2026-1-6

venv/Lib/site-packages/whoosh/support/levenshtein.py

@@ -0,0 +1,70 @@
+"""
+Contains functions implementing edit distance algorithms.
+"""
+
+from whoosh.compat import xrange
+
+
+def levenshtein(seq1, seq2, limit=None):
+    """Returns the Levenshtein edit distance between two strings.
+    """
+
+    oneago = None
+    thisrow = list(range(1, len(seq2) + 1)) + [0]
+    for x in xrange(len(seq1)):
+        # Python lists wrap around for negative indices, so put the
+        # leftmost column at the *end* of the list. This matches with
+        # the zero-indexed strings and saves extra calculation.
+        oneago, thisrow = thisrow, [0] * len(seq2) + [x + 1]
+        for y in xrange(len(seq2)):
+            delcost = oneago[y] + 1
+            addcost = thisrow[y - 1] + 1
+            subcost = oneago[y - 1] + (seq1[x] != seq2[y])
+            thisrow[y] = min(delcost, addcost, subcost)
+
+        if limit and x > limit and min(thisrow) > limit:
+            return limit + 1
+
+    return thisrow[len(seq2) - 1]
+
+
+def damerau_levenshtein(seq1, seq2, limit=None):
+    """Returns the Damerau-Levenshtein edit distance between two strings.
+    """
+
+    oneago = None
+    thisrow = list(range(1, len(seq2) + 1)) + [0]
+    for x in xrange(len(seq1)):
+        # Python lists wrap around for negative indices, so put the
+        # leftmost column at the *end* of the list. This matches with
+        # the zero-indexed strings and saves extra calculation.
+        twoago, oneago, thisrow = oneago, thisrow, [0] * len(seq2) + [x + 1]
+        for y in xrange(len(seq2)):
+            delcost = oneago[y] + 1
+            addcost = thisrow[y - 1] + 1
+            subcost = oneago[y - 1] + (seq1[x] != seq2[y])
+            thisrow[y] = min(delcost, addcost, subcost)
+            # This block deals with transpositions
+            if (x > 0 and y > 0 and seq1[x] == seq2[y - 1]
+                and seq1[x - 1] == seq2[y] and seq1[x] != seq2[y]):
+                thisrow[y] = min(thisrow[y], twoago[y - 2] + 1)
+
+        if limit and x > limit and min(thisrow) > limit:
+            return limit + 1
+
+    return thisrow[len(seq2) - 1]
+
+
+def relative(a, b):
+    """Returns the relative distance between two strings, in the range
+    [0-1] where 1 means total equality.
+    """
+
+    d = distance(a, b)
+    longer = float(max((len(a), len(b))))
+    shorter = float(min((len(a), len(b))))
+    r = ((longer - d) / longer) * (shorter / longer)
+    return r
+
+
+distance = damerau_levenshtein