Skip to main content

what is @something on a function, i heard it is for decoration?!

 


Title: ๐ŸŽจ Exploring Python Decorators: Adding Magic to Your Code! ✨


Python decorators are like the fairy godmothers of programming—they sprinkle a little magic onto your functions, enhancing them with extra functionality. In this blog post, we'll dive into the enchanting world of decorators, exploring how they work and unleashing their powers with two whimsical examples.


**Example 1: The Enigmatic @echo Decorator**


Imagine a decorator that echoes the inputs and outputs of a function, adding a touch of sparkle to the console. Behold, the @echo decorator!


```python

def echo(func):

    def wrapper(*args, **kwargs):

        print("✨ Echoing inputs:")

        for arg in args:

            print(f"\t- {arg}")

        result = func(*args, **kwargs)

        print("✨ Echoing output:")

        print(f"\t- {result}")

        return result

    return wrapper


@echo

def add(a, b):

    return a + b


add(3, 5)

```


When we call the `add` function, the @echo decorator adds a dash of magic by printing the inputs and the result with sparkling flair.


**Example 2: The Marvelous @vectorize Decorator**


Next, let's conjure up a decorator that vectorizes a function, making it soar through a list of inputs with the grace of a unicorn in flight.


```python

def vectorize(func):

    def wrapper(*args, **kwargs):

        results = []

        for arg in args[0]:

            results.append(func(arg))

        return results

    return wrapper


@vectorize

def square(x):

    return x ** 2


numbers = [1, 2, 3, 4, 5]

print(square(numbers))

```


With the power of the @vectorize decorator, our `square` function gracefully computes the square of each element in a list, unleashing a rainbow of results.


Decorators in Python are like wands in the hands of a wizard—they empower your functions with extraordinary capabilities, making your code more elegant and enchanting. So go ahead, sprinkle some decorator magic into your Python scripts and watch them come to life with brilliance and wonder! ✨๐Ÿ


Happy decorating! ๐ŸŽฉ๐ŸŒŸ

Comments

Popular posts from this blog

yer a wizard - making your own custom %%cellmagics for colab notebooks

    ## Dive into the Magic of Jupyter %%cellmagic! ✨๐Ÿ“š Hey there, fellow data enthusiasts! ๐Ÿ‘‹ Today, let's dive into the fascinating world of Jupyter's `%%cellmagic` ๐Ÿช„. This little-known feature can supercharge your Jupyter Notebook workflow! ๐Ÿš€๐Ÿ’ก ### What's `%%cellmagic`? ๐Ÿง™‍♂️✨ In the Jupyter ecosystem, `%magic` and `%%cellmagic` commands add special functionalities to your notebook cells. Think of them as magical commands that can transform how your cells behave! ๐ŸŒŸ For example, `%%time` can measure the execution time of a cell. But what if you want to create your own custom magic? That's where `%%cellmagic` shines! ๐Ÿ’ฅ ### Example: Create Your Own Cell Magic ๐Ÿ› ️๐Ÿ”ฎ Let's say you want to create a custom magic that processes a cell in a specific way. Here's a simple example to get you started: ```python from IPython.core.magic import (Magics, magics_class, cell_magic, needs_local_scope) @magics_class class class_mycellmagic(Magics):     @needs_local_scope ...

x=? or how can i make a random variable in python ?

 **Unleashing the Power of Randomness in Python/Numpy for Simple Game Structures! ๐ŸŽฒ๐Ÿ”€๐Ÿƒ** Welcome, fellow programmers, game enthusiasts, and curious minds! Today, we embark on an exciting journey into the realm of randomness within Python and Numpy. Whether you're a seasoned coder or a newbie explorer, buckle up as we uncover the magic of random functions and how they can breathe life into simple game structures. ๐Ÿš€ **1. Uniform Randomness:** ๐ŸŽฒ Ah, the beauty of unpredictability! With Python's `random` module or Numpy's `numpy.random` package, we can effortlessly generate uniformly distributed random numbers. This feature is ideal for scenarios like rolling dice, selecting random players, or determining the movement of objects in a game world. ```python import random # Roll a fair six-sided die roll_result = random.randint(1, 6) print("You rolled:", roll_result) ``` **2. List Choice:** ๐Ÿ”€ In the realm of games, sometimes decisions need to be made from a pool of ...

how to do the linear regression in python??

  ๐Ÿ“Š **Unlocking the Power of Linear Regression with Python's SciPy Library!** ๐Ÿ“ˆ Hey there, data enthusiasts! Today, we're diving into the world of linear regression using Python's powerful SciPy library. Strap in as we explore how to perform linear regression, calculate the coefficient of determination (R-squared), and unleash the potential of your data with just a few lines of code! ### ๐Ÿ“Š What is Linear Regression? Linear regression is a fundamental statistical technique used to model the relationship between two variables. It's like fitting a straight line to a scatter plot of data points, allowing us to make predictions and understand the underlying relationship between the variables. ### ๐Ÿ’ป Let's Get Coding! First things first, fire up your Python environment and make sure you have SciPy installed. If not, a quick `pip install scipy` should do the trick. Once that's done, import the necessary libraries: ```python from scipy.stats import linregress ``` Now...