The Walrus Operator := (Assignment Expressions)

Introduced in Python 3.8, the "walrus operator" := allows you to assign a value to a variable as part of a larger expression. It's a powerful tool for writing more concise and readable code, especially in while loops and comprehensions.

It solves the common problem where you need to compute a value, check it, and then use it again.

---

#### The Old Way: Repetitive Code

Consider a loop that repeatedly prompts a user for input and stops when the user enters "quit".

# We have to get the input once before the loop,
# and then again inside the loop.
command = input("Enter command: ")

while command != "quit":
    print(f"Executing: {command}")
    command = input("Enter command: ")

print("Exiting program.")

Notice how input("Enter command: ") is written twice.

---

#### The Pythonic Way: Using the Walrus Operator :=

The walrus operator lets you capture the value and test it in a single, elegant line.

while (command := input("Enter command: ")) != "quit":
    print(f"Executing: {command}")

print("Exiting program.")

Here, (command := input(...)) does two things:
• Calls input() and assigns its value to the command variable.
• The entire expression evaluates to that same value, which is then compared to "quit".

This eliminates redundant code, making your logic cleaner and more direct.

#Python #PythonTips #PythonTricks #WalrusOperator #Python3 #CleanCode #Programming #Developer #CodingTips

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

❔ Interview Question

What is the GIL (Global Interpreter Lock) in Python, and how does it impact the execution of multi-threaded programs?

Answer: The Global Interpreter Lock (GIL) is a mutex (or a lock) that allows only one thread to hold the control of the Python interpreter at any one time. This means that in a CPython process, only one thread can be executing Python bytecode at any given moment, even on a multi-core processor.

This has a significant impact on performance:

• For CPU-bound tasks: Multi-threaded Python programs see no performance gain from multiple CPU cores. If you have a task that performs heavy calculations (e.g., image processing, complex math), creating multiple threads will not make it run faster. The threads will execute sequentially, not in parallel, because they have to take turns acquiring the GIL.

• For I/O-bound tasks: The GIL is less of a problem. When a thread is waiting for Input/Output (I/O) operations (like waiting for a network response, reading from a file, or querying a database), it releases the GIL. This allows another thread to run. Therefore, the threading module is still highly effective for tasks that spend most of their time waiting, as it allows for concurrency.

How to achieve true parallelism?

To bypass the GIL and leverage multiple CPU cores for CPU-bound tasks, you must use the multiprocessing module. It creates separate processes, each with its own Python interpreter and memory space, so the GIL of one process does not affect the others.

tags: #Python #Interview #CodingInterview #GIL #Concurrency #Threading #Multiprocessing #SoftwareEngineering

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

🏆 NumPy Python Tips

📢 Boost your Python skills with NumPy! Learn quick tips for efficient array creation and manipulation to level up your data handling.

⚡ Tap to unlock the complete answer and gain instant insight.

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

Tired of missing perfect GOLD entries?
Last week alone: 1,740 pips profit, 10/12 trades won—all shared live in our channel.
Ready to catch the next move? Stay ahead with premium signals & real-time updates—don’t just watch, start profiting!
Join GOLD PIPS SIGNALS before the next trade drops!

#ad InsideAds

🌍 Remote Work — India Only 🇮🇳
💰 Earn $800–$2000/month
📆 Weekly payments — card or crypto
🕒 Work 3–4 hours/day
🏠 Fully remote — no office, no experience needed
🎓 Training provided
👉 Indian citizens aged 25+ only
📩 Message our HR manager to apply today!

#ad InsideAds

🏆 Master Vue.js for Modern UIs

📢 Master Vue.js, the intuitive JavaScript framework, and confidently build modern, reactive user interfaces. Your journey to dynamic web apps starts here!

⚡ Tap to unlock the complete answer and gain instant insight.

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

🏆 Python MCP Server: Create & Learn

📢 Unlock Minecraft's secrets! Build your own custom Minecraft Protocol (MCP) server with Python for ultimate game customization and deep dives into mechanics.

⚡ Tap to unlock the complete answer and gain instant insight.

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

Tip for clean tests in Python:

Structure your tests with the Arrange-Act-Assert pattern to improve readability and maintainability.

• Arrange: Set up the test. Initialize objects, prepare data, and configure any mocks or stubs.
• Act: Execute the code being tested. Call the specific function or method.
• Assert: Check the outcome. Verify that the result of the action is what you expected.

import pytest
from dataclasses import dataclass, field


# Code to be tested
@dataclass
class Product:
    name: str
    price: float


@dataclass
class ShoppingCart:
    items: list[Product] = field(default_factory=list)

    def add_item(self, product: Product):
        if product.price < 0:
            raise ValueError("Product price cannot be negative.")
        self.items.append(product)

    def get_total_price(self) -> float:
        return sum(item.price for item in self.items)


# Tests using the Arrange-Act-Assert pattern
def test_get_total_price_for_multiple_items():
    # Arrange
    product1 = Product(name="Mouse", price=25.50)
    product2 = Product(name="Keyboard", price=75.50)
    cart = ShoppingCart()
    cart.add_item(product1)
    cart.add_item(product2)

    # Act
    total_price = cart.get_total_price()

    # Assert
    assert total_price == 101.00


def test_get_total_price_for_empty_cart():
    # Arrange
    cart = ShoppingCart()

    # Act
    total_price = cart.get_total_price()

    # Assert
    assert total_price == 0.0


def test_add_item_with_negative_price_raises_value_error():
    # Arrange
    cart = ShoppingCart()
    product_with_negative_price = Product(name="Invalid Item", price=-50.0)

    # Act & Assert
    with pytest.raises(ValueError, match="Product price cannot be negative."):
        cart.add_item(product_with_negative_price)

#Python #Testing #CleanCode #SoftwareEngineering #Pytest #DeveloperTips #AAA

━━━━━━━━━━━━━━━
By: @DataScienceQ ✨

Hello! How can I assist you today?

By: @DataScienceQ 🚀

300 Real Time SQL Interview practical Questions Asked at multiple companies
••••••••••••••••••••••••••••••••••••••••••••••••••••••

Anyone who's preparing for an interview just reading theoretical concept will not help definitely you need to have practical hands on in #sql so create table with some data and try this queries running by your self so can help you to understand the logic of similar kind of queries

If you're preparing for an interview this doc will help a lot in the perpetration If you're experienced also freshers can also get hands on by practicing these queries and get confidence.

https://t.iss.one/DataScienceQ

🚀 THE 7-DAY PROFIT CHALLENGE! 🚀

Can you turn $100 into $5,000 in just 7 days?
Lisa can. And she’s challenging YOU to do the same. 👇

https://t.iss.one/+AOPQVJRWlJc5ZGRi
https://t.iss.one/+AOPQVJRWlJc5ZGRi
https://t.iss.one/+AOPQVJRWlJc5ZGRi