python 魔术方法

import time
func_count_time_dict = {}
def count_time(func):
    global func_count_time_dict
    func_count_time_dict[func]=[1,time.localtime()]
    def wrapper():

        global func_count_time_dict
        func()
        print ‘func name: ‘,func.__name__
        print ‘count: ‘,func_count_time_dict[func][0]
        print ‘last call time: ‘,time.asctime(func_count_time_dict[func][1])

        func_count_time_dict[func][0]+=1
        func_count_time_dict[func][1]=time.localtime()

    return wrapper

@count_time
def foo():
    print ‘in foo()‘

@count_time
def foo_1():
    print ‘in foo_1‘

foo_1()
foo_1()
foo_1()

foo()

foo_1()
foo()
foo()

foo_1()

class MyIterator(object):
    def __init__(self, data_iter):
        self.data_iter = data_iter
        self.start = 0

    def __iter__(self):
        return self  

    def next(self):
        print self.start
        if self.start >= len(self.data_iter):
            raise StopIteration
        ans = self.data_iter[self.start]
        self.start += 1
        return ans

if __name__ == "__main__":
    iter = MyIterator(range(10))
    for i in iter:
        print i

def fib(max):
    a, b = 0, 1
    while a < max:
        yield a
        a, b = b, a + b  

for i in fib(1000):
    print(i)

map_output = map(lambda x: 2 * x, range(10))
print map_output

print map(lambda x, y : x + y, range(8), range(8)) 

reduce_output = reduce(lambda x, y:x * y, range(1, 10))
##pep8?
print reduce_output

m=lambda x,y:x>y
print m(1,5)

filter_output = filter(lambda x:x % 2,  range(1, 10))
print filter_output