# Iterator  一个对象，代表了遗传数据流，使用__next__()方法或内置函数next()
# 返回连续的对象，没有数据返回时，抛出StopIteration异常

# iterable  一个对象，能每次返回数据组中的一个成员  for 循环中每次返回一个值 或
# 内置函数iter()传入参数返回iterator对象

# generator  使用了yield或者生成器表达式，申城iterator对象  用一种方便的
# 方法实现了iterator，在for循环取数据或使用next（）取数据

# Iterator和Generator的关系
# 针对函数的列表进行优化
# 针对读取大文件进行优化

def gen_num():
    yield 8
    yield 99
    yield 999

g = gen_num()

g

next(g) # 第一次运行

---------------------------------------------------------------------------

StopIteration                             Traceback (most recent call last)

 in ()
----> 1 next(g) # 第一次运行

StopIteration: 

def gen_num2():
    for i in range(8):
        yield  i  # yield有类似返回值return的效果

for g in gen_num2():
    print(g)  # 每次取一个值的时候，才生成这个值，节省内存

0
1
2
3
4
5
6
7

my_list = [1,2,3]

next(my_list)  # 用 next方法验证是否为迭代器

---------------------------------------------------------------------------

TypeError                                 Traceback (most recent call last)

 in ()
----> 1 next(my_list)

TypeError: 'list' object is not an iterator

next(iter(my_list))

1

next(iter(my_list))

1

it = iter(my_list)
next(it)

1

next(it)

2

from collections import Iterator, Iterable

isinstance(my_list, Iterator)

False

isinstance(iter(my_list), Iterator)

True

isinstance((), Iterator)

False

isinstance((), Iterable)  # 元组不是迭代器，但是可迭代

True

isinstance(range(8), Iterable)

True

isinstance(range(8), Iterator)

False

针对函数的列表进行优化

# Python 3:Fibonacci series up to n 
def fib(n):
    a, b = 0, 1
    while a < n:
        print(a, end='')
        a, b = b, a+b
        print()

fib(9)

0
1
1
2
3
5
8

def fil_list(n):
    a, b = 0, 1
    result = []
    while a < n:
        result.append(a) 
        a, b = b, a+b
    return result

fil_list(55)

[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

fil_list(1000)

[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987]

def fib_gen(n):
    a, b = 0, 1
    while a< n:
        yield a
        a, b = b, a+b

fib_gen(80)

for i in fib_gen(80):
    print(i)

0
1
1
2
3
5
8
13
21
34
55

[i for i in fib_gen(66)]  # 列表推导式

[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]

针对读取大文件进行优化

import os
base_dir = r'D:\全栈\全栈资料\第三阶段 python进阶\文件与日志-演示代码\02-auto\data'
log_path = os.path.join(base_dir, 'access.log')
log_file = open(log_path)
log_data = log_file.readlines()
log_file.close()

len(log_data)

864

def read_log(log_path):
    with open(log_path) as f:
        print('Iterator:', isinstance(f, Iterator))  # open方法已经为我们生成一个迭代器
        for line in f:
            print(line)
            break

read_log(log_path)

Iterator: True
220.181.7.76 - - [20/May/2010:07:26:23 +0100] "GET / HTTP/1.1" 200 29460 "-" "Baiduspider+(+http://www.baidu.com/search/spider.htm)"

列表推导式

[i for i in fib_gen(6)]

[0, 1, 1, 2, 3, 5]

m = [i for i in fib_gen(6)]
for i in m:
    print(i)

0
1
1
2
3
5

生成器表达式

(i for i in fib_gen(5))

 at 0x0000014F3EAC9C50>

n = (i for i in fib_gen(9))
for i in n:
    print(i)

0
1
1
2
3
5
8

本文题目：IteratorandGenerator
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