这是计算 Levenshtein 距离的通用算法的教科书示例（我从Magnus Hetland 的网站中提取）：
def levenshtein(a,b):
"Calculates the Levenshtein distance between a and b."
n, m = len(a), len(b)
if n > m:
# Make sure n <= m, to use O(min(n,m)) space
a,b = b,a
n,m = m,n
current = range(n+1)
for i in range(1,m+1):
previous, current = current, [i]+[0]*n
for j in range(1,n+1):
add, delete = previous[j]+1, current[j-1]+1
change = previous[j-1]
if a[j-1] != b[i-1]:
change = change + 1
current[j] = min(add, delete, change)
return current[n]
但是，我想知道是否可能存在使用 difflib 的 SequenceManager 的更高效（并且可能更优雅）的纯 Python 实现。在玩了它之后，这就是我想出的：
from difflib import SequenceMatcher as sm
def lev_using_difflib(s1, s2):
a = b = size = distance = 0
for m in sm(a=s1, b=s2).get_matching_blocks():
distance += max(m.a-a, m.b-b) - size
a, b, size = m
return distance
我想不出一个失败的测试用例，而且性能似乎明显优于标准算法。
以下是依赖 difflib 的 levenshtein 算法的结果：
>>> from timeit import Timer
>>> setup = """
... from difflib import SequenceMatcher as sm
...
... def lev_using_difflib(s1, s2):
... a = b = size = distance = 0
... for m in sm(a=s1, b=s2).get_matching_blocks():
... distance += max(m.a-a, m.b-b) - size
... a, b, size = m
... return distance
...
... strings = [('sunday','saturday'),
... ('fitting','babysitting'),
... ('rosettacode','raisethysword')]
... """
>>> stmt = """
... for s in strings:
... lev_using_difflib(*s)
... """
>>> Timer(stmt, setup).timeit(100000)
36.989389181137085
这是标准的纯python实现：
>>> from timeit import Timer
>>> setup2 = """
... def levenshtein(a,b):
... n, m = len(a), len(b)
... if n > m:
... a,b = b,a
... n,m = m,n
...
... current = range(n+1)
... for i in range(1,m+1):
... previous, current = current, [i]+[0]*n
... for j in range(1,n+1):
... add, delete = previous[j]+1, current[j-1]+1
... change = previous[j-1]
... if a[j-1] != b[i-1]:
... change = change + 1
... current[j] = min(add, delete, change)
...
... return current[n]
...
... strings = [('sunday','saturday'),
... ('fitting','babysitting'),
... ('rosettacode','raisethysword')]
... """
>>> stmt2 = """
... for s in strings:
... levenshtein(*s)
... """
>>> Timer(stmt2, setup2).timeit(100000)
55.594768047332764
使用 difflib 的 SequenceMatcher 算法的性能真的更好吗？或者它是否依赖于完全使比较无效的 C 库？如果它依赖于 C 扩展，我如何通过查看 difflib.py 实现来判断？
使用 Python 2.7.3 [GCC 4.2.1 (Apple Inc. build 5666)]
在此先感谢您的帮助！