Module: Jules
- Defined in:
- lib/jules.rb,
lib/jules/version.rb
Constant Summary collapse
- SIMILARITY_THRESHOLD =
0.6
- SIMHASH_BITLENGTH =
128
- ELEMENTS =
['div', 'li', 'tr', 'article']
- VERSION =
'0.1.0'
Class Method Summary collapse
-
.cluster_trees(trees) ⇒ Object
Cluster trees based on similarity.
- .collect(html, filters, elements = Jules::ELEMENTS) ⇒ Object
-
.filter_item(tree, filters) ⇒ Object
Try to find a single item in DOM tree.
-
.grade_clusters(clusters, filters) ⇒ Object
Grade clusters.
-
.items(clusters, filters) ⇒ Object
Pick items from best cluster, or combine items from multiple clusters.
-
.rearrange_trees(document, elements = Jules::ELEMENTS) ⇒ Object
Rearranges DOM trees with Simhash.
-
.simhash(data) ⇒ Object
Helper methods.
Class Method Details
.cluster_trees(trees) ⇒ Object
Cluster trees based on similarity
58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
# File 'lib/jules.rb', line 58 def cluster_trees(trees) clusters, cluster = [], [trees[0]] trees.each_with_previous do |prev, tree| next if prev.nil? # first item similarity = Simhash.similarity(prev[:simhash], tree[:simhash]) if similarity < Jules::SIMILARITY_THRESHOLD clusters << cluster cluster = [tree] else cluster << tree end end clusters << cluster if cluster.count > 0 # Reject clusters that only contain 1 tree clusters.reject { |cluster| cluster.count < 2 } end |
.collect(html, filters, elements = Jules::ELEMENTS) ⇒ Object
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
# File 'lib/jules.rb', line 15 def self.collect(html, filters, elements=Jules::ELEMENTS) unless html.is_a?(String) || html.is_a?(File) raise ArgumentError, 'html not a String or File' end raise ArgumentError, 'filters argument empty' if filters.nil? raise ArgumentError, 'filters not a Hash' unless filters.is_a? Hash raise ArgumentError, 'elements not an Array' unless elements.is_a? Array document = Nokogiri::HTML(html) trees = Jules.rearrange_trees(document, elements) clusters = Jules.cluster_trees(trees) clusters = Jules.grade_clusters(clusters, filters) Jules.items(clusters, filters) end |
.filter_item(tree, filters) ⇒ Object
Try to find a single item in DOM tree
108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 |
# File 'lib/jules.rb', line 108 def filter_item(tree, filters) filters.each do |key, filter| filter = filter[0] if filter.class == Array # TODO case filter when String value = tree[:node].at(filter) if value tree[:item] ||= {} if value.text.empty? tree[:item][key] = value['src'] || value['href'] else tree[:item][key] = value.text end end when Regexp match = filter.match(tree[:node].inner_html) if match && match.captures tree[:item] ||= {} tree[:item][key] = match.captures[0] end when Proc tree[:item][key] = filter.call(tree[:node]) else raise ArgumentError, "#{filter} is not a valid filter type" end end tree end |
.grade_clusters(clusters, filters) ⇒ Object
Grade clusters
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 |
# File 'lib/jules.rb', line 79 def grade_clusters(clusters, filters) # Map trees inside cluster hash, to make room for metadata clusters.map! {|cluster| {trees: cluster} } clusters.each do |cluster| cluster[:score] = 0 cluster[:trees].each do |tree| tree = filter_item(tree, filters) cluster[:score] += tree[:item].to_h.count end cluster[:items] = cluster[:trees] .sort_by { |tree| tree[:index] } .map { |tree| tree[:item] } .reject { |item| item.nil? } # Bonus points if all trees are at same depth depth_sd = cluster[:trees].map { |tree| tree[:depth] }.standard_deviation cluster[:score] += 1 if depth_sd < 0.5 cluster[:score_ratio] = cluster[:score] / cluster[:trees].count.to_f end clusters .reject{ |cluster| cluster[:items].count == 0 } .sort_by { |cluster| cluster[:score] } end |
.items(clusters, filters) ⇒ Object
Pick items from best cluster, or combine items from multiple clusters
140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 |
# File 'lib/jules.rb', line 140 def items(clusters, filters) # Clusters need to have at least one item field per tree clusters .select!{|cluster| cluster[:score_ratio] >= 1.0 } return [] if clusters.to_a.count == 0 # Find unique items, start with highest scoring clusters items = [] # Pick two best groups clusters = clusters.sort_by {|cluster| cluster[:score_ratio]}.reverse[0, 2] clusters.each do |cluster| cluster[:items].each do |item| items << item end end items.uniq! # Keep best items of partial duplicates items.delete_if do |item| items.find_by_partial_hash(item).map(&:count).max > item.count end return items end |
.rearrange_trees(document, elements = Jules::ELEMENTS) ⇒ Object
Rearranges DOM trees with Simhash
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 |
# File 'lib/jules.rb', line 32 def rearrange_trees(document, elements=Jules::ELEMENTS) trees = [] document_length = document.inner_html.length xpath = elements.map{ |x| '//' + x }.join('|') document.search(xpath).each do |tree| structure = Nokogiri::XML.remove_markup_outline(tree.to_outline).strip if structure.empty? tree.remove # This HTML tree does not contain any structure next end # Tree should be smaller than 50% of document size next if (tree.inner_html.length / document_length.to_f * 100) > 50 trees << { node: tree, depth: tree.depth, simhash: structure.simhash(hashbits: Jules::SIMHASH_BITLENGTH), index: tree.xpath('count(preceding-sibling::*)').to_i } end trees.sort_by { |tree| tree[:simhash] } end |
.simhash(data) ⇒ Object
Helper methods
170 |
# File 'lib/jules.rb', line 170 def self.simhash(data); data.simhash(hashbits: Jules::SIMHASH_BITLENGTH); end |