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牛逼!Python函数和文件操作(长文系列第三篇)

牛逼!Python函数和文件操作(长文系列第三篇)

原创 教授 程序员教授 8月4日
收录于话题 #Python系列文章

系列第三篇来说一下函数和文件。函数在编程中是一个很重要的角色,我们可以将若干个语句组合形成一个函数,它可以接受传入参数,并在内部进行相关计算后产生输出,将语句封装成函数是为了避免重复使用几个语句造成代码冗杂,让代码更简洁可观性更强。
文件的操作主要是介绍一些关于文件的读取及写入的方法,以及每个方法的不同点和需要注意的事项,最后会介绍一下利用pickle模块存储复杂数据的方式。


函数

函数主要包括两个方面:

  1. 内置函数
  2. 自定义函数

内置函数就是python自带的一些函数,我们只需要给函数传入相关参数就可以进行调用,print就是最基础、最典型的一个内置函数;而自定义函数是需要我们自己按照需求,封装若干个语句形成一个新的函数。

自定义函数

1.创建函数
下面通过自定义一个计算长方体体积的函数来介绍一些属性词:

In [1]: def  vol(length,width,height):
   ...:     volume = length*width*height
   ...:     return volume

上面三行代码中你需要了解:

def:定义函数的关键字
length,width,height:函数的形参
return:函数的返回值

2.调用函数

建好一个自定义函数后,可以通过函数名(实参)的方式调用函数:

In [2]: vol(2,2,3)
Out[2]: 12
    ```
在传入参数时需要注意的是,实参与形参必须完全对应,比如位置、个数等等,否则会出现报错。
```python
In [4]: vol(2,2)
TypeError: vol() missing 1 required positional argument: 'height'
    ```
如果想改变传参顺序,那么你需要指定为哪一个形参传值:
```python
In [8]: vol(width=3,length=4,height=5)
Out[8]: 60

</code></pre>

3.函数默认值

函数的形参还可以指定默认值,假如我们将上面的vol函数中height参数默认值设为2:

<pre><code class="language-python ">In [6]: def  vol(length,width,height=2):
   ...:     volume = length*width*height
   ...:     return volume
   ...:
In [7]: vol(2,2)
Out[7]: 8
</code></pre>

这时只向vol函数中传入两个实参,可以发现没有报错,并且得到返回值为8。也就是说如果一个形参有默认值,而调用函数时没有为这个形参传值,那么这个参数就取默认值。

4.收集函数(可变函数)

对于一个函数的形参我们也可以将其设置为可以变化的:

<pre><code class="language-python ">In [9]: def test(*params):
   ...:     print('参数的长度为%d'%len(params))
   ...:     print('第三个参数为%s'%params[2])
   ...:
In [10]: test(1,2,'mao',3.14,'pp')
</code></pre>

参数的长度为5
第三个参数为mao
这里需要将形参用*标识,然后在调用参数的时候可以传入若干个实参。

5.全局与局部

在函数中定义的常量被称为局部变量,也就是仅限在这个函数中可以调用,不接受在函数之外使用:

<pre><code class="language-python ">In [12]: def test(a,b):
    ...:     c = 2
    ...:     return a*b*c

In [13]: test(2,2)
Out[13]: 8
In [14]: print(c)
NameError: name 'c' is not defined
</code></pre>

6.匿名函数lambda

如果一个函数内部的语句不是很复杂,代码量很少,我们就可以利用匿名函数,比如上面计算体积的函数:

<pre><code class="language-python ">In [20]: vol = lambda a,b,c:a*b*c

In [21]: vol(2,2,3)
Out[21]: 12
</code></pre>

lambda表达式常常嵌套的语句中,结合相关函数使用会很简便,后面会给出例子。

7.内嵌函数

在定义函数时还支持几个函数嵌套,但用的时候需要注意逻辑关系:

<pre><code class="language-python ">In [24]: def fun1(a):
    ...:     b = 2
    ...:     def fun2():
    ...:         return a*b
    ...:     return fun2()
    ...:

In [25]: fun1(4)
Out[25]: 8
</code></pre>

<h3>常用内置函数</h3>

内置函数前两篇文章就有涉及过,比如常用的len、sorted、reversed、sum等等,除此之外再介绍几个比较基础的内置函数。

1.max和min

<pre><code class="language-python ">求一个序列中最大值和最小值:

In [28]: min(1,2,3)
Out[28]: 1

In [29]: max(1,2,3)
Out[29]: 3

</code></pre>

2.abs

<pre><code class="language-python ">求一个数的绝对值:

In [31]: abs(-1)
Out[31]: 1


</code></pre>

3.round

<pre><code class="language-python ">四舍五入保留小数点后几位:

In [32]: round(3.555,2)
Out[32]: 3.56


</code></pre>

4.pow

<pre><code class="language-python ">计算一个数的幂次方,或者再取余:

In [33]: pow(2,3)#2*2*2
Out[33]: 8

In [34]: pow(2,3,3)#(2*2*2)%3
Out[34]: 2


</code></pre>

5.divmod

<pre><code class="language-python ">计算一个数的商和余数:

In [36]: divmod(10,3)
Out[36]: (3, 1)

    ```
6.help
```python
用来查询一个函数的帮助文档:

In [37]: help(abs)
Help on built-in function abs in module builtins:

abs(x, /)
    Return the absolute value of the argument.

</code></pre>

7.filter

filter()函数接收两个参数,第一个参数可以是一个函数或者None,第二个参数是序列。作用是对每个元素进行判断,返回 True或 False,filter()根据判断结果自动过滤掉序列中为False的元素,留下为True的元素,可以结合lambda表达式使用:

<pre><code class="language-python ">In [38]: list(filter(lambda x:x%2,range(10)))
Out[38]: [1, 3, 5, 7, 9]
</code></pre>

8.map

map()函数接收两个参数,一个是函数,一个是序列。作用是将函数应用于序列中每一个元素上,同样可以结合lambda表达式使用:

<pre><code class="language-python ">In [42]: list(map(lambda x: x*2,range(10)))
Out[42]: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
</code></pre>

<hr />

<img src="https://www.xiaozhan95.com/wp-content/uploads/2020/09/1.png" alt="" />

<h2>文件</h2>

关于文件读写操作,open()函数是一定遇到的,如果文件已经存在则会打开文件,若不存在则会创建一个文件,通常的用法需要两个参数:open(filename,mode)。

第一个参数就是文件名字,第二个参数就指定文件将会被如何使用,可选模式常用的有以下几种:

<em>'r':以只读的方式打开文件(默认)
'w':以写入模式打开文件,会覆盖已存在的文件
'a':以写入模式打开文件,如果文件存在,则在末尾追加写入
'b':以二进制模式打开文件,进而会有rb、wb等模式组合</em>

1.read()方法读取

read()方法可传入一个参数size,也就是读取内容的长度。size是一个可选参数,如果不传入或者传入一个负数,那么会读取文件全部内容:

<pre><code class="language-python "><br />In [52]: fb = open('E:/Python基础/test.txt','r')

In [53]: fb.read(10)
Out[53]: 'nai\nniatan'

In [54]: fb.read()
Out[54]: 'g\nnaitangmao'

In [55]: fb.read()
Out[55]: ''
</code></pre>

需要注意的有三点:

<ol>
<li>原文件中换行的地方在读取时以换行符'\n'表示,并且也占有一个单位长度</li>
<li>已经被读取的内容不能被重复读取</li>
<li>如果读取内容返回为空字符串,表示已经到了文件末尾</li>
</ol>

2.readline()方法

readline()方法是从文件中读取单独一行,并且在这一行数据的末尾处会有一个换行符'\n',如果其中一行没有数据,则会只返回一个'\n',同样当返回空字符串时表示到达文件末尾。

<pre><code class="language-python ">In [59]: fb1 = open('E:/Python基础/test.txt','r')

In [60]: fb1.readline()
Out[60]: 'nai\n'
</code></pre>

3.readlines()方法

readlines()方法也是用来读取全部文件,与read()不同之处在于前者是按行读取,并且最后返回的是一个列表,每一行数据作为一个列表元素:

<pre><code class="language-python ">In [72]: fb3 = open('E:/Python基础/test.txt','r')

In [73]: fb3.readlines()
Out[73]: ['nai\n', 'niatang\n', 'naitangmao']
</code></pre>

4.遍历文件对象读取

这种方式读取出的内容看起来会比较规范一些:

<pre><code class="language-python ">In [81]: for i in fb4:
    ...:     print(i,end = '')
    ...:
nai
niatang
naitangmao
</code></pre>

5.文件的写入

在进行写入操作的时候,我们需要注意的两个点:

写入的数据如果是非字符串内容,需要转换为字符串
写入的方式要注意是覆盖还是追加

<pre><code class="language-python ">In [85]: fb5 = open('E:/Python基础/test1.txt','w')

In [89]: list1 = [1,2]
In [91]: fb5.write(str(list1))
Out[91]: 6

#用write写入后会返回写入字符串的长度
    ```


6.文件关闭

切记切记切记!如果你用open()的方式打开一个文件,在操作完成之后一定要用close()方法关闭文件。
```python
In [92]: fb5.close()
    ```

7.with方式

如果你感觉自己的记性不好,总是忘记用close()方法关闭文件,那么就要习惯利用with处理文件对象,它可以在文件用完之后自动关闭文件。
```python
In [93]: with open('E:/Python基础/test.txt','r') as fb:
    ...:     data = fb.read()

In [95]: fb.closed
Out[95]: True

8.pickle

上面说了将一个非字符串写入文件是不允许的,如果有没有办法保存一份字典或者列表形式的数据呢?pickle模块就可以实现这种序列化的存储与读取:

In [96]: import pickle
In [97]: list1 = ['nai','tang','mao',1,2,3]

In [98]: pic_f = open('E:/Python基础/list.pkl','wb')
In [99]: pickle.dump(list1,pic_f)
In [100]: pic_f.close()

dump()方法接收两个参数,第一个是要存储的内容,第二个是存储的文件对象,操作之后也需要用close()关闭文件对象,存储之后可以利用load()方法加载文件中的内容。

In [102]: pic_f = open('E:/Python基础/list.pkl','rb')
In [103]: list2 = pickle.load(pic_f)

In [104]: list2
Out[104]: ['nai', 'tang', 'mao', 1, 2, 3]
In [105]: pic_f.close()

利用pickle在存储或者读取的时候要注意以二进制的形式操作文件对象,也就是’wb’和’rb’,pickle很适合用来存储数据类型比较复杂并且数据量又很大的数据。


往期推介:

第一篇传送门
第二篇传送门

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