一、不要使用可变对象作为函数默认值

In [1]: def append_to_list(value, def_list=[]):

...:         def_list.append(value)

...:         return def_list

...:

In [2]: my_list = append_to_list(1)

In [3]: my_list

Out[3]: [1]

In [4]: my_other_list = append_to_list(2)

In [5]: my_other_list

Out[5]: [1, 2] # 看到了吧，其实我们本来只想生成[2] 但是却把第一次运行的效果页带了进来

In [6]: import time

In [7]: def report_arg(my_default=time.time()):

...:         print(my_default)

...:

In [8]: report_arg() # 第一次执行

1399562371.32

In [9]: time.sleep(2) # 隔了2秒

In [10]: report_arg()

1399562371.32 # 时间竟然没有变

这2个例子说明了什么? 字典,集合,列表等等对象是不适合作为函数默认值的. 因为这个默认值实在函数建立的时候就生成了, 每次调用都是用了这个对象的”缓存”. 我在上段时间的分享python高级编程也说到了这个问题,这个是实际开发遇到的问题，好好检查你学过的代码, 也许只是问题没有暴露

可以这样改:

def append_to_list(element, to=None):

if to is None:

to = []

to.append(element)

return to

二、生成器不保留迭代过后的结果

In [12]: gen = (i for i in range(5))

In [13]: 2 in gen

Out[13]: True

In [14]: 3 in gen

Out[14]: True

In [15]: 1 in gen

Out[15]: False # 1为什么不在gen里面了? 因为调用1->2,这个时候1已经不在迭代器里面了,被按需生成过了

In [20]: gen = (i for i in range(5))

In [21]: a_list = list(gen) # 可以转化成列表，当然a_tuple = tuple(gen) 也可以

In [22]: 2 in a_list

Out[22]: True

In [23]: 3 in a_list

Out[23]: True

In [24]: 1 in a_list # 就算循环过,值还在

Out[24]: True

三、lambda在闭包中会保存局部变量

In [29]: my_list = [lambda: i for i in range(5)]

In [30]: for l in my_list:

....:         print(l())

....:

4

4

4

4

4

这个问题还是上面说的python高级编程中说过具体原因. 其实就是当我赋值给my_list的时候,lambda表达式就执行了i会循环,直到 i =4,i会保留

但是可以用生成器

In [31]: my_gen = (lambda: n for n in range(5))

In [32]: for l in my_gen:

....:         print(l())

....:

0

1

2

3

4

也可以坚持用list：

In [33]: my_list = [lambda x=i: x for i in range(5)] # 看我给每个lambda表达式赋了默认值

In [34]: for l in my_list:

....:         print(l())

....:

0

1

2

3

4

有点不好懂是吧,在看看python的另外一个魔法:

In [35]: def groupby(items, size):

....:     return zip(*[iter(items)]*size)

....:

In [36]: groupby(range(9), 3)

Out[36]: [(0, 1, 2), (3, 4, 5), (6, 7, 8)]

一个分组的函数,看起来很不好懂,对吧? 我们来解析下这里

In [39]: [iter(items)]*3

Out[39]:

[,

,

] # 看到了吧, 其实就是把items变成可迭代的, 重复三回(同一个对象哦), 但是别忘了,每次都.next(), 所以起到了分组的作用

In [40]: [lambda x=i: x for i in range(5)]

Out[40]:

[>,

>,

>,

>,

>] # 看懂了吗?

四、在循环中修改列表项

In [44]: a = [1, 2, 3, 4, 5]

In [45]: for i in a:

....:     if not i % 2:

....:         a.remove(i)

....:

In [46]: a

Out[46]: [1, 3, 5] # 没有问题

In [50]: b = [2, 4, 5, 6]

In [51]: for i in b:

....:      if not i % 2:

....:          b.remove(i)

....:

In [52]: b

Out[52]: [4, 5] # 本来我想要的结果应该是去除偶数的列表

思考一下,为什么 – 是因为你对列表的remove,影响了它的index

In [53]: b = [2, 4, 5, 6]

In [54]: for index, item in enumerate(b):

....:     print(index, item)

....:     if not item % 2:

....:         b.remove(item)

....:

(0, 2) # 这里没有问题 2被删除了

(1, 5) # 因为2被删除目前的列表是[4, 5, 6], 所以索引list[1]直接去找5, 忽略了4

(2, 6)

五、IndexError - 列表取值超出了他的索引数

In [55]: my_list = [1, 2, 3, 4, 5]

In [56]: my_list[5] # 根本没有这个元素

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

IndexError                                Traceback (most recent call last)

in ()

----> 1 my_list[5]

IndexError: list index out of range # 抛异常了

In [57]: my_list[5:] # 但是可以这样， 一定要注意, 用好了是trick,用错了就是坑啊

Out[57]: []

六、重用全局变量

In [58]: def my_func():

....:         print(var) # 我可以先调用一个未定义的变量

....:

In [59]: var = 'global' # 后赋值

In [60]: my_func() # 反正只要调用函数时候变量被定义了就可以了

global

In [61]: def my_func():

....:     var = 'locally changed'

....:

In [62]: var = 'global'

In [63]: my_func()

In [64]: print(var)

global # 局部变量没有影响到全局变量

In [65]: def my_func():

....:         print(var) # 虽然你全局设置这个变量, 但是局部变量有同名的, python以为你忘了定义本地变量了

....:         var = 'locally changed'

....:

In [66]: var = 'global'

In [67]: my_func()

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

UnboundLocalError                         Traceback (most recent call last)

in ()

----> 1 my_func()

in my_func()

1 def my_func():

----> 2         print(var)

3         var = 'locally changed'

4

UnboundLocalError: local variable 'var' referenced before assignment

In [68]: def my_func():

....:         global var # 这个时候得加全局了

....:         print(var) # 这样就能正常使用

....:         var = 'locally changed'

....:

In [69]: var = 'global'

In [70]:

In [70]: my_func()

global

In [71]: print(var)

locally changed # 但是使用了global就改变了全局变量

七、拷贝可变对象

In [72]: my_list1 = [[1, 2, 3]] * 2

In [73]: my_list1

Out[73]: [[1, 2, 3], [1, 2, 3]]

In [74]: my_list1[1][0] = 'a' # 我只修改子列表中的一项

In [75]: my_list1

Out[75]: [['a', 2, 3], ['a', 2, 3]] # 但是都影响到了

In [76]: my_list2 = [[1, 2, 3] for i in range(2)] # 用这种循环生成不同对象的方法就不影响了

In [77]: my_list2[1][0] = 'a'

In [78]: my_list2

Out[78]: [[1, 2, 3], ['a', 2, 3]]

八、python多继承(C3)

In [1]: class A(object):

...:         def foo(self):

...:                 print("class A")

...:

In [2]: class B(object):

...:         def foo(self):

...:                 print("class B")

...:

In [3]: class C(A, B):

...:         pass

...:

In [4]: C().foo()

class A # 例子很好懂, C继承了A和B，从左到右,发现A有foo方法,返回了

看起来都是很简单, 有次序的从底向上,从前向后找,找到就返回. 再看例子:

In [5]: class A(object):

...:        def foo(self):

...:               print("class A")

...:

In [6]: class B(A):

...:        pass

...:

In [7]: class C(A):

...:        def foo(self):

...:               print("class C")

...:

In [8]: class D(B,C):

...:        pass

...:

In [9]: D().foo()

class C # ? 按道理, 顺序是 D->B->A,为什么找到了C哪去了

这也就涉及了MRO(Method Resolution Order):

In [10]: D.__mro__

Out[10]: (__main__.D, __main__.B, __main__.C, __main__.A, object)

简单的理解其实就是新式类是广度优先了， D->B, 但是发现C也是继承A，就先找C，最后再去找A

九、列表的+和+=, append和extend

In [17]: print('ID:', id(a_list))

('ID:', 4481323592)

In [18]: a_list += [1]

In [19]: print('ID (+=):', id(a_list))

('ID (+=):', 4481323592) # 使用+= 还是在原来的列表上操作

In [20]: a_list = a_list + [2]

In [21]: print('ID (list = list + ...):', id(a_list))

('ID (list = list + ...):', 4481293056) # 简单的+其实已经改变了原有列表

In [28]: a_list = []

In [29]: id(a_list)

Out[29]: 4481326976

In [30]: a_list.append(1)

In [31]: id(a_list)

Out[31]: 4481326976 # append 是在原有列表添加

In [32]: a_list.extend([2])

In [33]: id(a_list)

Out[33]: 4481326976 # extend 也是在原有列表上添加

十、datetime也有布尔值这是一个坑

In [34]: import datetime

In [35]: print('"datetime.time(0,0,0)" (Midnight) ->', bool(datetime.time(0,0,0)))

('"datetime.time(0,0,0)" (Midnight) ->', False)

In [36]: print('"datetime.time(1,0,0)" (1 am) ->', bool(datetime.time(1,0,0)))

('"datetime.time(1,0,0)" (1 am) ->', True)

十一、'==' 和 is 的区别我的理解是”is”是判断2个对象的身份, ==是判断2个对象的值

In [37]: a = 1

In [38]: b = 1

In [39]: print('a is b', bool(a is b))

('a is b', True)

In [40]: c = 999

In [41]: d = 999

In [42]: print('c is d', bool(c is d))

('c is d', False) # 原因是python的内存管理,缓存了-5 - 256的对象

In [43]: print('256 is 257-1', 256 is 257-1)

('256 is 257-1', True)

In [44]: print('257 is 258-1', 257 is 258 - 1)

('257 is 258-1', False)

In [45]: print('-5 is -6+1', -5 is -6+1)

('-5 is -6+1', True)

In [46]: print('-7 is -6-1', -7 is -6-1)

('-7 is -6-1', False)

In [47]: a = 'hello world!'

In [48]: b = 'hello world!'

In [49]: print('a is b,', a is b)

('a is b,', False) # 很明显 他们没有被缓存,这是2个字段串的对象

In [50]: print('a == b,', a == b)

('a == b,', True) # 但他们的值相同

# But, 有个特例

In [51]: a = float('nan')

In [52]: print('a is a,', a is a)

('a is a,', True)

In [53]: print('a == a,', a == a)

('a == a,', False) # 亮瞎我眼睛了~

十二、浅拷贝和深拷贝我们在实际开发中都可以向对某列表的对象做修改,但是可能不希望改动原来的列表. 浅拷贝只拷贝父对象，深拷贝还会拷贝对象的内部的子对象

In [65]: list1 = [1, 2]

In [66]: list2 = list1 # 就是个引用, 你操作list2,其实list1的结果也会变

In [67]: list3 = list1[:]

In [69]: import copy

In [70]: list4 = copy.copy(list1) # 他和list3一样 都是浅拷贝

In [71]: id(list1), id(list2), id(list3), id(list4)

Out[71]: (4480620232, 4480620232, 4479667880, 4494894720)

In [72]: list2[0] = 3

In [73]: print('list1:', list1)

('list1:', [3, 2])

In [74]: list3[0] = 4

In [75]: list4[1] = 4

In [76]: print('list1:', list1)

('list1:', [3, 2]) # 对list3和list4操作都没有对list1有影响

# 再看看深拷贝和浅拷贝的区别

In [88]: from copy import copy, deepcopy

In [89]: list1 = [[1], [2]]

In [90]: list2 = copy(list1) # 还是浅拷贝

In [91]: list3 = deepcopy(list1) # 深拷贝

In [92]: id(list1), id(list2), id(list3)

Out[92]: (4494896592, 4495349160, 4494896088)

In [93]: list2[0][0] = 3

In [94]: print('list1:', list1)

('list1:', [[3], [2]]) # 看到了吧 假如你操作其子对象 还是和引用一样 影响了源

In [95]: list3[0][0] = 5

In [96]: print('list1:', list1)

('list1:', [[3], [2]]) # 深拷贝就不会影响

十三、bool其实是int的子类

In [97]: isinstance(True, int)

Out[97]: True

In [98]: True + True

Out[98]: 2

In [99]: 3 * True + True

Out[99]: 4

In [100]: 3 * True - False

Out[100]: 3

In [104]: True << 10

Out[104]: 1024

十五、元组是不是真的不可变?

In [111]: tup = ([],)

In [112]: tup[0] += [1]

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

TypeError                                 Traceback (most recent call last)

in ()

----> 1 tup[0] += [1]

TypeError: 'tuple' object does not support item assignment

In [113]: tup

Out[113]: ([1],) # 我靠 又是亮瞎我眼睛,明明抛了异常 还能修改?

In [114]: tup = ([],)

In [115]: tup[0].extend([1])

In [116]: tup[0]

Out[116]: [1] # 好吧,我有点看明白了, 虽然我不能直接操作元组，但是不能阻止我操作元组中可变的子对象(list)

这里有个不错的解释Python's += Is Weird, Part II :

In [117]: my_tup = (1,)

In [118]: my_tup += (4,)

In [119]: my_tup = my_tup + (5,)

In [120]: my_tup

Out[120]: (1, 4, 5) # ? 嗯 不是不能操作元组嘛?

In [121]: my_tup = (1,)

In [122]: print(id(my_tup))

4481317904

In [123]: my_tup += (4,)

In [124]: print(id(my_tup))

4480606864 # 操作的不是原来的元组 所以可以

In [125]: my_tup = my_tup + (5,)

In [126]: print(id(my_tup))

4474234912

十六、python没有私有方法/变量? 但是可以有”伪”的

In [127]: class my_class(object^E):

.....:     def public_method(self):

.....:         print('Hello public world!')

.....:     def __private_method(self): # 私有以双下划线开头

.....:         print('Hello private world!')

.....:     def call_private_method_in_class(self):

.....:         self.__private_method()

In [132]: my_instance = my_class()

In [133]: my_instance.public_method()

Hello public world! # 普通方法

In [134]: my_instance._my_class__private_method()

Hello private world! # 私有的可以加"_ + 类名字 + 私有方法名字”

In [135]: my_instance.call_private_method_in_class()

Hello private world! # 还可以通过类提供的公有接口内部访问

In [136]: my_instance._my_class__private_variable

Out[136]: 1

十七、异常处理加else

In [150]: try:

.....:     print('third element:', a_list[2])

.....: except IndexError:

.....:     print('raised IndexError')

.....: else:

.....:     print('no error in try-block') # 只有在try里面没有异常的时候才会执行else里面的表达式

.....:

raised IndexError # 抛异常了 没完全完成

In [153]: i = 0

In [154]: while i < 2:

.....:     print(i)

.....:     i += 1

.....: else:

.....:     print('in else')

.....:

0

1

in else # while也支持哦~

In [155]: i = 0

In [156]: while i < 2:

.....:         print(i)

.....:         i += 1

.....:         break

.....: else:

.....:         print('completed while-loop')

.....:

0 # 被break了 没有完全执行完 就不执行else里面的了

In [158]: for i in range(2):

.....:         print(i)

.....: else:

.....:         print('completed for-loop')

.....:

0

1

completed for-loop

In [159]: for i in range(2):

.....:         print(i)

.....:         break

.....: else:

.....:         print('completed for-loop')

.....:

0 # 也是因为break了