另一个解决方案(不是pythonic,但速度非常快)是使用string.translate-
尽管请注意,这不适用于unipre。还值得注意的是,您可以通过将字符移动到集合(通过哈希查找,而不是每次都执行线性搜索)中来加快Dana的代码。以下是我给出的各种解决方案的时间安排:
import string, re, timeit# Precomputed values (for str_join_set and translate)letter_set = frozenset(string.ascii_lowercase + string.ascii_uppercase)tab = string.maketrans(string.ascii_lowercase + string.ascii_uppercase, string.ascii_lowercase * 2)deletions = ''.join(ch for ch in map(chr,range(256)) if ch not in letter_set)s="A235th@#$&( er Ra{}|?>ndom"# From unwind's filter approachdef test_filter(s): return filter(lambda x: x in string.ascii_lowercase, s.lower())# using set instead (and contains)def test_filter_set(s): return filter(letter_set.__contains__, s).lower()# Tomalak's solutiondef test_regex(s): return re.sub('[^a-z]', '', s.lower())# Dana'sdef test_str_join(s): return ''.join(c for c in s.lower() if c in string.ascii_lowercase)# Modified to use a set.def test_str_join_set(s): return ''.join(c for c in s.lower() if c in letter_set)# Translate approach.def test_translate(s): return string.translate(s, tab, deletions)for test in sorted(globals()): if test.startswith("test_"): assert globals()[test](s)=='atherrandom' print "%30s : %s" % (test, timeit.Timer("f(s)", "from __main__ import %s as f, s" % test).timeit(200000))
这给了我:
test_filter : 2.57138351271test_filter_set : 0.981806765698 test_regex : 3.10069885233 test_str_join : 2.87172979743 test_str_join_set : 2.43197956381 test_translate : 0.335367566218
[编辑]还更新了过滤器解决方案。(请注意,
set.__contains__此处使用的区别很大,因为它避免了对lambda进行额外的函数调用。
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