How to use Python basic modules

1. Module

A module can be seen as a collection of functions.

A bunch of functions can be placed inside a py file, so a py file can be regarded as a module.

If the file name of this py file is module.py, the module name is module.

1. Four forms of modules

In Python, there are a total of four forms of modules:

• Custom module: If you Write a py file yourself and write a bunch of functions in the file, then it is called a custom module, that is, a .py file written in python

• Third-party module: Has been A C or C extension compiled as a shared library or DLL, such as requests

• Built-in modules: Built-in modules written in C and linked to the python interpreter, such as time

• Package (folder): a folder that organizes a series of modules together (note: there is an __init__.py file under the folder, which is called a package)

2. Why use modules?

• Using third-party or built-in modules is a kind of borrowingism, which can greatly improve development efficiency.

• Custom module writes the public functions used in our own program into a python file, and then each component of the program can reference the custom module through import. Function.

2. How to use modules

Generally we use import and from...import... to import modules.

Take the following file code in spam.py as an example.

# spam.py
print('from the spam.py')
money = 1000
def read1():
print('spam模块：', money)
def read2():
print('spam模块')
read1()
def change():
global money
money = 0

1. Import module name

The syntax is as follows:

import module1[, module2[,... moduleN]

The imported module needs to be accessed with a prefix.

Three things happened when importing the module for the first time:

• Create a module namespace based on the module

• Execute the file corresponding to the module and throw all the names generated during the execution into the name space of the module

• Get a module name in the current execution file

Note: Repeated import of the module will directly refer to the previously created results, and the module files will not be executed repeatedly.

# run.py
import spam # from the spam.py
import spam
money = 111111
spam.read1() # 'spam模块：1000'
spam.change()
print(spam.money) # 0
print(money) # 111111

Import rename: smt variable points to the namespace of the span module

# run.py
import spam as sm
money = 111111
sm.money
sm.read1() # 'spam模块：1000'
sm.read2
sm.change()
print(money) # 1000

Import multiple modules

import spam, time, os
# 推荐使用下述方式
import spam
import time
import os

2. from module name import specific function

The syntax is as follows:

from modname import name1[, name2[, ... nameN]]

This statement will not import the entire module into the current namespace, it will only introduce one or more functions in the module.

module imported from...import... does not need to be accessed with a prefix.

from...import...Three things happened when importing the module for the first time:

• Create a module namespace based on the module

• Execute the file corresponding to the module and throw all the names generated during the execution into the namespace of the module

• Get one in the namespace of the currently executed file Name, the name directly points to a name in the module, which means that you can use it directly without adding any prefix

• Advantages: No prefix is ​​needed, the code is more streamlined

• Disadvantages: It is easy to conflict with the names in the name space in the current execution file

# run.py
from spam import money
from spam import money,read1
money = 10
print(money) # 10

rom … import * statement: Import all the names in the file Function:

# spam.py
__all__ = ['money', 'read1'] # 只允许导入'money'和'read1'

# run.py
from spam import * # 导入spam.py内的所有功能，但会受限制于__all__
money = 111111
read1() # 'spam模块：1000'
change()
read1() # 'spam模块：0'
print(money) # 111111

3. Circular import

Circular import will occur in the following situations:

# m1.py
print('from m1.py')
from m2 import x
y = 'm1'
# m2.py
print('from m2.py')
from m1 import y
x = 'm2'

You can use the feature of only recognizing syntax in the function definition stage to solve the problem of circular import. Or essentially solve the problem of circular import, but the best solution is to avoid circular import.

Option one:

# m1.py
print('from m1.py')
def func1():
from m2 import x
print(x)
y = 'm1'



# m2.py
print('from m2.py')
def func1():
from m1 import y
print(y)
x = 'm2'

Option two:

5、# m1.py
print('from m1.py')
y = 'm1'
from m2 import x



# m2.py
print('from m2.py')
x = 'm2'
from m1 import y

4. dir() function

The built-in function dir() can find the functions defined in the module All names. Returned in the form of a string list:

dir(sys)
['__displayhook__', '__doc__', '__excepthook__', '__loader__', '__name__',
'__package__', '__stderr__', '__stdin__', '__stdout__',
'_clear_type_cache', '_current_frames', '_debugmallocstats', '_getframe',
'_home', '_mercurial', '_xoptions', 'abiflags', 'api_version', 'argv',
'base_exec_prefix', 'base_prefix', 'builtin_module_names', 'byteorder',
'call_tracing', 'callstats', 'copyright', 'displayhook',
'dont_write_bytecode', 'exc_info', 'excepthook', 'exec_prefix',
'executable', 'exit', 'flags', 'float_info', 'float_repr_style',
'getcheckinterval', 'getdefaultencoding', 'getdlopenflags',
'getfilesystemencoding', 'getobjects', 'getprofile', 'getrecursionlimit',
'getrefcount', 'getsizeof', 'getswitchinterval', 'gettotalrefcount',
'gettrace', 'hash_info', 'hexversion', 'implementation', 'int_info',
'intern', 'maxsize', 'maxunicode', 'meta_path', 'modules', 'path',
'path_hooks', 'path_importer_cache', 'platform', 'prefix', 'ps1',
'setcheckinterval', 'setdlopenflags', 'setprofile', 'setrecursionlimit',
'setswitchinterval', 'settrace', 'stderr', 'stdin', 'stdout',
'thread_info', 'version', 'version_info', 'warnoptions']

If no parameters are given, the dir() function will list all the names currently defined:

a = [1, 2, 3, 4, 5]
import fibo
fib = fibo.fib
print(dir()) # 得到一个当前模块中定义的属性列表
# ['__builtins__', '__name__', 'a', 'fib', 'fibo', 'sys']

b = 5 # 建立一个新的变量 'a'
print(dir())
# ['__annotations__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'a', 'b']
del b # 删除变量名a
print(dir())
# ['__annotations__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'a']

3. Module search path

1. The order of searching for modules when importing modules.

1. First search from the modules that have been imported in the memory.

If we are running the run.py file, quickly Delete the mmm.py file and we will find that the file will continue to run without reporting an error because mmm has been imported into the memory. If we run run.py again, an error will be reported because mmm.py has been deleted.

# test.py
import m1 # 从m1.py文件中导入的,然后会生成m1模块的名称空间
import time
# 删除m1.py文件,m1模块的名称空间仍然存在

time.sleep(10)
import m1 # 不报错,一定不是从文件中获取了m1模块,而是从内存中获取的

2. Built-in modules

Verification will first look for the built-in module, not the custom time.py file first.

# time.py
print('from time.py')
# run.py
import time
print(time) #

3. Search in the environment variable sys.path (emphasis: the first value of sys.path is the folder where the currently executed file is located)

import sys
for n in sys.path:
print(n)
# C:\PycharmProjects\untitled\venv\Scripts\python.exe C:/PycharmProjects/untitled/hello.py
# C:\PycharmProjects\untitled
# C:\PycharmProjects\untitled
# C:\Python\Python38\python38.zip
# C:\Python\Python38\DLLs
# C:\Python\Python38\lib
# C:\Python\Python38
# C:\PycharmProjects\untitled\venv
# C:\PycharmProjects\untitled\venv\lib\site-packages

If mmm.py is in C :\PycharmProjects\untitled\day16 path, and the execution file path is C:\PycharmProjects\untitled. If it is imported normally, an error will be reported. We can add C:\PycharmProjects\untitled\day16 to the environment variable sys.path to prevent Report an error.

# run.py
import sys
sys.path.append(r'C:\PycharmProjects\untitled\day16')
print(sys.path)
import mmm
mmm.f1()

2. The search path is based on the executable file

Assume we have a file with the following directory structure, and the codes in the file are:

而hello和spam.py不是同目录下的，因此run.py的环境变量无法直接找到m2,需要从文件夹导入

from aa import spam
print(spam.money)

四、Python文件的两种用途

一个模块被另一个程序第一次引入时，其主程序将运行。如果我们想在模块被引入时，模块中的某一程序块不执行，我们可以用__name__属性来使该程序块仅在该模块自身运行时执行。

python文件总共有两种用途，一种是执行文件；另一种是被当做模块导入。

每个模块都有一个__name__属性，当其值是'__main__'时，表明该模块自身在运行，否则是被引入。

1、当run.py运行的时候，aaa.py被当做引用模块，它的__name__ == 'aaa'（模块名），会执行aaa.py中的f1()。

# aaa.py
x = 1
def f1():
print('from f1')
f1()
# run.py
import aaa

2、aaa.py被当做可执行文件时，加上__name__ == '__main__'，单独运行aaa.py才会执行aaa.py中的f1()。 run.py运行时可以防止执行f1()。

# aaa.py
x = 1
def f1():
print('from f1')

if __name__ == '__main__':
f1()

五、包

包是一种管理 Python 模块命名空间的形式，包的本质就是一个含有.py的文件的文件夹。

包采用"点模块名称"。比如一个模块的名称是 A.B， 那么他表示一个包 A中的子模块 B 。

目录只有包含一个叫做 __init__.py 的文件才会被认作是一个包。

在导入一个包的时候，Python 会根据 sys.path 中的目录来寻找这个包中包含的子目录。

导入包发生的三件事：

• 创建一个包的名称空间

• 由于包是一个文件夹，无法执行包，因此执行包下的.py文件，将执行过程中产生的名字存放于包名称空间中（即包名称空间中存放的名字都是来自于.py）

• 在当前执行文件中拿到一个名字aaa，aaa是指向包的名称空间的

导入包就是在导入包下的.py，导入m1就是导入m1中的__init__。

1、两种方式导入：

• import ... : 
  import item.subitem.subsubitem 这种导入形式，除了最后一项，都必须是包，而最后一项则可以是模块或者是包，但是不可以是类，函数或者变量的名字。

• from ... import...: 
  当使用 from package import item 这种形式的时候，对应的 item 既可以是包里面的子模块（子包），或者包里面定义的其他名称，比如函数，类或者变量。

2、import 导入包内的模块

import 可以每次只导入一个包里面的特定模块，他必须使用全名去访问。

import aaa.bbb.m3
print(aaa.bbb.m3.func3())

import方式不能导入函数、变量：import aaa.bbb.m3.f3错误

3、from import方式：

导入模块内具体的模块

这种方式不需要那些冗长的前缀进行访问

from aaa.bbb import m3
print(m3.func3())

导入模块内具体的功能

这种方式不需要那些冗长的前缀进行访问

from aaa.bbb.m3 import func3
print(func3())

4、 绝对导入和相对导入

绝对导入：

# aaa/.py
from aaa.m1 import func1
from aaa.m2 import func2

相对导入：

• .代表当前被导入文件所在的文件夹

• ..代表当前被导入文件所在的文件夹的上一级

• ...代表当前被导入文件所在的文件夹的上一级的上一级

from .m1 import func1
from .m2 import func2

5、from...import *

导入语句遵循如下规则：如果包定义文件 __init__.py 存在一个叫做 __all__ 的列表变量，那么在使用 from package import * 的时候就把这个列表中的所有名字作为包内容导入。

这里有一个例子，在:file:sounds/effects/__init__.py中包含如下代码:

__all__ = ["echo", "surround", "reverse"]

这表示当你使用from sound.effects import *这种用法时，你只会导入包里面这三个子模块。

六、软件开发的目录规范

为了提高程序的可读性与可维护性，我们应该为软件设计良好的目录结构，这与规范的编码风格同等重要，简而言之就是把软件代码分文件目录。假设你要写一个ATM软件，你可以按照下面的目录结构管理你的软件代码：

ATM/
|-- core/
| |-- src.py # 业务核心逻辑代码
|
|-- api/
| |-- api.py # 接口文件
|
|-- db/
| |-- db_handle.py # 操作数据文件
| |-- db.txt # 存储数据文件
|
|-- lib/
| |-- common.py # 共享功能
|
|-- conf/
| |-- settings.py # 配置相关
|
|-- bin/
| |-- run.py # 程序的启动文件，一般放在项目的根目录下，因为在运行时会默认将运行文件所在的文件夹作为sys.path的第一个路径，这样就省去了处理环境变量的步骤
|
|-- log/
| |-- log.log # 日志文件
|
|-- requirements.txt # 存放软件依赖的外部Python包列表，详见https://pip.readthedocs.io/en/1.1/requirements.html
|-- README # 项目说明文件

settings.py

# settings.py
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
DB_PATH = os.path.join(BASE_DIR, 'db', 'db.txt')
LOG_PATH = os.path.join(BASE_DIR, 'log', 'user.log')
# print(DB_PATH)
# print(LOG_PATH)

common.py

# common.py
import time
from conf import settings
def logger(msg):
current_time = time.strftime('%Y-%m-%d %X')
with open(settings.LOG_PATH, mode='a', encoding='utf-8') as f:
f.write('%s %s' % (current_time, msg))

src.py

# src.py
from conf import settings
from lib import common
def login():
print('登陆')
def register():
print('注册')
name = input('username>>: ')
pwd = input('password>>: ')
with open(settings.DB_PATH, mode='a', encoding='utf-8') as f:
f.write('%s:%s\n' % (name, pwd))
# 记录日志。。。。。。
common.logger('%s注册成功' % name)
print('注册成功')
def shopping():
print('购物')
def pay():
print('支付')
def transfer():
print('转账')
func_dic = {
'1': login,
'2': register,
'3': shopping,
'4': pay,
'5': transfer,
}
def run():
while True:
print("""
1 登陆
2 注册
3 购物
4 支付
5 转账
6 退出
""")
choice = input('>>>: ').strip()
if choice == '6': break
if choice not in func_dic:
print('输入错误命令，傻叉')
continue
func_dic[choice]()

run.py

# run.py
import sys
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(BASE_DIR)
from core import src
if __name__ == '__main__':
src.run()

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