章节号

内容

1图片格式(png)

宽度大于620px,保持高宽

第1章节  import模块

1-1 import模块—sys.path

↓import导入模块的搜索路径：

In [1]: import sys

In [2]: sys.path

Out[2]:

#第一个为当前路径

['',

'/usr/lib/python36.zip',

'/usr/lib/python3.6',

'/usr/lib/python3.6/lib-dynload',

'/home/li/.local/lib/python3.6/site-packages',

'/usr/local/lib/python3.6/dist-packages',

'/usr/lib/python3/dist-packages',

'/usr/lib/python3/dist-packages/IPython/extensions',

'/home/li/.ipython']

In [3]:

↓添加一条搜索路径：

In [4]: sys.path.append("/home")

In [5]: sys.path

Out[5]:

['',

'/usr/lib/python36.zip',

'/usr/lib/python3.6',

'/usr/lib/python3.6/lib-dynload',

'/home/li/.local/lib/python3.6/site-packages',

'/usr/local/lib/python3.6/dist-packages',

'/usr/lib/python3/dist-packages',

'/usr/lib/python3/dist-packages/IPython/extensions',

'/home/li/.ipython',

'/home']

In [6]:

↓sys.path的一些用法：

1-2 import模块—重新导入模块

1、自定义模块并导入：

↓在某路径下，新建一个test.py文件，输入以下代码：

vim test.py

1 def test():

2 print("test import")

↓在sys.path中添加当前路径，便可导入使用：

In [1]: import sys

In [2]: sys.path

Out[2]:

['',

'/usr/lib/python2.7',

'/usr/lib/python2.7/plat-x86_64-linux-gnu',

'/usr/lib/python2.7/lib-tk',

'/usr/lib/python2.7/lib-old',

'/usr/lib/python2.7/lib-dynload',

'/usr/local/lib/python2.7/dist-packages',

'/usr/lib/python2.7/dist-packages',

'/usr/lib/python2.7/dist-packages/IPython/extensions',

'/home/li/.ipython']

In [3]: sys.path.append("/home/li")

In [4]: sys.path

Out[4]:

['',

'/usr/lib/python2.7',

'/usr/lib/python2.7/plat-x86_64-linux-gnu',

'/usr/lib/python2.7/lib-tk',

'/usr/lib/python2.7/lib-old',

'/usr/lib/python2.7/lib-dynload',

'/usr/local/lib/python2.7/dist-packages',

'/usr/lib/python2.7/dist-packages',

'/usr/lib/python2.7/dist-packages/IPython/extensions',

'/home/li/.ipython',

'/home/li']

In [5]: import test

In [6]: test.test()

test import

In [7]:

↑退出后path的添加会失效，再次使用需要再次导入。

2、重新导入模块reload(模块)

应用场景：在导入一个模块后，该模块代码被修改，如果不重新导入，则新修改的代码无法使用。再次使用import也不能完成预期，正确做法为：

In [7]: reload(test)

Out[7]:

1-3 import模块—模块的循环导入问题

什么是循环导入？

我用你，我导入你。同时你也用我，你导入我。

from 模块名 import 函数名

root@li-ThinkPad-T420s:/home/li# cat test.py

from text import text

def test():

print("test import")

text()

test()

root@li-ThinkPad-T420s:/home/li# cat text.py

from test import test

def text():

print("text import")

test()

text()

root@li-ThinkPad-T420s:/home/li#

root@li-ThinkPad-T420s:/home/li# python test.py

Traceback (most recent call last):

File "test.py", line 1, in

from text import text

File "/home/li/text.py", line 1, in

from test import test

File "/home/li/test.py", line 1, in

from text import text

ImportError: cannot import name text

root@li-ThinkPad-T420s:/home/li#

↑从设计角度来说，这种情况要严格避免。

第2章节  == 和 is

==是判断值是否相同

is是判断id是否相同(是否指向同一个东西)

In [20]: a=[1,2]

In [21]: b=[1,2]

In [22]: a is b

Out[22]: False

In [23]: id(a)

Out[23]: 140065919094080

In [24]: id(b)

Out[24]: 140065919170680

In [25]: a == b

Out[25]: True

↓注意这个问题，数字在负的X到正的X这一范围内，所有的id会变成相同的，超过这个范围则会不同。切记。

In [26]: a = 100

In [27]: b = 100

In [28]: a == b

Out[28]: True

In [29]: a is b

Out[29]: True

In [30]: a=10000

In [31]: b=10000

In [32]: id(a)

Out[32]: 94786674642736

In [33]: id(b)

Out[33]: 94786674642640

第3章节  深拷贝和浅拷贝

3-1 深拷贝和浅拷贝—深和浅的不同

1、深：我拿到了数据(copy.deepcopy)。改一个，另一个不变。

In [35]: a=[1,2,3]

In [39]: import copy

In [40]: b=copy.deepcopy(a)

In [41]: id(a)

Out[41]: 140065900535752

In [42]: id(b)

Out[42]: 140065909328424

#深拷贝

2、浅：我只拿到了地址。改一个，另一个也跟着变。

In [35]: a=[1,2,3]

In [36]: b=a

In [37]: id(a)

Out[37]: 140065900535752

In [38]: id(b)

Out[38]: 140065900535752

#浅拷贝

3-2 深拷贝和浅拷贝—多重引用下的深拷贝

深拷贝对多重引用会自动进行递归拷贝，一直到最底层。

In [55]: a

Out[55]: [1, 2, 3, 4]

In [56]: b

Out[56]: [1, 2, 3]

In [57]: c=[a,b]

In [58]: c

Out[58]: [[1, 2, 3, 4], [1, 2, 3]]

In [59]: d=c

In [60]: id(c)

Out[60]: 140065909614568

In [61]: id(d)

Out[61]: 140065909614568

In [62]: e=copy.deepcopy(c)

In [63]: id(e)

Out[63]: 140065909636632

In [64]: id(e[0])

Out[64]: 140065919104784

In [65]: id(c[0])

Out[65]: 140065900535752

In [66]: id(d[0])

Out[66]: 140065900535752

In [67]: e

Out[67]: [[1, 2, 3, 4], [1, 2, 3]]

3-3 深拷贝和浅拷贝—copy和deepcopy

copy模块中，还有一个copy.copy函数。

In [70]: a=[1,2]

In [71]: b=[3,4]

In [72]: c=[a,b]

In [73]: c

Out[73]: [[1, 2], [3, 4]]

In [74]: d=copy.copy(c)

In [75]: d

Out[75]: [[1, 2], [3, 4]]

In [76]: id(c)

Out[76]: 140065919152424

In [77]: id(d)

Out[77]: 140065918710200

In [78]: id(c[0])

Out[78]: 140065919059368

In [79]: id(d[0])

Out[79]: 140065919059368

copy()只识别第一层引用。

deepcopy()识别所有引用，一直到最底。

3-4 深拷贝和浅拷贝—copy()元组时特点

In [81]: a

Out[81]: [1, 2]

In [82]: b

Out[82]: [3, 4]

In [83]: c=(a,b)

In [84]: d=copy.copy(c)

In [85]: id(c)

Out[85]: 140065900473808

In [86]: id(d)

Out[86]: 140065900473808

In [87]: id(c[0])

Out[87]: 140065919059368

In [88]: id(d[0])

Out[88]: 140065919059368

In [89]: id(c[0][0])

Out[89]: 94786668758568

In [90]: id(d[0][0])

Out[90]: 94786668758568

元组本身是不可变类型，copy()判断出是不可变类型，第一层引用都不深入拷贝。copy()判断出是可变类型，深入拷贝第一层。

copy模块的功能一定要慎用，想清楚再用！