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Decorators in Python are a powerful feature that allows you to modify or extend the behavior of functions without changing their actual code. In this blog post, we’ll explore two examples: a basic decorator to add behavior around a function and a more practical one to simulate access control. Let’s get started!1. Basic Decorator ExampleHere’s a simple decorator that adds some behavior before and..

When writing Python code, you often need to make your code more readable and maintainable, especially for larger projects. This is where type hinting becomes essential. Type hints help you specify the expected types of variables, function arguments, and return values. Let’s explore how to use type hints effectively with simple examples.Why Use Type Hints?Type hints help:Improve code readability...

When working on Python projects, you might encounter situations where a class needs to contain another class. This is where nested classes can be helpful. In this post, we will understand what nested classes are, when to use them, and how they compare to using two separate classes. Let’s begin with a simple example using two separate classes and then explore how the same functionality can be ach..

The requests library in Python is a powerful tool for making HTTP requests, allowing you to interact with APIs, fetch data from websites, and send data to servers. It's simple, user-friendly, and perfect for beginners.InstallationInstall the requests library using pip if you don’t have it installed:pip install requestsKey Features and ExamplesLet’s dive into the most useful and practical use cas..

IntroductionWhen dealing with configuration files or structured data, YAML (short for “YAML Ain’t Markup Language”) is a popular format due to its simplicity and readability. YAML organizes data in a human-readable manner with minimal syntax, using indentation and symbols like : for key-value pairs, - for lists, and nesting for hierarchy. In Python, the PyYAML library allows seamless interaction..

003_Python Advanced: Filter FunctionWhat is the filter() Function?The filter() function in Python is used to filter elements from an iterable (like a list, tuple, etc.) based on a condition provided by a function. It returns a filter object, which is an iterator containing elements that satisfy the condition.The power of filter() lies in its ability to simplify the process of filtering data with..

map() 함수란?Python에서 map() 함수는 주어진 함수를 반복 가능한 객체(예: 리스트, 튜플 등)의 모든 항목에 적용하는 데 사용됩니다. 이 함수는 맵 객체(iterator)를 반환하며, 이를 리스트, 튜플 또는 다른 반복 가능한 객체로 변환할 수 있습니다.map() 함수의 강력한 점은 반복 가능한 객체의 여러 항목에 동일한 작업을 적용할 때 명시적인 반복문을 작성할 필요 없이 간단하게 작업을 처리할 수 있다는 것입니다.map() 함수의 문법map(function, iterable, ...)​function: 반복 가능한 객체의 각 항목에 적용할 함수.iterable: 함수가 처리할 하나 이상의 반복 가능한 객체(리스트, 튜플 등).여러 개의 반복 가능한 객체가 전달되면 함수는 반복 가능한 객..

"이 블로그 포스트는 영어로 작성되었지만, 영어에 익숙하지 않은 분들을 위해 다음 글에서 한국어 버전도 제공하고 있습니다." What is the map() function?The map() function in Python is used to apply a given function to all items in an iterable (like a list, tuple, etc.). This function returns a map object (which is an iterator), which you can convert into a list, tuple, or any other iterable.The power of map() is in its ability to simplify applying t..

"이 블로그 포스트는 영어로 작성되었지만, 영어에 익숙하지 않은 분들을 위해 다음 글에서 한국어 버전도 제공하고 있습니다." Python Advanced _ List Compression Understanding Python List ComprehensionsPython list comprehensions are a concise and efficient way to create a new list from an existing iterable. This allows you to write code that is not only shorter, but also more readable and Pythonic. In this tutorial, we will first forshow you the tradi..

Python 리스트 컴프리헨션 이해하기Python 리스트 컴프리헨션(List Comprehensions)은 기존의 반복 가능한(iterable) 객체에서 새로운 리스트를 간결하고 효율적으로 생성하는 방법입니다. 이를 사용하면 더 짧고 가독성이 높은 Pythonic한 코드를 작성할 수 있습니다. 이 튜토리얼에서는 전통적인 for 루프 접근 방식을 먼저 보여준 후 이를 리스트 컴프리헨션으로 변환하는 방법을 설명합니다.리스트 컴프리헨션이란?리스트 컴프리헨션은 기존 반복 가능한 객체의 각 요소에 대해 연산을 수행하여 리스트를 생성하는 간결한 문법입니다. 조건을 추가하여 요소를 필터링할 수도 있습니다.문법:[expression for item in iterable if condition]expression: 각 ..