diff options
Diffstat (limited to 'background_scripts/completion.coffee')
| -rw-r--r-- | background_scripts/completion.coffee | 97 |
1 files changed, 60 insertions, 37 deletions
diff --git a/background_scripts/completion.coffee b/background_scripts/completion.coffee index c8650f45..fee4778a 100644 --- a/background_scripts/completion.coffee +++ b/background_scripts/completion.coffee @@ -346,29 +346,31 @@ class SearchEngineCompleter suggestions[0].autoSelect = true queryTerms = queryTerms[1..] - # For custom search-engine queries, this adds suggestions only if we have a completer. For other queries, - # this adds suggestions for the default search engine (if we have a completer for that). - SearchEngines.complete searchUrl, queryTerms, (searchSuggestions = []) => - - # Scoring: - # - The score does not depend upon the actual suggestion (so, it does not depend upon word relevancy). - # We assume that the completion engine has already factored that in. - # - The score is higher if the query is longer. The idea is that search suggestions are more likely - # to be relevant if, after typing quite some number of characters, the user hasn't yet found a - # useful suggestion from another completer. - # - Scores are weighted such that they retain the ordering provided by the completion engine. - characterCount = query.length - queryTerms.length + 1 - score = 0.8 * (Math.min(characterCount, 12.0)/12.0) - - for suggestion in searchSuggestions - suggestions.push @mkSuggestion true, queryTerms, type, mkUrl(suggestion), suggestion, @computeRelevancy, score - score *= 0.9 - - if custom - for suggestion in suggestions - suggestion.reinsertPrefix = "#{keyword} " if suggestion.insertText - - onComplete suggestions + onComplete suggestions, (onComplete) => + suggestions = [] + # For custom search-engine queries, this adds suggestions only if we have a completer. For other queries, + # this adds suggestions for the default search engine (if we have a completer for that). + SearchEngines.complete searchUrl, queryTerms, (searchSuggestions = []) => + + # Scoring: + # - The score does not depend upon the actual suggestion (so, it does not depend upon word relevancy). + # We assume that the completion engine has already factored that in. + # - The score is higher if the query is longer. The idea is that search suggestions are more likely + # to be relevant if, after typing quite some number of characters, the user hasn't yet found a + # useful suggestion from another completer. + # - Scores are weighted such that they retain the ordering provided by the completion engine. + characterCount = query.length - queryTerms.length + 1 + score = 0.8 * (Math.min(characterCount, 12.0)/12.0) + + for suggestion in searchSuggestions + suggestions.push @mkSuggestion true, queryTerms, type, mkUrl(suggestion), suggestion, @computeRelevancy, score + score *= 0.9 + + if custom + for suggestion in suggestions + suggestion.reinsertPrefix = "#{keyword} " if suggestion.insertText + + onComplete suggestions mkSuggestion: (insertText, args...) -> suggestion = new Suggestion args... @@ -410,9 +412,11 @@ class SearchEngineCompleter # A completer which calls filter() on many completers, aggregates the results, ranks them, and returns the top # 10. Queries from the vomnibar frontend script come through a multi completer. class MultiCompleter - constructor: (@completers) -> @maxResults = 10 + constructor: (@completers) -> + @maxResults = 10 - refresh: -> completer.refresh() for completer in @completers when completer.refresh + refresh: -> + completer.refresh?() for completer in @completers filter: (queryTerms, onComplete) -> # Allow only one query to run at a time. @@ -424,21 +428,40 @@ class MultiCompleter @filterInProgress = true suggestions = [] completersFinished = 0 + continuation = null for completer in @completers # Call filter() on every source completer and wait for them all to finish before returning results. - completer.filter queryTerms, (newSuggestions) => - suggestions = suggestions.concat(newSuggestions) - completersFinished += 1 - if completersFinished >= @completers.length - results = @sortSuggestions(suggestions)[0...@maxResults] - result.generateHtml() for result in results - onComplete(results) - @filterInProgress = false - @filter(@mostRecentQuery.queryTerms, @mostRecentQuery.onComplete) if @mostRecentQuery - - sortSuggestions: (suggestions) -> - suggestion.computeRelevancy(@queryTerms) for suggestion in suggestions + # At most one of the completers (SearchEngineCompleter) may pass a continuation function, which will be + # called asynchronously after the results of all of the other completers have been posted. Any + # additional results from this continuation will be added to the existing results and posted. We don't + # call the continuation if another query is already waiting. + completer.filter queryTerms, (newSuggestions, cont = null) => + # Allow completers to execute concurrently. + Utils.nextTick => + suggestions = suggestions.concat newSuggestions + continuation = cont if cont? + completersFinished += 1 + if completersFinished >= @completers.length + onComplete @prepareSuggestions(suggestions), keepAlive: continuation? + onDone = => + @filterInProgress = false + @filter @mostRecentQuery.queryTerms, @mostRecentQuery.onComplete if @mostRecentQuery + # We add a very short delay. It is possible for all of this processing to have been handled + # pretty-much synchronously, which would have prevented any newly-arriving queries from + # registering. + Utils.setTimeout 10, => + if continuation? and not @mostRecentQuery + continuation (newSuggestions) => + onComplete @prepareSuggestions suggestions.concat(newSuggestions) + onDone() + else + onDone() + + prepareSuggestions: (suggestions) -> + suggestion.computeRelevancy @queryTerms for suggestion in suggestions suggestions.sort (a, b) -> b.relevancy - a.relevancy + suggestions = suggestions[0...@maxResults] + suggestion.generateHtml() for suggestion in suggestions suggestions # Utilities which help us compute a relevancy score for a given item. |