Python高级特性与几种函数的讲解

list = [1, 2, 3, 4]
list[0 : 3] # [1, 2, 3]
list[-2 : -1] # -1表示最后一个，[3, 4]
list[1 :: 2] # index = 1开始，每两个取一个[2, 4]
list[:] # 复制list，[1, 2, 3, 4]
# 针对tuple，切片同样适用

# range转list
list(range(1, 5)) # [1, 2, 3, 4]
[x * x for x in range(1, 5)] # [1, 4, 9, 16]
[x * x for x in range(1, 5) if x % 2 == 0] # [4, 16]
[m + n for m in 'ABC' for n in 'XYZ'] # ['AX', 'AY', 'AZ', 'BX', 'BY', 'BZ', 'CX', 'CY', 'CZ']
[s.lower() for s in ['Hello', 'World', 'IBM', 'Apple']] # like map

g = (x * x for x in range(10))
next(g) # 0
next(g) # 1
next(g) # 4
for item in g:
  print(item) # 9 16 ... 81

# 有yield语句，表明时generator函数
def gen_fn():
  init = 0
  while init < 10:
    yield init
    init += 1
  return 'done'
call = gen_fn() # 获得可迭代对象call
next(call) # 0
next(call) # 1
# 每次调用generator函数，得到的是一个新的generator
# for-in无法获得generator的返回值'done'
for item in gen_fn():
  print(item) # 0 1 ... 9

# map(func, *iterables, ...)
i = map(lambda x : x * x, [1, 2, 3]) # 返回Iterator
list(i) # [1, 4, 9]

from functools import reduce
reduce(lambda previous, x : previous + x, [1, 2, 3, 4]) # 10

i = filter(lambda x : x % 2 == True, [1, 2, 3, 4])
list(i) # [1, 3]

sorted([1,3,2], key = lambda x : -x) # [3, 2, 1]

def lazy_sum(*args):
  ax = 0
  def sum():
    nonlocal ax
    for n in args:
      ax = ax + n
    return ax
  return sum
fn = lazy_sum(1, 2, 3)  # ax + sum构成了闭包
fn() # 6
fn() # 12

def log(fn):
  def call(*args, **kw):
    print('call %s():' % fn.__name__)
    return fn(*args, **kw)
  return call
# @log的作用等同now = log(now)
@log
def now():
  print('2018-03-18')
now() # call now(): 2018-03-18

from functools import partial
binary_int = partial(int, base = 2)
binary_int('1000000') # 64