Exploring Python Profiling Data with Profiling-Explorer

🐍📰 Variables in Python: Usage and Best Practices Explore Python variables from creation to best practices, covering naming conventions, dynamic typing, variable scope, and type hints with examples https://lnkd.in/dUFf5QGE

✍️ New post detailing a workaround I came up with for “leak” beahviour from Python 3.14’s new garbage collection algorithm. Topical as Hugo van Kemenade recently announced that the algorithm will be reverted in the next patch release! https://lnkd.in/eYG8843h #Django #Python

yield is one of those Python keywords that looks simple until someone asks you to explain it. Most developers can tell you a function with yield in it produces values and works in for loops. Fewer can explain why that same function doesn't actually run when you call it. Turns out, that's the whole point. Generators (functions with yield) are functions that pause mid-execution and resume exactly where they left off: local variables, loop counters, everything intact. In my Python Context Managers series, I'm covering generators as a dedicated article because they are not a standalone concept. They are the engine behind @contextmanager, a cleaner way to build context managers in Python. You can't fully understand one without understanding the other. This article is a deep dive into generator functions: https://lnkd.in/dSNegaWK A function that remembers where it left off changes everything. #Python #SoftwareEngineering #Backend #Programming #WebDevelopment #BuildBreakLearn

🐍📰 Python eval(): Evaluate Expressions Dynamically In this tutorial, you'll learn how eval() works and how to use it effectively in your programs. Additionally, you'll learn how to minimize the security risks associated to the use of eval() #python

Explore five beginner-friendly platforms that let you host Python apps for free, compare their limits, and pick the right one. https://lnkd.in/euMac4Hp

🐍📰 In this tutorial, you'll learn how and when to use the len() Python function. You'll also learn how to customize your class definitions so that objects of a user-defined class can be used as arguments in len() #python

https://lnkd.in/enAnqgKh This is how you name software Also a great solution for agents - giving them full access to Python can be a recipe for disaster but fully removing python can limit their ability as they often need it to do complex parsing or other tasks.

Python: 06 🐍 Python Tip: Master the input() Function! Ever wondered how to make your Python programs interactive? It all starts with taking input from the user! ⌨️ 1) How to capture input? -To get data from a user, we have to use the input() function. To see it in action, you need to write in the terminal using: '$ python3 app.py' 2) The "Type" Trap 🔍 -By default, Python is a bit picky. If you want to know the type of our functions, You can verify this using the type() function: Python code: x = input("x: ") print(type(x)) Output: <class 'str'> — This means 'x' is a string! 3) Converting Types (Type Casting) 🛠️ If you want to do math, you have to convert that string into an integer. Let's take a look at this example- Python code: x = input("x: ") y = int(x) + 4 # Converting x to an integer so we can add 4! [Why do this? Without int(), here we called int() function to detect the input from the user, otherwise Python tries to do "x" + 4. Since you can't add text to a number, your code would crash! 💥] print(f"x is: {x}, y is {y}") The Result 🚀: If you input 4, the output will be: ✅ x is: 4, y is: 8 Happy coding! 💻✨ #Python #CodingTips #Programming101 #LearnPython #SoftwareDevelopment

Most Python code works. That’s not the problem. The problem is - most of it doesn’t scale past the person who wrote it. You’ve probably seen code like this: • full of comments explaining what’s happening • try/finally blocks everywhere • repeated logic for caching, logging, auth • functions doing 5 things at once It works. Until it doesn’t. The shift that changed how I think about Python: 👉 Stop writing logic 👉 Start using language-level patterns Once you start seeing it this way: • with replaces cleanup logic • decorators replace repeated behavior • generators replace unnecessary data structures • dunder methods make your objects feel native The result? Code that explains itself without comments, removes entire classes of bugs, and actually scales across teams. I wrote a deep dive on this - not surface-level tips, but how these patterns actually work, when to use them, and how they reshape your code. 👉 Read the full article: https://lnkd.in/g_9GZDRk Curious — what’s one Python concept that only clicked after real-world experience? For me, it was realizing generators aren’t about syntax - they’re about thinking in streams instead of collections. #Python #CleanCode #SoftwareEngineering #ScalableSystems #DesignPatterns #AdvancedPython #BackendDevelopment