Tip for clean code in Python:
Use Dataclasses for classes that primarily store data. The
#Python #CleanCode #ProgrammingTips #SoftwareDevelopment #Dataclasses #CodeQuality
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By: @CodeProgrammer ✨
Use Dataclasses for classes that primarily store data. The
@dataclass decorator automatically generates special methods like __init__(), __repr__(), and __eq__(), reducing boilerplate code and making your intent clearer.from dataclasses import dataclass
# --- BEFORE: Using a standard class ---
# A lot of boilerplate code is needed for basic functionality.
class ProductOld:
def __init__(self, name: str, price: float, sku: str):
self.name = name
self.price = price
self.sku = sku
def __repr__(self):
return f"ProductOld(name='{self.name}', price={self.price}, sku='{self.sku}')"
def __eq__(self, other):
if not isinstance(other, ProductOld):
return NotImplemented
return (self.name, self.price, self.sku) == (other.name, other.price, other.sku)
# Example Usage
product_a = ProductOld("Laptop", 1200.00, "LP-123")
product_b = ProductOld("Laptop", 1200.00, "LP-123")
print(product_a) # Output: ProductOld(name='Laptop', price=1200.0, sku='LP-123')
print(product_a == product_b) # Output: True
# --- AFTER: Using a dataclass ---
# The code is concise, readable, and less error-prone.
@dataclass(frozen=True) # frozen=True makes instances immutable
class Product:
name: str
price: float
sku: str
# Example Usage
product_c = Product("Laptop", 1200.00, "LP-123")
product_d = Product("Laptop", 1200.00, "LP-123")
print(product_c) # Output: Product(name='Laptop', price=1200.0, sku='LP-123')
print(product_c == product_d) # Output: True
#Python #CleanCode #ProgrammingTips #SoftwareDevelopment #Dataclasses #CodeQuality
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By: @CodeProgrammer ✨
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Forwarded from Machine Learning
📌 PyTorch Tutorial for Beginners: Build a Multiple Regression Model from Scratch
🗂 Category: DEEP LEARNING
🕒 Date: 2025-11-19 | ⏱️ Read time: 14 min read
Dive into PyTorch with this hands-on tutorial for beginners. Learn to build a multiple regression model from the ground up using a 3-layer neural network. This guide provides a practical, step-by-step approach to machine learning with PyTorch, ideal for those new to the framework.
#PyTorch #MachineLearning #NeuralNetwork #Regression #Python
🗂 Category: DEEP LEARNING
🕒 Date: 2025-11-19 | ⏱️ Read time: 14 min read
Dive into PyTorch with this hands-on tutorial for beginners. Learn to build a multiple regression model from the ground up using a 3-layer neural network. This guide provides a practical, step-by-step approach to machine learning with PyTorch, ideal for those new to the framework.
#PyTorch #MachineLearning #NeuralNetwork #Regression #Python
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Comprehensive Python Cheatsheet.pdf
6.3 MB
Comprehensive Python Cheatsheet
This Comprehensive #Python Cheatsheet brings together core syntax, data structures, functions, #OOP, decorators, regular expressions, libraries, and more — neatly organized for quick reference and deep understanding.
This Comprehensive #Python Cheatsheet brings together core syntax, data structures, functions, #OOP, decorators, regular expressions, libraries, and more — neatly organized for quick reference and deep understanding.
https://t.iss.one/CodeProgrammer
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#python #datascience #DataAnalysis
https://t.iss.one/CodeProgrammer
React ♥️ for more amazing content
#python #datascience #DataAnalysis
https://t.iss.one/CodeProgrammer
React ♥️ for more amazing content
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https://t.iss.one/CodeProgrammer
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https://t.iss.one/CodeProgrammer
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Real Python.pdf
332 KB
Real Python - Pocket Reference (Important)
#python #py #PythonTips #programming
https://t.iss.one/CodeProgrammer🩵
#python #py #PythonTips #programming
https://t.iss.one/CodeProgrammer
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The #Python library #PandasAI has been released for simplified data analysis using AI.
You can ask questions about the dataset in plain language directly in the #AI dialogue, compare different datasets, and create graphs. It saves a lot of time, especially in the initial stage of getting acquainted with the data. It supports #CSV, #SQL, and Parquet.
And here's the link😍
👉 https://t.iss.one/CodeProgrammer
You can ask questions about the dataset in plain language directly in the #AI dialogue, compare different datasets, and create graphs. It saves a lot of time, especially in the initial stage of getting acquainted with the data. It supports #CSV, #SQL, and Parquet.
And here's the link
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I'm happy to announce that freeCodeCamp has launched a new certification in #Python 🐍
» Learning the basics of programming
» Project development
» Final exam
» Obtaining a certificate
Everything takes place directly in the browser, without installation. This is one of the six certificates in version 10 of the Full Stack Developer training program.
Full announcement with a detailed FAQ about the certificate, the course, and the exams
Link: https://www.freecodecamp.org/news/freecodecamps-new-python-certification-is-now-live/
👉 @codeprogrammer
» Learning the basics of programming
» Project development
» Final exam
» Obtaining a certificate
Everything takes place directly in the browser, without installation. This is one of the six certificates in version 10 of the Full Stack Developer training program.
Full announcement with a detailed FAQ about the certificate, the course, and the exams
Link: https://www.freecodecamp.org/news/freecodecamps-new-python-certification-is-now-live/
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