我有这样的代码:

good = [x for x in mylist if x in goodvals]
bad = [x for x in mylist if x not in goodvals]

目标是根据mylist的内容是否满足条件,将它们拆分为另外两个列表。

我怎样才能做得更优雅呢?我能避免在mylist上做两个单独的迭代吗?我可以通过这样做来提高性能吗?


当前回答

所有提出的解决方案的问题是,它将扫描和应用过滤功能两次。我会做一个简单的小函数,像这样:

def split_into_two_lists(lst, f):
    a = []
    b = []
    for elem in lst:
        if f(elem):
            a.append(elem)
        else:
            b.append(elem)
    return a, b

这样你就不会重复处理任何东西,也不会重复代码。

其他回答

第一步(pre-OP-edit):使用集合:

mylist = [1,2,3,4,5,6,7]
goodvals = [1,3,7,8,9]

myset = set(mylist)
goodset = set(goodvals)

print list(myset.intersection(goodset))  # [1, 3, 7]
print list(myset.difference(goodset))    # [2, 4, 5, 6]

这对可读性(IMHO)和性能都有好处。

第二步(post-OP-edit):

创建一个好的扩展列表:

IMAGE_TYPES = set(['.jpg','.jpeg','.gif','.bmp','.png'])

这将提高性能。否则,你现在的情况在我看来还不错。

这个问题已经有很多答案了,但似乎都不如我最喜欢的解决这个问题的方法,这种方法只遍历和测试每个项目一次,并使用列表理解的速度来构建两个输出列表之一,因此它只需要使用相对较慢的附加来构建一个输出列表:

bad = []
good = [x for x in mylist if x in goodvals or bad.append(x)]

In my answer to a similar question, I explain how this approach works (a combination of Python's greedy evaluation of or refraining from executing the append for "good" items, and append returning a false-like value which leaves the if condition false for "bad" items), and I show timeit results indicating that this approach outcompetes alternatives like those suggested here, especially in cases where the majority of items will go into the list built by list-comprehension (in this case, the good list).

清晰快速

这个列表理解是简单的阅读和快速。这正是上级要求的。

set_good_vals = set(good_vals)    # Speed boost.
good = [x for x in my_list if x in set_good_vals]
bad = [x for x in my_list if x not in set_good_vals]

我更喜欢一个列表理解而不是两个,但不像张贴的许多答案(其中一些相当巧妙),它是可读的和清晰的。这也是网页上最快的答案之一。

唯一(稍微)快一点的答案是:

set_good_vals = set(good_vals)
good, bad = [], []
for item in my_list:
    _ = good.append(item) if item in set_good_vals else bad.append(item)
    

...还有它的变体。(见我的另一个答案)。但我觉得第一种方法更优雅,而且几乎一样快。

def partition(pred, seq):
  return reduce( lambda (yes, no), x: (yes+[x], no) if pred(x) else (yes, no+[x]), seq, ([], []) )

我认为基于N个条件来划分一个可迭代对象是很方便的

from collections import OrderedDict
def partition(iterable,*conditions):
    '''Returns a list with the elements that satisfy each of condition.
       Conditions are assumed to be exclusive'''
    d= OrderedDict((i,list())for i in range(len(conditions)))        
    for e in iterable:
        for i,condition in enumerate(conditions):
            if condition(e):
                d[i].append(e)
                break                    
    return d.values()

例如:

ints,floats,other = partition([2, 3.14, 1, 1.69, [], None],
                              lambda x: isinstance(x, int), 
                              lambda x: isinstance(x, float),
                              lambda x: True)

print " ints: {}\n floats:{}\n other:{}".format(ints,floats,other)

 ints: [2, 1]
 floats:[3.14, 1.69]
 other:[[], None]

如果元素可以满足多个条件,则删除断点。