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This article mainly explains "how to use pipeline Pipe to write optimization code in python", interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn "how to write optimized code using pipeline Pipe in python".

We know that map and filter are two effective Python methods for dealing with iterable objects.

However, if you use both map and filter, the code may look messy.

Wouldn't it be better if you could use the pipe? To deal with it in a way like this.

The Pipe library can do this.

What is a pipe?

Pipe is a Python library that allows you to use pipes in Python.

The pipe (|) passes the result of one method to another.

I like Pipe because it makes my code look more concise when applying multiple methods to Python iterable objects. Since Pipe provides only a few methods, it is also easy to learn Pipe. In this article, I'll show you some of the methods I think are most useful.

To install Pipe, enter:

Pip install pipeWhere: filter elements in iterable objects

Similar to SQL, Pipe's where method can also be used to filter elements in iterable objects.

Select: apply a function to an iterable object

The select method is similar to the map method.

Select applies the method to each element that can be iterated.

In the following code, I use select to multiply each element in the list by 2.

Now, you may wonder: if map and filter have the same functionality, why do we need the where and select methods?

This is because you can use pipes to insert a method after another method. Therefore, the use of pipes eliminates nested parentheses and makes the code more readable.

Expand iterable object 1, chain method

Using nested iterable objects can be painful. Fortunately, we can use chain to link a series of iterable objects.

Although applying chain can reduce the nesting of iterable objects, we still need a more powerful tool. To deal with deeply nested lists, we can use traverse instead.

2. Traverse: recursively expand iterable objects

The traverse method can be used to expand iterable objects recursively. You can use this method to convert a deeply nested list into a flat list.

Let's integrate this method with the select method to get the values of the dictionary and flatten the list.

Isn't it cool to deal with this?

Group elements in a list

Sometimes it can be useful to use specific functions to group elements in a list. This can be easily done through the groupby method.

To see how this method works, let's turn a list of numbers into a dictionary that is grouped according to whether the numbers are even or odd.

In the above code, we use groupby to group numbers into even and odd arrays. The output after applying this method is as follows:

[('Even',), (' Odd',)]

Next, we use select to convert the tuple list into a dictionary list, where the key is the first element in the tuple and the value is the second element in the tuple.

[{'Even': [2,4,6,8]}, {' Odd': [1,3,5,7,9]}]

To get only values greater than 2, we can add the where method to the select method:

The dedup method removes duplicates from the list

This may not sound interesting because the set method can do the same thing. However, this method is more flexible and allows you to get unique elements.

For example, you can use this method to get a unique element less than 5 and another unique element greater than or equal to 5.

Now, let's combine this method with select to find where to get the value of a dictionary with duplicate keys and None values.

In the above code, we:

Delete items with the same name

Get the count value

Select only integer values.

At this point, I believe you have a deeper understanding of "how to use pipeline Pipe to write optimization code in python". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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