函数03
1 迭代器
"""
1、什么是迭代器？
迭代器指的是迭代取值的工具
迭代是一个重复的过程(不是单纯重复)，每次重复都是基于上一次的结果进行的
count = 1
while count < 5:
print(count)
count += 1
2、为何要用迭代器？
Ⅰ 为了找到一种通用的迭代取值的方案
Ⅱ 节省内存
3、如何用迭代器？
可迭代对象
内置有__iter__方法的类型都称之为可迭代对象
但凡调用了__iter__方法，就会将该类型转换成迭代对象
res = 值.__iter__()
迭代器对象的特点:
Ⅰ 内置有__next__方法
Ⅱ 内置有__iter__方法(为了方便for循环)
迭代器对象一定是可迭代对象
可迭代对象不一定是迭代器对象
4、迭代器优缺点总结:
优点:
Ⅰ 提供了一种不依赖索引的迭代取值方案
Ⅱ 惰性计算，节省内存
缺点:
Ⅰ 取值麻烦
Ⅱ 无法预测值的长度
Ⅲ 一次性的
"""
# 可迭代的对象
"hello".__iter__() # 字符串
[].__iter__() # 列表
(11,).__iter__() # 元组
{"k1": 12, }.__iter__() # 字典
{11, 22}.__iter__() # 集合
f = open("a.txt", mode="wt") # 文件
f.__iter__()
迭代器对象
l = [11, 22, 33]
iter_l = l.__iter__()
print(iter_l.__next__()) # 11
print(iter_l.__next__()) # 22
print(iter_l.__next__()) # 33
info = {'name': "ccc", "age": 18, "gender": 'male'}
iter_info = info.__iter__()
print(iter_info.__next__()) # name
print(iter_info.__next__()) # age
print(iter_info.__next__()) # gender
print(iter_info.__next__()) # 抛出异常StopIteration
迭代器的iter与本身
print(iter_info.__iter__().__iter__().__iter__() is iter_info) # True
l = [11, 222, 333, 444, 555]
iter_l = iter(l) # l.__iter__
while True:
try:
print(next(iter_l))
except StopIteration:
break
# 11
# 222
# 333
# 444
# 555
l = {'name': "ccc", "age": 18, "gender": 'male'}
iter_l = iter(l)
while True:
try:
print(next(iter_l))
except StopIteration:
break
print('--------------------')
while True:
try:
print(next(iter_l))
except StopIteration:
break
# name
# age
# gender
# --------------------
l = {'name': "ccc", "age": 18, "gender": 'male'}
iter_l = iter(l)
while True:
try:
print(next(iter_l))
except StopIteration:
break
print('--------------------')
iter_l = iter(l)
while True:
try:
print(next(iter_l))
except StopIteration:
break
# name
# age
# gender
# --------------------
# name
# age
# gender
l = [11, 222, 333, 444, 555]
iter_l = iter(l)
for item in iter_l:
print(item)
print('====================')
for item in iter_l:
print(item)
# 11
# 222
# 333
# 444
# 555
# ====================
l = [11, 222, 333, 444, 555]
iter_l = iter(l)
for item in iter_l:
print(item)
print('====================')
iter_l = iter(l)
for item in iter_l:
print(item)
# 11
# 222
# 333
# 444
# 555
# ====================
# 11
# 222
# 333
# 444
# 555
for循环原理:
1、调用可迭代对象.__iter__()，拿到一个迭代器对象
2、调用next(迭代对象)，将返回值赋值变量item
3、循环往复，直到抛出异常Stopiteration，for会检测异常然后结束循环
f = open('a.txt', mode='rt', encoding='utf-8')
for line in f:
print(line)
print('=======')
for line in f:
print(line)
f.close()
# 111
#
# 222
#
# 333
#
# 444
# =======
2 生成器
"""
1、生成器
生成器就是一种自定义迭代器
2、为何要用生成器
为了省内存
3、如何用生成器
函数体内但凡出现yield关键字，调用函数将不会触发函数体代码的运行
而是会返回一个生成器对象
yield与return:
相同点:在返回值角度用法一致
不同点:yield可以返回多次值，return只能返回一次
yield可以暂停函数，然后可以用next方法触发函数代码的运行->协程
"""
def func():
print("1111")
yield 1
print("2222")
yield 2
print("3333")
yield 3
print("4444")
g = func() # 生成器本质就是一个迭代器
print(g) # <generator object func at 0x0000024D38B57900>
res = next(g) # 1111
print(res) # 1
res = next(g) # 2222
print(res) # 2
res = next(g) # 3333
print(res) # 3
next(g) # 4444 检测异常StopIteration
def func():
print("1111")
yield 1
print("2222")
yield 2
print("3333")
yield 3
print("4444")
g = func()
print(g)
for i in g:
print(i)
# <generator object func at 0x0000020C4D217900>
# 1111
# 1
# 2222
# 2
# 3333
# 3
# 4444
def my_range(start, stop, step=1):
while start < stop:
yield start
start += step
for i in my_range(0, 5, 2):
print(i)
# 0
# 2
# 4
3 三元表达式
res = "条件成立时返回的值" if "条件" else "条件不成立时返回的值"
def max2(x, y):
if x > y:
return x
else:
return y
res = max2(11, 22)
print(res) # 22
x = 11
y = 22
res = x if x > y else y
print(res) # 22
res = "ok" if 10 > 3 else "no"
print(res) # ok
4 生成式
1、列表生成式
l = []
for i in range(10):
l.append(i)
print(l) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
l = [i for i in range(10)]
print(l) # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
names = ["egon", "lxx_sb", "hxx_sb"]
name = []
for item in names:
if item.endswith('sb'):
name.append(item)
print(name) # ['lxx_sb', 'hxx_sb']
names = ["egon", "lxx_sb", "hxx_sb"]
name = [name for name in names if name.endswith("sb")]
print(name) # ['lxx_sb', 'hxx_sb']
2、字典生成式
res = {i: i for i in range(5) if i > 2}
print(res) # {3: 3, 4: 4}
3、集合生成式
res = {i for i in range(5) if i > 2}
print(res, type(res)) # {3, 4} <class 'set'>
4、生成器表达式
res = (i for i in range(5))
print(res) # <generator object <genexpr> at 0x00000274941E7900>
print(next(res)) # 0
print(next(res)) # 1
print(next(res)) # 2
print(next(res)) # 3
print(next(res)) # 4
print(next(res)) # 抛出异常StopIteration
with open('a.txt', mode='rt', encoding='utf-8') as f:
res = 0
for line in f:
res += len(line)
print(res) # 15
with open('a.txt', mode='rt', encoding='utf-8') as f:
res = sum(len(line) for line in f)
print(res) # 15
5 面向过程编程
面向过程编程思想:
核心是过程二字
过程就是做事的步骤，即先干啥、后干啥、再干啥
所以基于该思想编写程序就好比在设计一条条流水线
优点:复杂的问题流程化，进而简单化
缺点:扩展性差