flog = open('test.txt', 'r')
flogLines = flog.readlines()
strlist = ['SUCCESS', 'Done','SUCCESSFUL']
res = False
for line in flogLines:
     for fstr in strlist:
         if line.find(fstr) != -1:
            print('found') 
            res = True


if res:
    print('res true')
else: 
    print('res false')

的元素上进行迭代。

a = ['a', 'b', 'c']
str = "a123"
found_a_string = False
for item in a:    
    if item in str:
        found_a_string = True

if found_a_string:
    print "found a match"
else:
    print "no match found"

这是set的另一个解。使用set.intersection。对于一行代码。

subset = {"some" ,"words"} 
text = "some words to be searched here"
if len(subset & set(text.split())) == len(subset):
   print("All values present in text")

if subset & set(text.split()):
   print("Atleast one values present in text")

a = ['a', 'b', 'c']
str =  "a123"

a_match = [True for match in a if match in str]

if True in a_match:
  print "some of the strings found in str"
else:
  print "no strings found in str"

为了降低复杂度，jbernadas已经提到了aho - corasick -算法。

下面是在Python中使用它的一种方法:

从这里下载aho_corasick.py 将它放在与Python主文件相同的目录中，并将其命名为aho_corasick.py 用以下代码尝试该算法: 导入aho_corasick #(字符串，关键字) Print (aho_corasick(string， ["keyword1"， "keyword2"]))

注意，搜索是区分大小写的

一个惊人的快速方法是使用set:

a = ['a', 'b', 'c']
str = "a123"
if set(a) & set(str):
    print("some of the strings found in str")
else:
    print("no strings found in str")

如果a不包含任何多字符值(在这种情况下使用上面列出的any)，则此方法有效。如果是这样，将a指定为字符串会更简单:a = 'abc'。