python工具的功能介绍_Python功能工具

python工具的功能介绍

One of the biggest power which Python demonstrates is providing tools for writing reusable code. In this lesson, we will learn about Python functools module, which makes writing reusable code easy and very much maintainable.

Python演示的最大功能之一就是提供用于编写可重用代码的工具。在本课程中，我们将学习Python functools模块，该模块使编写可重用的代码变得容易且非常可维护。

Python functools模块 (Python functools module)

Python functools module provides us various tools which allows and encourages us to write reusable code. Some of them are:

Python functools模块为我们提供了各种工具，这些工具允许并鼓励我们编写可重用的代码。他们之中有一些是：

Partial functions部分功能
Updating Partial wrappers更新部分包装器
Total ordering总订购

Let’s start our post with a short and informative discussion on partial functions.

让我们以关于局部函数的简短而丰富的讨论开始我们的文章。

什么是部分功能？ (What are partial functions?)

Python functools partial functions are used to:

Python functools局部函数用于：

Replicate existing functions with some arguments already passed in.使用已传入的一些参数复制现有函数。
Creating new version of the function in a well-documented manner.以有据可查的方式创建功能的新版本。

使用functools的部分功能 (partial functions using functools)

The points we stated above can be well understood with some examples. Let’s study them now.

我们上面列举的几点可以通过一些例子很好地理解。让我们现在研究它们。

Suppose you have a function called multiplier which just multiplies two numbers. Its definition looks like:

假设您有一个名为multiplier的函数，该函数仅将两个数字相乘。其定义如下：

def multiplier(x, y):return x * y

Now, what if we want to make some dedicated functions to double or triple a number? We will have to define new functions as:

现在，如果我们想做一些专用的功能来将数字加倍或三倍呢？我们将必须定义新功能为：

def multiplier(x, y):return x * ydef doubleIt(x):return multiplier(x, 2)def tripleIt(x):return multiplier(x, 3)

Well, these were easy but what happens when we need 1000 such functions? Here, we can use partial functions:

好吧，这些很容易，但是当我们需要1000个这样的功能时会发生什么呢？在这里，我们可以使用部分函数：

from functools import partialdef multiplier(x, y):return x * ydouble = partial(multiplier, y=2)
triple = partial(multiplier, y=3)print('Double of 2 is {}'.format(double(5)))

Well, that was much shorter, isn’t it? Output of the example remains unaffected as:

We can even make multiple partials in a loop:

好吧，那要短得多，不是吗？该示例的输出不受影响，因为：

我们甚至可以在循环中制作多个局部：

from functools import partialdef multiplier(x, y):return x * ymultiplier_partials = []
for i in range (1, 11):function = partial(multiplier, i)multiplier_partials.append(function)print('Product of 1 and 2 is {}'.format(multiplier_partials[0](2)))
print('Product of 3 and 2 is {}'.format(multiplier_partials[2](2)))
print('Product of 9 and 2 is {}'.format(multiplier_partials[8](2)))

This time, we collected more functions in a list and called them. Output will be:

这次，我们在列表中收集了更多函数并将其称为。输出将是：

部分功能是自我记录的 (partial functions are self-documented)

Even though partial functions can be treated as completely independent functions, they themselves never lose the memory of the function which powers them.

即使可以将部分功能视为完全独立的功能，但它们本身也永远不会失去为其提供动力的功能的记忆。

This can be proved from the doc meta-data they hold:

这可以从他们拥有的文档元数据中得到证明：

from functools import partialdef multiplier(x, y):return x * ydouble = partial(multiplier, y=2)
triple = partial(multiplier, y=3)print('Function powering double is {}'.format(double.func))
print('Default keywords for double is {}'.format(double.keywords))

Output will be:

First call gives the function name with its memory address.

输出将是：

首次调用将给出函数名称及其内存地址。

在functools中测试部分功能 (Testing partial functions in functools)

It is simple to test a partial function. We can even test its documentation. Let’s see how it is done:

测试部分功能很简单。我们甚至可以测试其文档。让我们看看它是如何完成的：

from functools import partialdef multiplier(x, y):return x * ydouble = partial(multiplier, y=2)
triple = partial(multiplier, y=3)assert double.func == multiplier
assert double.keywords == {'y': 2}

When you run this script, you won’t see any output as Assertions only give an error output when they fail. If they pass, they silently continue the execution of the code.

运行此脚本时，您将看不到任何输出，因为断言仅在失败时给出错误输出。如果通过，则它们将静默继续执行代码。

使用functool.update_wrapper（）更新部分函数元数据 (Update partial function metadata with functool.update_wrapper())

With functools module, we can update metadata of a function with wrappers. Let us look at example code snippet to clarify how this is done:

借助functools模块，我们可以使用包装器更新函数的元数据。让我们看一下示例代码片段，以阐明如何完成此操作：

import functoolsdef multiplier(x, y):"""Multiplier doc string."""return x * ydef show_details(name, function):"""Details callable object."""print('Name: {}'.format(name))print('\tObject: {}'.format(function))try:print('\t__name__: {}'.format(function.__name__))except AttributeError:print('\t__name__: {}'.format('__no name__'))print('\t__doc__ {}'.format(repr(function.__doc__)))returndouble = functools.partial(multiplier, y=2)show_details('raw wrapper', double)print('Updating wrapper:')
print('\tassign: {}'.format(functools.WRAPPER_ASSIGNMENTS))
print('\tupdate: {}'.format(functools.WRAPPER_UPDATES))functools.update_wrapper(double, multiplier)
show_details('updated wrapper', double)

Output of this script will be:

Before update wrapper, the partial function didn’t have any data about its name and proper doc string but update_wrapper() function changed that.

该脚本的输出为：

在更新包装器之前，部分函数没有有关其名称和适当的文档字符串的任何数据，但是update_wrapper()函数对此进行了更改。

使用functool进行总订购 (Total ordering with functool)

functools module also provide a way to provide automatic comparison functions. There are 2 conditions which needs to be met to accomplish the results:

functools模块还提供了一种提供自动比较功能的方法。要实现结果，需要满足两个条件：

Definition of at least one comparison function is a must like le, lt, gt or ge.必须至少定义一个比较函数，例如le ， lt ， gt或ge 。
Definition of eq function is mandatory.eq函数的定义是强制性的。

So, this is what we will do:

因此，这是我们将要做的：

from functools import total_ordering@total_ordering
class Number:def __init__(self, value):self.value = valuedef __lt__(self, other):return self.value < other.valuedef __eq__(self, other):return self.value == other.valueprint(Number(1) < Number(2))
print(Number(10) > Number(21))
print(Number(10) <= Number(2))
print(Number(10) >= Number(20))
print(Number(2) <= Number(2))
print(Number(2) >= Number(2))
print(Number(2) == Number(2))
print(Number(2) == Number(3))

Output of this script will be:

This was actually easy to understand as it allowed us to remove redundant code in our class definition.

该脚本的输出为：

这实际上很容易理解，因为它允许我们在类定义中删除冗余代码。

In this lesson, we learned about various ways through which we can improve code reusability with functools module in Python.

在本课程中，我们学习了各种方法，可以通过这些方法来提高Python中functools模块的代码可重用性。

Reference: API Doc

参考： API文档

翻译自: https://www.journaldev.com/17550/python-functools

python工具的功能介绍