1 使用%来格式字符串
2 使用zip来将两个list构造为一个dict
ages = [23, 40]
m = dict(zip(names,ages))
print (m)
3 不使用临时变量来交换两个值
4 使用str.join来连接字符串
result = ''.join(fruits)
5 使用in dict.keys()来判断dict中是否包含指定的key
if 1 in d.keys():
print("d dict has the key 1")
6 使用set来去除list中的重复元素
l2 = set(l)
print(l2)
7 对于in操作，set要快于list，因为set是使用hash来存储和查找的
8 使用with来读写文件，保证file对象的释放
for line in f:
print (line)
f.readline() #f is cleanup here, here will get ValueError exception
9 使用emumerate来遍历list
for index, value in enumerate(l):
print ('%d, %d' % (index, value))
10 分割字符串且去掉空白
result = [name for name in names.split(',') if name.strip()]
11 python中的a?b:c
12 Zen of python
The Zen of Python, by Tim Peters
Beautiful
is better than ugly.Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!
>>>
13 匿名函数lambda
print(add(1,2))
14 filter(bool_func,seq)，在python3以后，filter为类，filter的功能相当于过滤器。调用一个布尔函数bool_func来迭代遍历每个seq中的元素；返回一个使bool_seq返回值为true的元素的序列。
等价于(item for item in iterable if function(item)) 如果function不是None；等价于(item for item in iterable if item) 如果函数是None。
b=filter(None, a)
print (list(b))
c=filter(lambda x : x %2 == 0, a)
print(list(c))
d=filter(lambda x:x>5, a)
print (list(d))
#[1, 2, 3, 4, 5, 6, 7]
#[0, 2, 4, 6]
#[6, 7]
15 map(func,seq1[,seq2...])：在python3以后，map为类，map将函数func作用于给定序列的每个元素，并用一个列表来提供返回值；如果func为None，func表现为身份函数，返回一个含有每个序列中元素集合的n个元组的列表。
m = map(lambda x:x+3, a)
print(list(m))
#[3, 4, 5, 6, 7, 8, 9, 10]
16 reduce(func,seq[,init])：在python3以后，reduce一到functools模块下，func为二元函数，将func作用于seq序列的元素，每次携带一对（先前的结果以及下一个序列的元素），连续的将现有的结果和下一个值作用在获得的随后的结果上，最后减少我们的序列为一个单一的返回值：如果初始值init给定，第一个比较会是init和第一个序列元素而不是序列的头两个元素。
a = [1,2,3,4,5]
s = functools.reduce(lambda x,y:x+y,a)
print(s)
#15
17 range用来返回一个list
for index in range(len(strings)):
print (index)
# prints '0 1 2 3 4'
18 all用来检查list中所有的元素都满足一定的条件
if all(number < 10 for number in numbers):
print ("Success!")
# Output: 'Success!'
19 any用来检查list中是否至少由一个元素满足一定的条件
if any(number < 0 for number in numbers):
print ('Success!')
else:
print('Fail!')
# Output: 'Fail!'
20 使用set来检查list是否有重复的元素
if len(numbers) == len(set(numbers)):
print ('List is unique!')
# In this case, doesn't print anything
21 从已有的dict构造新的dict
email_at_dotcom = dict( [name, '.com' in email] for name, email in emails.items() )
print(email_at_dotcom)
# email_at_dotcom now is {'Dick': True, 'Jane': True, 'Stou': False}
22 And+or的执行过程
对于and语句，如果and左边的是true，and右边的值将被返回作为and的结果。
对于or语句，如果or左边的是false，or将右边的值将被返回作为or的结果。
# test = False
result = test and 'Test is True' or 'Test is False'
print(result)
# result is now 'Test is True'
23 检查字符串是否包含子字符串
# string = 'Good bye' # False example
if string.find('Hi') != -1:
print ("Success!")
string
= 'Hi there' # True example# string = 'Good bye' # False example
if 'Hi' in string:
print ('Success!')
24 从list构造新的list
squares_under_10 = (number*number for number in numbers if number*number < 10)
# squares_under_10 is now a generator object, from which each successive value can be gotten by calling .next()
for square in squares_under_10:
print ( square)
# prints '1 4 9'
参考：
http://www.siafoo.net/article/52#id26
http://jeffxie.blog.chinabyte.com/2010/06/08/10/
http://jianpx.javaeye.com/blog/736669
完！