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