Python Glossary: Function Annotation

🐍📰 Python 3's pathlib Module: Taming the File System How to effectively work with file system paths in Python 3 using the new "pathlib" module in the standard library. #python

"Understanding the pivotal role that wheels play in the Python ecosystem can make your life easier as both a user and developer of Python packages. Furthermore, increasing your Python literacy when it comes to wheels will help you to better understand what’s happening when you install a package and when, in increasingly rare cases, that operation goes awry." by Real Python #python #packages #codereuse #librarydevelopment https://lnkd.in/dWGiFhQF

😁 Advanced Python: Metaprogramming 😁 from O'Reilly! ✅ Insightful instruction from James Powell ✅ ➡️ Metaprogramming theory and practice ✅ ➡️ The Python interpreter in detail ✅ ➡️ Techniques for class construction and library design ✅ How to read and use byte code for understanding and debugging ✅ How to structure code so that runtime errors appear earlier ✅ How to write more robust, transparent, maintainable, and correct code ✅ How to write Python code the way it was designed to be written #Python #Metaprogramming #LibraryDesign #CodeQuality

🔹 What is return in Python? In Python, the keyword return is used inside a function to send a value back to the place where the function was called. When a function executes a return statement: It stops running immediately It sends the value written after return back to the caller 🔹 Example: def add(a, b): return a + b result = add(5, 3) print(result) # Output: 8 ✅ The return keyword sends back the result of a + b. If you don’t use return, Python automatically returns None. 🔹 In short: Situation What happens return value Function gives that value back return (nothing) Function ends, returns None No return Function ends, returns None automatically 💡 Tip: return is used to give a result back from a function, while print() is used only to display output on the screen. #Python #DataScience #LearningPython #CodingJourney #Abdurrahman

#100DaysLearningChallenge with Saurabh Shukla Sir 🎯 Day 27: Generators in Python ⚙️🐍 Today’s session was all about generators — one of Python’s most elegant and memory-efficient ways to handle iteration. Instead of creating and storing entire sequences in memory, generators produce items on the fly, making them perfect for working with large datasets or continuous data streams. 🧠 What are Generators? Generators are special functions that allow you to declare an iterator in a clean and concise way. Unlike regular functions that return a single value using return, a generator uses the yield keyword to pause and resume execution, returning a value each time it’s called. 🛠️ What I learned and implemented: ✅ Understood the concept of lazy evaluation — generating values only when needed ✅ Created generator functions using the yield keyword ✅ Explored generator expressions (a compact alternative to list comprehensions) ✅ Compared generators with custom iterator classes for simplicity and performance ✅ Used next() to manually fetch generator values ✅ Observed how for loops automatically handle generator exhaustion and StopIteration 📂 Real-world use cases: ➡️ Processing large files or data streams without loading everything into memory ➡️ Implementing infinite sequences (e.g., Fibonacci, data streams) ➡️ Efficient data pipelines and ETL workflows ➡️ Generating on-demand data for APIs or simulations 👨💻 Generators embody Python’s philosophy of simplicity and efficiency — they make code cleaner, faster, and more memory-friendly. Learning how they work deepens the understanding of iteration, state management, and lazy evaluation in Python. 📹 Video reference (MySirG): https://lnkd.in/gSzsgsGw 🚀 From iterables to generators — every step reveals how Python’s iteration model empowers developers to write smarter, scalable, and elegant code! #100DaysLearningChallenge #Day27 #Python #Generators #Yield #Iteration #LazyEvaluation #OOP #MySirG #SaurabhShuklaSir #LearnToCode #PythonTips

🐍📰 Nested Loops in Python Discover how to effectively use nested loops in Python to iterate over multiple sequences and perform repeated actions in your programs. #python

Python Operators and Expressions Operators let you combine objects to create expressions that perform computations -- the core of how Python works. https://lnkd.in/eZSC4ZZj

Revisited the complete set of user-defined function types in Python: 1. Standard functions 2. Parameterized functions  • Default parameters  • Keyword parameters  • Positional parameters  • Arbitrary parameters (*args, **kwargs) 3. Return-type functions 4. Void functions (no return value) 5. Lambda functions (inline anonymous functions) This practice helped strengthen my understanding of how to structure clean, reusable, and efficient Python code. #python #softwaredevelopment #vscode #learning#1000coders

🚀 Python 3.14 is here! 🐍 The new version of Python brings improvements that make our code cleaner, faster, and easier to understand. Here are some highlights: # T-Strings: A new way to interpolate strings, perfect when we need more control over the content inserted. # Lazy Annotations: Type annotations are now evaluated only when needed, improving performance and code clarity. # Safer Debugging: A new debugging interface allows debuggers and profilers to connect safely to running Python processes without interrupting or restarting them (docs.python.org). # Colorful REPL: The interactive interface is now more user-friendly with syntax highlighting and improved autocomplete. # New pathlib Methods: You can now copy and move files directly with Path objects, without relying on shutil. These changes make Python even more accessible and powerful, whether you’re a beginner or an experienced developer. #Python314 #Development #Technology #Innovation #Programming #Python

💡 Python Tip of the Day In Python, you can easily check if a value exists in a list using the in and not in operators — no need for loops! 🔹 in operator → Returns True if the value is present in the list. 🔹 not in operator → Returns True if the value is not present in the list. Simple, clean, and super useful for conditional checks 👇 #Python #TipOfTheDay #PythonDevelopers #CodingTips #LearnPython