Syntactic Sugar: Why Python Is Sweet and Pythonic
by:
blow post content copied from Real Python
click here to view original post
Python has several pieces of syntax that are syntactic sugar. This sugar is syntax that isn’t strictly necessary but gives Python some of its flavor as a readable, beginner-friendly, and powerful language. In this tutorial, you’ll explore some of Python’s most used pieces of syntactic sugar.
In practice, you already use most of these pieces of syntax, as they include many well-known Pythonic constructs. As you read on, you’ll see how Python works under the hood and learn how to use the language efficiently and securely.
In this tutorial, you’ll learn:
- What syntactic sugar is
- How syntactic sugar applies to operators
- How assignment expressions are syntactic sugar
- How
forloops and comprehensions are syntactic sugar - How other Python constructs are also syntactic sugar
To get the most out of this tutorial, you should be familiar with the basics of Python, including operators, expressions, loops, decorators, classes, context managers, and more.
Get Your Code: Click here to download the free sample code that shows you how to use syntactic sugar in Python.
Take the Quiz: Test your knowledge with our interactive “Syntactic Sugar: Why Python Is Sweet and Pythonic” quiz. You’ll receive a score upon completion to help you track your learning progress:
Interactive Quiz
Syntactic Sugar: Why Python Is Sweet and PythonicYou can take this quiz to test your understanding of Python's most common pieces of syntactic sugar and how they make your code more Pythonic and readable.
Syntactic Sugar
In programming, syntactic sugar refers to pieces of syntax that simplify the code and make it more readable or concise. Syntactic sugar lets you express things in a clearer and more readable way.
It makes the language sweeter for human use: things can be expressed more clearly, more concisely, or in an alternative style that some may prefer. (Source)
However, syntactic sugar is something that you may not need in practice because you can get the same result using a different, and often more involved, construct.
Note: This tutorial is slightly inspired by Brett Cannon’s series of posts about unraveling syntactic sugar in Python. In that series, Brett goes deep into each piece of syntactic sugar. You can check out the series if you’d like a detailed discussion of the syntax constructs covered in this tutorial and others.
Python has many pieces of syntactic sugar that you’ll regularly use in your code. These syntax constructs make Python more readable, quicker to write, and user-friendly. Understanding these syntactic sugar pieces and their significance will help you better understand the inner workings of Python.
In rare situations, you’ll find that desugared versions of a given piece of syntactic sugar can better fulfill your needs. So, knowing about the alternative code to a given sugar can be a good skill to have.
Operators in Python
As with most programming languages, Python makes extensive use of operators. You’ll find several categories of operators, including arithmetic, assignment, augmented assignment, comparison, Boolean, and membership operators. All these operators are part of Python’s syntactic sugar constructs because they let you write expressions in a quick and readable way.
Note: To dive deeper into Python operators, check out the Operators and Expressions in Python tutorial.
For example, arithmetic operators allow you to create math expressions that are quick to write and read because they look pretty similar to what you learned in math class:
>>> 5 + 7
12
>>> 10 - 4
6
>>> 2 * 4
8
>>> 20 / 2
10
In the first example, you use the plus operator (+) to add two numbers. In the second example, you use the subtraction operator (-) to subtract two numbers. The final two examples perform multiplication and division.
Python supports its arithmetic operators through special methods. Here’s a quick summary:
| Operator | Operation | Method |
|---|---|---|
+ |
Addition | .__add__() |
- |
Subtraction | .__sub__() |
* |
Multiplication | .__mul__() |
/ |
Division | .__truediv__() |
// |
Integer division | .__floordiv__() |
** |
Exponentiation | .__pow__() |
What does it mean to say Python supports its operators through special methods? It means that every time you use an operator, Python calls the corresponding special method under the hood.
Note: To learn more about special methods, also known as magic or dunder methods, check out Python’s Magic Methods: Leverage Their Power in Your Classes.
To illustrate, here’s how you can express the arithmetic operations you wrote earlier using the appropriate special methods:
Read the full article at https://realpython.com/syntactic-sugar-python/ »
[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]
October 14, 2024 at 07:30PM
Click here for more details...
=============================
The original post is available in Real Python by
this post has been published as it is through automation. Automation script brings all the top bloggers post under a single umbrella.
The purpose of this blog, Follow the top Salesforce bloggers and collect all blogs in a single place through automation.
============================
Post a Comment