add dynammic programming solution to edit distance

algorithms/Python/dynamic_programming/levenshtein_distance_dp.py

@@ -0,0 +1,27 @@
+
+def edit_distance(w1, w2):
+    """
+    Find edit distance (minimum number of changes) required to convert string w1 to string w2. 
+    """
+
+    m = [[0 if x != 0 else y if y != 0 else x for x in range(len(w2) + 1)] for y in range(len(w1) + 1)]
+
+    for i in range(1,len(w1) + 1):
+        m[i][0] = i 
+    for j in range(1, len(w2) + 1):
+        m[0][j] = j 
+    
+    for i in range(1, len(w1) + 1):
+        for j in range(1, len(w2) + 1):
+            m[i][j] = min(
+                m[i-1][j-1] + int(w1[i-1] != w2[j-1]),
+                m[i-1][j] + 1,
+                m[i][j-1] + 1
+            )
+    
+    return m
+
+
+if __name__ == "__main__":
+    print(edit_distance("sitting", "kitten"))
+