Python subprocess Module Tutorial

Day 20 of My 30-Day Python Challenge at GQT (Global Quest Technologies) Today, I explored the power of Lambda Functions and functional programming tools in Python, which make code more concise and efficient. 🔹 Lambda Functions ➕ Finding the sum of two numbers 🔢 Calculating the cube of a number 🥇 Determining the largest of two and three numbers 🔹 Functions Accepting Lambda as Parameters Used with built-in higher-order functions for cleaner and more expressive code. 🔹 Filter() Function ✔️ Filtering positive and negative numbers ✔️ Separating odd and even numbers ✔️ Selecting names starting with the letter 'A' 🔹 Map() Function 🔤 Converting all city names in a list to uppercase 🔹 Reduce() Function 🔁 Aggregating elements to produce a single result using functools.reduce 💡 Today’s Takeaway: Lambda functions and higher-order functions like filter(), map(), and reduce() enable writing elegant and efficient Python code with minimal syntax. ✨ “Write less, accomplish more – that’s the power of Python!”

🐍📰 Conditional Statements in Python In this step-by-step tutorial you'll learn how to work with conditional ("if") statements in Python. Master if-statements step-by-step and see how to write complex decision making code in your programs #python

11 Useful Python List Methods Working with lists is common in almost every Python project. Understanding these built-in methods makes your code cleaner and more efficient. Here are 11 essential list methods: 1) append() → Add a single item to the list. 2) extend() → Add multiple items individually. 3) insert() → Add an item at a specific index. 4) remove() → Remove the first matching item. 5) pop() → Remove and return an item. 6) index() → Find the position of an item. 7) count() → Count how many times an item appears. 8) sort() → Sort the list in place. 9) reverse() → Reverse the order of elements. 10) clear() → Remove all items from the list. 11) reverse() → Reverse the order of elements. These small methods are simple, but they appear frequently in real-world code. Mastering them improves readability and reduces unnecessary logic. Comment below, Which list method do you use the most? Comment below. Save this for quick revision later. 📌 I share simple Python and backend learnings here. #Python #LearnPython #Programming #Coding #SoftwareEngineering #PythonDeveloper

🐍📰 A Beginner’s Guide to the Python time Module In this tutorial, you'll learn how to use the Python time module to represent dates and times in your application, manage code execution, and measure performance #python

One small Python change that will be genuinely useful in production: timestamps in tracebacks. PEP 830 proposes adding time information directly to exceptions and tracebacks in Python 3.15. At first glance, this may look minor. In practice, it is not. When you work with async flows, retries, parallel tasks, or ExceptionGroup, timing matters. Not just which error happened, but when exactly it happened relative to the others. That makes debugging grouped failures much easier: - you can see the sequence of exceptions more clearly - sorting inside ExceptionGroup becomes more practical - incident analysis gets better without relying only on external tooling What also stands out here is that the performance impact looks negligible, except for control-flow cases that are expected to be excluded from this logic. A lot of teams already get similar value from external error trackers. The interesting part is that Python itself is moving in this direction natively. How do you handle this today? Do you rely mostly on Sentry or other observability tools for exception timing, or do you see value in having this directly in Python tracebacks?

🐍📺 In this video course, you'll learn how to manipulate ZIP files using Python's zipfile module from the standard library. Through hands-on examples, you'll learn how to read, write, compress, and extract files from your ZIP files quickly #python

Ever wondered why people get confused when it comes to Python’s Access Specifiers? A few days ago, while revisiting core Python concepts, I stumbled upon this exact question and honestly, it made me pause. If Python has public, protected, and private… why does it still feel so confusing? Here’s what I realized: Unlike languages like Java or C++, Python doesn’t strictly enforce access control. Instead, it follows a philosophy: “We are all consenting adults.” And that’s exactly where the confusion begins. 1. Everything is public by default 2. A single underscore (_) is just a convention, not a restriction 3. Double underscore (__) triggers name mangling, not true privacy So developers often expect strict rules… but Python gives flexibility instead. And that gap between expectation vs reality is what confuses most people. When I dug deeper, I found that understanding this isn’t just about syntax, it’s about understanding how Python thinks. From variables being simple references to memory, to how private variables are internally renamed… it completely changes your perspective. And here’s the surprising part, Even “private” variables can still be accessed (though not recommended), if you understand how name mangling works. If you're learning Python or preparing for interviews, this is one concept you don’t want to overlook. For a complete breakdown with examples, edge cases, and best practices, check out this detailed doc: https://lnkd.in/gi-iw_gM You might see Python a little differently after this. #Python #Programming #Coding #SoftwareDevelopment #Learning #PythonBasics #InterviewPrep #Tech

📺🐍 Using Loguru to Simplify Python Logging Learn how to use Loguru for simpler Python logging, from zero-config setup and custom formats to file rotation, retention, and adding context https://lnkd.in/gabD5QTq

🐍📰 How to Do a Binary Search in Python In this step-by-step tutorial, you'll learn how to implement this algorithm in Python. You'll learn how to leverage existing libraries as well as craft your own binary search Python implementation. #python

🐍📰 Python and PyQt: Creating Menus, Toolbars, and Status Bars In this step-by-step tutorial, you’ll learn how to create, customize, and use Python menus, toolbars, and status bars for creating GUI applications using PyQt. #python