#Author wangmengzhu salaries = { ‘egon‘:3000, ‘alex‘:100000, ‘wupeiqi‘:1000, ‘yuanhao‘:2000}# print(list(zip(salaries.values(),salaries.keys()))) # print(max(list(zip(salaries.values(),salaries.keys())))) # print(max(salaries,key = lambda name:salaries[name])) ##filter,map,reducenames = [‘alex‘,‘wupeiqi‘,‘yuanhao‘,‘egon‘]# res = map(lambda x:x + ‘_SB‘,names)# print(list(res)) #从functools中导入reduce模块from functools import reduce# print(reduce(lambda x,y:x + y,range(101))) def my_map(seq): for item in seq: item = item + ‘_SB‘ yield itemres1 = my_map(names)# print(next(res1)) def my_map(func,seq): for item in seq: yield func(item)# res1 = my_map(lambda x:x + ‘_SB‘,names)# print(next(res1)) ##filter函数names = [‘alex_SB‘,‘wupeiqi‘,‘yuanhao‘,‘egon‘]# print(list(filter(lambda name:name.endswith(‘SB‘),names))) ##eval与exec# cmd = ‘print(x)‘# x = 1# eval(cmd)# eval(cmd,{},{})#第一个大括号表示的是全局作用域,第二个大括号表示的是局部作用域# eval(cmd,{‘x‘:0},{‘y‘:10000}) s = ‘for i in range(10):print(i)‘code = compile(s,‘‘,‘exec‘)exec(code)
时间: 2024-10-30 23:46:28