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Task/Jaro-Winkler-distance/Python/jaro-winkler-distance.py

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+"""
+Test Jaro-Winkler distance metric.
+linuxwords.txt is from http://users.cs.duke.edu/~ola/ap/linuxwords
+"""
+
+WORDS = [s.strip() for s in open("linuxwords.txt").read().split()]
+MISSPELLINGS = [
+    "accomodate​",
+    "definately​",
+    "goverment",
+    "occured",
+    "publically",
+    "recieve",
+    "seperate",
+    "untill",
+    "wich",
+]
+
+def jaro_winkler_distance(st1, st2):
+    """
+    Compute Jaro-Winkler distance between two strings.
+    """
+    if len(st1) < len(st2):
+        st1, st2 = st2, st1
+    len1, len2 = len(st1), len(st2)
+    if len2 == 0:
+        return 0.0
+    delta = max(0, len2 // 2 - 1)
+    flag = [False for _ in range(len2)]  # flags for possible transpositions
+    ch1_match = []
+    for idx1, ch1 in enumerate(st1):
+        for idx2, ch2 in enumerate(st2):
+            if idx2 <= idx1 + delta and idx2 >= idx1 - delta and ch1 == ch2 and not flag[idx2]:
+                flag[idx2] = True
+                ch1_match.append(ch1)
+                break
+
+    matches = len(ch1_match)
+    if matches == 0:
+        return 1.0
+    transpositions, idx1 = 0, 0
+    for idx2, ch2 in enumerate(st2):
+        if flag[idx2]:
+            transpositions += (ch2 != ch1_match[idx1])
+            idx1 += 1
+
+    jaro = (matches / len1 + matches / len2 + (matches - transpositions/2) / matches) / 3.0
+    commonprefix = 0
+    for i in range(min(4, len2)):
+        commonprefix += (st1[i] == st2[i])
+
+    return 1.0 - (jaro + commonprefix * 0.1 * (1 - jaro))
+
+def within_distance(maxdistance, stri, maxtoreturn):
+    """
+    Find words in WORDS of closeness to stri within maxdistance, return up to maxreturn of them.
+    """
+    arr = [w for w in WORDS if jaro_winkler_distance(stri, w) <= maxdistance]
+    arr.sort(key=lambda x: jaro_winkler_distance(stri, x))
+    return arr if len(arr) <= maxtoreturn else arr[:maxtoreturn]
+
+for STR in MISSPELLINGS:
+    print('\nClose dictionary words ( distance < 0.15 using Jaro-Winkler distance) to "',
+          STR, '" are:\n        Word   |  Distance')
+    for w in within_distance(0.15, STR, 5):
+        print('{:>14} | {:6.4f}'.format(w, jaro_winkler_distance(STR, w)))