fuzzy_match.rb in eco-helpers-2.5.1

- old
+ new

@@ -1,9 +1,5 @@
-require 'fuzzy_match'
-require 'amatch'
-require 'jaro_winkler'
-
 require_relative 'fuzzy_match/stop_words'
 require_relative 'fuzzy_match/array_helpers'
 require_relative 'fuzzy_match/string_helpers'
 require_relative 'fuzzy_match/pairing'
 require_relative 'fuzzy_match/chars_position_score'
@@ -31,10 +27,12 @@
           return 0 if !str1 || !str2
           options = {
             ignore_case: true,
             weight:      0.25
           }.merge(options)
+
+          require 'jaro_winkler'
           JaroWinkler.distance(str1, str2, **options)
         end
 
       end
 
@@ -61,11 +59,14 @@
         def fuzzy_match(haystack_data = nil, **options)
           if instance_variable_defined?(:@fuzzy_match) && !haystack_data
             return @fuzzy_match if fuzzy_match_options == fuzzy_match_options(options)
           end
           @fuzzy_options = options
+
           # make it run with a native C extension (for better performance: ~130 % increase of performance)
+          require 'fuzzy_match'
+          require 'amatch'
           ::FuzzyMatch.engine = :amatch
           @fuzzy_match = ::FuzzyMatch.new(haystack(haystack_data), fuzzy_match_options)
         end
 
         # TODO: integration for options[:unique_words] => to ensure repeated words do not bring down the score are cut by threshold
@@ -113,10 +114,13 @@
               unless istr = needle_str
                 dice = lev = jaro_res = ngram_res = ngram_res = wngram_res = pos_res  = 0
               end
             end
 
+            require 'fuzzy_match'
+            require 'amatch'
             res          = ::FuzzyMatch.score_class.new(nstr, istr) unless dice && lev
+            
             dice       ||= res&.dices_coefficient_similar || 0
             lev        ||= res&.levenshtein_similar       || 0
             jaro_res   ||= jaro(nstr, istr)
             ngram_res  ||= ngram(nstr, istr)
             wngram_res ||= words_ngram(nstr, istr)