute to the result of fetching our URL.\n// TODO: This should gracefully handle timeouts and raise the\n//       proper exceptions on the many failure cases of HTTP.\n// TODO: Ensure we are not fetching something enormous. Always return\n//       unicode content for HTML, with charset conversion.\n\nexport default async function fetchResource(url, parsedUrl) {\n  parsedUrl = parsedUrl || URL.parse(encodeURI(url));\n\n  const options = {\n    url: parsedUrl.href,\n    headers: { ...REQUEST_HEADERS },\n    timeout: FETCH_TIMEOUT,\n    // Accept cookies\n    jar: true,\n    // Set to null so the response returns as binary and body as buffer\n    // https://github.com/request/request#requestoptions-callback\n    encoding: null,\n    // Accept and decode gzip\n    gzip: true,\n    // Follow any redirect\n    followAllRedirects: true,\n  };\n\n  const { response, body } = await get(options);\n\n  try {\n    validateResponse(response);\n    return {\n      body,\n      response,\n    };\n  } catch (e) {\n    return Errors.badUrl;\n  }\n}\n","function convertMetaProp($, from, to) {\n  $(`meta[${from}]`).each((_, node) => {\n    const $node = $(node);\n\n    const value = $node.attr(from);\n    $node.attr(to, value);\n    $node.removeAttr(from);\n  });\n\n  return $;\n}\n\n// For ease of use in extracting from meta tags,\n// replace the \"content\" attribute on meta tags with the\n// \"value\" attribute.\n//\n// In addition, normalize 'property' attributes to 'name' for ease of\n// querying later. See, e.g., og or twitter meta tags.\n\nexport default function normalizeMetaTags($) {\n  $ = convertMetaProp($, 'content', 'value');\n  $ = convertMetaProp($, 'property', 'name');\n  return $;\n}\n","// Spacer images to be removed\nexport const SPACER_RE = new RegExp('transparent|spacer|blank', 'i');\n\n// The class we will use to mark elements we want to keep\n// but would normally remove\nexport const KEEP_CLASS = 'mercury-parser-keep';\n\nexport const KEEP_SELECTORS = [\n  'iframe[src^=\"https://www.youtube.com\"]',\n  'iframe[src^=\"https://www.youtube-nocookie.com\"]',\n  'iframe[src^=\"http://www.youtube.com\"]',\n  'iframe[src^=\"https://player.vimeo\"]',\n  'iframe[src^=\"http://player.vimeo\"]',\n];\n\n// A list of tags to strip from the output if we encounter them.\nexport const STRIP_OUTPUT_TAGS = [\n  'title',\n  'script',\n  'noscript',\n  'link',\n  'style',\n  'hr',\n  'embed',\n  'iframe',\n  'object',\n];\n\n// cleanAttributes\nexport const REMOVE_ATTRS = ['style', 'align'];\nexport const REMOVE_ATTR_SELECTORS = REMOVE_ATTRS.map(selector => `[${selector}]`);\nexport const REMOVE_ATTR_LIST = REMOVE_ATTRS.join(',');\nexport const WHITELIST_ATTRS = [\n  'src',\n  'srcset',\n  'href',\n  'class',\n  'id',\n  'alt',\n  'xlink:href',\n  'width',\n  'height',\n];\n\nexport const WHITELIST_ATTRS_RE = new RegExp(`^(${WHITELIST_ATTRS.join('|')})$`, 'i');\n\n// removeEmpty\nexport const REMOVE_EMPTY_TAGS = ['p'];\nexport const REMOVE_EMPTY_SELECTORS = REMOVE_EMPTY_TAGS.map(tag => `${tag}:empty`).join(',');\n\n// cleanTags\nexport const CLEAN_CONDITIONALLY_TAGS = ['ul', 'ol', 'table', 'div', 'button', 'form'].join(',');\n\n// cleanHeaders\nconst HEADER_TAGS = ['h2', 'h3', 'h4', 'h5', 'h6'];\nexport const HEADER_TAG_LIST = HEADER_TAGS.join(',');\n\n// // CONTENT FETCHING CONSTANTS ////\n\n// A list of strings that can be considered unlikely candidates when\n// extracting content from a resource. These strings are joined together\n// and then tested for existence using re:test, so may contain simple,\n// non-pipe style regular expression queries if necessary.\nexport const UNLIKELY_CANDIDATES_BLACKLIST = [\n  'ad-break',\n  'adbox',\n  'advert',\n  'addthis',\n  'agegate',\n  'aux',\n  'blogger-labels',\n  'combx',\n  'comment',\n  'conversation',\n  'disqus',\n  'entry-unrelated',\n  'extra',\n  'foot',\n  // 'form', // This is too generic, has too many false positives\n  'header',\n  'hidden',\n  'loader',\n  'login',                     // Note: This can hit 'blogindex'.\n  'menu',\n  'meta',\n  'nav',\n  'outbrain',\n  'pager',\n  'pagination',\n  'predicta',                  // readwriteweb inline ad box\n  'presence_control_external', // lifehacker.com container full of false positives\n  'popup',\n  'printfriendly',\n  'related',\n  'remove',\n  'remark',\n  'rss',\n  'share',\n  'shoutbox',\n  'sidebar',\n  'sociable',\n  'sponsor',\n  'taboola',\n  'tools',\n];\n\n// A list of strings that can be considered LIKELY candidates when\n// extracting content from a resource. Essentially, the inverse of the\n// blacklist above - if something matches both blacklist and whitelist,\n// it is kept. This is useful, for example, if something has a className\n// of \"rss-content entry-content\". It matched 'rss', so it would normally\n// be removed, however, it's also the entry content, so it should be left\n// alone.\n//\n// These strings are joined together and then tested for existence using\n// re:test, so may contain simple, non-pipe style regular expression queries\n// if necessary.\nexport const UNLIKELY_CANDIDATES_WHITELIST = [\n  'and',\n  'article',\n  'body',\n  'blogindex',\n  'column',\n  'content',\n  'entry-content-asset',\n  'format', // misuse of form\n  'hfeed',\n  'hentry',\n  'hatom',\n  'main',\n  'page',\n  'posts',\n  'shadow',\n];\n\n// A list of tags which, if found inside, should cause a <div /> to NOT\n// be turned into a paragraph tag. Shallow div tags without these elements\n// should be turned into <p /> tags.\nexport const DIV_TO_P_BLOCK_TAGS = [\n  'a',\n  'blockquote',\n  'dl',\n  'div',\n  'img',\n  'p',\n  'pre',\n  'table',\n].join(',');\n\n// A list of tags that should be ignored when trying to find the top candidate\n// for a document.\nexport const NON_TOP_CANDIDATE_TAGS = [\n  'br',\n  'b',\n  'i',\n  'label',\n  'hr',\n  'area',\n  'base',\n  'basefont',\n  'input',\n  'img',\n  'link',\n  'meta',\n];\n\nexport const NON_TOP_CANDIDATE_TAGS_RE =\n  new RegExp(`^(${NON_TOP_CANDIDATE_TAGS.join('|')})$`, 'i');\n\n// A list of selectors that specify, very clearly, either hNews or other\n// very content-specific style content, like Blogger templates.\n// More examples here: http://microformats.org/wiki/blog-post-formats\nexport const HNEWS_CONTENT_SELECTORS = [\n  ['.hentry', '.entry-content'],\n  ['entry', '.entry-content'],\n  ['.entry', '.entry_content'],\n  ['.post', '.postbody'],\n  ['.post', '.post_body'],\n  ['.post', '.post-body'],\n];\n\nexport const PHOTO_HINTS = [\n  'figure',\n  'photo',\n  'image',\n  'caption',\n];\nexport const PHOTO_HINTS_RE = new RegExp(PHOTO_HINTS.join('|'), 'i');\n\n// A list of strings that denote a positive scoring for this content as being\n// an article container. Checked against className and id.\n//\n// TODO: Perhaps have these scale based on their odds of being quality?\nexport const POSITIVE_SCORE_HINTS = [\n  'article',\n  'articlecontent',\n  'instapaper_body',\n  'blog',\n  'body',\n  'content',\n  'entry-content-asset',\n  'entry',\n  'hentry',\n  'main',\n  'Normal',\n  'page',\n  'pagination',\n  'permalink',\n  'post',\n  'story',\n  'text',\n  '[-_]copy', // usatoday\n  '\\\\Bcopy',\n];\n\n// The above list, joined into a matching regular expression\nexport const POSITIVE_SCORE_RE = new RegExp(POSITIVE_SCORE_HINTS.join('|'), 'i');\n\n// Readability publisher-specific guidelines\nexport const READABILITY_ASSET = new RegExp('entry-content-asset', 'i');\n\n// A list of strings that denote a negative scoring for this content as being\n// an article container. Checked against className and id.\n//\n// TODO: Perhaps have these scale based on their odds of being quality?\nexport const NEGATIVE_SCORE_HINTS = [\n  'adbox',\n  'advert',\n  'author',\n  'bio',\n  'bookmark',\n  'bottom',\n  'byline',\n  'clear',\n  'com-',\n  'combx',\n  'comment',\n  'comment\\\\B',\n  'contact',\n  'copy',\n  'credit',\n  'crumb',\n  'date',\n  'deck',\n  'excerpt',\n  'featured', // tnr.com has a featured_content which throws us off\n  'foot',\n  'footer',\n  'footnote',\n  'graf',\n  'head',\n  'info',\n  'infotext', // newscientist.com copyright\n  'instapaper_ignore',\n  'jump',\n  'linebreak',\n  'link',\n  'masthead',\n  'media',\n  'meta',\n  'modal',\n  'outbrain', // slate.com junk\n  'promo',\n  'pr_', // autoblog - press release\n  'related',\n  'respond',\n  'roundcontent', // lifehacker restricted content warning\n  'scroll',\n  'secondary',\n  'share',\n  'shopping',\n  'shoutbox',\n  'side',\n  'sidebar',\n  'sponsor',\n  'stamp',\n  'sub',\n  'summary',\n  'tags',\n  'tools',\n  'widget',\n];\n// The above list, joined into a matching regular expression\nexport const NEGATIVE_SCORE_RE = new RegExp(NEGATIVE_SCORE_HINTS.join('|'), 'i');\n\n// XPath to try to determine if a page is wordpress. Not always successful.\nexport const IS_WP_SELECTOR = 'meta[name=generator][value^=WordPress]';\n\n// Match a digit. Pretty clear.\nexport const DIGIT_RE = new RegExp('[0-9]');\n\n// A list of words that, if found in link text or URLs, likely mean that\n// this link is not a next page link.\nexport const EXTRANEOUS_LINK_HINTS = [\n  'print',\n  'archive',\n  'comment',\n  'discuss',\n  'e-mail',\n  'email',\n  'share',\n  'reply',\n  'all',\n  'login',\n  'sign',\n  'single',\n  'adx',\n  'entry-unrelated',\n];\nexport const EXTRANEOUS_LINK_HINTS_RE = new RegExp(EXTRANEOUS_LINK_HINTS.join('|'), 'i');\n\n// Match any phrase that looks like it could be page, or paging, or pagination\nexport const PAGE_RE = new RegExp('pag(e|ing|inat)', 'i');\n\n// Match any link text/classname/id that looks like it could mean the next\n// page. Things like: next, continue, >, >>, » but not >|, »| as those can\n// mean last page.\n// export const NEXT_LINK_TEXT_RE = new RegExp('(next|weiter|continue|>([^\\|]|$)|»([^\\|]|$))', 'i');\nexport const NEXT_LINK_TEXT_RE = /(next|weiter|continue|>([^|]|$)|»([^|]|$))/i;\n\n// Match any link text/classname/id that looks like it is an end link: things\n// like \"first\", \"last\", \"end\", etc.\nexport const CAP_LINK_TEXT_RE = new RegExp('(first|last|end)', 'i');\n\n// Match any link text/classname/id that looks like it means the previous\n// page.\nexport const PREV_LINK_TEXT_RE = new RegExp('(prev|earl|old|new|<|«)', 'i');\n\n// Match 2 or more consecutive <br> tags\nexport const BR_TAGS_RE = new RegExp('(<br[^>]*>[ \\n\\r\\t]*){2,}', 'i');\n\n// Match 1 BR tag.\nexport const BR_TAG_RE = new RegExp('<br[^>]*>', 'i');\n\n// A list of all of the block level tags known in HTML5 and below. Taken from\n// http://bit.ly/qneNIT\nexport const BLOCK_LEVEL_TAGS = [\n  'article',\n  'aside',\n  'blockquote',\n  'body',\n  'br',\n  'button',\n  'canvas',\n  'caption',\n  'col',\n  'colgroup',\n  'dd',\n  'div',\n  'dl',\n  'dt',\n  'embed',\n  'fieldset',\n  'figcaption',\n  'figure',\n  'footer',\n  'form',\n  'h1',\n  'h2',\n  'h3',\n  'h4',\n  'h5',\n  'h6',\n  'header',\n  'hgroup',\n  'hr',\n  'li',\n  'map',\n  'object',\n  'ol',\n  'output',\n  'p',\n  'pre',\n  'progress',\n  'section',\n  'table',\n  'tbody',\n  'textarea',\n  'tfoot',\n  'th',\n  'thead',\n  'tr',\n  'ul',\n  'video',\n];\nexport const BLOCK_LEVEL_TAGS_RE = new RegExp(`^(${BLOCK_LEVEL_TAGS.join('|')})$`, 'i');\n\n// The removal is implemented as a blacklist and whitelist, this test finds\n// blacklisted elements that aren't whitelisted. We do this all in one\n// expression-both because it's only one pass, and because this skips the\n// serialization for whitelisted nodes.\nconst candidatesBlacklist = UNLIKELY_CANDIDATES_BLACKLIST.join('|');\nexport const CANDIDATES_BLACKLIST = new RegExp(candidatesBlacklist, 'i');\n\nconst candidatesWhitelist = UNLIKELY_CANDIDATES_WHITELIST.join('|');\nexport const CANDIDATES_WHITELIST = new RegExp(candidatesWhitelist, 'i');\n\nexport const UNLIKELY_RE = new RegExp(`!(${candidatesWhitelist})|(${candidatesBlacklist})`, 'i');\n\nexport const PARAGRAPH_SCORE_TAGS = new RegExp('^(p|li|span|pre)$', 'i');\nexport const CHILD_CONTENT_TAGS = new RegExp('^(td|blockquote|ol|ul|dl)$', 'i');\nexport const BAD_TAGS = new RegExp('^(address|form)$', 'i');\n\nexport const HTML_OR_BODY_RE = new RegExp('^(html|body)$', 'i');\n","import {\n  CANDIDATES_WHITELIST,\n  CANDIDATES_BLACKLIST,\n} from './constants';\n\nexport default function stripUnlikelyCandidates($) {\n  //  Loop through the provided document and remove any non-link nodes\n  //  that are unlikely candidates for article content.\n  //\n  //  Links are ignored because there are very often links to content\n  //  that are identified as non-body-content, but may be inside\n  //  article-like content.\n  //\n  //  :param $: a cheerio object to strip nodes from\n  //  :return $: the cleaned cheerio object\n  $('*').not('a').each((index, node) => {\n    const $node = $(node);\n    const classes = $node.attr('class');\n    const id = $node.attr('id');\n    if (!id && !classes) return;\n\n    const classAndId = `${classes || ''} ${id || ''}`;\n    if (CANDIDATES_WHITELIST.test(classAndId)) {\n      return;\n    } else if (CANDIDATES_BLACKLIST.test(classAndId)) {\n      $node.remove();\n    }\n  });\n\n  return $;\n}\n","import { paragraphize } from './index';\n\n// ## NOTES:\n// Another good candidate for refactoring/optimizing.\n// Very imperative code, I don't love it. - AP\n\n//  Given cheerio object, convert consecutive <br /> tags into\n//  <p /> tags instead.\n//\n//  :param $: A cheerio object\n\nexport default function brsToPs($) {\n  let collapsing = false;\n  $('br').each((index, element) => {\n    const $element = $(element);\n    const nextElement = $element.next().get(0);\n\n    if (nextElement && nextElement.tagName.toLowerCase() === 'br') {\n      collapsing = true;\n      $element.remove();\n    } else if (collapsing) {\n      collapsing = false;\n      // $(element).replaceWith('<p />')\n      paragraphize(element, $, true);\n    }\n  });\n\n  return $;\n}\n","import { BLOCK_LEVEL_TAGS_RE } from './constants';\n\n// Given a node, turn it into a P if it is not already a P, and\n// make sure it conforms to the constraints of a P tag (I.E. does\n// not contain any other block tags.)\n//\n// If the node is a <br />, it treats the following inline siblings\n// as if they were its children.\n//\n// :param node: The node to paragraphize; this is a raw node\n// :param $: The cheerio object to handle dom manipulation\n// :param br: Whether or not the passed node is a br\n\nexport default function paragraphize(node, $, br = false) {\n  const $node = $(node);\n\n  if (br) {\n    let sibling = node.nextSibling;\n    const p = $('<p></p>');\n\n    // while the next node is text or not a block level element\n    // append it to a new p node\n    while (sibling && !(sibling.tagName && BLOCK_LEVEL_TAGS_RE.test(sibling.tagName))) {\n      const nextSibling = sibling.nextSibling;\n      $(sibling).appendTo(p);\n      sibling = nextSibling;\n    }\n\n    $node.replaceWith(p);\n    $node.remove();\n    return $;\n  }\n\n  return $;\n}\n","import { brsToPs, convertNodeTo } from 'utils/dom';\n\nimport { DIV_TO_P_BLOCK_TAGS } from './constants';\n\nfunction convertDivs($) {\n  $('div').each((index, div) => {\n    const $div = $(div);\n    const convertable = $div.children(DIV_TO_P_BLOCK_TAGS).length === 0;\n\n    if (convertable) {\n      convertNodeTo($div, $, 'p');\n    }\n  });\n\n  return $;\n}\n\nfunction convertSpans($) {\n  $('span').each((index, span) => {\n    const $span = $(span);\n    const convertable = $span.parents('p, div').length === 0;\n    if (convertable) {\n      convertNodeTo($span, $, 'p');\n    }\n  });\n\n  return $;\n}\n\n// Loop through the provided doc, and convert any p-like elements to\n// actual paragraph tags.\n//\n//   Things fitting this criteria:\n//   * Multiple consecutive <br /> tags.\n//   * <div /> tags without block level elements inside of them\n//   * <span /> tags who are not children of <p /> or <div /> tags.\n//\n//   :param $: A cheerio object to search\n//   :return cheerio object with new p elements\n//   (By-reference mutation, though. Returned just for convenience.)\n\nexport default function convertToParagraphs($) {\n  $ = brsToPs($);\n  $ = convertDivs($);\n  $ = convertSpans($);\n\n  return $;\n}\n","import { getAttrs } from 'utils/dom';\n\nexport default function convertNodeTo($node, $, tag = 'p') {\n  const node = $node.get(0);\n  if (!node) {\n    return $;\n  }\n  const attrs = getAttrs(node) || {};\n  // console.log(attrs)\n\n  const attribString = Reflect.ownKeys(attrs)\n                              .map(key => `${key}=${attrs[key]}`)\n                              .join(' ');\n  let html;\n\n  if ($.browser) {\n    // In the browser, the contents of noscript tags aren't rendered, therefore\n    // transforms on the noscript tag (commonly used for lazy-loading) don't work\n    // as expected. This test case handles that\n    html = node.tagName.toLowerCase() === 'noscript' ? $node.text() : $node.html();\n  } else {\n    html = $node.contents();\n  }\n  $node.replaceWith(\n    `<${tag} ${attribString}>${html}</${tag}>`\n  );\n  return $;\n}\n","import { SPACER_RE } from './constants';\n\nfunction cleanForHeight($img, $) {\n  const height = parseInt($img.attr('height'), 10);\n  const width = parseInt($img.attr('width'), 10) || 20;\n\n  // Remove images that explicitly have very small heights or\n  // widths, because they are most likely shims or icons,\n  // which aren't very useful for reading.\n  if ((height || 20) < 10 || width < 10) {\n    $img.remove();\n  } else if (height) {\n    // Don't ever specify a height on images, so that we can\n    // scale with respect to width without screwing up the\n    // aspect ratio.\n    $img.removeAttr('height');\n  }\n\n  return $;\n}\n\n// Cleans out images where the source string matches transparent/spacer/etc\n// TODO This seems very aggressive - AP\nfunction removeSpacers($img, $) {\n  if (SPACER_RE.test($img.attr('src'))) {\n    $img.remove();\n  }\n\n  return $;\n}\n\nexport default function cleanImages($article, $) {\n  $article.find('img').each((index, img) => {\n    const $img = $(img);\n\n    cleanForHeight($img, $);\n    removeSpacers($img, $);\n  });\n\n  return $;\n}\n","import URL from 'url';\n\nimport {\n  KEEP_SELECTORS,\n  KEEP_CLASS,\n} from './constants';\n\nexport default function markToKeep(article, $, url, tags = []) {\n  if (tags.length === 0) {\n    tags = KEEP_SELECTORS;\n  }\n\n  if (url) {\n    const { protocol, hostname } = URL.parse(url);\n    tags = [...tags, `iframe[src^=\"${protocol}//${hostname}\"]`];\n  }\n\n  $(tags.join(','), article).addClass(KEEP_CLASS);\n\n  return $;\n}\n","import {\n  STRIP_OUTPUT_TAGS,\n  KEEP_CLASS,\n} from './constants';\n\nexport default function stripJunkTags(article, $, tags = []) {\n  if (tags.length === 0) {\n    tags = STRIP_OUTPUT_TAGS;\n  }\n\n  // Remove matching elements, but ignore\n  // any element with a class of mercury-parser-keep\n  $(tags.join(','), article).not(`.${KEEP_CLASS}`).remove();\n\n  return $;\n}\n","import { convertNodeTo } from 'utils/dom';\n\n// H1 tags are typically the article title, which should be extracted\n// by the title extractor instead. If there's less than 3 of them (<3),\n// strip them. Otherwise, turn 'em into H2s.\nexport default function cleanHOnes(article, $) {\n  const $hOnes = $('h1', article);\n\n  if ($hOnes.length < 3) {\n    $hOnes.each((index, node) => $(node).remove());\n  } else {\n    $hOnes.each((index, node) => {\n      convertNodeTo($(node), $, 'h2');\n    });\n  }\n\n  return $;\n}\n","import {\n  getAttrs,\n  setAttrs,\n} from 'utils/dom';\n\nimport {\n  WHITELIST_ATTRS_RE,\n  KEEP_CLASS,\n} from './constants';\n\nfunction removeAllButWhitelist($article, $) {\n  $article.find('*').each((index, node) => {\n    const attrs = getAttrs(node);\n\n    setAttrs(node, Reflect.ownKeys(attrs).reduce((acc, attr) => {\n      if (WHITELIST_ATTRS_RE.test(attr)) {\n        return { ...acc, [attr]: attrs[attr] };\n      }\n\n      return acc;\n    }, {}));\n  });\n\n  // Remove the mercury-parser-keep class from result\n  $(`.${KEEP_CLASS}`, $article).removeClass(KEEP_CLASS);\n\n  return $article;\n}\n\n// function removeAttrs(article, $) {\n//   REMOVE_ATTRS.forEach((attr) => {\n//     $(`[${attr}]`, article).removeAttr(attr);\n//   });\n// }\n\n// Remove attributes like style or align\nexport default function cleanAttributes($article, $) {\n  // Grabbing the parent because at this point\n  // $article will be wrapped in a div which will\n  // have a score set on it.\n  return removeAllButWhitelist(\n    $article.parent().length ? $article.parent() : $article,\n    $,\n  );\n}\n","export default function removeEmpty($article, $) {\n  $article.find('p').each((index, p) => {\n    const $p = $(p);\n    if ($p.find('iframe, img').length === 0 && $p.text().trim() === '') $p.remove();\n  });\n\n  return $;\n}\n","// // CONTENT FETCHING CONSTANTS ////\n\n// A list of strings that can be considered unlikely candidates when\n// extracting content from a resource. These strings are joined together\n// and then tested for existence using re:test, so may contain simple,\n// non-pipe style regular expression queries if necessary.\nexport const UNLIKELY_CANDIDATES_BLACKLIST = [\n  'ad-break',\n  'adbox',\n  'advert',\n  'addthis',\n  'agegate',\n  'aux',\n  'blogger-labels',\n  'combx',\n  'comment',\n  'conversation',\n  'disqus',\n  'entry-unrelated',\n  'extra',\n  'foot',\n  'form',\n  'header',\n  'hidden',\n  'loader',\n  'login',                     // Note: This can hit 'blogindex'.\n  'menu',\n  'meta',\n  'nav',\n  'pager',\n  'pagination',\n  'predicta',                  // readwriteweb inline ad box\n  'presence_control_external', // lifehacker.com container full of false positives\n  'popup',\n  'printfriendly',\n  'related',\n  'remove',\n  'remark',\n  'rss',\n  'share',\n  'shoutbox',\n  'sidebar',\n  'sociable',\n  'sponsor',\n  'tools',\n];\n\n// A list of strings that can be considered LIKELY candidates when\n// extracting content from a resource. Essentially, the inverse of the\n// blacklist above - if something matches both blacklist and whitelist,\n// it is kept. This is useful, for example, if something has a className\n// of \"rss-content entry-content\". It matched 'rss', so it would normally\n// be removed, however, it's also the entry content, so it should be left\n// alone.\n//\n// These strings are joined together and then tested for existence using\n// re:test, so may contain simple, non-pipe style regular expression queries\n// if necessary.\nexport const UNLIKELY_CANDIDATES_WHITELIST = [\n  'and',\n  'article',\n  'body',\n  'blogindex',\n  'column',\n  'content',\n  'entry-content-asset',\n  'format', // misuse of form\n  'hfeed',\n  'hentry',\n  'hatom',\n  'main',\n  'page',\n  'posts',\n  'shadow',\n];\n\n// A list of tags which, if found inside, should cause a <div /> to NOT\n// be turned into a paragraph tag. Shallow div tags without these elements\n// should be turned into <p /> tags.\nexport const DIV_TO_P_BLOCK_TAGS = [\n  'a',\n  'blockquote',\n  'dl',\n  'div',\n  'img',\n  'p',\n  'pre',\n  'table',\n].join(',');\n\n// A list of tags that should be ignored when trying to find the top candidate\n// for a document.\nexport const NON_TOP_CANDIDATE_TAGS = [\n  'br',\n  'b',\n  'i',\n  'label',\n  'hr',\n  'area',\n  'base',\n  'basefont',\n  'input',\n  'img',\n  'link',\n  'meta',\n];\n\nexport const NON_TOP_CANDIDATE_TAGS_RE =\n  new RegExp(`^(${NON_TOP_CANDIDATE_TAGS.join('|')})$`, 'i');\n\n// A list of selectors that specify, very clearly, either hNews or other\n// very content-specific style content, like Blogger templates.\n// More examples here: http://microformats.org/wiki/blog-post-formats\nexport const HNEWS_CONTENT_SELECTORS = [\n  ['.hentry', '.entry-content'],\n  ['entry', '.entry-content'],\n  ['.entry', '.entry_content'],\n  ['.post', '.postbody'],\n  ['.post', '.post_body'],\n  ['.post', '.post-body'],\n];\n\nexport const PHOTO_HINTS = [\n  'figure',\n  'photo',\n  'image',\n  'caption',\n];\nexport const PHOTO_HINTS_RE = new RegExp(PHOTO_HINTS.join('|'), 'i');\n\n// A list of strings that denote a positive scoring for this content as being\n// an article container. Checked against className and id.\n//\n// TODO: Perhaps have these scale based on their odds of being quality?\nexport const POSITIVE_SCORE_HINTS = [\n  'article',\n  'articlecontent',\n  'instapaper_body',\n  'blog',\n  'body',\n  'content',\n  'entry-content-asset',\n  'entry',\n  'hentry',\n  'main',\n  'Normal',\n  'page',\n  'pagination',\n  'permalink',\n  'post',\n  'story',\n  'text',\n  '[-_]copy', // usatoday\n  '\\\\Bcopy',\n];\n\n// The above list, joined into a matching regular expression\nexport const POSITIVE_SCORE_RE = new RegExp(POSITIVE_SCORE_HINTS.join('|'), 'i');\n\n// Readability publisher-specific guidelines\nexport const READABILITY_ASSET = new RegExp('entry-content-asset', 'i');\n\n// A list of strings that denote a negative scoring for this content as being\n// an article container. Checked against className and id.\n//\n// TODO: Perhaps have these scale based on their odds of being quality?\nexport const NEGATIVE_SCORE_HINTS = [\n  'adbox',\n  'advert',\n  'author',\n  'bio',\n  'bookmark',\n  'bottom',\n  'byline',\n  'clear',\n  'com-',\n  'combx',\n  'comment',\n  'comment\\\\B',\n  'contact',\n  'copy',\n  'credit',\n  'crumb',\n  'date',\n  'deck',\n  'excerpt',\n  'featured', // tnr.com has a featured_content which throws us off\n  'foot',\n  'footer',\n  'footnote',\n  'graf',\n  'head',\n  'info',\n  'infotext', // newscientist.com copyright\n  'instapaper_ignore',\n  'jump',\n  'linebreak',\n  'link',\n  'masthead',\n  'media',\n  'meta',\n  'modal',\n  'outbrain', // slate.com junk\n  'promo',\n  'pr_', // autoblog - press release\n  'related',\n  'respond',\n  'roundcontent', // lifehacker restricted content warning\n  'scroll',\n  'secondary',\n  'share',\n  'shopping',\n  'shoutbox',\n  'side',\n  'sidebar',\n  'sponsor',\n  'stamp',\n  'sub',\n  'summary',\n  'tags',\n  'tools',\n  'widget',\n];\n// The above list, joined into a matching regular expression\nexport const NEGATIVE_SCORE_RE = new RegExp(NEGATIVE_SCORE_HINTS.join('|'), 'i');\n\n// Match a digit. Pretty clear.\nexport const DIGIT_RE = new RegExp('[0-9]');\n\n// Match 2 or more consecutive <br> tags\nexport const BR_TAGS_RE = new RegExp('(<br[^>]*>[ \\n\\r\\t]*){2,}', 'i');\n\n// Match 1 BR tag.\nexport const BR_TAG_RE = new RegExp('<br[^>]*>', 'i');\n\n// A list of all of the block level tags known in HTML5 and below. Taken from\n// http://bit.ly/qneNIT\nexport const BLOCK_LEVEL_TAGS = [\n  'article',\n  'aside',\n  'blockquote',\n  'body',\n  'br',\n  'button',\n  'canvas',\n  'caption',\n  'col',\n  'colgroup',\n  'dd',\n  'div',\n  'dl',\n  'dt',\n  'embed',\n  'fieldset',\n  'figcaption',\n  'figure',\n  'footer',\n  'form',\n  'h1',\n  'h2',\n  'h3',\n  'h4',\n  'h5',\n  'h6',\n  'header',\n  'hgroup',\n  'hr',\n  'li',\n  'map',\n  'object',\n  'ol',\n  'output',\n  'p',\n  'pre',\n  'progress',\n  'section',\n  'table',\n  'tbody',\n  'textarea',\n  'tfoot',\n  'th',\n  'thead',\n  'tr',\n  'ul',\n  'video',\n];\nexport const BLOCK_LEVEL_TAGS_RE = new RegExp(`^(${BLOCK_LEVEL_TAGS.join('|')})$`, 'i');\n\n// The removal is implemented as a blacklist and whitelist, this test finds\n// blacklisted elements that aren't whitelisted. We do this all in one\n// expression-both because it's only one pass, and because this skips the\n// serialization for whitelisted nodes.\nconst candidatesBlacklist = UNLIKELY_CANDIDATES_BLACKLIST.join('|');\nexport const CANDIDATES_BLACKLIST = new RegExp(candidatesBlacklist, 'i');\n\nconst candidatesWhitelist = UNLIKELY_CANDIDATES_WHITELIST.join('|');\nexport const CANDIDATES_WHITELIST = new RegExp(candidatesWhitelist, 'i');\n\nexport const UNLIKELY_RE = new RegExp(`!(${candidatesWhitelist})|(${candidatesBlacklist})`, 'i');\n\nexport const PARAGRAPH_SCORE_TAGS = new RegExp('^(p|li|span|pre)$', 'i');\nexport const CHILD_CONTENT_TAGS = new RegExp('^(td|blockquote|ol|ul|dl)$', 'i');\nexport const BAD_TAGS = new RegExp('^(address|form)$', 'i');\n\nexport const HTML_OR_BODY_RE = new RegExp('^(html|body)$', 'i');\n","import {\n  NEGATIVE_SCORE_RE,\n  POSITIVE_SCORE_RE,\n  PHOTO_HINTS_RE,\n  READABILITY_ASSET,\n} from './constants';\n\n// Get the score of a node based on its className and id.\nexport default function getWeight(node) {\n  const classes = node.attr('class');\n  const id = node.attr('id');\n  let score = 0;\n\n  if (id) {\n    // if id exists, try to score on both positive and negative\n    if (POSITIVE_SCORE_RE.test(id)) {\n      score += 25;\n    }\n    if (NEGATIVE_SCORE_RE.test(id)) {\n      score -= 25;\n    }\n  }\n\n  if (classes) {\n    if (score === 0) {\n      // if classes exist and id did not contribute to score\n      // try to score on both positive and negative\n      if (POSITIVE_SCORE_RE.test(classes)) {\n        score += 25;\n      }\n      if (NEGATIVE_SCORE_RE.test(classes)) {\n        score -= 25;\n      }\n    }\n\n    // even if score has been set by id, add score for\n    // possible photo matches\n    // \"try to keep photos if we can\"\n    if (PHOTO_HINTS_RE.test(classes)) {\n      score += 10;\n    }\n\n    // add 25 if class matches entry-content-asset,\n    // a class apparently instructed for use in the\n    // Readability publisher guidelines\n    // https://www.readability.com/developers/guidelines\n    if (READABILITY_ASSET.test(classes)) {\n      score += 25;\n    }\n  }\n\n  return score;\n}\n","// returns the score of a node based on\n// the node's score attribute\n// returns null if no score set\nexport default function getScore($node) {\n  return parseFloat($node.attr('score')) || null;\n}\n","// return 1 for every comma in text\nexport default function scoreCommas(text) {\n  return (text.match(/,/g) || []).length;\n}\n","const idkRe = new RegExp('^(p|pre)$', 'i');\n\nexport default function scoreLength(textLength, tagName = 'p') {\n  const chunks = textLength / 50;\n\n  if (chunks > 0) {\n    let lengthBonus;\n\n    // No idea why p or pre are being tamped down here\n    // but just following the source for now\n    // Not even sure why tagName is included here,\n    // since this is only being called from the context\n    // of scoreParagraph\n    if (idkRe.test(tagName)) {\n      lengthBonus = chunks - 2;\n    } else {\n      lengthBonus = chunks - 1.25;\n    }\n\n    return Math.min(Math.max(lengthBonus, 0), 3);\n  }\n\n  return 0;\n}\n","import {\n  scoreCommas,\n  scoreLength,\n} from './index';\n\n// Score a paragraph using various methods. Things like number of\n// commas, etc. Higher is better.\nexport default function scoreParagraph(node) {\n  let score = 1;\n  const text = node.text().trim();\n  const textLength = text.length;\n\n  // If this paragraph is less than 25 characters, don't count it.\n  if (textLength < 25) {\n    return 0;\n  }\n\n  // Add points for any commas within this paragraph\n  score += scoreCommas(text);\n\n  // For every 50 characters in this paragraph, add another point. Up\n  // to 3 points.\n  score += scoreLength(textLength);\n\n  // Articles can end with short paragraphs when people are being clever\n  // but they can also end with short paragraphs setting up lists of junk\n  // that we strip. This negative tweaks junk setup paragraphs just below\n  // the cutoff threshold.\n  if (text.slice(-1) === ':') {\n    score -= 1;\n  }\n\n  return score;\n}\n","export default function setScore($node, $, score) {\n  $node.attr('score', score);\n  return $node;\n}\n","import {\n  getOrInitScore,\n  setScore,\n} from './index';\n\nexport default function addScore($node, $, amount) {\n  try {\n    const score = getOrInitScore($node, $) + amount;\n    setScore($node, $, score);\n  } catch (e) {\n    // Ignoring; error occurs in scoreNode\n  }\n\n  return $node;\n}\n","import { addScore } from './index';\n\n// Adds 1/4 of a child's score to its parent\nexport default function addToParent(node, $, score) {\n  const parent = node.parent();\n  if (parent) {\n    addScore(parent, $, score * 0.25);\n  }\n\n  return node;\n}\n","import {\n  getScore,\n  scoreNode,\n  getWeight,\n  addToParent,\n} from './index';\n\n// gets and returns the score if it exists\n// if not, initializes a score based on\n// the node's tag type\nexport default function getOrInitScore($node, $, weightNodes = true) {\n  let score = getScore($node);\n\n  if (score) {\n    return score;\n  }\n\n  score = scoreNode($node);\n\n  if (weightNodes) {\n    score += getWeight($node);\n  }\n\n  addToParent($node, $, score);\n\n  return score;\n}\n","import { scoreParagraph } from './index';\nimport {\n  PARAGRAPH_SCORE_TAGS,\n  CHILD_CONTENT_TAGS,\n  BAD_TAGS,\n} from './constants';\n\n// Score an individual node. Has some smarts for paragraphs, otherwise\n// just scores based on tag.\nexport default function scoreNode($node) {\n  const { tagName } = $node.get(0);\n\n  // TODO: Consider ordering by most likely.\n  // E.g., if divs are a more common tag on a page,\n  // Could save doing that regex test on every node – AP\n  if (PARAGRAPH_SCORE_TAGS.test(tagName)) {\n    return scoreParagraph($node);\n  } else if (tagName.toLowerCase() === 'div') {\n    return 5;\n  } else if (CHILD_CONTENT_TAGS.test(tagName)) {\n    return 3;\n  } else if (BAD_TAGS.test(tagName)) {\n    return -3;\n  } else if (tagName.toLowerCase() === 'th') {\n    return -5;\n  }\n\n  return 0;\n}\n","import { convertNodeTo } from 'utils/dom';\n\nimport { HNEWS_CONTENT_SELECTORS } from './constants';\nimport {\n  scoreNode,\n  setScore,\n  getOrInitScore,\n  addScore,\n} from './index';\n\nfunction convertSpans($node, $) {\n  if ($node.get(0)) {\n    const { tagName } = $node.get(0);\n\n    if (tagName === 'span') {\n      // convert spans to divs\n      convertNodeTo($node, $, 'div');\n    }\n  }\n}\n\nfunction addScoreTo($node, $, score) {\n  if ($node) {\n    convertSpans($node, $);\n    addScore($node, $, score);\n  }\n}\n\nfunction scorePs($, weightNodes) {\n  $('p, pre').not('[score]').each((index, node) => {\n    // The raw score for this paragraph, before we add any parent/child\n    // scores.\n    let $node = $(node);\n    $node = setScore($node, $, getOrInitScore($node, $, weightNodes));\n\n    const $parent = $node.parent();\n    const rawScore = scoreNode($node);\n\n    addScoreTo($parent, $, rawScore, weightNodes);\n    if ($parent) {\n      // Add half of the individual content score to the\n      // grandparent\n      addScoreTo($parent.parent(), $, rawScore / 2, weightNodes);\n    }\n  });\n\n  return $;\n}\n\n// score content. Parents get the full value of their children's\n// content score, grandparents half\nexport default function scoreContent($, weightNodes = true) {\n  // First, look for special hNews based selectors and give them a big\n  // boost, if they exist\n  HNEWS_CONTENT_SELECTORS.forEach(([parentSelector, childSelector]) => {\n    $(`${parentSelector} ${childSelector}`).each((index, node) => {\n      addScore($(node).parent(parentSelector), $, 80);\n    });\n  });\n\n  // Doubling this again\n  // Previous solution caused a bug\n  // in which parents weren't retaining\n  // scores. This is not ideal, and\n  // should be fixed.\n  scorePs($, weightNodes);\n  scorePs($, weightNodes);\n\n  return $;\n}\n","import {\n  textLength,\n  linkDensity,\n} from 'utils/dom';\nimport { hasSentenceEnd } from 'utils/text';\n\nimport { NON_TOP_CANDIDATE_TAGS_RE } from './constants';\nimport { getScore } from './index';\n\n// Now that we have a top_candidate, look through the siblings of\n// it to see if any of them are decently scored. If they are, they\n// may be split parts of the content (Like two divs, a preamble and\n// a body.) Example:\n// http://articles.latimes.com/2009/oct/14/business/fi-bigtvs14\nexport default function mergeSiblings($candidate, topScore, $) {\n  if (!$candidate.parent().length) {\n    return $candidate;\n  }\n\n  const siblingScoreThreshold = Math.max(10, topScore * 0.25);\n  const wrappingDiv = $('<div></div>');\n\n  $candidate.parent().children().each((index, sibling) => {\n    const $sibling = $(sibling);\n    // Ignore tags like BR, HR, etc\n    if (NON_TOP_CANDIDATE_TAGS_RE.test(sibling.tagName)) {\n      return null;\n    }\n\n    const siblingScore = getScore($sibling);\n    if (siblingScore) {\n      if ($sibling.get(0) === $candidate.get(0)) {\n        wrappingDiv.append($sibling);\n      } else {\n        let contentBonus = 0;\n        const density = linkDensity($sibling);\n\n        // If sibling has a very low link density,\n        // give it a small bonus\n        if (density < 0.05) {\n          contentBonus += 20;\n        }\n\n        // If sibling has a high link density,\n        // give it a penalty\n        if (density >= 0.5) {\n          contentBonus -= 20;\n        }\n\n        // If sibling node has the same class as\n        // candidate, give it a bonus\n        if ($sibling.attr('class') === $candidate.attr('class')) {\n          contentBonus += topScore * 0.2;\n        }\n\n        const newScore = siblingScore + contentBonus;\n\n        if (newScore >= siblingScoreThreshold) {\n          return wrappingDiv.append($sibling);\n        } else if (sibling.tagName === 'p') {\n          const siblingContent = $sibling.text();\n          const siblingContentLength = textLength(siblingContent);\n\n          if (siblingContentLength > 80 && density < 0.25) {\n            return wrappingDiv.append($sibling);\n          } else if (siblingContentLength <= 80 && density === 0 &&\n                    hasSentenceEnd(siblingContent)) {\n            return wrappingDiv.append($sibling);\n          }\n        }\n      }\n    }\n\n    return null;\n  });\n\n  if (wrappingDiv.children().length === 1 &&\n    wrappingDiv.children().first().get(0) === $candidate.get(0)) {\n    return $candidate;\n  }\n\n  return wrappingDiv;\n}\n","import { NON_TOP_CANDIDATE_TAGS_RE } from './constants';\nimport { getScore } from './index';\nimport mergeSiblings from './merge-siblings';\n\n// After we've calculated scores, loop through all of the possible\n// candidate nodes we found and find the one with the highest score.\nexport default function findTopCandidate($) {\n  let $candidate;\n  let topScore = 0;\n\n  $('[score]').each((index, node) => {\n    // Ignore tags like BR, HR, etc\n    if (NON_TOP_CANDIDATE_TAGS_RE.test(node.tagName)) {\n      return;\n    }\n\n    const $node = $(node);\n    const score = getScore($node);\n\n    if (score > topScore) {\n      topScore = score;\n      $candidate = $node;\n    }\n  });\n\n  // If we don't have a candidate, return the body\n  // or whatever the first element is\n  if (!$candidate) {\n    return $('body') || $('*').first();\n  }\n\n  $candidate = mergeSiblings($candidate, topScore, $);\n\n  return $candidate;\n}\n","// Scoring\nexport { default as getWeight } from './get-weight';\nexport { default as getScore } from './get-score';\nexport { default as scoreCommas } from './score-commas';\nexport { default as scoreLength } from './score-length';\nexport { default as scoreParagraph } from './score-paragraph';\nexport { default as setScore } from './set-score';\nexport { default as addScore } from './add-score';\nexport { default as addToParent } from './add-to-parent';\nexport { default as getOrInitScore } from './get-or-init-score';\nexport { default as scoreNode } from './score-node';\nexport { default as scoreContent } from './score-content';\nexport { default as findTopCandidate } from './find-top-candidate';\n","import {\n  getScore,\n  setScore,\n  getOrInitScore,\n  scoreCommas,\n} from 'extractors/generic/content/scoring';\n\nimport {\n  CLEAN_CONDITIONALLY_TAGS,\n  KEEP_CLASS,\n} from './constants';\nimport { normalizeSpaces } from '../text';\nimport { linkDensity } from './index';\n\nfunction removeUnlessContent($node, $, weight) {\n    // Explicitly save entry-content-asset tags, which are\n    // noted as valuable in the Publisher guidelines. For now\n    // this works everywhere. We may want to consider making\n    // this less of a sure-thing later.\n  if ($node.hasClass('entry-content-asset')) {\n    return;\n  }\n\n  const content = normalizeSpaces($node.text());\n\n  if (scoreCommas(content) < 10) {\n    const pCount = $('p', $node).length;\n    const inputCount = $('input', $node).length;\n\n      // Looks like a form, too many inputs.\n    if (inputCount > (pCount / 3)) {\n      $node.remove();\n      return;\n    }\n\n    const contentLength = content.length;\n    const imgCount = $('img', $node).length;\n\n      // Content is too short, and there are no images, so\n      // this is probably junk content.\n    if (contentLength < 25 && imgCount === 0) {\n      $node.remove();\n      return;\n    }\n\n    const density = linkDensity($node);\n\n      // Too high of link density, is probably a menu or\n      // something similar.\n      // console.log(weight, density, contentLength)\n    if (weight < 25 && density > 0.2 && contentLength > 75) {\n      $node.remove();\n      return;\n    }\n\n      // Too high of a link density, despite the score being\n      // high.\n    if (weight >= 25 && density > 0.5) {\n        // Don't remove the node if it's a list and the\n        // previous sibling starts with a colon though. That\n        // means it's probably content.\n      const tagName = $node.get(0).tagName.toLowerCase();\n      const nodeIsList = tagName === 'ol' || tagName === 'ul';\n      if (nodeIsList) {\n        const previousNode = $node.prev();\n        if (previousNode && normalizeSpaces(previousNode.text()).slice(-1) === ':') {\n          return;\n        }\n      }\n\n      $node.remove();\n      return;\n    }\n\n    const scriptCount = $('script', $node).length;\n\n      // Too many script tags, not enough content.\n    if (scriptCount > 0 && contentLength < 150) {\n      $node.remove();\n      return;\n    }\n  }\n}\n\n// Given an article, clean it of some superfluous content specified by\n// tags. Things like forms, ads, etc.\n//\n// Tags is an array of tag name's to search through. (like div, form,\n// etc)\n//\n// Return this same doc.\nexport default function cleanTags($article, $) {\n  $(CLEAN_CONDITIONALLY_TAGS, $article).each((index, node) => {\n    const $node = $(node);\n    // If marked to keep, skip it\n    if ($node.hasClass(KEEP_CLASS) || $node.find(`.${KEEP_CLASS}`).length > 0) return;\n\n    let weight = getScore($node);\n    if (!weight) {\n      weight = getOrInitScore($node, $);\n      setScore($node, $, weight);\n    }\n\n    // drop node if its weight is < 0\n    if (weight < 0) {\n      $node.remove();\n    } else {\n      // deteremine if node seems like content\n      removeUnlessContent($node, $, weight);\n    }\n  });\n\n  return $;\n}\n","import { getWeight } from 'extractors/generic/content/scoring';\n\nimport { HEADER_TAG_LIST } from './constants';\nimport { normalizeSpaces } from '../text';\n\nexport default function cleanHeaders($article, $, title = '') {\n  $(HEADER_TAG_LIST, $article).each((index, header) => {\n    const $header = $(header);\n    // Remove any headers that appear before all other p tags in the\n    // document. This probably means that it was part of the title, a\n    // subtitle or something else extraneous like a datestamp or byline,\n    // all of which should be handled by other metadata handling.\n    if ($($header, $article).prevAll('p').length === 0) {\n      return $header.remove();\n    }\n\n    // Remove any headers that match the title exactly.\n    if (normalizeSpaces($(header).text()) === title) {\n      return $header.remove();\n    }\n\n    // If this header has a negative weight, it's probably junk.\n    // Get rid of it.\n    if (getWeight($(header)) < 0) {\n      return $header.remove();\n    }\n\n    return $header;\n  });\n\n  return $;\n}\n","import { convertNodeTo } from 'utils/dom';\n\n// Rewrite the tag name to div if it's a top level node like body or\n// html to avoid later complications with multiple body tags.\nexport default function rewriteTopLevel(article, $) {\n  // I'm not using context here because\n  // it's problematic when converting the\n  // top-level/root node - AP\n  $ = convertNodeTo($('html'), $, 'div');\n  $ = convertNodeTo($('body'), $, 'div');\n\n  return $;\n}\n","import URL from 'url';\n\nimport {\n  getAttrs,\n  setAttr,\n} from 'utils/dom';\n\nfunction absolutize($, rootUrl, attr, $content) {\n  $(`[${attr}]`, $content).each((_, node) => {\n    const attrs = getAttrs(node);\n    const url = attrs[attr];\n\n    if (url) {\n      const absoluteUrl = URL.resolve(rootUrl, url);\n      setAttr(node, attr, absoluteUrl);\n    }\n  });\n}\n\nexport default function makeLinksAbsolute($content, $, url) {\n  ['href', 'src'].forEach(attr => absolutize($, url, attr, $content));\n\n  return $content;\n}\n","export function textLength(text) {\n  return text.trim()\n             .replace(/\\s+/g, ' ')\n             .length;\n}\n\n// Determines what percentage of the text\n// in a node is link text\n// Takes a node, returns a float\nexport function linkDensity($node) {\n  const totalTextLength = textLength($node.text());\n\n  const linkText = $node.find('a').text();\n  const linkLength = textLength(linkText);\n\n  if (totalTextLength > 0) {\n    return linkLength / totalTextLength;\n  } else if (totalTextLength === 0 && linkLength > 0) {\n    return 1;\n  }\n\n  return 0;\n}\n","import { stripTags } from 'utils/dom';\n\n// Given a node type to search for, and a list of meta tag names to\n// search for, find a meta tag associated.\nexport default function extractFromMeta(\n  $,\n  metaNames,\n  cachedNames,\n  cleanTags = true\n) {\n  const foundNames = metaNames.filter(name => cachedNames.indexOf(name) !== -1);\n\n  for (const name of foundNames) {\n    const type = 'name';\n    const value = 'value';\n\n    const nodes = $(`meta[${type}=\"${name}\"]`);\n\n    // Get the unique value of every matching node, in case there\n    // are two meta tags with the same name and value.\n    // Remove empty values.\n    const values =\n      nodes.map((index, node) => $(node).attr(value))\n           .toArray()\n           .filter(text => text !== '');\n\n      // If we have more than one value for the same name, we have a\n      // conflict and can't trust any of them. Skip this name. If we have\n      // zero, that means our meta tags had no values. Skip this name\n      // also.\n    if (values.length === 1) {\n      let metaValue;\n        // Meta values that contain HTML should be stripped, as they\n        // weren't subject to cleaning previously.\n      if (cleanTags) {\n        metaValue = stripTags(values[0], $);\n      } else {\n        metaValue = values[0];\n      }\n\n      return metaValue;\n    }\n  }\n\n  // If nothing is found, return null\n  return null;\n}\n","import { withinComment } from 'utils/dom';\n\nfunction isGoodNode($node, maxChildren) {\n  // If it has a number of children, it's more likely a container\n  // element. Skip it.\n  if ($node.children().length > maxChildren) {\n    return false;\n  }\n  // If it looks to be within a comment, skip it.\n  if (withinComment($node)) {\n    return false;\n  }\n\n  return true;\n}\n\n// Given a a list of selectors find content that may\n// be extractable from the document. This is for flat\n// meta-information, like author, title, date published, etc.\nexport default function extractFromSelectors(\n  $,\n  selectors,\n  maxChildren = 1,\n  textOnly = true\n) {\n  for (const selector of selectors) {\n    const nodes = $(selector);\n\n    // If we didn't get exactly one of this selector, this may be\n    // a list of articles or comments. Skip it.\n    if (nodes.length === 1) {\n      const $node = $(nodes[0]);\n\n      if (isGoodNode($node, maxChildren)) {\n        let content;\n        if (textOnly) {\n          content = $node.text();\n        } else {\n          content = $node.html();\n        }\n\n        if (content) {\n          return content;\n        }\n      }\n    }\n  }\n\n  return null;\n}\n","// strips all tags from a string of text\nexport default function stripTags(text, $) {\n  // Wrapping text in html element prevents errors when text\n  // has no html\n  const cleanText = $(`<span>${text}</span>`).text();\n  return cleanText === '' ? text : cleanText;\n}\n","import { getAttrs } from 'utils/dom';\n\nexport default function withinComment($node) {\n  const parents = $node.parents().toArray();\n  const commentParent = parents.find((parent) => {\n    const attrs = getAttrs(parent);\n    const { class: nodeClass, id } = attrs;\n    const classAndId = `${nodeClass} ${id}`;\n    return classAndId.includes('comment');\n  });\n\n  return commentParent !== undefined;\n}\n","// Given a node, determine if it's article-like enough to return\n// param: node (a cheerio node)\n// return: boolean\n\nexport default function nodeIsSufficient($node) {\n  return $node.text().trim().length >= 100;\n}\n","import { IS_WP_SELECTOR } from './constants';\n\nexport default function isWordpress($) {\n  return $(IS_WP_SELECTOR).length > 0;\n}\n","export default function getAttrs(node) {\n  const { attribs, attributes } = node;\n\n  if (!attribs && attributes) {\n    const attrs = Reflect.ownKeys(attributes).reduce((acc, index) => {\n      const attr = attributes[index];\n\n      if (!attr.name || !attr.value) return acc;\n\n      acc[attr.name] = attr.value;\n      return acc;\n    }, {});\n    return attrs;\n  }\n\n  return attribs;\n}\n","export default function setAttr(node, attr, val) {\n  if (node.attribs) {\n    node.attribs[attr] = val;\n  } else if (node.attributes) {\n    node.setAttribute(attr, val);\n  }\n\n  return node;\n}\n","export default function setAttrs(node, attrs) {\n  if (node.attribs) {\n    node.attribs = attrs;\n  } else if (node.attributes) {\n    while (node.attributes.length > 0) {\n      node.removeAttribute(node.attributes[0].name);\n    }\n\n    Reflect.ownKeys(attrs).forEach((key) => {\n      node.setAttribute(key, attrs[key]);\n    });\n  }\n\n  return node;\n}\n","// DOM manipulation\nexport { default as stripUnlikelyCandidates } from './strip-unlikely-candidates';\nexport { default as brsToPs } from './brs-to-ps';\nexport { default as paragraphize } from './paragraphize';\nexport { default as convertToParagraphs } from './convert-to-paragraphs';\nexport { default as convertNodeTo } from './convert-node-to';\nexport { default as cleanImages } from './clean-images';\nexport { default as markToKeep } from './mark-to-keep';\nexport { default as stripJunkTags } from './strip-junk-tags';\nexport { default as cleanHOnes } from './clean-h-ones';\nexport { default as cleanAttributes } from './clean-attributes';\nexport { default as removeEmpty } from './remove-empty';\nexport { default as cleanTags } from './clean-tags';\nexport { default as cleanHeaders } from './clean-headers';\nexport { default as rewriteTopLevel } from './rewrite-top-level';\nexport { default as makeLinksAbsolute } from './make-links-absolute';\nexport { textLength, linkDensity } from './link-density';\nexport { default as extractFromMeta } from './extract-from-meta';\nexport { default as extractFromSelectors } from './extract-from-selectors';\nexport { default as stripTags } from './strip-tags';\nexport { default as withinComment } from './within-comment';\nexport { default as nodeIsSufficient } from './node-is-sufficient';\nexport { default as isWordpress } from './is-wordpress';\nexport { default as getAttrs } from './get-attrs';\nexport { default as setAttr } from './set-attr';\nexport { default as setAttrs } from './set-attrs';\n","export const IS_LINK = new RegExp('https?://', 'i');\nexport const IS_IMAGE = new RegExp('.(png|gif|jpe?g)', 'i');\n\nexport const TAGS_TO_REMOVE = [\n  'script',\n  'style',\n  'form',\n].join(',');\n","import { getAttrs } from 'utils/dom';\n\nimport {\n  IS_LINK,\n  IS_IMAGE,\n} from './constants';\n\n// Convert all instances of images with potentially\n// lazy loaded images into normal images.\n// Many sites will have img tags with no source, or an image tag with a src\n// attribute that a is a placeholer. We need to be able to properly fill in\n// the src attribute so the images are no longer lazy loaded.\nexport default function convertLazyLoadedImages($) {\n  $('img').each((_, img) => {\n    const attrs = getAttrs(img);\n\n    Reflect.ownKeys(attrs).forEach((attr) => {\n      const value = attrs[attr];\n\n      if (attr !== 'src' && IS_LINK.test(value) &&\n          IS_IMAGE.test(value)) {\n        $(img).attr('src', value);\n      }\n    });\n  });\n\n  return $;\n}\n","import { TAGS_TO_REMOVE } from './constants';\n\nfunction isComment(index, node) {\n  return node.type === 'comment';\n}\n\nfunction cleanComments($) {\n  $.root().find('*')\n          .contents()\n          .filter(isComment)\n          .remove();\n\n  return $;\n}\n\nexport default function clean($) {\n  $(TAGS_TO_REMOVE).remove();\n\n  $ = cleanComments($);\n  return $;\n}\n","import cheerio from 'cheerio';\nimport iconv from 'iconv-lite';\n\nimport { getEncoding } from 'utils/text';\nimport { fetchResource } from './utils';\nimport {\n  normalizeMetaTags,\n  convertLazyLoadedImages,\n  clean,\n} from './utils/dom';\n\nconst Resource = {\n\n  // Create a Resource.\n  //\n  // :param url: The URL for the document we should retrieve.\n  // :param response: If set, use as the response rather than\n  //                  attempting to fetch it ourselves. Expects a\n  //                  string.\n  async create(url, preparedResponse, parsedUrl) {\n    let result;\n\n    if (preparedResponse) {\n      const validResponse = {\n        statusMessage: 'OK',\n        statusCode: 200,\n        headers: {\n          'content-type': 'text/html',\n          'content-length': 500,\n        },\n      };\n\n      result = { body: preparedResponse, response: validResponse };\n    } else {\n      result = await fetchResource(url, parsedUrl);\n    }\n\n    if (result.error) {\n      result.failed = true;\n      return result;\n    }\n\n    return this.generateDoc(result);\n  },\n\n  generateDoc({ body: content, response }) {\n    const { 'content-type': contentType } = response.headers;\n\n    // TODO: Implement is_text function from\n    // https://github.com/ReadabilityHoldings/readability/blob/8dc89613241d04741ebd42fa9fa7df1b1d746303/readability/utils/text.py#L57\n    if (!contentType.includes('html') &&\n        !contentType.includes('text')) {\n      throw new Error('Content does not appear to be text.');\n    }\n\n    let $ = this.encodeDoc({ content, contentType });\n\n    if ($.root().children().length === 0) {\n      throw new Error('No children, likely a bad parse.');\n    }\n\n    $ = normalizeMetaTags($);\n    $ = convertLazyLoadedImages($);\n    $ = clean($);\n\n    return $;\n  },\n\n  encodeDoc({ content, contentType }) {\n    const encoding = getEncoding(contentType);\n    let decodedContent = iconv.decode(content, encoding);\n    let $ = cheerio.load(decodedContent);\n\n    // after first cheerio.load, check to see if encoding matches\n    const metaContentType = $('meta[http-equiv=content-type]').attr('content');\n    const properEncoding = getEncoding(metaContentType);\n\n    // if encodings in the header/body dont match, use the one in the body\n    if (properEncoding !== encoding) {\n      decodedContent = iconv.decode(content, properEncoding);\n      $ = cheerio.load(decodedContent);\n    }\n\n    return $;\n  },\n};\n\nexport default Resource;\n","const merge = (extractor, domains) => (\n  domains.reduce((acc, domain) => {\n    acc[domain] = extractor;\n    return acc;\n  }, {})\n);\n\nexport default function mergeSupportedDomains(extractor) {\n  return extractor.supportedDomains ?\n    merge(extractor, [extractor.domain, ...extractor.supportedDomains])\n    :\n    merge(extractor, [extractor.domain]);\n}\n","export const BloggerExtractor = {\n  domain: 'blogspot.com',\n  content: {\n    // Blogger is insane and does not load its content\n    // initially in the page, but it's all there\n    // in noscript\n    selectors: [\n      '.post-content noscript',\n    ],\n\n    // Selectors to remove from the extracted content\n    clean: [\n    ],\n\n    // Convert the noscript tag to a div\n    transforms: {\n      noscript: 'div',\n    },\n  },\n\n  author: {\n    selectors: [\n      '.post-author-name',\n    ],\n  },\n\n  title: {\n    selectors: [\n      '.post h2.title',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'span.publishdate',\n    ],\n  },\n};\n","export const NYMagExtractor = {\n  domain: 'nymag.com',\n  content: {\n    // Order by most likely. Extractor will stop on first occurrence\n    selectors: [\n      'div.article-content',\n      'section.body',\n      'article.article',\n    ],\n\n    // Selectors to remove from the extracted content\n    clean: [\n      '.ad',\n      '.single-related-story',\n    ],\n\n    // Object of tranformations to make on matched elements\n    // Each key is the selector, each value is the tag to\n    // transform to.\n    // If a function is given, it should return a string\n    // to convert to or nothing (in which case it will not perform\n    // the transformation.\n    transforms: {\n      // Convert h1s to h2s\n      h1: 'h2',\n\n      // Convert lazy-loaded noscript images to figures\n      noscript: ($node, $) => {\n        const $children = $.browser ? $($node.text()) : $node.children();\n        if ($children.length === 1 && $children.get(0) !== undefined &&\n          $children.get(0).tagName.toLowerCase() === 'img') {\n          return 'figure';\n        }\n\n        return null;\n      },\n    },\n  },\n\n  title: {\n    selectors: [\n      'h1.lede-feature-title',\n      'h1.headline-primary',\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.by-authors',\n      '.lede-feature-author',\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.lede-feature-teaser',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time.article-timestamp[datetime]', 'datetime'],\n      'time.article-timestamp',\n    ],\n  },\n};\n","export const WikipediaExtractor = {\n  domain: 'wikipedia.org',\n  content: {\n    selectors: [\n      '#mw-content-text',\n    ],\n\n    defaultCleaner: false,\n\n    // transform top infobox to an image with caption\n    transforms: {\n      '.infobox img': ($node) => {\n        const $parent = $node.parents('.infobox');\n        // Only prepend the first image in .infobox\n        if ($parent.children('img').length === 0) {\n          $parent.prepend($node);\n        }\n      },\n      '.infobox caption': 'figcaption',\n      '.infobox': 'figure',\n    },\n\n    // Selectors to remove from the extracted content\n    clean: [\n      '.mw-editsection',\n      'figure tr, figure td, figure tbody',\n      '#toc',\n      '.navbox',\n    ],\n\n  },\n\n  author: 'Wikipedia Contributors',\n\n  title: {\n    selectors: [\n      'h2.title',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '#footer-info-lastmod',\n    ],\n  },\n\n};\n","export const TwitterExtractor = {\n  domain: 'twitter.com',\n\n  content: {\n    transforms: {\n      // We're transforming essentially the whole page here.\n      // Twitter doesn't have nice selectors, so our initial\n      // selector grabs the whole page, then we're re-writing\n      // it to fit our needs before we clean it up.\n      '.permalink[role=main]': ($node, $) => {\n        const tweets = $node.find('.tweet');\n        const $tweetContainer = $('<div id=\"TWEETS_GO_HERE\"></div>');\n        $tweetContainer.append(tweets);\n        $node.replaceWith($tweetContainer);\n      },\n\n      // Twitter wraps @ with s, which\n      // renders as a strikethrough\n      s: 'span',\n    },\n\n    selectors: [\n      '.permalink[role=main]',\n    ],\n\n    defaultCleaner: false,\n\n    clean: [\n      '.stream-item-footer',\n      'button',\n      '.tweet-details-fixer',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.tweet.permalink-tweet .username',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.permalink-tweet ._timestamp[data-time-ms]', 'data-time-ms'],\n      // '.tweet.permalink-tweet .metadata',\n    ],\n  },\n\n};\n","export const NYTimesExtractor = {\n  domain: 'www.nytimes.com',\n\n  title: {\n    selectors: [\n      'h1.g-headline',\n      'h1[itemprop=\"headline\"]',\n      'h1.headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n      '.g-byline',\n      '.byline',\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.g-blocks',\n      'article#story',\n    ],\n\n    transforms: {\n      'img.g-lazy': ($node) => {\n        let src = $node.attr('src');\n        // const widths = $node.attr('data-widths')\n        //                   .slice(1)\n        //                   .slice(0, -1)\n        //                   .split(',');\n        // if (widths.length) {\n        //   width = widths.slice(-1);\n        // } else {\n        //   width = '900';\n        // }\n        const width = 640;\n\n        src = src.replace('{{size}}', width);\n        $node.attr('src', src);\n      },\n    },\n\n    clean: [\n      '.ad',\n      'header#story-header',\n      '.story-body-1 .lede.video',\n      '.visually-hidden',\n      '#newsletter-promo',\n      '.promo',\n      '.comments-button',\n      '.hidden',\n      '.comments',\n      '.supplemental',\n      '.nocontent',\n      '.story-footer-links',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: null,\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\nexport const TheAtlanticExtractor = {\n  domain: 'www.theatlantic.com',\n  title: {\n    selectors: [\n      'h1.hed',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'article#article .article-cover-extra .metadata .byline a',\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.article-cover figure.lead-img', '.article-body'],\n      '.article-body',\n    ],\n\n  // Is there anything in the content you selected that needs transformed\n  // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n  // Is there anything that is in the result that shouldn't be?\n  // The clean selectors will remove anything that matches from\n  // the result\n    clean: [\n      '.partner-box',\n      '.callout',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time[itemProp=\"datePublished\"]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: null,\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const NewYorkerExtractor = {\n  domain: 'www.newyorker.com',\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.contributors',\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div#articleBody',\n      'div.articleBody',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n      ['time[itemProp=\"datePublished\"]', 'content'],\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.dek',\n      'h2.dek',\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const WiredExtractor = {\n  domain: 'www.wired.com',\n  title: {\n    selectors: [\n      'h1.post-title',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a[rel=\"author\"]',\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      'article.content',\n      // enter content selectors\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.visually-hidden',\n      'figcaption img.photo',\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemprop=\"datePublished\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const MSNExtractor = {\n  domain: 'www.msn.com',\n  title: {\n    selectors: [\n      'h1',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.authorname-txt',\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.richtext',\n      // enter content selectors\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      'span.caption',\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'span.time',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const YahooExtractor = {\n  domain: 'www.yahoo.com',\n  title: {\n    selectors: [\n      'header.canvas-header',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.provider-name',\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      // enter content selectors\n      '.content-canvas',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.figure-caption',\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time.date[datetime]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    // enter dek selectors\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const BuzzfeedExtractor = {\n  domain: 'www.buzzfeed.com',\n  title: {\n    selectors: [\n      'h1[id=\"post-title\"]',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a[data-action=\"user/username\"]', 'byline__author',\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.longform_custom_header_media', '#buzz_sub_buzz'],\n      '#buzz_sub_buzz',\n    ],\n\n    defaultCleaner: false,\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      h2: 'b',\n\n      'div.longform_custom_header_media': ($node) => {\n        if ($node.has('img') && $node.has('.longform_header_image_source')) {\n          return 'figure';\n        }\n\n        return null;\n      },\n\n      'figure.longform_custom_header_media .longform_header_image_source':\n        'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.instapaper_ignore',\n      '.suplist_list_hide .buzz_superlist_item .buzz_superlist_number_inline',\n      '.share-box',\n      '.print',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.buzz-datetime',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const WikiaExtractor = {\n  domain: 'fandom.wikia.com',\n  title: {\n    selectors: [\n      'h1.entry-title',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author vcard', '.fn',\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.grid-content',\n      '.entry-content',\n      // enter content selectors\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const LittleThingsExtractor = {\n  domain: 'www.littlethings.com',\n  title: {\n    selectors: [\n      'h1.post-title',\n      // enter title selectors\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n      // enter author selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      // enter content selectors\n      '.mainContentIntro',\n      '.content-wrapper',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const PoliticoExtractor = {\n  domain: 'www.politico.com',\n  title: {\n    selectors: [\n      // enter title selectors\n      ['meta[name=\"og:title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.story-main-content .byline .vcard',\n    ],\n  },\n\n  content: {\n    selectors: [\n      // enter content selectors\n      '.story-main-content',\n      '.content-group', '.story-core',\n      '.story-text',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: [\n    ],\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      'figcaption',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.story-main-content .timestamp time[datetime]', 'datetime'],\n\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      // enter lead_image_url selectors\n      ['meta[name=\"og:image\"]', 'value'],\n\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: null,\n\n  excerpt: null,\n};\n","export const DeadspinExtractor = {\n  domain: 'deadspin.com',\n\n  supportedDomains: [\n    'jezebel.com',\n    'lifehacker.com',\n    'kotaku.com',\n    'gizmodo.com',\n    'jalopnik.com',\n    'kinja.com',\n  ],\n\n  title: {\n    selectors: [\n      'h1.headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.post-content',\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'iframe.lazyload[data-recommend-id^=\"youtube://\"]': ($node) => {\n        const youtubeId = $node.attr('id').split('youtube-')[1];\n        $node.attr('src', `https://www.youtube.com/embed/${youtubeId}`);\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.magnifier',\n      '.lightbox',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time.updated[datetime]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  next_page_url: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  excerpt: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const BroadwayWorldExtractor = {\n  domain: 'www.broadwayworld.com',\n  title: {\n    selectors: [\n      'h1.article-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span[itemprop=author]',\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div[itemprop=articlebody]',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemprop=datePublished]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  excerpt: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n};\n","// Rename CustomExtractor\n// to fit your publication\n// (e.g., NYTimesExtractor)\nexport const ApartmentTherapyExtractor = {\n  domain: 'www.apartmenttherapy.com',\n  title: {\n    selectors: [\n      'h1.headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.PostByline__name',\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.post__content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div[data-render-react-id=\"images/LazyPicture\"]': ($node, $) => {\n        const data = JSON.parse($node.attr('data-props'));\n        const { src } = data.sources[0];\n        const $img = $('<img />').attr('src', src);\n        $node.replaceWith($img);\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.PostByline__timestamp[datetime]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  next_page_url: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  excerpt: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n};\n","export const MediumExtractor = {\n  domain: 'medium.com',\n\n  supportedDomains: [\n    'trackchanges.postlight.com',\n  ],\n\n  title: {\n    selectors: [\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.section-content'],\n      '.section-content',\n      'article > div > section',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      // Re-write lazy-loaded youtube videos\n      iframe: ($node) => {\n        const ytRe =\n          /https:\\/\\/i.embed.ly\\/.+url=https:\\/\\/i\\.ytimg\\.com\\/vi\\/(\\w+)\\//;\n        const thumb = decodeURIComponent($node.attr('data-thumbnail'));\n\n        if (ytRe.test(thumb)) {\n          const [_, youtubeId] = thumb.match(ytRe) // eslint-disable-line\n          $node.attr('src', `https://www.youtube.com/embed/${youtubeId}`);\n          const $parent = $node.parents('figure');\n          const $caption = $parent.find('figcaption');\n          $parent.empty().append([$node, $caption]);\n        }\n      },\n\n      // rewrite figures to pull out image and caption, remove rest\n      figure: ($node) => {\n        // ignore if figure has an iframe\n        if ($node.find('iframe').length > 0) return;\n\n        const $img = $node.find('img').slice(-1)[0];\n        const $caption = $node.find('figcaption');\n        $node.empty().append([$img, $caption]);\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time[datetime]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  next_page_url: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  excerpt: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n};\n","export const WwwTmzComExtractor = {\n  domain: 'www.tmz.com',\n\n  title: {\n    selectors: [\n      '.post-title-breadcrumb',\n      'h1',\n      '.headline',\n    ],\n  },\n\n  author: 'TMZ STAFF',\n\n  date_published: {\n    selectors: [\n      '.article-posted-date',\n    ],\n\n    timezone: 'America/Los_Angeles',\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-content',\n      '.all-post-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.lightbox-link',\n    ],\n  },\n};\n","export const WwwWashingtonpostComExtractor = {\n  domain: 'www.washingtonpost.com',\n\n  title: {\n    selectors: [\n      'h1',\n      '#topper-headline-wrapper',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.pb-byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.pb-timestamp[itemprop=\"datePublished\"]', 'content'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div.inline-content': ($node) => {\n        if ($node.has('img,iframe,video').length > 0) {\n          return 'figure';\n        }\n\n        $node.remove();\n        return null;\n      },\n      '.pb-caption': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.interstitial-link',\n      '.newsletter-inline-unit',\n    ],\n  },\n};\n","export const WwwHuffingtonpostComExtractor = {\n  domain: 'www.huffingtonpost.com',\n\n  title: {\n    selectors: [\n      'h1.headline__title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.author-card__details__name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:modified_time\"]', 'value'],\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'h2.headline__subtitle',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.entry__body',\n    ],\n\n    defaultCleaner: false,\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      // 'div.top-media': ($node) => {\n      //   const $figure = $node.children('figure');\n      //   $node.replaceWith($figure);\n      // },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.pull-quote',\n      '.tag-cloud',\n      '.embed-asset',\n      '.below-entry',\n      '.entry-corrections',\n      '#suggested-story',\n    ],\n  },\n};\n","export const NewrepublicComExtractor = {\n  domain: 'newrepublic.com',\n\n  title: {\n    selectors: [\n      'h1.article-headline',\n      '.minutes-primary h1.minute-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.author-list',\n      '.minutes-primary h3.minute-byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      'h2.article-subhead',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.article-cover', 'div.content-body'],\n      ['.minute-image', '.minutes-primary div.content-body'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      'aside',\n    ],\n  },\n};\n","export const MoneyCnnComExtractor = {\n  domain: 'money.cnn.com',\n\n  title: {\n    selectors: [\n      '.article-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.byline a',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"date\"]', 'value'],\n    ],\n\n    timezone: 'GMT',\n  },\n\n  dek: {\n    selectors: [\n      '#storytext h2',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '#storytext',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.inStoryHeading',\n    ],\n  },\n};\n","export const WwwThevergeComExtractor = {\n  domain: 'www.theverge.com',\n\n  supportedDomains: ['www.polygon.com'],\n\n  title: {\n    selectors: [\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'h2.p-dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      // feature template multi-match\n      ['.c-entry-hero .e-image', '.c-entry-intro', '.c-entry-content'],\n      // regular post multi-match\n      ['.e-image--hero', '.c-entry-content'],\n      // feature template fallback\n      '.l-wrapper .l-feature',\n      // regular post fallback\n      'div.c-entry-content',\n    ],\n\n    // Transform lazy-loaded images\n    transforms: {\n      noscript: ($node) => {\n        const $children = $node.children();\n        if ($children.length === 1 && $children.get(0).tagName === 'img') {\n          return 'span';\n        }\n\n        return null;\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.aside',\n      'img.c-dynamic-image', // images come from noscript transform\n    ],\n  },\n};\n","export const WwwCnnComExtractor = {\n  domain: 'www.cnn.com',\n\n  title: {\n    selectors: [\n      'h1.pg-headline',\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.metadata__byline__author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"pubdate\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      // a more specific selector to grab the lead image and the body\n      ['.media__video--thumbnail', '.zn-body-text'],\n      // a fallback for the above\n      '.zn-body-text',\n      'div[itemprop=\"articleBody\"]',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.zn-body__paragraph, .el__leafmedia--sourced-paragraph': ($node) => {\n        const $text = $node.html();\n        if ($text) {\n          return 'p';\n        }\n\n        return null;\n      },\n\n      // this transform cleans the short, all-link sections linking\n      // to related content but not marked as such in any way.\n      '.zn-body__paragraph': ($node) => {\n        if ($node.has('a')) {\n          if ($node.text().trim() === $node.find('a').text().trim()) {\n            $node.remove();\n          }\n        }\n      },\n\n      '.media__video--thumbnail': 'figure',\n\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n    ],\n  },\n};\n","export const WwwAolComExtractor = {\n  domain: 'www.aol.com',\n\n  title: {\n    selectors: [\n      'h1.p-article__title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.p-article__byline__date',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwYoutubeComExtractor = {\n  domain: 'www.youtube.com',\n\n  title: {\n    selectors: [\n      '.watch-title',\n      'h1.watch-title-container',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.yt-user-info',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemProp=\"datePublished\"]', 'value'],\n    ],\n\n    timezone: 'GMT',\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    defaultCleaner: false,\n\n    selectors: [\n      ['#player-api', '#eow-description'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '#player-api': ($node, $) => {\n        const videoId = $('meta[itemProp=\"videoId\"]').attr('value');\n        $node.html(`\n          <iframe src=\"https://www.youtube.com/embed/${videoId}\" frameborder=\"0\" allowfullscreen></iframe>`\n        );\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwTheguardianComExtractor = {\n  domain: 'www.theguardian.com',\n\n  title: {\n    selectors: [\n      '.content__headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'p.byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.content__standfirst',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.content__article-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.hide-on-mobile',\n      '.inline-icon',\n    ],\n  },\n};\n","export const WwwSbnationComExtractor = {\n  domain: 'www.sbnation.com',\n\n  title: {\n    selectors: [\n      'h1.c-page-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n       ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n       ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'h2.c-entry-summary.p-dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.c-entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwBloombergComExtractor = {\n  domain: 'www.bloomberg.com',\n\n  title: {\n    selectors: [\n      // normal articles\n      '.lede-headline',\n\n      // /graphics/ template\n      'h1.article-title',\n\n      // /news/ template\n      'h1.lede-text-only__hed',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"parsely-author\"]', 'value'],\n      '.byline-details__link',\n\n      // /graphics/ template\n      '.bydek',\n\n      // /news/ template\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time.published-at', 'datetime'],\n      ['time[datetime]', 'datetime'],\n      ['meta[name=\"date\"]', 'value'],\n      ['meta[name=\"parsely-pub-date\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-body__content',\n\n      // /graphics/ template\n      ['section.copy-block'],\n\n      // /news/ template\n      '.body-copy',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.inline-newsletter',\n      '.page-ad',\n    ],\n  },\n};\n","export const WwwBustleComExtractor = {\n  domain: 'www.bustle.com',\n\n  title: {\n    selectors: [\n      'h1.post-page__title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.content-meta__author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time.content-meta__published-date[datetime]', 'datetime'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.post-page__body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwNprOrgExtractor = {\n  domain: 'www.npr.org',\n\n  title: {\n    selectors: [\n      'h1',\n      '.storytitle',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'p.byline__name.byline__name--block',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.dateblock time[datetime]', 'datetime'],\n      ['meta[name=\"date\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n      ['meta[name=\"twitter:image:src\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.storytext',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.bucketwrap.image': 'figure',\n      '.bucketwrap.image .credit-caption': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      'div.enlarge_measure',\n    ],\n  },\n};\n","export const WwwRecodeNetExtractor = {\n  domain: 'www.recode.net',\n\n  title: {\n    selectors: [\n      'h1.c-page-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'h2.c-entry-summary.p-dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['figure.e-image--hero', '.c-entry-content'],\n      '.c-entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const QzComExtractor = {\n  domain: 'qz.com',\n\n  title: {\n    selectors: [\n      'header.item-header.content-width-responsive',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.timestamp',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['figure.featured-image', '.item-body'],\n      '.item-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.article-aside',\n      '.progressive-image-thumbnail',\n    ],\n  },\n};\n","export const WwwDmagazineComExtractor = {\n  domain: 'www.dmagazine.com',\n\n  title: {\n    selectors: [\n      'h1.story__title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.story__info .story__info__item:first-child',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      // enter selectors\n      '.story__info',\n    ],\n\n    timezone: 'America/Chicago',\n  },\n\n  dek: {\n    selectors: [\n      '.story__subhead',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['article figure a:first-child', 'href'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.story__content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwReutersComExtractor = {\n  domain: 'www.reuters.com',\n\n  title: {\n    selectors: [\n      'h1.article-headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"og:article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '#article-text',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.article-subtitle': 'h4',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '#article-byline .author',\n      // 'span.location',\n      // 'span.articleLocation',\n    ],\n  },\n};\n","export const MashableComExtractor = {\n  domain: 'mashable.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.author_name a',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"og:article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'section.article-content.blueprint',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.image-credit': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwChicagotribuneComExtractor = {\n  domain: 'www.chicagotribune.com',\n\n  title: {\n    selectors: [\n      'h1.trb_ar_hl_t',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.trb_ar_by_nm_au',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemprop=\"datePublished\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.trb_ar_page',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwVoxComExtractor = {\n  domain: 'www.vox.com',\n\n  title: {\n    selectors: [\n      'h1.c-page-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n        ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n        ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.p-dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['figure.e-image--hero', '.c-entry-content'],\n      '.c-entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'figure .e-image__image noscript': ($node) => {\n        const imgHtml = $node.html();\n        $node.parents('.e-image__image').find('.c-dynamic-image').replaceWith(imgHtml);\n      },\n\n      'figure .e-image__meta': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const NewsNationalgeographicComExtractor = {\n  domain: 'news.nationalgeographic.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.main-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.byline-component__contributors b span',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n       ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n    format: 'ddd MMM DD HH:mm:ss zz YYYY',\n    timezone: 'EST',\n  },\n\n  dek: {\n    selectors: [\n      '.article__deck',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.parsys.content', '.__image-lead__'],\n      '.content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.parsys.content': ($node, $) => {\n        const $imgSrc = $node.find('.image.parbase.section')\n            .find('.picturefill')\n            .first()\n            .data('platform-src');\n        if ($imgSrc) {\n          $node.prepend($(`<img class=\"__image-lead__\" src=\"${$imgSrc}\"/>`));\n        }\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.pull-quote.pull-quote--large',\n    ],\n  },\n};\n","export const WwwNationalgeographicComExtractor = {\n  domain: 'www.nationalgeographic.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.main-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.byline-component__contributors b span',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.article__deck',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.parsys.content', '.__image-lead__'],\n      '.content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.parsys.content': ($node, $) => {\n        const $imageParent = $node.children().first();\n        if ($imageParent.hasClass('imageGroup')) {\n          const $dataAttrContainer = $imageParent.find('.media--medium__container').children().first();\n          const imgPath1 = $dataAttrContainer.data('platform-image1-path');\n          const imgPath2 = $dataAttrContainer.data('platform-image2-path');\n          if (imgPath2 && imgPath1) {\n            $node.prepend($(`<div class=\"__image-lead__\">\n                <img src=\"${imgPath1}\"/>\n                <img src=\"${imgPath2}\"/>\n              </div>`));\n          }\n        } else {\n          const $imgSrc = $node.find('.image.parbase.section')\n            .find('.picturefill')\n            .first()\n            .data('platform-src');\n          if ($imgSrc) {\n            $node.prepend($(`<img class=\"__image-lead__\" src=\"${$imgSrc}\"/>`));\n          }\n        }\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.pull-quote.pull-quote--small',\n    ],\n  },\n};\n","export const WwwLatimesComExtractor = {\n  domain: 'www.latimes.com',\n\n  title: {\n    selectors: [\n      '.trb_ar_hl',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemprop=\"datePublished\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.trb_ar_main',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.trb_ar_la': ($node) => {\n        const $figure = $node.find('figure');\n        $node.replaceWith($figure);\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.trb_ar_by',\n      '.trb_ar_cr',\n    ],\n  },\n};\n","export const PagesixComExtractor = {\n  domain: 'pagesix.com',\n\n  supportedDomains: [\n    'nypost.com',\n  ],\n\n  title: {\n    selectors: [\n      'h1 a',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      ['meta[name=\"description\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['#featured-image-wrapper', '.entry-content'],\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '#featured-image-wrapper': 'figure',\n      '.wp-caption-text': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.modal-trigger',\n    ],\n  },\n};\n","export const ThefederalistpapersOrgExtractor = {\n  domain: 'thefederalistpapers.org',\n\n  title: {\n    selectors: [\n      'h1.entry-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'main span.entry-author-name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      ['p[style]'],\n    ],\n  },\n};\n","export const WwwCbssportsComExtractor = {\n  domain: 'www.cbssports.com',\n\n  title: {\n    selectors: [\n      '.article-headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author-name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.date-original-reading-time time', 'datetime'],\n    ],\n    timezone: 'UTC',\n  },\n\n  dek: {\n    selectors: [\n      '.article-subline',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwMsnbcComExtractor = {\n  domain: 'www.msnbc.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.is-title-pane',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"DC.date.issued\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      ['meta[name=\"description\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.pane-node-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.pane-node-body': ($node, $) => {\n        const [selector, attr] = WwwMsnbcComExtractor.lead_image_url.selectors[0];\n        const src = $(selector).attr(attr);\n        if (src) {\n          $node.prepend(`<img src=\"${src}\" />`);\n        }\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwThepoliticalinsiderComExtractor = {\n  domain: 'www.thepoliticalinsider.com',\n\n  title: {\n    selectors: [\n       ['meta[name=\"sailthru.title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"sailthru.author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"sailthru.date\"]', 'value'],\n    ],\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],  // enter selectors\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div#article-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwMentalflossComExtractor = {\n  domain: 'www.mentalfloss.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n      '.title-group',\n      '.inner',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.field-name-field-enhanced-authors',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.date-display-single',\n    ],\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.field.field-name-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const AbcnewsGoComExtractor = {\n  domain: 'abcnews.go.com',\n\n  title: {\n    selectors: [\n      '.article-header h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.authors',\n    ],\n    clean: [\n      '.author-overlay',\n      '.by-text',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.timestamp',\n    ],\n    timezone: 'America/New_York',\n\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-copy',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwNydailynewsComExtractor = {\n  domain: 'www.nydailynews.com',\n\n  title: {\n    selectors: [\n      'h1#ra-headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"parsely-author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"sailthru.date\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'article#ra-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      'dl#ra-tags',\n      '.ra-related',\n      'a.ra-editor',\n      'dl#ra-share-bottom',\n    ],\n  },\n};\n","export const WwwCnbcComExtractor = {\n  domain: 'www.cnbc.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div#article_body.content',\n      'div.story',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwPopsugarComExtractor = {\n  domain: 'www.popsugar.com',\n\n  title: {\n    selectors: [\n      'h2.post-title',\n      'title-text',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"article:author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n        ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '#content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.share-copy-title',\n      '.post-tags',\n      '.reactions',\n    ],\n  },\n};\n","export const ObserverComExtractor = {\n  domain: 'observer.com',\n\n  title: {\n    selectors: [\n      'h1.entry-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n      '.vcard',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'h2.dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const PeopleComExtractor = {\n  domain: 'people.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"og:title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a.author.url.fn',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n       ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.article-body__inner',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwUsmagazineComExtractor = {\n  domain: 'www.usmagazine.com',\n\n  title: {\n    selectors: [\n      'header h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a.article-byline.tracked-offpage',\n    ],\n  },\n\n  date_published: {\n    timezone: 'America/New_York',\n\n    selectors: [\n      'time.article-published-date',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.article-body-inner',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.module-related',\n    ],\n  },\n};\n","export const WwwRollingstoneComExtractor = {\n  domain: 'www.rollingstone.com',\n\n  title: {\n    selectors: [\n      'h1.content-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a.content-author.tracked-offpage',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'time.content-published-date',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      '.content-description',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.lead-container', '.article-content'],\n      '.article-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.module-related',\n    ],\n  },\n};\n","export const twofortysevensportsComExtractor = {\n  domain: '247sports.com',\n\n  title: {\n    selectors: [\n      'title',\n      'article header h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time[data-published]', 'data-published'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'section.body.article',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const UproxxComExtractor = {\n  domain: 'uproxx.com',\n\n  title: {\n    selectors: [\n      'div.post-top h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.post-top .authorname',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n       ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.post-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div.image': 'figure',\n      'div.image .wp-media-credit': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwEonlineComExtractor = {\n  domain: 'www.eonline.com',\n\n  title: {\n    selectors: [\n      'h1.article__title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.entry-meta__author a',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[itemprop=\"datePublished\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.post-content section, .post-content div.post-content__image'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div.post-content__image': 'figure',\n      'div.post-content__image .image__credits': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwMiamiheraldComExtractor = {\n  domain: 'www.miamiherald.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'p.published-date',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.dateline-storybody',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwRefinery29ComExtractor = {\n  domain: 'www.refinery29.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.contributor',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"sailthru.date\"]', 'value'],\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.full-width-opener', '.article-content'],\n      '.article-content',\n      '.body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div.loading noscript': ($node) => {\n        const imgHtml = $node.html();\n        $node.parents('.loading').replaceWith(imgHtml);\n      },\n\n      '.section-image': 'figure',\n\n      '.section-image .content-caption': 'figcaption',\n\n      '.section-text': 'p',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.story-share',\n    ],\n  },\n};\n","export const WwwMacrumorsComExtractor = {\n  domain: 'www.macrumors.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author-url',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.article .byline',\n    ],\n\n    // Wednesday January 18, 2017 11:44 am PST\n    format: 'dddd MMMM D, YYYY h:mm A zz',\n\n    timezone: 'America/Los_Angeles',\n  },\n\n  dek: {\n    selectors: [\n      ['meta[name=\"description\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwAndroidcentralComExtractor = {\n  domain: 'www.androidcentral.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.main-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.meta-by',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      ['meta[name=\"og:description\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['.image-large', 'src'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.intro',\n      'blockquote',\n    ],\n  },\n};\n","export const WwwSiComExtractor = {\n  domain: 'www.si.com',\n\n  title: {\n    selectors: [\n      'h1',\n      'h1.headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.timestamp',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      '.quick-hit ul',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['p', '.marquee_large_2x', '.component.image'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n\n      noscript: ($node) => {\n        const $children = $node.children();\n        if ($children.length === 1 && $children.get(0).tagName === 'img') {\n          return 'figure';\n        }\n\n        return null;\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      [\n        '.inline-thumb',\n        '.primary-message',\n        '.description',\n        '.instructions',\n      ],\n    ],\n  },\n};\n","export const WwwRawstoryComExtractor = {\n  domain: 'www.rawstory.com',\n\n  title: {\n    selectors: [\n      '.blog-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.blog-author a:first-of-type',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.blog-author a:last-of-type',\n    ],\n\n    timezone: 'EST',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.blog-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwCnetComExtractor = {\n  domain: 'www.cnet.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"og:title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'time',\n    ],\n\n    timezone: 'America/Los_Angeles',\n  },\n\n  dek: {\n    selectors: [\n      '.article-dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['img.__image-lead__', '.article-main-body'],\n      '.article-main-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'figure.image': ($node) => {\n        const $img = $node.find('img');\n        $img.attr('width', '100%');\n        $img.attr('height', '100%');\n        $img.addClass('__image-lead__');\n        $node.remove('.imgContainer').prepend($img);\n      },\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwCinemablendComExtractor = {\n  domain: 'www.cinemablend.com',\n\n  title: {\n    selectors: [\n      '.story_title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n\n    timezone: 'EST',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div#wrap_left_content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwTodayComExtractor = {\n  domain: 'www.today.com',\n\n  title: {\n    selectors: [\n      'h1.entry-headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"DC.date.issued\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-container',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.label-comment',\n    ],\n  },\n};\n","export const WwwHowtogeekComExtractor = {\n  domain: 'www.howtogeek.com',\n\n  title: {\n    selectors: [\n      'title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '#authorinfobox a',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '#authorinfobox + div li',\n    ],\n    timezone: 'GMT',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.thecontent',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwAlComExtractor = {\n  domain: 'www.al.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"article_author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article_date_original\"]', 'value'],\n    ],\n    timezone: 'EST',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwThepennyhoarderComExtractor = {\n  domain: 'www.thepennyhoarder.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"dcterms.title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['link[rel=\"author\"]', 'title'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.post-img', '.post-text'],\n      '.post-text',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwWesternjournalismComExtractor = {\n  domain: 'www.westernjournalism.com',\n\n  title: {\n    selectors: [\n      'title',\n      'h1.entry-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"DC.date.issued\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.subtitle',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.article-sharing.top + div',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.ad-notice-small',\n    ],\n  },\n};\n","export const FusionNetExtractor = {\n  domain: 'fusion.net',\n\n  title: {\n    selectors: [\n      '.post-title',\n      '.single-title',\n      '.headline',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.show-for-medium .byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n        ['time.local-time', 'datetime'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.post-featured-media', '.article-content'],\n      '.article-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.fusion-youtube-oembed': 'figure',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwAmericanowComExtractor = {\n  domain: 'www.americanow.com',\n\n  title: {\n    selectors: [\n      '.title',\n      ['meta[name=\"title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.byline',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"publish_date\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.article-content', '.image', '.body'],\n      '.body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.article-video-wrapper',\n      '.show-for-small-only',\n    ],\n  },\n};\n","export const ScienceflyComExtractor = {\n  domain: 'sciencefly.com',\n\n  title: {\n    selectors: [\n      '.entry-title',\n      '.cb-entry-title',\n      '.cb-single-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.cb-author',\n      'div.cb-author-title',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['div.theiaPostSlider_slides img', 'src'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.theiaPostSlider_slides',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const HellogigglesComExtractor = {\n  domain: 'hellogiggles.com',\n\n  title: {\n    selectors: [\n      '.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author-link',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const ThoughtcatalogComExtractor = {\n  domain: 'thoughtcatalog.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n      ['meta[name=\"og:title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.col-xs-12.article_header div.writer-container.writer-container-inline.writer-no-avatar h4.writer-name',\n      'h1.writer-name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry.post',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.tc_mark',\n    ],\n  },\n};\n","export const WwwNjComExtractor = {\n  domain: 'www.nj.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"article_author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article_date_original\"]', 'value'],\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwInquisitrComExtractor = {\n  domain: 'www.inquisitr.com',\n\n  title: {\n    selectors: [\n      'h1.entry-title.story--header--title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.story--header--author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"datePublished\"]', 'value'],\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'article.story',\n      '.entry-content.',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.post-category',\n      '.story--header--socials',\n      '.story--header--content',\n    ],\n  },\n};\n","export const WwwNbcnewsComExtractor = {\n  domain: 'www.nbcnews.com',\n\n  title: {\n    selectors: [\n      'div.article-hed h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'span.byline_author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.flag_article-wrapper time.timestamp_article[datetime]', 'datetime'],\n      '.flag_article-wrapper time',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      'div.article-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const FortuneComExtractor = {\n  domain: 'fortune.com',\n\n  title: {\n    selectors: [\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.MblGHNMJ',\n    ],\n\n    timezone: 'UTC',\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['picture', 'article.row'],\n      'article.row',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const WwwLinkedinComExtractor = {\n  domain: 'www.linkedin.com',\n\n  title: {\n    selectors: [\n      '.article-title',\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"article:author\"]', 'value'],\n      '.entity-name a[rel=author]',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['time[itemprop=\"datePublished\"]', 'datetime'],\n    ],\n\n    timezone: 'America/Los_Angeles',\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['header figure', '.prose'],\n      '.prose',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.entity-image',\n    ],\n  },\n};\n","export const ObamawhitehouseArchivesGovExtractor = {\n  domain: 'obamawhitehouse.archives.gov',\n\n  supportedDomains: [\n    'whitehouse.gov',\n  ],\n\n  title: {\n    selectors: [\n      'h1',\n      '.pane-node-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.blog-author-link',\n      '.node-person-name-link',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"article:published_time\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.field-name-field-forall-summary',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    defaultCleaner: false,\n\n    selectors: [\n      'div#content-start',\n      '.pane-node-field-forall-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.pane-node-title',\n      '.pane-custom.pane-1',\n    ],\n  },\n};\n","export const WwwOpposingviewsComExtractor = {\n  domain: 'www.opposingviews.com',\n\n  title: {\n    selectors: [\n      'h1.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'div.date span span a',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"publish_date\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.show-for-small-only',\n    ],\n  },\n};\n","export const WwwProspectmagazineCoUkExtractor = {\n  domain: 'www.prospectmagazine.co.uk',\n\n  title: {\n    selectors: [\n      '.page-title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.aside_author .title',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.post-info',\n    ],\n\n    timezone: 'Europe/London',\n  },\n\n  dek: {\n    selectors: [\n      '.page-subtitle',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      // ['article.type-post div.post_content p'],\n      'article .post_content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","export const ForwardComExtractor = {\n  domain: 'forward.com',\n\n  title: {\n    selectors: [\n      ['meta[name=\"og:title\"]', 'value'],\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author-name',\n      ['meta[name=\"sailthru.author\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"date\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      // enter selectors\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.post-item-media-wrap', '.post-item p'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.donate-box',\n      '.message',\n      '.subtitle',\n    ],\n  },\n};\n","export const WwwQdailyComExtractor = {\n  domain: 'www.qdaily.com',\n\n  title: {\n    selectors: [\n      'h2',\n      'h2.title',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['.date.smart-date', 'data-origindate'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      '.excerpt',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['.article-detail-hd img', 'src'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.detail',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.lazyload',\n      '.lazylad',\n      '.lazylood',\n    ],\n  },\n};\n","export const GothamistComExtractor = {\n  domain: 'gothamist.com',\n\n  supportedDomains: [\n    'chicagoist.com',\n    'laist.com',\n    'sfist.com',\n    'shanghaiist.com',\n    'dcist.com',\n  ],\n\n  title: {\n    selectors: [\n      'h1',\n      '.entry-header h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      'abbr',\n      'abbr.published',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      null,\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.entry-body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      'div.image-none': 'figure',\n      '.image-none i': 'figcaption',\n      'div.image-left': 'figure',\n      '.image-left i': 'figcaption',\n      'div.image-right': 'figure',\n      '.image-right i': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.image-none br',\n      '.image-left br',\n      '.image-right br',\n      '.galleryEase',\n    ],\n  },\n};\n","export const WwwFoolComExtractor = {\n  domain: 'www.fool.com',\n\n  title: {\n    selectors: [\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      '.author-inline .author-name',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"date\"]', 'value'],\n    ],\n  },\n\n  dek: {\n    selectors: [\n      'header h2',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.article-content',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n      '.caption img': ($node) => {\n        const src = $node.attr('src');\n        $node.parent().replaceWith(`<figure><img src=\"${src}\"/></figure>`);\n      },\n      '.caption': 'figcaption',\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '#pitch',\n    ],\n  },\n};\n","export const WwwSlateComExtractor = {\n  domain: 'www.slate.com',\n\n  title: {\n    selectors: [\n      '.hed',\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      'a[rel=author]',\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      '.pub-date',\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      '.dek',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      '.body',\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n      '.about-the-author',\n      '.pullquote',\n      '.newsletter-signup-component',\n      '.top-comment',\n    ],\n  },\n};\n","export const IciRadioCanadaCaExtractor = {\n  domain: 'ici.radio-canada.ca',\n\n  title: {\n    selectors: [\n      'h1',\n    ],\n  },\n\n  author: {\n    selectors: [\n      ['meta[name=\"dc.creator\"]', 'value'],\n    ],\n  },\n\n  date_published: {\n    selectors: [\n      ['meta[name=\"dc.date.created\"]', 'value'],\n    ],\n\n    timezone: 'America/New_York',\n  },\n\n  dek: {\n    selectors: [\n      '.bunker-component.lead',\n    ],\n  },\n\n  lead_image_url: {\n    selectors: [\n      ['meta[name=\"og:image\"]', 'value'],\n    ],\n  },\n\n  content: {\n    selectors: [\n      ['.main-multimedia-item', '.news-story-content'],\n    ],\n\n    // Is there anything in the content you selected that needs transformed\n    // before it's consumable content? E.g., unusual lazy loaded images\n    transforms: {\n    },\n\n    // Is there anything that is in the result that shouldn't be?\n    // The clean selectors will remove anything that matches from\n    // the result\n    clean: [\n\n    ],\n  },\n};\n","import mergeSupportedDomains from 'utils/merge-supported-domains';\nimport * as CustomExtractors from './custom/index';\n\nexport default Object.keys(CustomExtractors).reduce((acc, key) => {\n  const extractor = CustomExtractors[key];\n  return {\n    ...acc,\n    ...mergeSupportedDomains(extractor),\n  };\n}, {});\n","// CLEAN AUTHOR CONSTANTS\nexport const CLEAN_AUTHOR_RE = /^\\s*(posted |written )?by\\s*:?\\s*(.*)/i;\n    //     author = re.sub(r'^\\s*(posted |written )?by\\s*:?\\s*(.*)(?i)',\n\n// CLEAN DEK CONSTANTS\nexport const TEXT_LINK_RE = new RegExp('http(s)?://', 'i');\n// An ordered list of meta tag names that denote likely article deks.\n// From most distinct to least distinct.\n//\n// NOTE: There are currently no meta tags that seem to provide the right\n// content consistenty enough. Two options were:\n//  - og:description\n//  - dc.description\n// However, these tags often have SEO-specific junk in them that's not\n// header-worthy like a dek is. Excerpt material at best.\nexport const DEK_META_TAGS = [\n];\n\n// An ordered list of Selectors to find likely article deks. From\n// most explicit to least explicit.\n//\n// Should be more restrictive than not, as a failed dek can be pretty\n// detrimental to the aesthetics of an article.\nexport const DEK_SELECTORS = [\n  '.entry-summary',\n];\n\n// CLEAN DATE PUBLISHED CONSTANTS\nexport const MS_DATE_STRING = /^\\d{13}$/i;\nexport const SEC_DATE_STRING = /^\\d{10}$/i;\nexport const CLEAN_DATE_STRING_RE = /^\\s*published\\s*:?\\s*(.*)/i;\nexport const TIME_MERIDIAN_SPACE_RE = /(.*\\d)(am|pm)(.*)/i;\nexport const TIME_MERIDIAN_DOTS_RE = /\\.m\\./i;\nconst months = [\n  'jan',\n  'feb',\n  'mar',\n  'apr',\n  'may',\n  'jun',\n  'jul',\n  'aug',\n  'sep',\n  'oct',\n  'nov',\n  'dec',\n];\nconst allMonths = months.join('|');\nconst timestamp1 = '[0-9]{1,2}:[0-9]{2,2}( ?[ap].?m.?)?';\nconst timestamp2 = '[0-9]{1,2}[/-][0-9]{1,2}[/-][0-9]{2,4}';\nconst timestamp3 = '-[0-9]{3,4}$';\nexport const SPLIT_DATE_STRING =\n  new RegExp(`(${timestamp1})|(${timestamp2})|(${timestamp3})|([0-9]{1,4})|(${allMonths})`, 'ig');\n\n// 2016-11-22T08:57-500\n// Check if datetime string has an offset at the end\nexport const TIME_WITH_OFFSET_RE = /-\\d{3,4}$/;\n\n// CLEAN TITLE CONSTANTS\n// A regular expression that will match separating characters on a\n// title, that usually denote breadcrumbs or something similar.\nexport const TITLE_SPLITTERS_RE = /(: | - | \\| )/g;\n\nexport const DOMAIN_ENDINGS_RE =\n  new RegExp('.com$|.net$|.org$|.co.uk$', 'g');\n","import { normalizeSpaces } from 'utils/text';\nimport { CLEAN_AUTHOR_RE } from './constants';\n\n// Take an author string (like 'By David Smith ') and clean it to\n// just the name(s): 'David Smith'.\nexport default function cleanAuthor(author) {\n  return normalizeSpaces(\n    author.replace(CLEAN_AUTHOR_RE, '$2').trim()\n  );\n}\n","import validUrl from 'valid-url';\n\nexport default function clean(leadImageUrl) {\n  leadImageUrl = leadImageUrl.trim();\n  if (validUrl.isWebUri(leadImageUrl)) {\n    return leadImageUrl;\n  }\n\n  return null;\n}\n","import { stripTags } from 'utils/dom';\nimport {\n  excerptContent,\n  normalizeSpaces,\n} from 'utils/text';\n\nimport { TEXT_LINK_RE } from './constants';\n\n// Take a dek HTML fragment, and return the cleaned version of it.\n// Return None if the dek wasn't good enough.\nexport default function cleanDek(dek, { $, excerpt }) {\n  // Sanity check that we didn't get too short or long of a dek.\n  if (dek.length > 1000 || dek.length < 5) return null;\n\n  // Check that dek isn't the same as excerpt\n  if (excerpt && excerptContent(excerpt, 10) === excerptContent(dek, 10)) return null;\n\n  const dekText = stripTags(dek, $);\n\n  // Plain text links shouldn't exist in the dek. If we have some, it's\n  // not a good dek - bail.\n  if (TEXT_LINK_RE.test(dekText)) return null;\n\n  return normalizeSpaces(dekText.trim());\n}\n","import moment from 'moment-timezone';\nimport parseFormat from 'moment-parseformat';\n// Is there a compelling reason to use moment here?\n// Mostly only being used for the isValid() method,\n// but could just check for 'Invalid Date' string.\n\nimport {\n  MS_DATE_STRING,\n  SEC_DATE_STRING,\n  CLEAN_DATE_STRING_RE,\n  SPLIT_DATE_STRING,\n  TIME_MERIDIAN_SPACE_RE,\n  TIME_MERIDIAN_DOTS_RE,\n  TIME_WITH_OFFSET_RE,\n} from './constants';\n\nexport function cleanDateString(dateString) {\n  return (dateString.match(SPLIT_DATE_STRING) || [])\n                   .join(' ')\n                   .replace(TIME_MERIDIAN_DOTS_RE, 'm')\n                   .replace(TIME_MERIDIAN_SPACE_RE, '$1 $2 $3')\n                   .replace(CLEAN_DATE_STRING_RE, '$1')\n                   .trim();\n}\n\nexport function createDate(dateString, timezone, format) {\n  if (TIME_WITH_OFFSET_RE.test(dateString)) {\n    return moment(new Date(dateString));\n  }\n\n  return timezone ?\n    moment.tz(dateString, format || parseFormat(dateString), timezone) :\n    moment(dateString, format || parseFormat(dateString));\n}\n\n// Take a date published string, and hopefully return a date out of\n// it. Return none if we fail.\nexport default function cleanDatePublished(dateString, { timezone, format } = {}) {\n  // If string is in milliseconds or seconds, convert to int and return\n  if (MS_DATE_STRING.test(dateString) || SEC_DATE_STRING.test(dateString)) {\n    return new Date(parseInt(dateString, 10)).toISOString();\n  }\n\n  let date = createDate(dateString, timezone, format);\n\n  if (!date.isValid()) {\n    dateString = cleanDateString(dateString);\n    date = createDate(dateString, timezone, format);\n  }\n\n  return date.isValid() ? date.toISOString() : null;\n}\n","import {\n  cleanAttributes,\n  cleanHeaders,\n  cleanHOnes,\n  cleanImages,\n  cleanTags,\n  removeEmpty,\n  rewriteTopLevel,\n  markToKeep,\n  stripJunkTags,\n  makeLinksAbsolute,\n} from 'utils/dom';\n\n// Clean our article content, returning a new, cleaned node.\nexport default function extractCleanNode(\n  article,\n  {\n    $,\n    cleanConditionally = true,\n    title = '',\n    url = '',\n    defaultCleaner = true,\n  }\n) {\n  // Rewrite the tag name to div if it's a top level node like body or\n  // html to avoid later complications with multiple body tags.\n  rewriteTopLevel(article, $);\n\n  // Drop small images and spacer images\n  // Only do this is defaultCleaner is set to true;\n  // this can sometimes be too aggressive.\n  if (defaultCleaner) cleanImages(article, $);\n\n  // Make links absolute\n  makeLinksAbsolute(article, $, url);\n\n  // Mark elements to keep that would normally be removed.\n  // E.g., stripJunkTags will remove iframes, so we're going to mark\n  // YouTube/Vimeo videos as elements we want to keep.\n  markToKeep(article, $, url);\n\n  // Drop certain tags like <title>, etc\n  // This is -mostly- for cleanliness, not security.\n  stripJunkTags(article, $);\n\n  // H1 tags are typically the article title, which should be extracted\n  // by the title extractor instead. If there's less than 3 of them (<3),\n  // strip them. Otherwise, turn 'em into H2s.\n  cleanHOnes(article, $);\n\n  // Clean headers\n  cleanHeaders(article, $, title);\n\n  // We used to clean UL's and OL's here, but it was leading to\n  // too many in-article lists being removed. Consider a better\n  // way to detect menus particularly and remove them.\n  // Also optionally running, since it can be overly aggressive.\n  if (defaultCleaner) cleanTags(article, $, cleanConditionally);\n\n  // Remove empty paragraph nodes\n  removeEmpty(article, $);\n\n  // Remove unnecessary attributes\n  cleanAttributes(article, $);\n\n  return article;\n}\n","import { stripTags } from 'utils/dom';\nimport { normalizeSpaces } from 'utils/text';\n\nimport { TITLE_SPLITTERS_RE } from './constants';\nimport { resolveSplitTitle } from './index';\n\nexport default function cleanTitle(title, { url, $ }) {\n  // If title has |, :, or - in it, see if\n  // we can clean it up.\n  if (TITLE_SPLITTERS_RE.test(title)) {\n    title = resolveSplitTitle(title, url);\n  }\n\n  // Final sanity check that we didn't get a crazy title.\n  // if (title.length > 150 || title.length < 15) {\n  if (title.length > 150) {\n    // If we did, return h1 from the document if it exists\n    const h1 = $('h1');\n    if (h1.length === 1) {\n      title = h1.text();\n    }\n  }\n\n  // strip any html tags in the title text\n  return normalizeSpaces(stripTags(title, $).trim());\n}\n","import URL from 'url';\nimport wuzzy from 'wuzzy';\n\nimport {\n  TITLE_SPLITTERS_RE,\n  DOMAIN_ENDINGS_RE,\n} from './constants';\n\nfunction extractBreadcrumbTitle(splitTitle, text) {\n  // This must be a very breadcrumbed title, like:\n  // The Best Gadgets on Earth : Bits : Blogs : NYTimes.com\n  // NYTimes - Blogs - Bits - The Best Gadgets on Earth\n  if (splitTitle.length >= 6) {\n    // Look to see if we can find a breadcrumb splitter that happens\n    // more than once. If we can, we'll be able to better pull out\n    // the title.\n    const termCounts = splitTitle.reduce((acc, titleText) => {\n      acc[titleText] = acc[titleText] ? acc[titleText] + 1 : 1;\n      return acc;\n    }, {});\n\n    const [maxTerm, termCount] =\n      Reflect.ownKeys(termCounts)\n             .reduce((acc, key) => {\n               if (acc[1] < termCounts[key]) {\n                 return [key, termCounts[key]];\n               }\n\n               return acc;\n             }, [0, 0]);\n\n    // We found a splitter that was used more than once, so it\n    // is probably the breadcrumber. Split our title on that instead.\n    // Note: max_term should be <= 4 characters, so that \" >> \"\n    // will match, but nothing longer than that.\n    if (termCount >= 2 && maxTerm.length <= 4) {\n      splitTitle = text.split(maxTerm);\n    }\n\n    const splitEnds = [splitTitle[0], splitTitle.slice(-1)];\n    const longestEnd = splitEnds.reduce((acc, end) => acc.length > end.length ? acc : end, '');\n\n    if (longestEnd.length > 10) {\n      return longestEnd;\n    }\n\n    return text;\n  }\n\n  return null;\n}\n\nfunction cleanDomainFromTitle(splitTitle, url) {\n  // Search the ends of the title, looking for bits that fuzzy match\n  // the URL too closely. If one is found, discard it and return the\n  // rest.\n  //\n  // Strip out the big TLDs - it just makes the matching a bit more\n  // accurate. Not the end of the world if it doesn't strip right.\n  const { host } = URL.parse(url);\n  const nakedDomain = host.replace(DOMAIN_ENDINGS_RE, '');\n\n  const startSlug = splitTitle[0].toLowerCase().replace(' ', '');\n  const startSlugRatio = wuzzy.levenshtein(startSlug, nakedDomain);\n\n  if (startSlugRatio > 0.4 && startSlug.length > 5) {\n    return splitTitle.slice(2).join('');\n  }\n\n  const endSlug = splitTitle.slice(-1)[0].toLowerCase().replace(' ', '');\n  const endSlugRatio = wuzzy.levenshtein(endSlug, nakedDomain);\n\n  if (endSlugRatio > 0.4 && endSlug.length >= 5) {\n    return splitTitle.slice(0, -2).join('');\n  }\n\n  return null;\n}\n\n// Given a title with separators in it (colons, dashes, etc),\n// resolve whether any of the segments should be removed.\nexport default function resolveSplitTitle(title, url = '') {\n  // Splits while preserving splitters, like:\n  // ['The New New York', ' - ', 'The Washington Post']\n  const splitTitle = title.split(TITLE_SPLITTERS_RE);\n  if (splitTitle.length === 1) {\n    return title;\n  }\n\n  let newTitle = extractBreadcrumbTitle(splitTitle, title);\n  if (newTitle) return newTitle;\n\n  newTitle = cleanDomainFromTitle(splitTitle, url);\n  if (newTitle) return newTitle;\n\n  // Fuzzy ratio didn't find anything, so this title is probably legit.\n  // Just return it all.\n  return title;\n}\n","import cleanAuthor from './author';\nimport cleanImage from './lead-image-url';\nimport cleanDek from './dek';\nimport cleanDatePublished from './date-published';\nimport cleanContent from './content';\nimport cleanTitle from './title';\n\nconst Cleaners = {\n  author: cleanAuthor,\n  lead_image_url: cleanImage,\n  dek: cleanDek,\n  date_published: cleanDatePublished,\n  content: cleanContent,\n  title: cleanTitle,\n};\n\nexport default Cleaners;\n\nexport { cleanAuthor };\nexport { cleanImage };\nexport { cleanDek };\nexport { cleanDatePublished };\nexport { cleanContent };\nexport { cleanTitle };\nexport { default as resolveSplitTitle } from './resolve-split-title';\n","import {\n  stripUnlikelyCandidates,\n  convertToParagraphs,\n} from 'utils/dom';\n\nimport {\n  scoreContent,\n  findTopCandidate,\n} from './scoring';\n\n// Using a variety of scoring techniques, extract the content most\n// likely to be article text.\n//\n// If strip_unlikely_candidates is True, remove any elements that\n// match certain criteria first. (Like, does this element have a\n// classname of \"comment\")\n//\n// If weight_nodes is True, use classNames and IDs to determine the\n// worthiness of nodes.\n//\n// Returns a cheerio object $\nexport default function extractBestNode($, opts) {\n  // clone the node so we can get back to our\n  // initial parsed state if needed\n  // TODO Do I need this? – AP\n  // let $root = $.root().clone()\n\n  if (opts.stripUnlikelyCandidates) {\n    $ = stripUnlikelyCandidates($);\n  }\n\n  $ = convertToParagraphs($);\n  $ = scoreContent($, opts.weightNodes);\n  const $topCandidate = findTopCandidate($);\n\n  return $topCandidate;\n}\n","import cheerio from 'cheerio';\n\nimport { nodeIsSufficient } from 'utils/dom';\nimport { cleanContent } from 'cleaners';\nimport { normalizeSpaces } from 'utils/text';\n\nimport extractBestNode from './extract-best-node';\n\nconst GenericContentExtractor = {\n  defaultOpts: {\n    stripUnlikelyCandidates: true,\n    weightNodes: true,\n    cleanConditionally: true,\n  },\n\n  // Extract the content for this resource - initially, pass in our\n  // most restrictive opts which will return the highest quality\n  // content. On each failure, retry with slightly more lax opts.\n  //\n  // :param return_type: string. If \"node\", should return the content\n  // as a cheerio node rather than as an HTML string.\n  //\n  // Opts:\n  // stripUnlikelyCandidates: Remove any elements that match\n  // non-article-like criteria first.(Like, does this element\n  //   have a classname of \"comment\")\n  //\n  // weightNodes: Modify an elements score based on whether it has\n  // certain classNames or IDs. Examples: Subtract if a node has\n  // a className of 'comment', Add if a node has an ID of\n  // 'entry-content'.\n  //\n  // cleanConditionally: Clean the node to return of some\n  // superfluous content. Things like forms, ads, etc.\n  extract({ $, html, title, url }, opts) {\n    opts = { ...this.defaultOpts, ...opts };\n\n    $ = $ || cheerio.load(html);\n\n    // Cascade through our extraction-specific opts in an ordered fashion,\n    // turning them off as we try to extract content.\n    let node = this.getContentNode($, title, url, opts);\n\n    if (nodeIsSufficient(node)) {\n      return this.cleanAndReturnNode(node, $);\n    }\n\n    // We didn't succeed on first pass, one by one disable our\n    // extraction opts and try again.\n    for (const key of Reflect.ownKeys(opts).filter(k => opts[k] === true)) {\n      opts[key] = false;\n      $ = cheerio.load(html);\n\n      node = this.getContentNode($, title, url, opts);\n\n      if (nodeIsSufficient(node)) {\n        break;\n      }\n    }\n\n    return this.cleanAndReturnNode(node, $);\n  },\n\n  // Get node given current options\n  getContentNode($, title, url, opts) {\n    return cleanContent(\n              extractBestNode($, opts),\n      {\n        $,\n        cleanConditionally: opts.cleanConditionally,\n        title,\n        url,\n      });\n  },\n\n  // Once we got here, either we're at our last-resort node, or\n  // we broke early. Make sure we at least have -something- before we\n  // move forward.\n  cleanAndReturnNode(node, $) {\n    if (!node) {\n      return null;\n    }\n\n    return normalizeSpaces($.html(node));\n\n    // if return_type == \"html\":\n    //     return normalize_spaces(node_to_html(node))\n    // else:\n    //     return node\n  },\n\n};\n\nexport default GenericContentExtractor;\n","// TODO: It would be great if we could merge the meta and selector lists into\n// a list of objects, because we could then rank them better. For example,\n// .hentry .entry-title is far better suited than <meta title>.\n\n// An ordered list of meta tag names that denote likely article titles. All\n// attributes should be lowercase for faster case-insensitive matching. From\n// most distinct to least distinct.\nexport const STRONG_TITLE_META_TAGS = [\n  'tweetmeme-title',\n  'dc.title',\n  'rbtitle',\n  'headline',\n  'title',\n];\n\n// og:title is weak because it typically contains context that we don't like,\n// for example the source site's name. Gotta get that brand into facebook!\nexport const WEAK_TITLE_META_TAGS = [\n  'og:title',\n];\n\n// An ordered list of XPath Selectors to find likely article titles. From\n// most explicit to least explicit.\n//\n// Note - this does not use classes like CSS. This checks to see if the string\n// exists in the className, which is not as accurate as .className (which\n// splits on spaces/endlines), but for our purposes it's close enough. The\n// speed tradeoff is worth the accuracy hit.\nexport const STRONG_TITLE_SELECTORS = [\n  '.hentry .entry-title',\n  'h1#articleHeader',\n  'h1.articleHeader',\n  'h1.article',\n  '.instapaper_title',\n  '#meebo-title',\n];\n\nexport const WEAK_TITLE_SELECTORS = [\n  'article h1',\n  '#entry-title',\n  '.entry-title',\n  '#entryTitle',\n  '#entrytitle',\n  '.entryTitle',\n  '.entrytitle',\n  '#articleTitle',\n  '.articleTitle',\n  'post post-title',\n  'h1.title',\n  'h2.article',\n  'h1',\n  'html head title',\n  'title',\n];\n","import { cleanTitle } from 'cleaners';\nimport {\n  extractFromMeta,\n  extractFromSelectors,\n} from 'utils/dom';\n\nimport {\n  STRONG_TITLE_META_TAGS,\n  WEAK_TITLE_META_TAGS,\n  STRONG_TITLE_SELECTORS,\n  WEAK_TITLE_SELECTORS,\n} from './constants';\n\nconst GenericTitleExtractor = {\n  extract({ $, url, metaCache }) {\n    // First, check to see if we have a matching meta tag that we can make\n    // use of that is strongly associated with the headline.\n    let title;\n\n    title = extractFromMeta($, STRONG_TITLE_META_TAGS, metaCache);\n    if (title) return cleanTitle(title, { url, $ });\n\n    // Second, look through our content selectors for the most likely\n    // article title that is strongly associated with the headline.\n    title = extractFromSelectors($, STRONG_TITLE_SELECTORS);\n    if (title) return cleanTitle(title, { url, $ });\n\n    // Third, check for weaker meta tags that may match.\n    title = extractFromMeta($, WEAK_TITLE_META_TAGS, metaCache);\n    if (title) return cleanTitle(title, { url, $ });\n\n    // Last, look for weaker selector tags that may match.\n    title = extractFromSelectors($, WEAK_TITLE_SELECTORS);\n    if (title) return cleanTitle(title, { url, $ });\n\n    // If no matches, return an empty string\n    return '';\n  },\n};\n\nexport default GenericTitleExtractor;\n","// An ordered list of meta tag names that denote likely article authors. All\n// attributes should be lowercase for faster case-insensitive matching. From\n// most distinct to least distinct.\n//\n// Note: \"author\" is too often the -developer- of the page, so it is not\n// added here.\nexport const AUTHOR_META_TAGS = [\n  'byl',\n  'clmst',\n  'dc.author',\n  'dcsext.author',\n  'dc.creator',\n  'rbauthors',\n  'authors',\n];\n\nexport const AUTHOR_MAX_LENGTH = 300;\n\n// An ordered list of XPath Selectors to find likely article authors. From\n// most explicit to least explicit.\n//\n// Note - this does not use classes like CSS. This checks to see if the string\n// exists in the className, which is not as accurate as .className (which\n// splits on spaces/endlines), but for our purposes it's close enough. The\n// speed tradeoff is worth the accuracy hit.\nexport const AUTHOR_SELECTORS = [\n  '.entry .entry-author',\n  '.author.vcard .fn',\n  '.author .vcard .fn',\n  '.byline.vcard .fn',\n  '.byline .vcard .fn',\n  '.byline .by .author',\n  '.byline .by',\n  '.byline .author',\n  '.post-author.vcard',\n  '.post-author .vcard',\n  'a[rel=author]',\n  '#by_author',\n  '.by_author',\n  '#entryAuthor',\n  '.entryAuthor',\n  '.byline a[href*=author]',\n  '#author .authorname',\n  '.author .authorname',\n  '#author',\n  '.author',\n  '.articleauthor',\n  '.ArticleAuthor',\n  '.byline',\n];\n\n// An ordered list of Selectors to find likely article authors, with\n// regular expression for content.\nconst bylineRe = /^[\\n\\s]*By/i;\nexport const BYLINE_SELECTORS_RE = [\n  ['#byline', bylineRe],\n  ['.byline', bylineRe],\n];\n","import { cleanAuthor } from 'cleaners';\nimport {\n  extractFromMeta,\n  extractFromSelectors,\n} from 'utils/dom';\n\nimport {\n  AUTHOR_META_TAGS,\n  AUTHOR_MAX_LENGTH,\n  AUTHOR_SELECTORS,\n  BYLINE_SELECTORS_RE,\n} from './constants';\n\nconst GenericAuthorExtractor = {\n  extract({ $, metaCache }) {\n    let author;\n\n    // First, check to see if we have a matching\n    // meta tag that we can make use of.\n    author = extractFromMeta($, AUTHOR_META_TAGS, metaCache);\n    if (author && author.length < AUTHOR_MAX_LENGTH) {\n      return cleanAuthor(author);\n    }\n\n    // Second, look through our selectors looking for potential authors.\n    author = extractFromSelectors($, AUTHOR_SELECTORS, 2);\n    if (author && author.length < AUTHOR_MAX_LENGTH) {\n      return cleanAuthor(author);\n    }\n\n    // Last, use our looser regular-expression based selectors for\n    // potential authors.\n    for (const [selector, regex] of BYLINE_SELECTORS_RE) {\n      const node = $(selector);\n      if (node.length === 1) {\n        const text = node.text();\n        if (regex.test(text)) {\n          return cleanAuthor(text);\n        }\n      }\n    }\n\n    return null;\n  },\n};\n\nexport default GenericAuthorExtractor;\n","// An ordered list of meta tag names that denote\n// likely date published dates. All attributes\n// should be lowercase for faster case-insensitive matching.\n// From most distinct to least distinct.\nexport const DATE_PUBLISHED_META_TAGS = [\n  'article:published_time',\n  'displaydate',\n  'dc.date',\n  'dc.date.issued',\n  'rbpubdate',\n  'publish_date',\n  'pub_date',\n  'pagedate',\n  'pubdate',\n  'revision_date',\n  'doc_date',\n  'date_created',\n  'content_create_date',\n  'lastmodified',\n  'created',\n  'date',\n];\n\n// An ordered list of XPath Selectors to find\n// likely date published dates. From most explicit\n// to least explicit.\nexport const DATE_PUBLISHED_SELECTORS = [\n  '.hentry .dtstamp.published',\n  '.hentry .published',\n  '.hentry .dtstamp.updated',\n  '.hentry .updated',\n  '.single .published',\n  '.meta .published',\n  '.meta .postDate',\n  '.entry-date',\n  '.byline .date',\n  '.postmetadata .date',\n  '.article_datetime',\n  '.date-header',\n  '.story-date',\n  '.dateStamp',\n  '#story .datetime',\n  '.dateline',\n  '.pubdate',\n];\n\n// An ordered list of compiled regular expressions to find likely date\n// published dates from the URL. These should always have the first\n// reference be a date string that is parseable by dateutil.parser.parse\nconst abbrevMonthsStr = '(jan|feb|mar|apr|may|jun|jul|aug|sep|oct|nov|dec)';\nexport const DATE_PUBLISHED_URL_RES = [\n    // /2012/01/27/ but not /2012/01/293\n  new RegExp('/(20\\\\d{2}/\\\\d{2}/\\\\d{2})/', 'i'),\n    // 20120127 or 20120127T but not 2012012733 or 8201201733\n    // /[^0-9](20\\d{2}[01]\\d[0-3]\\d)([^0-9]|$)/i,\n    // 2012-01-27\n  new RegExp('(20\\\\d{2}-[01]\\\\d-[0-3]\\\\d)', 'i'),\n    // /2012/jan/27/\n  new RegExp(`/(20\\\\d{2}/${abbrevMonthsStr}/[0-3]\\\\d)/`, 'i'),\n];\n","import { cleanDatePublished } from 'cleaners';\nimport {\n  extractFromMeta,\n  extractFromSelectors,\n} from 'utils/dom';\nimport { extractFromUrl } from 'utils/text';\n\nimport {\n  DATE_PUBLISHED_META_TAGS,\n  DATE_PUBLISHED_SELECTORS,\n  DATE_PUBLISHED_URL_RES,\n} from './constants';\n\nconst GenericDatePublishedExtractor = {\n  extract({ $, url, metaCache }) {\n    let datePublished;\n    // First, check to see if we have a matching meta tag\n    // that we can make use of.\n    // Don't try cleaning tags from this string\n    datePublished = extractFromMeta($, DATE_PUBLISHED_META_TAGS, metaCache, false);\n    if (datePublished) return cleanDatePublished(datePublished);\n\n    // Second, look through our selectors looking for potential\n    // date_published's.\n    datePublished = extractFromSelectors($, DATE_PUBLISHED_SELECTORS);\n    if (datePublished) return cleanDatePublished(datePublished);\n\n    // Lastly, look to see if a dately string exists in the URL\n    datePublished = extractFromUrl(url, DATE_PUBLISHED_URL_RES);\n    if (datePublished) return cleanDatePublished(datePublished);\n\n    return null;\n  },\n};\n\nexport default GenericDatePublishedExtractor;\n","// import {\n//   DEK_META_TAGS,\n//   DEK_SELECTORS,\n//   DEK_URL_RES,\n// } from './constants';\n\n// import { cleanDek } from 'cleaners';\n\n// import {\n//   extractFromMeta,\n//   extractFromSelectors,\n// } from 'utils/dom';\n\n// Currently there is only one selector for\n// deks. We should simply return null here\n// until we have a more robust generic option.\n// Below is the original source for this, for reference.\nconst GenericDekExtractor = {\n  // extract({ $, content, metaCache }) {\n  extract() {\n    return null;\n  },\n};\n\nexport default GenericDekExtractor;\n\n// def extract_dek(self):\n//     # First, check to see if we have a matching meta tag that we can make\n//     # use of.\n//     dek = self.extract_from_meta('dek', constants.DEK_META_TAGS)\n//     if not dek:\n//         # Second, look through our CSS/XPath selectors. This may return\n//         # an HTML fragment.\n//         dek = self.extract_from_selectors('dek',\n//                                            constants.DEK_SELECTORS,\n//                                            text_only=False)\n//\n//     if dek:\n//         # Make sure our dek isn't in the first few thousand characters\n//         # of the content, otherwise it's just the start of the article\n//         # and not a true dek.\n//         content = self.extract_content()\n//         content_chunk = normalize_spaces(strip_tags(content[:2000]))\n//         dek_chunk = normalize_spaces(dek[:100]) # Already has no tags.\n//\n//         # 80% or greater similarity means the dek was very similar to some\n//         # of the starting content, so we skip it.\n//         if fuzz.partial_ratio(content_chunk, dek_chunk) < 80:\n//             return dek\n//\n//     return None\n","// An ordered list of meta tag names that denote likely article leading images.\n// All attributes should be lowercase for faster case-insensitive matching.\n// From most distinct to least distinct.\nexport const LEAD_IMAGE_URL_META_TAGS = [\n  'og:image',\n  'twitter:image',\n  'image_src',\n];\n\nexport const LEAD_IMAGE_URL_SELECTORS = [\n  'link[rel=image_src]',\n];\n\nexport const POSITIVE_LEAD_IMAGE_URL_HINTS = [\n  'upload',\n  'wp-content',\n  'large',\n  'photo',\n  'wp-image',\n];\nexport const POSITIVE_LEAD_IMAGE_URL_HINTS_RE = new RegExp(POSITIVE_LEAD_IMAGE_URL_HINTS.join('|'), 'i');\n\nexport const NEGATIVE_LEAD_IMAGE_URL_HINTS = [\n  'spacer',\n  'sprite',\n  'blank',\n  'throbber',\n  'gradient',\n  'tile',\n  'bg',\n  'background',\n  'icon',\n  'social',\n  'header',\n  'hdr',\n  'advert',\n  'spinner',\n  'loader',\n  'loading',\n  'default',\n  'rating',\n  'share',\n  'facebook',\n  'twitter',\n  'theme',\n  'promo',\n  'ads',\n  'wp-includes',\n];\nexport const NEGATIVE_LEAD_IMAGE_URL_HINTS_RE = new RegExp(NEGATIVE_LEAD_IMAGE_URL_HINTS.join('|'), 'i');\n\nexport const GIF_RE = /\\.gif(\\?.*)?$/i;\nexport const JPG_RE = /\\.jpe?g(\\?.*)?$/i;\n","import {\n  POSITIVE_LEAD_IMAGE_URL_HINTS_RE,\n  NEGATIVE_LEAD_IMAGE_URL_HINTS_RE,\n  GIF_RE,\n  JPG_RE,\n} from './constants';\n\nimport { PHOTO_HINTS_RE } from '../content/scoring/constants';\n\nfunction getSig($node) {\n  return `${$node.attr('class') || ''} ${$node.attr('id') || ''}`;\n}\n\n// Scores image urls based on a variety of heuristics.\nexport function scoreImageUrl(url) {\n  url = url.trim();\n  let score = 0;\n\n  if (POSITIVE_LEAD_IMAGE_URL_HINTS_RE.test(url)) {\n    score += 20;\n  }\n\n  if (NEGATIVE_LEAD_IMAGE_URL_HINTS_RE.test(url)) {\n    score -= 20;\n  }\n\n  // TODO: We might want to consider removing this as\n  // gifs are much more common/popular than they once were\n  if (GIF_RE.test(url)) {\n    score -= 10;\n  }\n\n  if (JPG_RE.test(url)) {\n    score += 10;\n  }\n\n  // PNGs are neutral.\n\n  return score;\n}\n\n// Alt attribute usually means non-presentational image.\nexport function scoreAttr($img) {\n  if ($img.attr('alt')) {\n    return 5;\n  }\n\n  return 0;\n}\n\n// Look through our parent and grandparent for figure-like\n// container elements, give a bonus if we find them\nexport function scoreByParents($img) {\n  let score = 0;\n  const $figParent = $img.parents('figure').first();\n\n  if ($figParent.length === 1) {\n    score += 25;\n  }\n\n  const $parent = $img.parent();\n  let $gParent;\n  if ($parent.length === 1) {\n    $gParent = $parent.parent();\n  }\n\n  [$parent, $gParent].forEach(($node) => {\n    if (PHOTO_HINTS_RE.test(getSig($node))) {\n      score += 15;\n    }\n  });\n\n  return score;\n}\n\n// Look at our immediate sibling and see if it looks like it's a\n// caption. Bonus if so.\nexport function scoreBySibling($img) {\n  let score = 0;\n  const $sibling = $img.next();\n  const sibling = $sibling.get(0);\n\n  if (sibling && sibling.tagName.toLowerCase() === 'figcaption') {\n    score += 25;\n  }\n\n  if (PHOTO_HINTS_RE.test(getSig($sibling))) {\n    score += 15;\n  }\n\n  return score;\n}\n\nexport function scoreByDimensions($img) {\n  let score = 0;\n\n  const width = parseFloat($img.attr('width'));\n  const height = parseFloat($img.attr('height'));\n  const src = $img.attr('src');\n\n  // Penalty for skinny images\n  if (width && width <= 50) {\n    score -= 50;\n  }\n\n  // Penalty for short images\n  if (height && height <= 50) {\n    score -= 50;\n  }\n\n  if (width && height && !src.includes('sprite')) {\n    const area = width * height;\n    if (area < 5000) { // Smaller than 50 x 100\n      score -= 100;\n    } else {\n      score += Math.round(area / 1000);\n    }\n  }\n\n  return score;\n}\n\nexport function scoreByPosition($imgs, index) {\n  return ($imgs.length / 2) - index;\n}\n","import { extractFromMeta } from 'utils/dom';\nimport { cleanImage } from 'cleaners';\n\nimport {\n  LEAD_IMAGE_URL_META_TAGS,\n  LEAD_IMAGE_URL_SELECTORS,\n} from './constants';\n\nimport {\n  scoreImageUrl,\n  scoreAttr,\n  scoreByParents,\n  scoreBySibling,\n  scoreByDimensions,\n  scoreByPosition,\n} from './score-image';\n\n// Given a resource, try to find the lead image URL from within\n// it. Like content and next page extraction, uses a scoring system\n// to determine what the most likely image may be. Short circuits\n// on really probable things like og:image meta tags.\n//\n// Potential signals to still take advantage of:\n//   * domain\n//   * weird aspect ratio\nconst GenericLeadImageUrlExtractor = {\n  extract({ $, content, metaCache, html }) {\n    let cleanUrl;\n    if (!$.browser && $('head').length === 0) {\n      $('*').first().prepend(html);\n    }\n\n    // Check to see if we have a matching meta tag that we can make use of.\n    // Moving this higher because common practice is now to use large\n    // images on things like Open Graph or Twitter cards.\n    // images usually have for things like Open Graph.\n    const imageUrl =\n      extractFromMeta(\n        $,\n        LEAD_IMAGE_URL_META_TAGS,\n        metaCache,\n        false\n      );\n\n    if (imageUrl) {\n      cleanUrl = cleanImage(imageUrl);\n\n      if (cleanUrl) return cleanUrl;\n    }\n\n    // Next, try to find the \"best\" image via the content.\n    // We'd rather not have to fetch each image and check dimensions,\n    // so try to do some analysis and determine them instead.\n    const $content = $(content);\n    const imgs = $('img', $content).toArray();\n    const imgScores = {};\n\n    imgs.forEach((img, index) => {\n      const $img = $(img);\n      const src = $img.attr('src');\n\n      if (!src) return;\n\n      let score = scoreImageUrl(src);\n      score += scoreAttr($img);\n      score += scoreByParents($img);\n      score += scoreBySibling($img);\n      score += scoreByDimensions($img);\n      score += scoreByPosition(imgs, index);\n\n      imgScores[src] = score;\n    });\n\n    const [topUrl, topScore] =\n      Reflect.ownKeys(imgScores).reduce((acc, key) =>\n        imgScores[key] > acc[1] ? [key, imgScores[key]] : acc\n      , [null, 0]);\n\n    if (topScore > 0) {\n      cleanUrl = cleanImage(topUrl);\n\n      if (cleanUrl) return cleanUrl;\n    }\n\n    // If nothing else worked, check to see if there are any really\n    // probable nodes in the doc, like <link rel=\"image_src\" />.\n    for (const selector of LEAD_IMAGE_URL_SELECTORS) {\n      const $node = $(selector).first();\n      const src = $node.attr('src');\n      if (src) {\n        cleanUrl = cleanImage(src);\n        if (cleanUrl) return cleanUrl;\n      }\n\n      const href = $node.attr('href');\n      if (href) {\n        cleanUrl = cleanImage(href);\n        if (cleanUrl) return cleanUrl;\n      }\n\n      const value = $node.attr('value');\n      if (value) {\n        cleanUrl = cleanImage(value);\n        if (cleanUrl) return cleanUrl;\n      }\n    }\n\n    return null;\n  },\n};\n\nexport default GenericLeadImageUrlExtractor;\n\n// def extract(self):\n//     \"\"\"\n//     # First, try to find the \"best\" image via the content.\n//     # We'd rather not have to fetch each image and check dimensions,\n//     # so try to do some analysis and determine them instead.\n//     content = self.extractor.extract_content(return_type=\"node\")\n//     imgs = content.xpath('.//img')\n//     img_scores = defaultdict(int)\n//     logger.debug('Scoring %d images from content', len(imgs))\n//     for (i, img) in enumerate(imgs):\n//         img_score = 0\n//\n//         if not 'src' in img.attrib:\n//             logger.debug('No src attribute found')\n//             continue\n//\n//         try:\n//             parsed_img = urlparse(img.attrib['src'])\n//             img_path = parsed_img.path.lower()\n//         except ValueError:\n//             logger.debug('ValueError getting img path.')\n//             continue\n//         logger.debug('Image path is %s', img_path)\n//\n//         if constants.POSITIVE_LEAD_IMAGE_URL_HINTS_RE.match(img_path):\n//             logger.debug('Positive URL hints match. Adding 20.')\n//             img_score += 20\n//\n//         if constants.NEGATIVE_LEAD_IMAGE_URL_HINTS_RE.match(img_path):\n//             logger.debug('Negative URL hints match. Subtracting 20.')\n//             img_score -= 20\n//\n//         # Gifs are more often structure than photos\n//         if img_path.endswith('gif'):\n//             logger.debug('gif found. Subtracting 10.')\n//             img_score -= 10\n//\n//         # JPGs are more often photographs\n//         if img_path.endswith('jpg'):\n//             logger.debug('jpg found. Adding 10.')\n//             img_score += 10\n//\n//         # PNGs are neutral.\n//\n//         # Alt attribute usually means non-presentational image.\n//         if 'alt' in img.attrib and len(img.attrib['alt']) > 5:\n//             logger.debug('alt attribute found. Adding 5.')\n//             img_score += 5\n//\n//         # Look through our parent and grandparent for figure-like\n//         # container elements, give a bonus if we find them\n//         parents = [img.getparent()]\n//         if parents[0] is not None and parents[0].getparent() is not None:\n//             parents.append(parents[0].getparent())\n//         for p in parents:\n//             if p.tag == 'figure':\n//                 logger.debug('Parent with <figure> tag found. Adding 25.')\n//                 img_score += 25\n//\n//             p_sig = ' '.join([p.get('id', ''), p.get('class', '')])\n//             if constants.PHOTO_HINTS_RE.search(p_sig):\n//                 logger.debug('Photo hints regex match. Adding 15.')\n//                 img_score += 15\n//\n//         # Look at our immediate sibling and see if it looks like it's a\n//         # caption. Bonus if so.\n//         sibling = img.getnext()\n//         if sibling is not None:\n//             if sibling.tag == 'figcaption':\n//                 img_score += 25\n//\n//             sib_sig = ' '.join([sibling.get('id', ''),\n//                                 sibling.get('class', '')]).lower()\n//             if 'caption' in sib_sig:\n//                 img_score += 15\n//\n//         # Pull out width/height if they were set.\n//         img_width = None\n//         img_height = None\n//         if 'width' in img.attrib:\n//             try:\n//                 img_width = float(img.get('width'))\n//             except ValueError:\n//                 pass\n//         if 'height' in img.attrib:\n//             try:\n//                 img_height = float(img.get('height'))\n//             except ValueError:\n//                 pass\n//\n//         # Penalty for skinny images\n//         if img_width and img_width <= 50:\n//             logger.debug('Skinny image found. Subtracting 50.')\n//             img_score -= 50\n//\n//         # Penalty for short images\n//         if img_height and img_height <= 50:\n//             # Wide, short images are more common than narrow, tall ones\n//             logger.debug('Short image found. Subtracting 25.')\n//             img_score -= 25\n//\n//         if img_width and img_height and not 'sprite' in img_path:\n//             area = img_width * img_height\n//\n//             if area < 5000: # Smaller than 50x100\n//                 logger.debug('Image with small area found. Subtracting 100.')\n//                 img_score -= 100\n//             else:\n//                 img_score += round(area/1000.0)\n//\n//         # If the image is higher on the page than other images,\n//         # it gets a bonus. Penalty if lower.\n//         logger.debug('Adding page placement bonus of %d.', len(imgs)/2 - i)\n//         img_score += len(imgs)/2 - i\n//\n//         # Use the raw src here because we munged img_path for case\n//         # insensitivity\n//         logger.debug('Final score is %d.', img_score)\n//         img_scores[img.attrib['src']] += img_score\n//\n//     top_score = 0\n//     top_url = None\n//     for (url, score) in img_scores.items():\n//         if score > top_score:\n//             top_url = url\n//             top_score = score\n//\n//     if top_score > 0:\n//         logger.debug('Using top score image from content. Score was %d', top_score)\n//         return top_url\n//\n//\n//     # If nothing else worked, check to see if there are any really\n//     # probable nodes in the doc, like <link rel=\"image_src\" />.\n//     logger.debug('Trying to find lead image in probable nodes')\n//     for selector in constants.LEAD_IMAGE_URL_SELECTORS:\n//         nodes = self.resource.extract_by_selector(selector)\n//         for node in nodes:\n//             clean_value = None\n//             if node.attrib.get('src'):\n//                 clean_value = self.clean(node.attrib['src'])\n//\n//             if not clean_value and node.attrib.get('href'):\n//                 clean_value = self.clean(node.attrib['href'])\n//\n//             if not clean_value and node.attrib.get('value'):\n//                 clean_value = self.clean(node.attrib['value'])\n//\n//             if clean_value:\n//                 logger.debug('Found lead image in probable nodes.')\n//                 logger.debug('Node was: %s', node)\n//                 return clean_value\n//\n//     return None\n","import difflib from 'difflib';\n\nexport default function scoreSimilarity(score, articleUrl, href) {\n  // Do this last and only if we have a real candidate, because it's\n  // potentially expensive computationally. Compare the link to this\n  // URL using difflib to get the % similarity of these URLs. On a\n  // sliding scale, subtract points from this link based on\n  // similarity.\n  if (score > 0) {\n    const similarity = new difflib.SequenceMatcher(null, articleUrl, href).ratio();\n    // Subtract .1 from diff_percent when calculating modifier,\n    // which means that if it's less than 10% different, we give a\n    // bonus instead. Ex:\n    //  3% different = +17.5 points\n    // 10% different = 0 points\n    // 20% different = -25 points\n    const diffPercent = 1.0 - similarity;\n    const diffModifier = -(250 * (diffPercent - 0.2));\n    return score + diffModifier;\n  }\n\n  return 0;\n}\n","import { IS_DIGIT_RE } from 'utils/text/constants';\n\nexport default function scoreLinkText(linkText, pageNum) {\n  // If the link text can be parsed as a number, give it a minor\n  // bonus, with a slight bias towards lower numbered pages. This is\n  // so that pages that might not have 'next' in their text can still\n  // get scored, and sorted properly by score.\n  let score = 0;\n\n  if (IS_DIGIT_RE.test(linkText.trim())) {\n    const linkTextAsNum = parseInt(linkText, 10);\n    // If it's the first page, we already got it on the first call.\n    // Give it a negative score. Otherwise, up to page 10, give a\n    // small bonus.\n    if (linkTextAsNum < 2) {\n      score = -30;\n    } else {\n      score = Math.max(0, 10 - linkTextAsNum);\n    }\n\n    // If it appears that the current page number is greater than\n    // this links page number, it's a very bad sign. Give it a big\n    // penalty.\n    if (pageNum && pageNum >= linkTextAsNum) {\n      score -= 50;\n    }\n  }\n\n  return score;\n}\n","export default function scorePageInLink(pageNum, isWp) {\n  // page in the link = bonus. Intentionally ignore wordpress because\n  // their ?p=123 link style gets caught by this even though it means\n  // separate documents entirely.\n  if (pageNum && !isWp) {\n    return 50;\n  }\n\n  return 0;\n}\n","export const DIGIT_RE = /\\d/;\n\n// A list of words that, if found in link text or URLs, likely mean that\n// this link is not a next page link.\nexport const EXTRANEOUS_LINK_HINTS = [\n  'print',\n  'archive',\n  'comment',\n  'discuss',\n  'e-mail',\n  'email',\n  'share',\n  'reply',\n  'all',\n  'login',\n  'sign',\n  'single',\n  'adx',\n  'entry-unrelated',\n];\nexport const EXTRANEOUS_LINK_HINTS_RE = new RegExp(EXTRANEOUS_LINK_HINTS.join('|'), 'i');\n\n// Match any link text/classname/id that looks like it could mean the next\n// page. Things like: next, continue, >, >>, » but not >|, »| as those can\n// mean last page.\nexport const NEXT_LINK_TEXT_RE = new RegExp('(next|weiter|continue|>([^|]|$)|»([^|]|$))', 'i');\n\n// Match any link text/classname/id that looks like it is an end link: things\n// like \"first\", \"last\", \"end\", etc.\nexport const CAP_LINK_TEXT_RE = new RegExp('(first|last|end)', 'i');\n\n// Match any link text/classname/id that looks like it means the previous\n// page.\nexport const PREV_LINK_TEXT_RE = new RegExp('(prev|earl|old|new|<|«)', 'i');\n\n// Match any phrase that looks like it could be page, or paging, or pagination\nexport const PAGE_RE = new RegExp('pag(e|ing|inat)', 'i');\n","import { EXTRANEOUS_LINK_HINTS_RE } from '../constants';\n\nexport default function scoreExtraneousLinks(href) {\n  // If the URL itself contains extraneous values, give a penalty.\n  if (EXTRANEOUS_LINK_HINTS_RE.test(href)) {\n    return -25;\n  }\n\n  return 0;\n}\n","import { range } from 'utils';\nimport {\n  NEGATIVE_SCORE_RE,\n  POSITIVE_SCORE_RE,\n  PAGE_RE,\n} from 'utils/dom/constants';\nimport { EXTRANEOUS_LINK_HINTS_RE } from '../constants';\n\nfunction makeSig($link) {\n  return `${$link.attr('class') || ''} ${$link.attr('id') || ''}`;\n}\n\nexport default function scoreByParents($link) {\n  // If a parent node contains paging-like classname or id, give a\n  // bonus. Additionally, if a parent_node contains bad content\n  // (like 'sponsor'), give a penalty.\n  let $parent = $link.parent();\n  let positiveMatch = false;\n  let negativeMatch = false;\n  let score = 0;\n\n  Array.from(range(0, 4)).forEach(() => {\n    if ($parent.length === 0) {\n      return;\n    }\n\n    const parentData = makeSig($parent, ' ');\n\n    // If we have 'page' or 'paging' in our data, that's a good\n    // sign. Add a bonus.\n    if (!positiveMatch && PAGE_RE.test(parentData)) {\n      positiveMatch = true;\n      score += 25;\n    }\n\n    // If we have 'comment' or something in our data, and\n    // we don't have something like 'content' as well, that's\n    // a bad sign. Give a penalty.\n    if (!negativeMatch && NEGATIVE_SCORE_RE.test(parentData)\n       && EXTRANEOUS_LINK_HINTS_RE.test(parentData)) {\n      if (!POSITIVE_SCORE_RE.test(parentData)) {\n        negativeMatch = true;\n        score -= 25;\n      }\n    }\n\n    $parent = $parent.parent();\n  });\n\n  return score;\n}\n","import { PREV_LINK_TEXT_RE } from '../constants';\n\nexport default function scorePrevLink(linkData) {\n  // If the link has something like \"previous\", its definitely\n  // an old link, skip it.\n  if (PREV_LINK_TEXT_RE.test(linkData)) {\n    return -200;\n  }\n\n  return 0;\n}\n","import URL from 'url';\n\nimport {\n  DIGIT_RE,\n  EXTRANEOUS_LINK_HINTS_RE,\n} from '../constants';\n\nexport default function shouldScore(\n  href,\n  articleUrl,\n  baseUrl,\n  parsedUrl,\n  linkText,\n  previousUrls\n) {\n  // skip if we've already fetched this url\n  if (previousUrls.find(url => href === url) !== undefined) {\n    return false;\n  }\n\n  // If we've already parsed this URL, or the URL matches the base\n  // URL, or is empty, skip it.\n  if (!href || href === articleUrl || href === baseUrl) {\n    return false;\n  }\n\n  const { hostname } = parsedUrl;\n  const { hostname: linkHost } = URL.parse(href);\n\n  // Domain mismatch.\n  if (linkHost !== hostname) {\n    return false;\n  }\n\n  // If href doesn't contain a digit after removing the base URL,\n  // it's certainly not the next page.\n  const fragment = href.replace(baseUrl, '');\n  if (!DIGIT_RE.test(fragment)) {\n    return false;\n  }\n\n  // This link has extraneous content (like \"comment\") in its link\n  // text, so we skip it.\n  if (EXTRANEOUS_LINK_HINTS_RE.test(linkText)) {\n    return false;\n  }\n\n  // Next page link text is never long, skip if it is too long.\n  if (linkText.length > 25) {\n    return false;\n  }\n\n  return true;\n}\n","export default function scoreBaseUrl(href, baseRegex) {\n  // If the baseUrl isn't part of this URL, penalize this\n  // link. It could still be the link, but the odds are lower.\n  // Example:\n  // http://www.actionscript.org/resources/articles/745/1/JavaScript-and-VBScript-Injection-in-ActionScript-3/Page1.html\n  if (!baseRegex.test(href)) {\n    return -25;\n  }\n\n  return 0;\n}\n","import { NEXT_LINK_TEXT_RE } from '../constants';\n\nexport default function scoreNextLinkText(linkData) {\n  // Things like \"next\", \">>\", etc.\n  if (NEXT_LINK_TEXT_RE.test(linkData)) {\n    return 50;\n  }\n\n  return 0;\n}\n","import {\n  NEXT_LINK_TEXT_RE,\n  CAP_LINK_TEXT_RE,\n} from '../constants';\n\nexport default function scoreCapLinks(linkData) {\n  // Cap links are links like \"last\", etc.\n  if (CAP_LINK_TEXT_RE.test(linkData)) {\n    // If we found a link like \"last\", but we've already seen that\n    // this link is also \"next\", it's fine. If it's not been\n    // previously marked as \"next\", then it's probably bad.\n    // Penalize.\n    if (NEXT_LINK_TEXT_RE.test(linkData)) {\n      return -65;\n    }\n  }\n\n  return 0;\n}\n","import URL from 'url';\n\nimport {\n  getAttrs,\n  isWordpress,\n} from 'utils/dom';\nimport {\n  removeAnchor,\n  pageNumFromUrl,\n} from 'utils/text';\n\nimport {\n  scoreSimilarity,\n  scoreLinkText,\n  scorePageInLink,\n  scoreExtraneousLinks,\n  scoreByParents,\n  scorePrevLink,\n  shouldScore,\n  scoreBaseUrl,\n  scoreCapLinks,\n  scoreNextLinkText,\n} from './utils';\n\nexport function makeBaseRegex(baseUrl) {\n  return new RegExp(`^${baseUrl}`, 'i');\n}\n\nfunction makeSig($link, linkText) {\n  return `${linkText || $link.text()} ${$link.attr('class') || ''} ${$link.attr('id') || ''}`;\n}\n\nexport default function scoreLinks({\n  links,\n  articleUrl,\n  baseUrl,\n  parsedUrl,\n  $,\n  previousUrls = [],\n}) {\n  parsedUrl = parsedUrl || URL.parse(articleUrl);\n  const baseRegex = makeBaseRegex(baseUrl);\n  const isWp = isWordpress($);\n\n  // Loop through all links, looking for hints that they may be next-page\n  // links. Things like having \"page\" in their textContent, className or\n  // id, or being a child of a node with a page-y className or id.\n  //\n  // After we do that, assign each page a score, and pick the one that\n  // looks most like the next page link, as long as its score is strong\n  // enough to have decent confidence.\n  const scoredPages = links.reduce((possiblePages, link) => {\n    // Remove any anchor data since we don't do a good job\n    // standardizing URLs (it's hard), we're going to do\n    // some checking with and without a trailing slash\n    const attrs = getAttrs(link);\n\n    // if href is undefined, return\n    if (!attrs.href) return possiblePages;\n\n    const href = removeAnchor(attrs.href);\n    const $link = $(link);\n    const linkText = $link.text();\n\n    if (!shouldScore(href, articleUrl, baseUrl, parsedUrl, linkText, previousUrls)) {\n      return possiblePages;\n    }\n\n    // ## PASSED THE FIRST-PASS TESTS. Start scoring. ##\n    if (!possiblePages[href]) {\n      possiblePages[href] = {\n        score: 0,\n        linkText,\n        href,\n      };\n    } else {\n      possiblePages[href].linkText = `${possiblePages[href].linkText}|${linkText}`;\n    }\n\n    const possiblePage = possiblePages[href];\n    const linkData = makeSig($link, linkText);\n    const pageNum = pageNumFromUrl(href);\n\n    let score = scoreBaseUrl(href, baseRegex);\n    score += scoreNextLinkText(linkData);\n    score += scoreCapLinks(linkData);\n    score += scorePrevLink(linkData);\n    score += scoreByParents($link);\n    score += scoreExtraneousLinks(href);\n    score += scorePageInLink(pageNum, isWp);\n    score += scoreLinkText(linkText, pageNum);\n    score += scoreSimilarity(score, articleUrl, href);\n\n    possiblePage.score = score;\n\n    return possiblePages;\n  }, {});\n\n  return Reflect.ownKeys(scoredPages).length === 0 ? null : scoredPages;\n}\n","import URL from 'url';\n\nimport {\n  articleBaseUrl,\n  removeAnchor,\n} from 'utils/text';\nimport scoreLinks from './scoring/score-links';\n\n// Looks for and returns next page url\n// for multi-page articles\nconst GenericNextPageUrlExtractor = {\n  extract({ $, url, parsedUrl, previousUrls = [] }) {\n    parsedUrl = parsedUrl || URL.parse(url);\n\n    const articleUrl = removeAnchor(url);\n    const baseUrl = articleBaseUrl(url, parsedUrl);\n\n    const links = $('a[href]').toArray();\n\n    const scoredLinks = scoreLinks({\n      links,\n      articleUrl,\n      baseUrl,\n      parsedUrl,\n      $,\n      previousUrls,\n    });\n\n    // If no links were scored, return null\n    if (!scoredLinks) return null;\n\n    // now that we've scored all possible pages,\n    // find the biggest one.\n    const topPage = Reflect.ownKeys(scoredLinks).reduce((acc, link) => {\n      const scoredLink = scoredLinks[link];\n      return scoredLink.score > acc.score ? scoredLink : acc;\n    }, { score: -100 });\n\n    // If the score is less than 50, we're not confident enough to use it,\n    // so we fail.\n    if (topPage.score >= 50) {\n      return topPage.href;\n    }\n\n    return null;\n  },\n};\n\nexport default GenericNextPageUrlExtractor;\n","export const CANONICAL_META_SELECTORS = [\n  'og:url',\n];\n","import URL from 'url';\nimport { extractFromMeta } from 'utils/dom';\n\nimport { CANONICAL_META_SELECTORS } from './constants';\n\nfunction parseDomain(url) {\n  const parsedUrl = URL.parse(url);\n  const { hostname } = parsedUrl;\n  return hostname;\n}\n\nfunction result(url) {\n  return {\n    url,\n    domain: parseDomain(url),\n  };\n}\n\nconst GenericUrlExtractor = {\n  extract({ $, url, metaCache }) {\n    const $canonical = $('link[rel=canonical]');\n    if ($canonical.length !== 0) {\n      const href = $canonical.attr('href');\n      if (href) {\n        return result(href);\n      }\n    }\n\n    const metaUrl = extractFromMeta($, CANONICAL_META_SELECTORS, metaCache);\n    if (metaUrl) {\n      return result(metaUrl);\n    }\n\n    return result(url);\n  },\n\n};\n\nexport default GenericUrlExtractor;\n","export const EXCERPT_META_SELECTORS = [\n  'og:description',\n  'twitter:description',\n];\n","import ellipsize from 'ellipsize';\n\nimport {\n  extractFromMeta,\n  stripTags,\n} from 'utils/dom';\n\nimport { EXCERPT_META_SELECTORS } from './constants';\n\nexport function clean(content, $, maxLength = 200) {\n  content = content.replace(/[\\s\\n]+/g, ' ').trim();\n  return ellipsize(content, maxLength, { ellipse: '&hellip;' });\n}\n\nconst GenericExcerptExtractor = {\n  extract({ $, content, metaCache }) {\n    const excerpt = extractFromMeta($, EXCERPT_META_SELECTORS, metaCache);\n    if (excerpt) {\n      return clean(stripTags(excerpt, $));\n    }\n    // Fall back to excerpting from the extracted content\n    const maxLength = 200;\n    const shortContent = content.slice(0, maxLength * 5);\n    return clean($(shortContent).text(), $, maxLength);\n  },\n};\n\nexport default GenericExcerptExtractor;\n","import cheerio from 'cheerio';\n\nimport { normalizeSpaces } from 'utils/text';\n\nconst GenericWordCountExtractor = {\n  extract({ content }) {\n    const $ = cheerio.load(content);\n    const $content = $('div').first();\n\n    const text = normalizeSpaces($content.text());\n    return text.split(/\\s/).length;\n  },\n};\n\nexport default GenericWordCountExtractor;\n","import cheerio from 'cheerio';\nimport stringDirection from 'string-direction';\n\nimport GenericContentExtractor from './content/extractor';\nimport GenericTitleExtractor from './title/extractor';\nimport GenericAuthorExtractor from './author/extractor';\nimport GenericDatePublishedExtractor from './date-published/extractor';\nimport GenericDekExtractor from './dek/extractor';\nimport GenericLeadImageUrlExtractor from './lead-image-url/extractor';\nimport GenericNextPageUrlExtractor from './next-page-url/extractor';\nimport GenericUrlExtractor from './url/extractor';\nimport GenericExcerptExtractor from './excerpt/extractor';\nimport GenericWordCountExtractor from './word-count/extractor';\n\nconst GenericExtractor = {\n  // This extractor is the default for all domains\n  domain: '*',\n  title: GenericTitleExtractor.extract,\n  date_published: GenericDatePublishedExtractor.extract,\n  author: GenericAuthorExtractor.extract,\n  content: GenericContentExtractor.extract.bind(GenericContentExtractor),\n  lead_image_url: GenericLeadImageUrlExtractor.extract,\n  dek: GenericDekExtractor.extract,\n  next_page_url: GenericNextPageUrlExtractor.extract,\n  url_and_domain: GenericUrlExtractor.extract,\n  excerpt: GenericExcerptExtractor.extract,\n  word_count: GenericWordCountExtractor.extract,\n  direction: ({ title }) => stringDirection.getDirection(title),\n\n  extract(options) {\n    const { html, $ } = options;\n\n    if (html && !$) {\n      const loaded = cheerio.load(html);\n      options.$ = loaded;\n    }\n\n    const title = this.title(options);\n    const date_published = this.date_published(options);\n    const author = this.author(options);\n    const content = this.content({ ...options, title });\n    const lead_image_url = this.lead_image_url({ ...options, content });\n    const dek = this.dek({ ...options, content });\n    const next_page_url = this.next_page_url(options);\n    const excerpt = this.excerpt({ ...options, content });\n    const word_count = this.word_count({ ...options, content });\n    const direction = this.direction({ title });\n    const { url, domain } = this.url_and_domain(options);\n\n    return {\n      title,\n      author,\n      date_published: date_published || null,\n      dek,\n      lead_image_url,\n      content,\n      next_page_url,\n      url,\n      domain,\n      excerpt,\n      word_count,\n      direction,\n    };\n  },\n};\n\nexport default GenericExtractor;\n","import {\n  MediumExtractor,\n  BloggerExtractor,\n} from './custom/';\n\nconst Detectors = {\n  'meta[name=\"al:ios:app_name\"][value=\"Medium\"]': MediumExtractor,\n  'meta[name=\"generator\"][value=\"blogger\"]': BloggerExtractor,\n};\n\nexport default function detectByHtml($) {\n  const selector = Reflect.ownKeys(Detectors).find(s => $(s).length > 0);\n\n  return Detectors[selector];\n}\n","import URL from 'url';\n\nimport Extractors from './all';\nimport GenericExtractor from './generic';\nimport detectByHtml from './detect-by-html';\n\nexport default function getExtractor(url, parsedUrl, $) {\n  parsedUrl = parsedUrl || URL.parse(url);\n  const { hostname } = parsedUrl;\n  const baseDomain = hostname.split('.').slice(-2).join('.');\n\n  return Extractors[hostname] || Extractors[baseDomain] ||\n    detectByHtml($) || GenericExtractor;\n}\n","import Cleaners from 'cleaners';\nimport { convertNodeTo } from 'utils/dom';\nimport GenericExtractor from './generic';\n\n// Remove elements by an array of selectors\nexport function cleanBySelectors($content, $, { clean }) {\n  if (!clean) return $content;\n\n  $(clean.join(','), $content).remove();\n\n  return $content;\n}\n\n// Transform matching elements\nexport function transformElements($content, $, { transforms }) {\n  if (!transforms) return $content;\n\n  Reflect.ownKeys(transforms).forEach((key) => {\n    const $matches = $(key, $content);\n    const value = transforms[key];\n\n    // If value is a string, convert directly\n    if (typeof value === 'string') {\n      $matches.each((index, node) => {\n        convertNodeTo($(node), $, transforms[key]);\n      });\n    } else if (typeof value === 'function') {\n      // If value is function, apply function to node\n      $matches.each((index, node) => {\n        const result = value($(node), $);\n        // If function returns a string, convert node to that value\n        if (typeof result === 'string') {\n          convertNodeTo($(node), $, result);\n        }\n      });\n    }\n  });\n\n  return $content;\n}\n\nfunction findMatchingSelector($, selectors, extractHtml) {\n  return selectors.find((selector) => {\n    if (Array.isArray(selector)) {\n      if (extractHtml) {\n        return selector.reduce((acc, s) => acc && $(s).length > 0, true);\n      }\n\n      const [s, attr] = selector;\n      return $(s).length === 1 && $(s).attr(attr) && $(s).attr(attr).trim() !== '';\n    }\n\n    return $(selector).length === 1 && $(selector).text().trim() !== '';\n  });\n}\n\nexport function select(opts) {\n  const { $, type, extractionOpts, extractHtml = false } = opts;\n  // Skip if there's not extraction for this type\n  if (!extractionOpts) return null;\n\n  // If a string is hardcoded for a type (e.g., Wikipedia\n  // contributors), return the string\n  if (typeof extractionOpts === 'string') return extractionOpts;\n\n  const { selectors, defaultCleaner = true } = extractionOpts;\n\n  const matchingSelector = findMatchingSelector($, selectors, extractHtml);\n\n  if (!matchingSelector) return null;\n\n  // Declaring result; will contain either\n  // text or html, which will be cleaned\n  // by the appropriate cleaner type\n\n  // If the selector type requests html as its return type\n  // transform and clean the element with provided selectors\n  let $content;\n  if (extractHtml) {\n    // If matching selector is an array, we're considering this a\n    // multi-match selection, which allows the parser to choose several\n    // selectors to include in the result. Note that all selectors in the\n    // array must match in order for this selector to trigger\n    if (Array.isArray(matchingSelector)) {\n      $content = $(matchingSelector.join(','));\n      const $wrapper = $('<div></div>');\n      $content.each((index, element) => {\n        $wrapper.append(element);\n      });\n\n      $content = $wrapper;\n    } else {\n      $content = $(matchingSelector);\n    }\n\n    // Wrap in div so transformation can take place on root element\n    $content.wrap($('<div></div>'));\n    $content = $content.parent();\n\n    $content = transformElements($content, $, extractionOpts);\n    $content = cleanBySelectors($content, $, extractionOpts);\n\n    $content = Cleaners[type]($content, { ...opts, defaultCleaner });\n\n    return $.html($content);\n  }\n\n  let result;\n\n  // if selector is an array (e.g., ['img', 'src']),\n  // extract the attr\n  if (Array.isArray(matchingSelector)) {\n    const [selector, attr] = matchingSelector;\n    result = $(selector).attr(attr).trim();\n  } else {\n    let $node = $(matchingSelector);\n\n    $node = cleanBySelectors($node, $, extractionOpts);\n    $node = transformElements($node, $, extractionOpts);\n\n    result = $node.text().trim();\n  }\n\n  // Allow custom extractor to skip default cleaner\n  // for this type; defaults to true\n  if (defaultCleaner) {\n    return Cleaners[type](result, { ...opts, ...extractionOpts });\n  }\n\n  return result;\n}\n\nfunction extractResult(opts) {\n  const { type, extractor, fallback = true } = opts;\n\n  const result = select({ ...opts, extractionOpts: extractor[type] });\n\n  // If custom parser succeeds, return the result\n  if (result) {\n    return result;\n  }\n\n  // If nothing matches the selector, and fallback is enabled,\n  // run the Generic extraction\n  if (fallback) return GenericExtractor[type](opts);\n\n  return null;\n}\n\nconst RootExtractor = {\n  extract(extractor = GenericExtractor, opts) {\n    const { contentOnly, extractedTitle } = opts;\n    // This is the generic extractor. Run its extract method\n    if (extractor.domain === '*') return extractor.extract(opts);\n\n    opts = {\n      ...opts,\n      extractor,\n    };\n\n    if (contentOnly) {\n      const content = extractResult({\n        ...opts, type: 'content', extractHtml: true, title: extractedTitle,\n      });\n      return {\n        content,\n      };\n    }\n    const title = extractResult({ ...opts, type: 'title' });\n    const date_published = extractResult({ ...opts, type: 'date_published' });\n    const author = extractResult({ ...opts, type: 'author' });\n    const next_page_url = extractResult({ ...opts, type: 'next_page_url' });\n    const content = extractResult({\n      ...opts, type: 'content', extractHtml: true, title,\n    });\n    const lead_image_url = extractResult({ ...opts, type: 'lead_image_url', content });\n    const excerpt = extractResult({ ...opts, type: 'excerpt', content });\n    const dek = extractResult({ ...opts, type: 'dek', content, excerpt });\n    const word_count = extractResult({ ...opts, type: 'word_count', content });\n    const direction = extractResult({ ...opts, type: 'direction', title });\n    const { url, domain } =\n      extractResult({ ...opts, type: 'url_and_domain' }) || { url: null, domain: null };\n\n    return {\n      title,\n      content,\n      author,\n      date_published,\n      lead_image_url,\n      dek,\n      next_page_url,\n      url,\n      domain,\n      excerpt,\n      word_count,\n      direction,\n    };\n  },\n};\n\nexport default RootExtractor;\n","import { removeAnchor } from 'utils/text';\nimport RootExtractor from 'extractors/root-extractor';\nimport GenericExtractor from 'extractors/generic';\nimport Resource from 'resource';\n\nexport default async function collectAllPages(\n  {\n    next_page_url,\n    html,\n    $,\n    metaCache,\n    result,\n    Extractor,\n    title,\n    url,\n  }\n) {\n  // At this point, we've fetched just the first page\n  let pages = 1;\n  const previousUrls = [removeAnchor(url)];\n\n  // If we've gone over 26 pages, something has\n  // likely gone wrong.\n  while (next_page_url && pages < 26) {\n    pages += 1;\n    $ = await Resource.create(next_page_url);\n    html = $.html();\n\n    const extractorOpts = {\n      url: next_page_url,\n      html,\n      $,\n      metaCache,\n      contentOnly: true,\n      extractedTitle: title,\n      previousUrls,\n    };\n\n    const nextPageResult = RootExtractor.extract(Extractor, extractorOpts);\n\n    previousUrls.push(next_page_url);\n    result = {\n      ...result,\n      content: `${result.content}<hr><h4>Page ${pages}</h4>${nextPageResult.content}`,\n    };\n\n    next_page_url = nextPageResult.next_page_url;\n  }\n\n  const word_count = GenericExtractor.word_count({ content: `<div>${result.content}</div>` });\n  return {\n    ...result,\n    total_pages: pages,\n    pages_rendered: pages,\n    word_count,\n  };\n}\n","import URL from 'url';\nimport cheerio from 'cheerio';\n\nimport Resource from 'resource';\nimport {\n  validateUrl,\n  Errors,\n} from 'utils';\nimport getExtractor from 'extractors/get-extractor';\nimport RootExtractor from 'extractors/root-extractor';\nimport collectAllPages from 'extractors/collect-all-pages';\n\nconst Mercury = {\n  async parse(url, html, opts = {}) {\n    const {\n      fetchAllPages = true,\n      fallback = true,\n    } = opts;\n\n    // if no url was passed and this is the browser version,\n    // set url to window.location.href and load the html\n    // from the current page\n    if (!url && cheerio.browser) {\n      url = window.location.href; // eslint-disable-line no-undef\n      html = html || cheerio.html();\n    }\n\n    const parsedUrl = URL.parse(url);\n\n    if (!validateUrl(parsedUrl)) {\n      return Errors.badUrl;\n    }\n\n    const $ = await Resource.create(url, html, parsedUrl);\n\n    const Extractor = getExtractor(url, parsedUrl, $);\n    // console.log(`Using extractor for ${Extractor.domain}`);\n\n    // If we found an error creating the resource, return that error\n    if ($.failed) {\n      return $;\n    }\n\n    // if html still has not been set (i.e., url passed to Mercury.parse),\n    // set html from the response of Resource.create\n    if (!html) {\n      html = $.html();\n    }\n\n    // Cached value of every meta name in our document.\n    // Used when extracting title/author/date_published/dek\n    const metaCache = $('meta').map((_, node) => $(node).attr('name')).toArray();\n\n    let result = RootExtractor.extract(\n      Extractor,\n      {\n        url,\n        html,\n        $,\n        metaCache,\n        parsedUrl,\n        fallback,\n      });\n\n    const { title, next_page_url } = result;\n\n    // Fetch more pages if next_page_url found\n    if (fetchAllPages && next_page_url) {\n      result = await collectAllPages(\n        {\n          Extractor,\n          next_page_url,\n          html,\n          $,\n          metaCache,\n          result,\n          title,\n          url,\n        }\n      );\n    } else {\n      result = {\n        ...result,\n        total_pages: 1,\n        rendered_pages: 1,\n      };\n    }\n\n    return result;\n  },\n\n  browser: !!cheerio.browser,\n\n  // A convenience method for getting a resource\n  // to work with, e.g., for custom extractor generator\n  async fetchResource(url) {\n    return await Resource.create(url);\n  },\n\n};\n\nexport default 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