add extract + handle Missing

README.md

@@ -99,6 +99,13 @@ evaluate(Levenshtein(), "New York", "New York")
 #> 0
 ```
 
+## Extract
+An experimental `extract` funciton finds the best match in an iterator of AbstractStrings:
+```julia
+extract("New York", ["NewYork", "Newark", "San Francisco"], Levenshtein()) = "NewYork"
+```
+The function works for `Levenshtein`, `DamerauLevenshtein`, possibly modified by `Partial`, `TokenSort`, `TokenSet`, `TokenMax`
+
 ## Which distance should I use?
 
 As a rule of thumb, 

benchmark/.sublime2Terminal.jl

@@ -1 +1 @@
-@time f(DamerauLevenshtein(), x, y)
+@time extract.(x[1:10], Ref(y), Ref(DamerauLevenshtein()))

benchmark/benchmark.jl

@@ -7,15 +7,13 @@ y = map(Random.randstring, rand(5:25,500_000))
 function f(t, x, y; min_dist = nothing)
     [compare(x[i], y[i], t; min_dist = min_dist) for i in 1:length(x)]
 end
-function f(t, x, y; min_dist = nothing)
-    [evaluate(t, x[i], y[i]; min_dist = min_dist) for i in 1:length(x)]
-end
+
 @time f(Hamming(), x, y)
+#0.1s
 @time f(Jaro(), x, y)
-
-
+#0.3s
 @time f(Levenshtein(), x, y)
-# 0.3s. A bit faster than StringDist
+# 0.35s. A bit faster than StringDist
 @time f(Levenshtein(), x, y, min_dist = 0.8)
 @time f(DamerauLevenshtein(), x, y)
 @time f(DamerauLevenshtein(), x, y, min_dist = 0.8)

src/StringDistances.jl

@@ -26,7 +26,8 @@ Partial,
 TokenSort,
 TokenSet,
 TokenMax,
-qgram
+qgram,
+extract
 
 ##############################################################################
 ##

src/compare.jl

@@ -9,7 +9,6 @@
 
 compare returns a similarity score between the strings `s1` and `s2` based on the distance `dist`
 """
-
 function compare(s1::AbstractString, s2::AbstractString, 
     dist::Union{Hamming, Levenshtein, DamerauLevenshtein}; min_dist = nothing)
     s1, s2 = reorder(s1, s2)
@@ -43,6 +42,16 @@ end
 
 @deprecate compare(dist::PreMetric, s1::AbstractString, s2::AbstractString) compare(s1, s2, dist)
 
+# Handle missing values
+function compare(s1::AbstractString, ::Missing, dist::PreMetric; min_dist = nothing)
+    missing
+end
+function compare(::Missing, s2::AbstractString, dist::PreMetric; min_dist = nothing)
+    missing
+end
+function compare(::Missing, ::Missing, dist::PreMetric; min_dist = nothing)
+    missing
+end
 ##############################################################################
 ##
 ## Winkler
@@ -218,4 +227,26 @@ function compare(s1::AbstractString, s2::AbstractString, dist::TokenMax; min_dis
                 ptsor * unbase_scale, 
                 ptser * unbase_scale)
     end
-end
+end
+
+##############################################################################
+##
+## Extract
+##
+##############################################################################
+function extract(s1::AbstractString, iter_s2, dist::Union{T, Partial{T}, TokenSort{T}, TokenSet{T}, TokenMax{T}}) where T <: Union{Levenshtein, DamerauLevenshtein}
+    best_score = 0.0
+    best_s2 = nothing
+    for s2 in iter_s2
+        score = compare(s1, s2, dist; min_dist = best_score)
+        if (score !== missing) && (score > best_score)
+            best_s2 = s2
+            best_score = score
+        end
+    end
+    return best_s2
+end
+function extract(::Missing, iter_s2, dist::Union{T, Partial{T}, TokenSort{T}, TokenSet{T}, TokenMax{T}}) where T <: Union{Levenshtein, DamerauLevenshtein}
+    missing
+end
+

test/modifiers.jl

@@ -145,3 +145,14 @@ s1 = SubString(s1, 1, 4)
 s2 = SubString(s2, 1, 4)
 dist = QGram(2)
 @test evaluate(dist, s1, s2) == 2
+
+
+# check missing
+@test compare(s1, missing, Levenshtein()) === missing
+
+# check extract
+@test extract("New York", ["NewYork", "Newark", "San Francisco"], Levenshtein()) == "NewYork"
+@test extract("New York", ["NewYork", "Newark", missing], Levenshtein()) == "NewYork"
+@test extract("New York", [missing, "NewYork", "Newark"], Levenshtein()) == "NewYork"
+
+