迭代器，生成器（yield语句），正则表达式，re模块的使用

1.定义一个生成器函数，生成1-10
使用next(generator)方法获取1-10
使用for循环获取

def generator():        
    for i in range(1, 11):
        yield i
 
 
gen = generator()     
print(next(gen))
print(next(gen))
print(next(gen))
print(next(gen))
print(next(gen))
for j in gen:          
    print(j)
 
1
2
3
4
5
6
7
8
9
10
 

2.模拟range的功能，自己建立一个range:MyRange
 

class MyRange:
    def __init__(self, start, stop=None, step=1):
        if step == 0:
            raise ValueError('range() arg 3 must not be zero')
        elif stop is None:
            start, stop = 0, start
        elif step > 0:
            self.__length = max(0, ((stop - start - 1)//step)+1)
        else:
            self.__length = max(0, ((start - stop - 1)//abs(step))+1)
        self.__start = start
        self.__stop = stop
        self.__step = step
 
    def __iter__(self):
        num = self.__start
        if self.__step > 0:
            while num < self.__stop:
                yield num
                num += self.__step
        else:
            while num > self.__stop:
                yield num
                num += self.__step
 
    def __len__(self):
        return self.__length
 
    def __getitem__(self, k):
        if k < 0:
            k += self.__length
        if 0 <= k < self.__length:
            return self.__start + k*self.__step
        else:
            raise IndexError('range object index out of range')

3. re中函数的使用（正则表达式）

正则表达式(regular expression)描述了一种字符串匹配的模式（pattern），可以用来检查一个串是否含有某种子串、将匹配的子串替换或者从某个串中取出符合某个条件的子串等。
 

pattern    匹配的正则表达式

string    要匹配的字符串。

flags    标志位，用于控制正则表达式的匹配方式，如：是否区分大小写，多行匹配等等

match

re.match 尝试从字符串的起始位置匹配一个模式，如果不是起始位置匹配成功的话，match()就返回none。

import re

str_data = "apple,hello,world"
pattern = 'a'
match_obj = re.match(pattern, str_data)
print(match_obj)



<re.Match object; span=(0, 1), match='a'>

fullmatch

search

re.search 扫描整个字符串并返回第一个成功的匹配。即找到就返回

str_data = "apple,hello,world"
pattern = 'p'
match_obj = re.search(pattern, str_data)
print(match_obj)



<re.Match object; span=(1, 2), match='p'>

findall

查找所有,以列表形式返回

str_data = "apple,hello,world"
pattern = 'p'
match_obj = re.findall(pattern, str_data)
print(match_obj)



['p', 'p']

finditer

查找所有，将查找的结果的match object放入迭代器中

str_data = "apple,hello,world"
pattern = 'a'
match_obj = re.finditer(pattern, str_data)
print(match_obj.__next__())




<re.Match object; span=(0, 1), match='a'>

split

按照正则表达式进行分割，返回一个列表

str_data = "apple,hello,world"
pattern = ' '
match_obj = re.split(pattern, str_data)
print(match_obj)



['apple,hello,world']

sub

替换

count:替换次数

str_data = "apple,hello,world"
pattern = 'a'
match_obj = re.sub(pattern, 'f', str_data, 1)
print(match_obj)




fpple,hello,world

subn

count: 替换次数

str_data = "apple,hello,world"
pattern = 'a'
match_obj = re.subn(pattern, 'f', str_data, 1)
print(match_obj)


('fpple,hello,world', 1)

complie

编译，用来生成正则表达式对象

str_data = "apple,hello,world"
pattern = 'a'
match_obj = re.compile(pattern)
print(match_obj.search(str_data))



<re.Match object; span=(0, 1), match='a'>