python 魔術方法

標籤：

import timefunc_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_timedef foo():    print ‘in foo()‘ @count_timedef 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_outputprint map(lambda x, y : x + y, range(8), range(8)) reduce_output = reduce(lambda x, y:x * y, range(1, 10))##pep8?print reduce_outputm=lambda x,y:x>yprint m(1,5)filter_output = filter(lambda x:x % 2,  range(1, 10))print filter_output

 

python 魔術方法