Jaro winkler (TheAlgorithms#2041)

* Added jaro_winkler first version

* Added doctests

* Fix flake warnings

* Refactor

* Fixes bug in jaro winkler implementation

* Commit suggestions

* Missing comming suggestions

* Remove unused math module

* Import doctest

Co-authored-by: John Law <johnlaw.po@gmail.com>

Author: l3str4nge

strings/jaro_winkler.py

@@ -0,0 +1,71 @@
+"""https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance"""
+
+
+def jaro_winkler(str1: str, str2: str) -> float:
+    """
+    Jaro–Winkler distance is a string metric measuring an edit distance between two sequences.
+    Output value is between 0.0 and 1.0.
+
+    >>> jaro_winkler("martha", "marhta")
+    0.9611111111111111
+    >>> jaro_winkler("CRATE", "TRACE")
+    0.7333333333333334
+    >>> jaro_winkler("test", "dbdbdbdb")
+    0.0
+    >>> jaro_winkler("test", "test")
+    1.0
+    >>> jaro_winkler("hello world", "HeLLo W0rlD")
+    0.6363636363636364
+    >>> jaro_winkler("test", "")
+    0.0
+    >>> jaro_winkler("hello", "world")
+    0.4666666666666666
+    >>> jaro_winkler("hell**o", "*world")
+    0.4365079365079365
+    """
+
+    def get_matched_characters(_str1: str, _str2: str) -> str:
+        matched = []
+        limit = min(len(_str1), len(_str2)) // 2
+        for i, l in enumerate(_str1):
+            left = int(max(0, i - limit))
+            right = int(min(i + limit + 1, len(_str2)))
+            if l in _str2[left:right]:
+                matched.append(l)
+                _str2 = f"{_str2[0:_str2.index(l)]} {_str2[_str2.index(l) + 1:]}"
+
+        return ''.join(matched)
+
+    # matching characters
+    matching_1 = get_matched_characters(str1, str2)
+    matching_2 = get_matched_characters(str2, str1)
+    match_count = len(matching_1)
+
+    # transposition
+    transpositions = len(
+        [(c1, c2) for c1, c2 in zip(matching_1, matching_2) if c1 != c2]
+    ) // 2
+
+    if not match_count:
+        jaro = 0.0
+    else:
+        jaro = 1 / 3 * (
+            match_count / len(str1)
+            + match_count / len(str2)
+            + (match_count - transpositions) / match_count)
+
+    # common prefix up to 4 characters
+    prefix_len = 0
+    for c1, c2 in zip(str1[:4], str2[:4]):
+        if c1 == c2:
+            prefix_len += 1
+        else:
+            break
+
+    return jaro + 0.1 * prefix_len * (1 - jaro)
+
+
+if __name__ == '__main__':
+    import doctest
+    doctest.testmod()
+    print(jaro_winkler("hello", "world"))