一个衬套:

diff = lambda l1,l2: [x for x in l1 if x not in l2]
diff(A,B)
diff(B,A)

Or:

diff = lambda l1,l2: filter(lambda x: x not in l2, l1)
diff(A,B)
diff(B,A)

一个衬套:

diff = lambda l1,l2: [x for x in l1 if x not in l2]
diff(A,B)
diff(B,A)

Or:

diff = lambda l1,l2: filter(lambda x: x not in l2, l1)
diff(A,B)
diff(B,A)

上面的例子使计算差异的问题变得微不足道。假设排序或重复数据删除确实使计算差异变得更容易，但如果您的比较无法承担这些假设，那么您将需要一个diff算法的重要实现。请参阅python标准库中的difflib。

#! /usr/bin/python2
from difflib import SequenceMatcher

A = [1,2,3,4]
B = [2,5]

squeeze=SequenceMatcher( None, A, B )

print "A - B = [%s]"%( reduce( lambda p,q: p+q,
                               map( lambda t: squeeze.a[t[1]:t[2]],
                                    filter(lambda x:x[0]!='equal',
                                           squeeze.get_opcodes() ) ) ) )

或Python3…

#! /usr/bin/python3
from difflib import SequenceMatcher
from functools import reduce

A = [1,2,3,4]
B = [2,5]

squeeze=SequenceMatcher( None, A, B )

print( "A - B = [%s]"%( reduce( lambda p,q: p+q,
                               map( lambda t: squeeze.a[t[1]:t[2]],
                                    filter(lambda x:x[0]!='equal',
                                           squeeze.get_opcodes() ) ) ) ) )

输出:

A - B = [[1, 3, 4]]

当查看in -operator的TimeComplexity时，在最坏的情况下它与O(n)一起工作。即使是集合。

因此，当比较两个数组时，最好情况下的TimeComplexity为O(n)，最坏情况下为O(n²)。

另一种(但不幸的是更复杂)解决方案，在最好和最坏的情况下都适用于O(n):

# Compares the difference of list a and b
# uses a callback function to compare items
def diff(a, b, callback):
  a_missing_in_b = []
  ai = 0
  bi = 0

  a = sorted(a, callback)
  b = sorted(b, callback)

  while (ai < len(a)) and (bi < len(b)):

    cmp = callback(a[ai], b[bi])
    if cmp < 0:
      a_missing_in_b.append(a[ai])
      ai += 1
    elif cmp > 0:
      # Item b is missing in a
      bi += 1
    else:
      # a and b intersecting on this item
      ai += 1
      bi += 1

  # if a and b are not of same length, we need to add the remaining items
  for ai in xrange(ai, len(a)):
    a_missing_in_b.append(a[ai])


  return a_missing_in_b

e.g.

>>> a=[1,2,3]
>>> b=[2,4,6]
>>> diff(a, b, cmp)
[1, 3]

如果你不关心项目的顺序或重复，请使用set。使用列表推导式:

>>> def diff(first, second):
        second = set(second)
        return [item for item in first if item not in second]

>>> diff(A, B)
[1, 3, 4]
>>> diff(B, A)
[5]
>>> 

在这个线程中，我没有看到保留a中的重复的解决方案。当a中的一个元素与B中的一个元素匹配时，这个元素必须在B中删除，这样当相同的元素在a中再次出现时，如果这个元素在B中只出现一次，那么它必须出现在差异中。

def diff(first, second):
   l2 = list(second)
   l3 = []
   for el in first:
      if el in l2:
         l2.remove(el)
      else:
         l3 += [el]
   return l3

l1 = [1, 2, 1, 3, 4]
l2 = [1, 2, 3, 3]
diff(l1, l2)
>>> [1, 4]