2023-06-19 17:42:47 -04:00
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// SPDX-FileCopyrightText: Copyright The Miniflux Authors. All rights reserved.
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// SPDX-License-Identifier: Apache-2.0
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2017-12-10 22:01:38 -05:00
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2023-08-10 22:46:45 -04:00
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package readability // import "miniflux.app/v2/internal/reader/readability"
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2017-12-10 22:01:38 -05:00
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import (
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"bytes"
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"fmt"
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"io"
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2023-09-24 19:32:09 -04:00
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"log/slog"
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2017-12-10 22:01:38 -05:00
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"math"
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"regexp"
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"strings"
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"github.com/PuerkitoBio/goquery"
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"golang.org/x/net/html"
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)
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const (
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defaultTagsToScore = "section,h2,h3,h4,h5,h6,p,td,pre,div"
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)
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var (
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divToPElementsRegexp = regexp.MustCompile(`(?i)<(a|blockquote|dl|div|img|ol|p|pre|table|ul)`)
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sentenceRegexp = regexp.MustCompile(`\.( |$)`)
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blacklistCandidatesRegexp = regexp.MustCompile(`(?i)popupbody|-ad|g-plus`)
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okMaybeItsACandidateRegexp = regexp.MustCompile(`(?i)and|article|body|column|main|shadow`)
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unlikelyCandidatesRegexp = regexp.MustCompile(`(?i)banner|breadcrumbs|combx|comment|community|cover-wrap|disqus|extra|foot|header|legends|menu|modal|related|remark|replies|rss|shoutbox|sidebar|skyscraper|social|sponsor|supplemental|ad-break|agegate|pagination|pager|popup|yom-remote`)
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negativeRegexp = regexp.MustCompile(`(?i)hidden|^hid$|hid$|hid|^hid |banner|combx|comment|com-|contact|foot|footer|footnote|masthead|media|meta|modal|outbrain|promo|related|scroll|share|shoutbox|sidebar|skyscraper|sponsor|shopping|tags|tool|widget|byline|author|dateline|writtenby|p-author`)
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positiveRegexp = regexp.MustCompile(`(?i)article|body|content|entry|hentry|h-entry|main|page|pagination|post|text|blog|story`)
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)
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type candidate struct {
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selection *goquery.Selection
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score float32
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}
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func (c *candidate) Node() *html.Node {
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return c.selection.Get(0)
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}
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func (c *candidate) String() string {
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id, _ := c.selection.Attr("id")
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class, _ := c.selection.Attr("class")
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if id != "" && class != "" {
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return fmt.Sprintf("%s#%s.%s => %f", c.Node().DataAtom, id, class, c.score)
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} else if id != "" {
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return fmt.Sprintf("%s#%s => %f", c.Node().DataAtom, id, c.score)
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} else if class != "" {
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return fmt.Sprintf("%s.%s => %f", c.Node().DataAtom, class, c.score)
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}
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return fmt.Sprintf("%s => %f", c.Node().DataAtom, c.score)
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}
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type candidateList map[*html.Node]*candidate
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func (c candidateList) String() string {
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var output []string
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for _, candidate := range c {
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output = append(output, candidate.String())
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}
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return strings.Join(output, ", ")
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}
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// ExtractContent returns relevant content.
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func ExtractContent(page io.Reader) (string, error) {
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document, err := goquery.NewDocumentFromReader(page)
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if err != nil {
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return "", err
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}
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2020-09-30 01:22:25 -04:00
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document.Find("script,style").Each(func(i int, s *goquery.Selection) {
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removeNodes(s)
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})
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transformMisusedDivsIntoParagraphs(document)
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removeUnlikelyCandidates(document)
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candidates := getCandidates(document)
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topCandidate := getTopCandidate(document, candidates)
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2023-09-24 19:32:09 -04:00
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slog.Debug("Readability parsing",
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slog.Any("candidates", candidates),
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slog.Any("topCandidate", topCandidate),
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)
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output := getArticle(topCandidate, candidates)
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return output, nil
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}
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// Now that we have the top candidate, look through its siblings for content that might also be related.
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// Things like preambles, content split by ads that we removed, etc.
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func getArticle(topCandidate *candidate, candidates candidateList) string {
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output := bytes.NewBufferString("<div>")
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siblingScoreThreshold := float32(math.Max(10, float64(topCandidate.score*.2)))
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topCandidate.selection.Siblings().Union(topCandidate.selection).Each(func(i int, s *goquery.Selection) {
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append := false
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node := s.Get(0)
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if node == topCandidate.Node() {
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append = true
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} else if c, ok := candidates[node]; ok && c.score >= siblingScoreThreshold {
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append = true
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}
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if s.Is("p") {
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linkDensity := getLinkDensity(s)
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content := s.Text()
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contentLength := len(content)
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if contentLength >= 80 && linkDensity < .25 {
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append = true
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} else if contentLength < 80 && linkDensity == 0 && sentenceRegexp.MatchString(content) {
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append = true
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}
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}
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if append {
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tag := "div"
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if s.Is("p") {
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tag = node.Data
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}
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html, _ := s.Html()
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fmt.Fprintf(output, "<%s>%s</%s>", tag, html, tag)
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}
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})
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output.Write([]byte("</div>"))
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return output.String()
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}
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func removeUnlikelyCandidates(document *goquery.Document) {
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document.Find("*").Not("html,body").Each(func(i int, s *goquery.Selection) {
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class, _ := s.Attr("class")
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id, _ := s.Attr("id")
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str := class + id
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if blacklistCandidatesRegexp.MatchString(str) || (unlikelyCandidatesRegexp.MatchString(str) && !okMaybeItsACandidateRegexp.MatchString(str)) {
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removeNodes(s)
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}
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})
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}
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func getTopCandidate(document *goquery.Document, candidates candidateList) *candidate {
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var best *candidate
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for _, c := range candidates {
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if best == nil {
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best = c
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} else if best.score < c.score {
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best = c
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}
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}
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if best == nil {
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best = &candidate{document.Find("body"), 0}
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}
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return best
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}
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// Loop through all paragraphs, and assign a score to them based on how content-y they look.
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// Then add their score to their parent node.
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// A score is determined by things like number of commas, class names, etc.
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// Maybe eventually link density.
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func getCandidates(document *goquery.Document) candidateList {
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candidates := make(candidateList)
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document.Find(defaultTagsToScore).Each(func(i int, s *goquery.Selection) {
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text := s.Text()
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// If this paragraph is less than 25 characters, don't even count it.
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if len(text) < 25 {
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return
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}
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parent := s.Parent()
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parentNode := parent.Get(0)
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grandParent := parent.Parent()
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var grandParentNode *html.Node
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if grandParent.Length() > 0 {
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grandParentNode = grandParent.Get(0)
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}
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if _, found := candidates[parentNode]; !found {
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candidates[parentNode] = scoreNode(parent)
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}
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if grandParentNode != nil {
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if _, found := candidates[grandParentNode]; !found {
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candidates[grandParentNode] = scoreNode(grandParent)
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}
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}
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// Add a point for the paragraph itself as a base.
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contentScore := float32(1.0)
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// Add points for any commas within this paragraph.
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contentScore += float32(strings.Count(text, ",") + 1)
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// For every 100 characters in this paragraph, add another point. Up to 3 points.
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contentScore += float32(math.Min(float64(int(len(text)/100.0)), 3))
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candidates[parentNode].score += contentScore
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if grandParentNode != nil {
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candidates[grandParentNode].score += contentScore / 2.0
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}
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})
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// Scale the final candidates score based on link density. Good content
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// should have a relatively small link density (5% or less) and be mostly
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// unaffected by this operation
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for _, candidate := range candidates {
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candidate.score = candidate.score * (1 - getLinkDensity(candidate.selection))
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}
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return candidates
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}
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func scoreNode(s *goquery.Selection) *candidate {
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c := &candidate{selection: s, score: 0}
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switch s.Get(0).DataAtom.String() {
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case "div":
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c.score += 5
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case "pre", "td", "blockquote", "img":
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c.score += 3
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case "address", "ol", "ul", "dl", "dd", "dt", "li", "form":
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c.score -= 3
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case "h1", "h2", "h3", "h4", "h5", "h6", "th":
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c.score -= 5
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}
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c.score += getClassWeight(s)
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return c
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}
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// Get the density of links as a percentage of the content
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// This is the amount of text that is inside a link divided by the total text in the node.
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func getLinkDensity(s *goquery.Selection) float32 {
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linkLength := len(s.Find("a").Text())
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textLength := len(s.Text())
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if textLength == 0 {
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return 0
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}
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return float32(linkLength) / float32(textLength)
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}
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// Get an elements class/id weight. Uses regular expressions to tell if this
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// element looks good or bad.
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func getClassWeight(s *goquery.Selection) float32 {
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weight := 0
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class, _ := s.Attr("class")
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id, _ := s.Attr("id")
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if class != "" {
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if negativeRegexp.MatchString(class) {
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weight -= 25
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}
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if positiveRegexp.MatchString(class) {
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weight += 25
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}
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}
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if id != "" {
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if negativeRegexp.MatchString(id) {
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weight -= 25
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}
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if positiveRegexp.MatchString(id) {
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weight += 25
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}
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}
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return float32(weight)
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}
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func transformMisusedDivsIntoParagraphs(document *goquery.Document) {
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document.Find("div").Each(func(i int, s *goquery.Selection) {
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html, _ := s.Html()
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if !divToPElementsRegexp.MatchString(html) {
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node := s.Get(0)
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node.Data = "p"
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}
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})
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}
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func removeNodes(s *goquery.Selection) {
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s.Each(func(i int, s *goquery.Selection) {
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parent := s.Parent()
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if parent.Length() > 0 {
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parent.Get(0).RemoveChild(s.Get(0))
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}
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})
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}
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