😍 learnxinyminutes — a brief and informative reference guide!

A convenient cheat sheet that allows you to quickly get acquainted with the basics of Python or refresh your knowledge before work. On one page, the key constructs of the language are collected: variables, functions, classes, collections, exception handling, etc. The format is as compact as possible, with a minimum of theory and a maximum of practical examples.

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Here, the language's capabilities are explained, which many only know superficially. The material focuses not on basic syntax, but on a deep understanding and proper use of its capabilities in real projects. There are many examples of working with objects, collections, functions, decorators, generators, async code, and Python's internal logic.

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What is the difference between copy() and deepcopy() in Python?

copy() creates a shallow copy of the object: nested elements remain shared between both copies. In contrast, deepcopy() recursively copies all nested objects, making the new structure completely independent. This is particularly important when working with mutable data

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When applying multiple filters to a series in Pandas, it's better to break the condition into several lines:

s = pd.Series([10, 15, 20, 25, 30])

s.loc[
    (s > 20) &
    (s % 2 == 1)
]

Such code is easier to read, write, and maintain. 🛠️✨

As a result, the value:
25
will be selected,
since it is both greater than 20 and an odd number. 🎯

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# How to Implement a Decorator with Parameters Using a Class in Python

You can create a parameterized decorator in Python by using a class that implements the __call__ method. The class acts as the decorator factory, where the __init__ method stores the parameters, call__call__ method applies the decorator logic to the target function.

## Example Implementation

class my_decorator:
    def __init__(self, param):
        self.param = param

    def __call__(self, func):
        def wrapper(*args, **kwargs):
            print(f"Decorator parameter: {self.param}")
            return func(*args, **kwargs)
        return wrapper

@my_decorator("Hello")
def say_hello(name):
    print(f"Hello, {name}!")

say_hello("World")

## Explanation

1. Class Definition: Define a class that will serve as the decoratorinit.
2. **__init__**: Store the parameters passed to the decoracall.
3. **__call__**: Make the instance callable. This method receives the function being decorated and returns the wrappWrapperrapper**: The inner function executes the actual decorator logic before or after calling the original function.