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This article mainly introduces "what are the skills of writing more concise Python code". In daily operation, I believe that many people have doubts about the skills of writing more concise Python code. Xiaobian consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful for you to answer the questions of "what are the skills of writing more concise Python code?" Next, please follow the editor to study!

1. List, Dictionary and set understanding

List understanding is one of the favorite features of many Python programmers. This is a very concise way to create list objects from iterators. The basic syntax is [iterable x expression]. Let's look at some examples to see how they are used.

As you can see, without using list derivation, we must create an empty list and add the square of each number by running the for loop, which requires three lines of code. By contrast, we can build the same list of squares through list understanding with only one line of code. Isn't that cool?

In addition to list understanding, there are also dictionaries and set understandings. Dictionary understanding has the following basic syntax {key_expr: value_expr} for x in iterable, while for collection understanding, the basic syntax is {expression} for iterable in x. Let's look at some simple examples below. Similar to the list understanding example, it will take multiple lines of code to build the required dictionary and set it up without using understanding techniques.

two。 Name the tuple a data structure

We know that tuples are useful for storing some related data. However, it is not very convenient to use them, especially when it comes to accessing specific elements, because we have to remember the order and use the correct index of specific elements.

Although we can create a custom class to manage the relevant data if we don't want to use tuples, the namedtuple data type can be a very useful lightweight data structure. Through the collection module available, the namedtuple data type uses the following basic syntax: namedtuple (Typename,field_names). Although the grammar is not very simple, it is actually conceptually easy to understand.

Let's look at some relevant examples. The ideal function is to create a data structure that can store student information, including name, gender, and student ID number.

As you know, with namedtuple, we can write lightweight data structures in more concise code. Of course, it should be noted that custom classes provide you with more functionality that you can manipulate. However, if your goal is to create data structures for data storage and retrieval purposes, you can definitely consider using namedtuple.

3. Iterate with enumerate () and zip ()

An important principle of coding is DRY, which stands for "Don't repeat yourself." This is a common task when we are dealing with a series of data, such as a list of numbers, and we need to do the same for each number in the list. To avoid repeating the same code, we can use the for loop to run iterations of the entire list.

When we iterate over a list or any sequence, sometimes we also need to know where the item is in the sequence. There are two ways to do this. Let's see what they are.

As you can see, by using the built-in function enumerate (), we can easily access the indexes and elements in the sequence, which is more concise than the first iteration. More importantly, it can set a starting number to count. In the above example, we set it to 1.

In addition to the enumerate () function, the zip () function is also useful in iterations. This function can create tuples from multiple iterable objects without explicitly creating composite iterable objects of those iterable objects. It sounds confusing, but we can see its usage in the following example.

Basically, the zip () function fetches each element from the iterable object in each iteration to form a tuple in turn. This code is more concise and more readable than lengthy code, isn't it?

4. Format a string with an f string

Strings are a basic data type and we use them almost everywhere. A basic application of strings is to use them in a certain format. There are several ways to format strings, for which I'd like to introduce f strings.

In short, an f string is an interpolated string text, using the letter f (or F) as the prefix for the string text. To write concise code, I'll show you only two use cases of preferred f strings.

Displays variables. The most basic use is to display the values of some variables for debugging during development. If you use the traditional format () method, it takes longer.

Connection variable / connection string. Instead of directly using the + symbol and the join () method of the string, the f string is a very simple method for concatenating strings and is highly readable. Practical uses include construction file paths, as shown in the following example.

5. Lambda function

The Lambda function is an anonymous function in Python and is usually used where minor operations are required. The Lambda function can take one or more parameters, has a single expression, and has the following syntax Lambda parameter: expression.

I will only use the built-in sorted () function to demonstrate the use of the lambda function. Specifically, the sorted () function sorts iteratable objects using the key function specified by the key parameter. I'll show you that we can use the lambda function as a key parameter instead of declaring a regular function using the def keyword.

At this point, the study of "what are the techniques for writing more concise Python code" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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