使用Python的集合交集:

>>> list1 = [1,2,3,4,5,6]
>>> list2 = [3, 5, 7, 9]
>>> list(set(list1).intersection(list2))
[3, 5]

使用集合交叉，set(list1) & set(list2)

>>> def common_elements(list1, list2):
...     return list(set(list1) & set(list2))
...
>>>
>>> common_elements([1,2,3,4,5,6], [3,5,7,9])
[3, 5]
>>>
>>> common_elements(['this','this','n','that'],['this','not','that','that'])
['this', 'that']
>>>
>>>

注意，结果列表可能与原始列表顺序不同。

S.Mark和SilentGhost建议的解决方案通常会告诉您应该如何以Pythonic方式完成，但我认为您也可以从了解为什么您的解决方案不起作用中受益。问题是，一旦找到两个列表中的第一个公共元素，就只返回该元素。您的解决方案可以通过创建一个结果列表并收集该列表中的公共元素来修复:

def common_elements(list1, list2):
    result = []
    for element in list1:
        if element in list2:
            result.append(element)
    return result

一个使用列表推导式的更简短的版本:

def common_elements(list1, list2):
    return [element for element in list1 if element in list2]

然而，正如我所说，这是一种非常低效的方式——Python的内置集类型更高效，因为它们是在C内部实现的。

前面的答案都可以找到唯一的公共元素，但不能解释列表中重复的项目。如果你想让公共元素在列表中以相同的数字出现，你可以使用下面的一行代码:

l2, common = l2[:], [ e for e in l1 if e in l2 and (l2.pop(l2.index(e)) or True)]

或True部分仅在您希望任何元素求值为False时才需要。

1) Method1 保存list1是字典，然后迭代list2中的每个elem

def findarrayhash(a,b):
    h1={k:1 for k in a}
    for val in b:
        if val in h1:
            print("common found",val)
            del h1[val]
        else:
            print("different found",val)
    for key in h1.iterkeys():
        print ("different found",key)

找到共同和不同的元素:

2) Method2 使用设置

def findarrayset(a,b):
    common = set(a)&set(b)
    diff=set(a)^set(b)
    print list(common)
    print list(diff) 

您还可以使用集合并在一行中获得共性:从其中一个集合中减去包含差异的集合。

A = [1,2,3,4]
B = [2,4,7,8]
commonalities = set(A) - (set(A) - set(B))

集合是另一种解法

a = [3,2,4]
b = [2,3,5]
set(a)&set(b)
{2, 3}

使用发电机:

common = (x for x in list1 if x in list2)

这样做的好处是，即使在使用庞大的列表或其他庞大的可迭代对象时，它也会在常数时间内(几乎立即)返回生成器。

例如,

list1 =  list(range(0,10000000))
list2=list(range(1000,20000000))
common = (x for x in list1 if x in list2)

对于list1和list2的这些值，这里的所有其他答案都将花费很长时间。

然后，您可以用

for i in common: print(i)

我比较了每个答案提到的每一种方法。目前，我使用python 3.6.3来实现这个功能。这是我使用的代码:

import time
import random
from decimal import Decimal


def method1():
    common_elements = [x for x in li1_temp if x in li2_temp]
     print(len(common_elements))


def method2():
    common_elements = (x for x in li1_temp if x in li2_temp)
    print(len(list(common_elements)))


def method3():
    common_elements = set(li1_temp) & set(li2_temp)
    print(len(common_elements))


def method4():
    common_elements = set(li1_temp).intersection(li2_temp)
    print(len(common_elements))


if __name__ == "__main__":
    li1 = []
    li2 = []
    for i in range(100000):
        li1.append(random.randint(0, 10000))
        li2.append(random.randint(0, 10000))

    li1_temp = list(set(li1))
    li2_temp = list(set(li2))

    methods = [method1, method2, method3, method4]
    for m in methods:
        start = time.perf_counter()
        m()
        end = time.perf_counter()
        print(Decimal((end - start)))

如果你运行这段代码，你可以看到如果你使用列表或生成器(如果你迭代生成器，而不是仅仅使用它)。当我强迫生成器打印它的长度时，我这样做了)，你会得到几乎相同的性能。但是如果你使用set，你会得到更好的性能。如果你使用交叉方法你会得到更好的性能。在我的电脑中，每种方法的结果如下:

method1: 0.8150673999999999974619413478649221360683441 method2: 0.8329545000000001531148541289439890533685684 method3: 0.0016547000000000089414697868051007390022277 method4: 0.0010262999999999244948867271887138485908508

你可以使用numpy来解决这个问题:

import numpy as np

list1 = [1, 2, 3, 4, 5, 6]
list2 = [3, 5, 7, 9]

common_elements = np.intersect1d(list1, list2)
print(common_elements)

Common_elements将是numpy数组:[3 5]。

这里有一些解决方案是在O(l1+l2)不计算重复项目，而缓慢的解决方案(至少O(l1*l2)，但可能更昂贵)确实考虑重复项目。

所以我想我应该添加一个O(l1*log(l1)+l2*(log(l2))解。如果列表已经排序，这尤其有用。

def common_elems_with_repeats(first_list, second_list):
    first_list = sorted(first_list)
    second_list = sorted(second_list)
    marker_first = 0
    marker_second = 0
    common = []
    while marker_first < len(first_list) and marker_second < len(second_list):
        if(first_list[marker_first] == second_list[marker_second]):
            common.append(first_list[marker_first])
            marker_first +=1
            marker_second +=1
        elif first_list[marker_first] > second_list[marker_second]:
            marker_second += 1
        else:
            marker_first += 1
    return common

另一个更快的解决方案包括从list1创建一个item->计数映射，并遍历list2，同时更新映射和计数。不需要排序。需要额外的内存，但技术上是O(l1+l2)

如果list1和list2是无序的:

使用交叉:

print((set(list1)).intersection(set(list2)))

合并列表并检查元素的出现次数是否大于1:

combined_list = list1 + list2
set([num for num in combined_list if combined_list.count(num) > 1])

类似于上面，但不使用set:

for num in combined_list:
    if combined_list.count(num) > 1:
        print(num)
        combined_list.remove(num)

对于排序列表，没有python特殊的内置，一个O(n)解决方案

p1 = 0
p2 = 0
result = []
while p1 < len(list1) and p2 < len(list2):
    if list1[p1] == list2[p2]:
        result.append(list1[p1])
        p1 += 1
        p2 += 2
    elif list1[p1] > list2[p2]:
        p2 += 1
    else:
        p1 += 1
print(result)

我已经制定出了深度交叉口的完整解决方案

def common_items_dict(d1, d2, use_set_for_list_commons=True, use_set_for_dict_key_commons=True, append_empty=False):
    result = {}
    if use_set_for_dict_key_commons:
        shared_keys=list(set(d1.keys()).intersection(d2.keys())) # faster, order not preserved
    else:
        shared_keys=common_items_list(d1.keys(), d2.keys(), use_set_for_list_commons=False)

    for k in  shared_keys:
        v1 = d1[k]
        v2 = d2[k]
        if isinstance(v1, dict) and isinstance(v2, dict):
            result_dict=common_items_dict(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
            if len(result_dict)>0 or append_empty:
                result[k] = result_dict 
        elif isinstance(v1, list) and isinstance(v2, list):
            result_list=common_items_list(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
            if len(result_list)>0 or append_empty:
                result[k] = result_list 
        elif v1 == v2:
            result[k] = v1
    return result

def common_items_list(d1, d2, use_set_for_list_commons=True, use_set_for_dict_key_commons=True, append_empty=False):
    if use_set_for_list_commons: 
        result_list= list(set(d2).intersection(d1)) # faster, order not preserved, support only simple data types in list values
        return result_list

    result = []
    for v1 in d1: 
        for v2 in d2:
            if isinstance(v1, dict) and isinstance(v2, dict):
                result_dict=common_items_dict(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
                if len(result_dict)>0 or append_empty:
                    result.append(result_dict)
            elif isinstance(v1, list) and isinstance(v2, list):
                result_list=common_items_list(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
                if len(result_list)>0 or append_empty:
                    result.append(result_list)
            elif v1 == v2:
                result.append(v1)
    return result


def deep_commons(v1,v2, use_set_for_list_commons=True, use_set_for_dict_key_commons=True, append_empty=False):
    """
    deep_commons
     returns intersection of items of dict and list combinations recursively

    this function is a starter function, 
    i.e. if you know that the initial input is always dict then you can use common_items_dict directly
    or if it is a list you can use common_items_list directly

    v1 - dict/list/simple_value
    v2 - dict/list/simple_value
    use_set_for_dict_key_commons - bool - using set is faster, dict key order is not preserved 
    use_set_for_list_commons - bool - using set is faster, list values order not preserved, support only simple data types in list values
    append_empty - bool - if there is a common key, but no common items in value of key , if True it keeps the key with an empty list of dict

    """

    if isinstance(v1, dict) and isinstance(v2, dict):
        return common_items_dict(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
    elif isinstance(v1, list) and isinstance(v2, list):
        return common_items_list(v1, v2, use_set_for_list_commons, use_set_for_dict_key_commons, append_empty)
    elif v1 == v2:
        return v1
    else:
        return None


needed_services={'group1':['item1','item2'],'group3':['item1','item2']}
needed_services2={'group1':['item1','item2'],'group3':['item1','item2']}

result=deep_commons(needed_services,needed_services2)

print(result)

list1=[123,324523,5432,311,23]
list2=[2343254,34234,234,322123,123,234,23]
common=[]
def common_elements(list1,list2):
    for x in range(0,len(list1)):
        if list1[x] in list2:
            common.append(list1[x])
            
common_elements(list1,list2)
print(common)