Add Jaro-Winkler regression tests and a large-input benchmark

Preserve all eight existing examples and append three regressions that fail before the fix. Add an optional 2,000-character timing comparison without changing the production implementation.

Author: dhairyajangir

strings/jaro_winkler.py

@@ -23,6 +23,16 @@ def jaro_winkler(str1: str, str2: str) -> float:
     0.4666666666666666
     >>> jaro_winkler("hell**o", "*world")
     0.4365079365079365
+
+    Matched positions cannot be reused as literal spaces.
+    >>> round(jaro_winkler("aa ", "aa"), 6)
+    0.911111
+    >>> round(jaro_winkler("a a", "aa"), 6)
+    0.9
+
+    Repeated characters must be consumed inside the matching window.
+    >>> round(jaro_winkler("aabb", "bab"), 6)
+    0.722222
     """
 
     def get_matched_characters(_str1: str, _str2: str) -> str:
@@ -76,6 +86,26 @@ def get_matched_characters(_str1: str, _str2: str) -> str:
 
 if __name__ == "__main__":
     import doctest
+    import sys
+    from timeit import repeat
 
     doctest.testmod()
     print(jaro_winkler("hello", "world"))
+
+    # Run with --benchmark on each revision using the same 2,000-character inputs.
+    if "--benchmark" in sys.argv:
+        size = 2000
+        cases = (
+            ("identical", "a" * size, "a" * size),
+            ("no matches", "a" * size, "b" * size),
+            ("trailing space", "a" * (size - 1) + " ", "a" * (size - 1)),
+        )
+        for name, first, second in cases:
+            score = jaro_winkler(first, second)
+            timings = repeat(
+                "jaro_winkler(first, second)", repeat=5, number=1, globals=globals()
+            )
+            print(
+                f"{name}, {len(first)}/{len(second)} characters: "
+                f"{min(timings):.6f} seconds (best of 5), score={score}"
+            )