map,reduce,filter

map

map(function,Iterable) map将传入的函数一次作用到序列的每个元素，并把结果作为新的 Iterator返回

  names = ['james','ooc','rose','green']

方式一：手动实现

  new_names = []
  for name in names:
      new_names.append('steven ' + name)
  print(new_names)
  # ['steven james', 'steven ooc', 'steven rose', 'steven green']

方式二：列表生成

  new_names = ['steven ' + name for name in names]
  print(new_names)
  # ['steven james', 'steven ooc', 'steven rose', 'steven green']

方式三：map + 匿名函数

  lam_name = map(lambda x:'steven' + x , names)
  print(lam_name)
  print(list(lam_name))
  # ['steven james', 'steven ooc', 'steven rose', 'steven green'] 

Reduce

reduce(function,sequence) reduce把一个函数作用在一个序列[x1, x2, x3, …]上，reduce把结果继续和序列的下一个元素做累计计算

方式一：手动实现

  num = 0
  for i in range(101):
      num += i
  print(num)
  # 5050

方式二：列表生成式

  print(sum([i for i in range(101)]))
  # 5050

方式三：reduce + 匿名函数

在python3中 reduce要在functools中调用

  from functools import reduce
  print(reduce(lambda x,y:x+y,[i for i in range(101)],100))
  # 5150 reduce
  # 实际上 def reduce(function, sequence, initial=None) 有第三个参数# 初始值为none
  print(reduce(lambda x,y:x+y,[i for i in range(101)]))
  # 5050
  print(reduce(lambda x,y:x+y,['h','e','l','l','o'],'-------'))
  # -------hello

Filter

filter()函数用于过滤序列。和map()类似，filter()也接受一个函数和一个序列。和map()不同的是，fileter()把传入的函数依次作用于每个元素，然后根据返回值true 还是false 决定保留还是丢弃该元素。

  names = ['steven james','ooc','steven rose','steven green']

方式一：手动实现

  new_names = []
  for name in names:
      if name.startswith('steven'):
          new_names.append(name)
  print(new_names)
  # ['steven james', 'steven rose', 'steven green']

方式二：列表生成式

  new_names=[name for name in names if name.startswith('steven')] 
  # ['steven james', 'steven rose', 'steven green']

方式三：filter + 匿名函数

  lam = filter(lambda name:name.startswith('steven'),names)
  print(lam)
  print(list(lam))
  # <filter object at 0x1050d6550>
  # ['steven james', 'steven rose', 'steven green']