Learn Python Coding

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

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This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

📌 Marking Deprecated Code in Python: deprecated() In large projects, old functions are not always immediately removed. They are often left for compatibility, but it's important to warn developers that they should no longer be used. Previously,

warnings.warn()

was often used for this purpose:

import warnings

def old_api():
    warnings.warn(
        "Use new_api()",
        DeprecationWarning
    )

In Python 3.13, a

deprecated()

decorator has been introduced:

from warnings import deprecated

@deprecated("Use new_api()")
def old_api():
    return "old"

Now, the information about deprecation is part of the API itself. It can be recognized not only during runtime, but also by editors and static analysis tools. This also works for classes:

@deprecated("Use NewClient")
class OldClient:
    pass

This is convenient for libraries, SDKs, and large projects where the API is gradually changing. #Python #Python313 #Deprecated #Coding #Programming #SoftwareDevelopment ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

Do not violate the Single Responsibility Principle 🎯 A function should do one thing, and do it well. This function does too much:

def calculate_final_total(
    price: float,
    quantity: int,
    discount_rate: float,
    tax_rate: float
) -> float:
    # Calculate the subtotal
    subtotal = price * quantity

    # Apply the discount
    discounted_amount = subtotal * (1 - discount_rate)

    # Calculate the tax
    final_total = discounted_amount * (1 + tax_rate)

    return final_total

The problem here is that the calculation of the subtotal, discount, and tax are all combined into one function. Any change to one of these steps can affect the entire calculation. It's better to break down the logic into smaller, more specialized functions:

def calculate_subtotal(price: float, quantity: int) -> float:
    return price * quantity

def apply_discount(subtotal: float, discount: float) -> float:
    return subtotal * (1 - discount)

def calculate_tax(amount: float, tax_rate: float) -> float:
    return amount * (1 + tax_rate)

This is much better. ✅ Smaller functions with a single task are easier to test with unit tests because they have fewer dependencies and require less mocking. Furthermore, isolated components are easier to reuse in different parts of the application or pipeline without bringing in unnecessary dependencies. Therefore, keep your functions simple and focused. One function – one responsibility. 📝 #Python #Coding #SoftwareDevelopment #CleanCode #Programming #BestPractices ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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    print(f"You said: {line}")

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