Optimize Python Performance with Codon

Python runs — even when your logic doesn’t. I’ve never thought of Python as a true programming language — more like a tool language than something you’d teach in a Computer Science class. In CS, the whole point of designing data structures and inventing algorithms is efficiency. Python — it often trades efficiency for convenience. Type safety matters. Static, strict type-safe languages catch bugs before they bite. Python lets them slip through until runtime. And don’t get me started on indentation. Imagine an `if-else` block shifted one tab in the wrong direction; the code still runs, happily hiding a bug until it explodes later. Python is powerful, no doubt — but maybe too forgiving for its own good. I won’t tell you which one of these two versions the developer meant as the solution ! Can you guess ?

🔷 Python Output | Using + and , In Python, we can display text and variables together using the print() function. 🔹 Example Using + (Concatenation) • language = "Python" • print("My favourite computer language is " + language) ▶ Output: My favourite computer language is Python 🔹 Example Using , (Comma Separator) • language = "Python" • print("My favourite computer language is ", language) ▶ Output: My favourite computer language is Python ⭐ Key Point ✔ + is used to join strings ✔ , is used to print multiple values with automatic spacing Both methods help in displaying clear and meaningful output in Python. #Python #PythonOutput #StringConcatenation #ProgrammingBasics #LearningJourney #Upskilling

Here’s a simple yet powerful Python program that demonstrates how functions and loops work together to solve real-world problems efficiently. 🔹 In this program, we define a function even(li) that: Takes a list as input Iterates through each element Checks whether the number is even Prints only the even numbers from the list This is a great example for beginners to understand: ✔ Functions in Python ✔ Loops (for) ✔ Conditional statements (if) ✔ Modulus operator (%) Such small programs build strong logical thinking and problem-solving skills in programming. def even(li):   for i in li:     if i%2 == 0 :       print(i,end=" ") lst= [1,2,3,4,5,6,7,8,9,10] even(lst) #Python #Coding #ProgrammingBasics #DataScience #Learning #TechEducation

📘 Python Fundamentals: Expressions & Operators Expressions and operators are the backbone of every Python program. This visual breaks down how Python evaluates values and performs actions to produce results. 🔹 What is an Expression? An expression is a combination of values, variables, and operators that Python evaluates into a single result — just like a mathematical sentence. 🔹 Anatomy of an Expression Operands are the values, operators define the action, and together they produce a result (e.g., 10 + 5 = 15). 🔹 Types of Operators Covered ✔️ Arithmetic Operators – perform mathematical calculations ✔️ Comparison Operators – compare values and return True/False ✔️ Logical Operators – combine multiple conditions ✔️ Assignment Operators – assign and update variable values 🔹 Real Python Examples The poster also includes practical code examples to show how expressions work in real programs. Perfect for beginners building strong Python fundamentals and for anyone revising core concepts. #Python #PythonProgramming #LearnPython #PythonForBeginners #CodingTips #Programming #TechEducation

🚀 Revisiting Python Fundamentals Day 5: Operators in Python Operators are the actions in Python. 🔴 Arithmetic Operators Used for basic mathematical operations. + Addition - Subtraction * Multiplication / Division Example: result = 10 + 5 🔵 Relational Operators (Compare Values) Used to compare two values. == Equal to != Not equal to > Greater than < Less than Example: x > 10 🟢 Logical Operators Used to work with True/False values. and or not Example: x > 5 and y < 10 🟡 Assignment Operators Used to assign or update variables. = += -= *= Example: x += 5 🔵 Bitwise Operators Used at the bit level. & AND | OR ^ XOR ~ NOT << Left shift >> Right shift Example: x = 5 & 3 🟣 Membership Operators Used to check if a value exists in a collection. in not in Example: "Python" in ["Python", "SQL"] 🟢 Identity Operators (Check Same Object) Used to check memory identity, not value. is is not Example: a is b #Python #Operators #PythonBasics #LearnPython #CodingJourney

📌 Python Tuple – Negative Indexing Today, I learned about negative indexing in Python tuples 🔄 ✔️ Negative index starts from -1 ✔️ -1 → Last element ✔️ -2 → Second last element ✔️ -3 → Third last element ✔️ -4 → First element 📖 Example: If tuple = ("apple", "banana", "cherry", "orange") ➡️ mytuple[-1] → orange ➡️ mytuple[-4] → apple Negative indexing helps us access elements from the end easily ✅ Learning step by step 🚀💻 #Python #PythonLearning #Tuple #NegativeIndexing #CodingJourney #LearningInPublic #Programming #TechSkills

If you’re learning Python and feel scattered, use this: our 87-skill checklist aligned to UC’s first-year CS path — CS1 basics, CS2 data structures, CS3 algorithms. The course also maps to real workplace skills like APIs, Git, and even AI app patterns. https://lnkd.in/gs85MpFY #python #learnpython

Python is moving towards a no-GIL world, but that does not imply faster execution speed implicitly. Recent Python versions (3.12+ and upcoming 3.13+) are have started to support for an optional GIL-free mode. Python is not removing the GIL overnight though. Instead, it’s preparing for C extensions and existing libraries to adopt this new world. Removing GIL means: -> better CPU parallelism with threads -> but also more responsibility on developers and libraries What this does not mean (for now): -> Async programming is not going away -> Multiprocessing is still relevant It’s fascinating to see how Python evolves; balancing performance, safety and backward compatibility. I am trying to learn Python Internals and its recent changes and will share my learnings. Do follow along and tell your experiences in comments. #Python #PythonInternals #SoftwareEngineering #BackendDevelopment

Linear Regression Model (From Scratch in Python) 😵 I built a complete linear regression model from scratch using Python, without relying on machine learning libraries . it was exciting and very helpful to have deep understanding how model works 1️⃣ Model Training (Fitting) Compute the Mean Squared Error (MSE) as the loss function. Use Gradient Descent to minimize the error by: Computing gradients with respect to the parameters (weights w and bias b) Updating the parameters iteratively Repeating the process until the loss reaches its minimum (least MSE) 2️⃣ Model Equation ŷ=w⋅x+b Where: w = weight (slope) b = bias (intercept) x = input features ŷ = predicted output Amr Helal Judy Kasbar Rawan Gamal DotPy

🧠 Python Trick : Chained Comparisons Most people write this 👇 x > 5 and x < 10 But Python lets you write this 😲 ✅ The Python Way 5 < x < 10 ✔️ Same meaning. Cleaner. More readable. 🧒 Simple Explanation Imagine checking if a number is between two walls 🧱 Python checks both sides at the same time. No extra thinking needed 🧠✨ 💡 Why This Is Special ✔ Easier to read ✔ Fewer logical mistakes ✔ Unique to Python (not common in many languages) ⚠️ One Thing to Remember This works only for comparisons, not math: 5 < x < 10 ✅ 5 + x + 10 ❌ 💯 Python doesn’t just work… it reads like English. 💯 Small features like this are why developers love it 🐍💙 #Python #PythonTricks #CleanCode #LearnPython #DeveloperTips #Programming