Tour Python Six: basic function - the difference between functional programming and process-oriented programming, open the function, lambda expressions, built-in parameter lists, recursion

One, background

Before learning function, has followed: process-oriented programming, namely: realize the function from top to bottom based on business logic, it is often with a long piece of code to implement the specified functions, the process of developing the most common operation is to copy and paste, that is, copy to the function now required to achieve the previous code blocks, as follows:

while True：

if cpu利用率 > 90%:

#发送邮件提醒

连接邮箱服务器

发送邮件

关闭连接

if 硬盘使用空间 > 90%:

#发送邮件提醒

连接邮箱服务器

发送邮件

关闭连接

if 内存占用 > 80%:

#发送邮件提醒

连接邮箱服务器

发送邮件

关闭连接

The contents described above if condition code may be extracted from the multiplexed as follows:

def 发送邮件(内容)

#发送邮件提醒

连接邮箱服务器

发送邮件

关闭连接

while True：

if cpu利用率 > 90%:

发送邮件('CPU报警')

if 硬盘使用空间 > 90%:

发送邮件('硬盘报警')

if 内存占用 > 80%:

For the above two implementations, the second time than the first necessity of reusability and readability is better, in fact, this is the difference between functional programming and process-oriented programming:

Functional: The function code is encapsulated into a function, not need to repeat the preparation of the future, the function can be called only
Object-oriented: the classification and packaging of the function, allowing developers to "faster and better and stronger ..."

The most important functional programming is to enhance reusability and readability of the code

Second, the definition and use of

def 函数名(参数):

...

函数体

...

返回值

Defined functions have the following main points:

def: function representation keywords
Function name: name of the function, later calling the function according to the function name
Body function: function series of logic calculation, such as: send a message, to calculate the maximum number of [11,22,38,888,2] ... the like
Parameters: providing data as a function of the body
Return value: When the function is finished, you can return data to the caller.

1. Return value

Function is a function block, this function is executed successfully or not in the end, it is necessary to inform the caller by the return value.

In the above points, the more important parameters and return values:

def 发送短信():

发送短信的代码...

if 发送成功:

return True

else:

return False

while True:

# 每次执行发送短信函数，都会将返回值自动赋值给result

# 之后，可以根据result来写日志，或重发等操作

result = 发送短信()

if result == False:

记录日志，短信发送失败...

2. Parameters

Why should the parameters? Next, the case where the parameters have not achieved and no parameters

1) No case of parameters to achieve:

def CPU报警邮件()
    #发送邮件提醒
    连接邮箱服务器
    发送邮件
    关闭连接

def 硬盘报警邮件()
    #发送邮件提醒
    连接邮箱服务器
    发送邮件
    关闭连接

def 内存报警邮件()
    #发送邮件提醒
    连接邮箱服务器
    发送邮件
    关闭连接
 
while True：
 
    if cpu利用率 > 90%:
        CPU报警邮件（）
 
    if 硬盘使用空间 > 90%:
        硬盘报警邮件（）
 
    if 内存占用 > 80%:
        内存报警邮件（）

2) There are cases parameters to achieve:

def 发送邮件(邮件内容)

    #发送邮件提醒
    连接邮箱服务器
    发送邮件
    关闭连接

 
while True：
 
    if cpu利用率 > 90%:
        发送邮件("CPU报警了。")
 
    if 硬盘使用空间 > 90%:
        发送邮件("硬盘报警了。")
 
    if 内存占用 > 80%:
        发送邮件("内存报警了。")

3. The function of the three different parameters:

1) the general parameters

2) default parameters

3) dynamic parameters

Case of the normal parameters as follows:

# ######### 定义函数 ######### 

# name 叫做函数func的形式参数，简称：形参
def func(name):
    print name

# ######### 执行函数 ######### 
#  'wupeiqi' 叫做函数func的实际参数，简称：实参
func('wupeiqi')

Default parameters are as follows:

def func(name, age = 18):
    
    print "%s:%s" %(name,age)

# 指定参数
func('wupeiqi', 19)
# 使用默认参数
func('alex')

注：默认参数需要放在参数列表最后

The dynamic parameters are as follows:

A case where the movable reference:

def func(*args):

    print args


# 执行方式一
func(11,33,4,4454,5)

# 执行方式二
li = [11,2,2,3,3,4,54]
func(*li)

Where two dynamic parameters:

def func(**kwargs):

    print args


# 执行方式一
func(name＝'wupeiqi',age=18)

# 执行方式二
li = {'name':'wupeiqi', age:18, 'gender':'male'}
func(**li)

Fixed the reference case three:

def func(*args, **kwargs):

    print args
    print kwargs

4. Extension: send a message instance

import smtplib
from email.mime.text import MIMEText
from email.utils import formataddr
  
  
msg = MIMEText('邮件内容', 'plain', 'utf-8')
msg['From'] = formataddr(["武沛齐",'[email protected]'])
msg['To'] = formataddr(["走人",'[email protected]'])
msg['Subject'] = "主题"
  
server = smtplib.SMTP("smtp.126.com", 25)
server.login("[email protected]", "邮箱密码")
server.sendmail('[email protected]', ['[email protected]',], msg.as_string())
server.quit()

The built-in parameter list taken from: https://docs.python.org/3/library/functions.html#next

6. open function

This function is used to process the file, the file operation generally go through the steps of:

open a file
Action File

1) Open the file

1	`文件句柄` `=` `open('文件路径',` `'模式')`

打开文件时，需要指定文件路径和以何等方式打开文件，打开后，即可获取该文件句柄，日后通过此文件句柄对该文件操作。

打开文件的模式有：

r ，只读模式【默认】
w，只写模式【不可读；不存在则创建；存在则清空内容；】
x，只写模式【不可读；不存在则创建，存在则报错】
a，追加模式【可读；不存在则创建；存在则只追加内容；】

"+" 表示可以同时读写某个文件

r+，读写【可读，可写】
w+，写读【可读，可写】
x+ ，写读【可读，可写】
a+，写读【可读，可写】

"b"表示以字节的方式操作

rb 或 r+b
wb 或 w+b
xb 或 w+b
ab 或 a+b

注：以b方式打开时，读取到的内容是字节类型，写入时也需要提供字节类型

2）操作方法（3.x情况）

class TextIOWrapper(_TextIOBase):
    """
    Character and line based layer over a BufferedIOBase object, buffer.
    
    encoding gives the name of the encoding that the stream will be
    decoded or encoded with. It defaults to locale.getpreferredencoding(False).
    
    errors determines the strictness of encoding and decoding (see
    help(codecs.Codec) or the documentation for codecs.register) and
    defaults to "strict".
    
    newline controls how line endings are handled. It can be None, '',
    '\n', '\r', and '\r\n'.  It works as follows:
    
    * On input, if newline is None, universal newlines mode is
      enabled. Lines in the input can end in '\n', '\r', or '\r\n', and
      these are translated into '\n' before being returned to the
      caller. If it is '', universal newline mode is enabled, but line
      endings are returned to the caller untranslated. If it has any of
      the other legal values, input lines are only terminated by the given
      string, and the line ending is returned to the caller untranslated.
    
    * On output, if newline is None, any '\n' characters written are
      translated to the system default line separator, os.linesep. If
      newline is '' or '\n', no translation takes place. If newline is any
      of the other legal values, any '\n' characters written are translated
      to the given string.
    
    If line_buffering is True, a call to flush is implied when a call to
    write contains a newline character.
    """
    def close(self, *args, **kwargs): # real signature unknown
        关闭文件
        pass

    def fileno(self, *args, **kwargs): # real signature unknown
        文件描述符  
        pass

    def flush(self, *args, **kwargs): # real signature unknown
        刷新文件内部缓冲区
        pass

    def isatty(self, *args, **kwargs): # real signature unknown
        判断文件是否是同意tty设备
        pass

    def read(self, *args, **kwargs): # real signature unknown
        读取指定字节数据
        pass

    def readable(self, *args, **kwargs): # real signature unknown
        是否可读
        pass

    def readline(self, *args, **kwargs): # real signature unknown
        仅读取一行数据
        pass

    def seek(self, *args, **kwargs): # real signature unknown
        指定文件中指针位置
        pass

    def seekable(self, *args, **kwargs): # real signature unknown
        指针是否可操作
        pass

    def tell(self, *args, **kwargs): # real signature unknown
        获取指针位置
        pass

    def truncate(self, *args, **kwargs): # real signature unknown
        截断数据，仅保留指定之前数据
        pass

    def writable(self, *args, **kwargs): # real signature unknown
        是否可写
        pass

    def write(self, *args, **kwargs): # real signature unknown
        写内容
        pass

    def __getstate__(self, *args, **kwargs): # real signature unknown
        pass

    def __init__(self, *args, **kwargs): # real signature unknown
        pass

    @staticmethod # known case of __new__
    def __new__(*args, **kwargs): # real signature unknown
        """ Create and return a new object.  See help(type) for accurate signature. """
        pass

    def __next__(self, *args, **kwargs): # real signature unknown
        """ Implement next(self). """
        pass

    def __repr__(self, *args, **kwargs): # real signature unknown
        """ Return repr(self). """
        pass

    buffer = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    closed = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    encoding = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    errors = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    line_buffering = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    name = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    newlines = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    _CHUNK_SIZE = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

    _finalizing = property(lambda self: object(), lambda self, v: None, lambda self: None)  # default

3）管理上下文

为了避免打开文件后忘记关闭，可以通过管理上下文，即：

1 with open('log','r') as f:
2
3    ...

如此方式，当with代码块执行完毕时，内部会自动关闭并释放文件资源。

在Python 2.7 及以后，with又支持同时对多个文件的上下文进行管理，即：

1 with open('log1') as obj1, open('log2') as obj2:
2    pass

7. lambda表达式

学习条件运算时，对于简单的 if else 语句，可以使用三目运算来表示，即：

1 # 普通条件语句
2 if 1 == 1:
3    name = 'wupeiqi'
4 else:
5    name = 'alex'
6    
7 # 三元运算
8 name = 'wupeiqi' if 1 == 1 else 'alex'

对于简单的函数，也存在一种简便的表示方式，即：lambda表达式

1 # ###################### 普通函数 ######################
2 # 定义函数（普通方式）
3 def func(arg):
4    return arg + 1
5    
6 # 执行函数
7 result = func(123)
8    
9 # ###################### lambda ######################
10    
11 # 定义函数（lambda表达式）
12 my_lambda = lambda arg : arg + 1
13    
14 # 执行函数
15 result = my_lambda(123)

8. 递归

利用函数编写如下数列：

斐波那契数列指的是这样一个数列 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233，377，610，987，1597，2584，4181，6765，10946，17711，28657，46368...

1 def func(arg1,arg2):
2   if arg1 == 0:
3        print arg1, arg2
4    arg3 = arg1 + arg2
5    print arg3
6    func(arg2, arg3)
7  
8 func(0,1)

9. 练习题

1）简述普通参数、指定参数、默认参数、动态参数的区别

2）写函数，计算传入字符串中【数字】、【字母】、【空格] 以及【其他】的个数

3）写函数，判断用户传入的对象（字符串、列表、元组）长度是否大于5。

4）写函数，检查用户传入的对象（字符串、列表、元组）的每一个元素是否含有空内容。

5）写函数，检查传入列表的长度，如果大于2，那么仅保留前两个长度的内容，并将新内容返回给调用者。

6）写函数，检查获取传入列表或元组对象的所有奇数位索引对应的元素，并将其作为新列表返回给调用者。

7）写函数，检查传入字典的每一个value的长度,如果大于2，那么仅保留前两个长度的内容，并将新内容返回给调用者。

1 dic = {"k1": "v1v1", "k2": [11,22,33,44]}
2  
3 PS:字典中的value只能是字符串或列表

8）写函数，利用递归获取斐波那契数列中的第 10 个数，并将该值返回给调用者。

Tour Python Six: basic function - the difference between functional programming and process-oriented programming, open the function, lambda expressions, built-in parameter lists, recursion

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