Python Loops! 👀 Loops helps us avoid repetition in our code and consolidate large data into clean, short and readable code. 💭 Why Loops Matter? Loops allow programs to repeat actions efficiently without writing the same code multiple times. In my Jupyter Notebook, I explored both major types of loops: 🔹 for loops: perfect for iterating through sequences, lists, and ranges 🔹 while loops: great when repetition depends on a condition rather than a count 🔹 break / continue: for controlling flow precisely 🔹 range(start, stop, step): mastering how iteration sequences work 🔹 Nested loops: loops inside loops for multi-dimensional logic 🔹 Avoiding infinite loops: understanding when and how to end repetition safely 😊Good News: My Jupyter Notebook for Python Loops Is Up On My Github! Make sure to check it out and try to do mini projects for python loops that i made there! Good Luck Python Beginners! 😊What Is Coming Next?: Python Functions In detail for Beginners like me! --------------------------- ☺️ Here are Python (Beginner to Intermediate) GitHub Repos for you: 📁Python Variables: https://lnkd.in/e9rjz-_D 📁Python Operators: https://lnkd.in/e6hzgHSn 📁Python Conditionals: https://lnkd.in/egQNGZBF 📁Python Loops: https://lnkd.in/eezUg_-y ------------------------- ⚡ Follow my learning journey: 📎 GitHub: https://lnkd.in/ehu8wX85 🔗GitLab: https://lnkd.in/eiiQP2gw 💬 Feedback: I’d love your thoughts and tips! 🤝 Collab: If you’re also exploring Python, DM me! Let’s grow together! -------------------------- #pythonconditionals #ifelifelseinpython #ternaryconditionals #nestedconditionals #conditionalswithoperators #pythonbasicknowledge #pythonbasicconcepts #pythonforbeginners #pythonprogramming #pythonfordatascience #pythonforaiml

map(), filter(), sort() with Lambda Functions In Python! ⚙️ ✨I explored how map, filter, and sort work with lambda functions that results in 2-3 code lines, sped up coding, and code redeability 👉The best part about lambda functions is that they can easily shrink 4-5 lines of code into just 2-3, crazy right? 🤓Also, lambda functions are interesting in a way that they collaborate seamlessly with map, filter, and sort to provide you with same results that a big chunk of code would ‼️Important: My python functions repo has been updated for Lambda Functions with map, filter, and sort HAPPY CODING! 😉 ---------------------------- ☺️ Here are Python (Beginner to Intermediate) GitHub Repos for you: 📁Python Variables: https://lnkd.in/e9rjz-_D 📁Python Operators: https://lnkd.in/e6hzgHSn 📁Python Conditionals: https://lnkd.in/egQNGZBF 📁Python Loops: https://lnkd.in/eezUg_-y 📁Python Functions: https://lnkd.in/eKdU6nex 📁Python Lists & Tuples: https://lnkd.in/eZ8KiQNs 📁Python Dictionaries & Sets: https://lnkd.in/eDmgj7pc 📁Python OOP: https://lnkd.in/eJFupCiK ------------------------- ⚡ Follow my learning journey: 📎 GitHub: https://lnkd.in/ehu8wX85 🔗GitLab: https://lnkd.in/eiiQP2gw 💬 Feedback: I’d love your thoughts and tips! 🤝 Collab: If you’re also exploring Python, DM me! Let’s grow together! -------------------------- 📞Book A Call With Me: https://lnkd.in/e23BtnR9 -------------------------- #lambdafunctions #pythonprogramming #pythonforbeginners #lambdafunctionsinpython #pythonlanguage

💪Python DSAs: Trees 🤓Trees like Binary Trees, Binary Search Trees, and AVL Trees are some of the core data structures for python 👉Binary Tree: Its nodes can have maximum 2 children 👉Binary Search Tree: Its a type of binary tree but we can use it to find a particular node, the inorder of BSTs will always be sorted 👉AVL Trees: Its a self-balancing BST where its unbalanced nodes are rotated in a way so that they are balanced ‼️AVL Trees use 4 cases of rotations (Left-Left, Left-Right, Right-Right, Right-Left) to create balance among the nodes ‼️How do we know if a node in AVL Tree is unbalanced? 👉 Balance Factor = Height of left subtree - Height of right subtree should be between 1 and -1 , if a node has a difference more than this range, it is unabalanced 💭 I will be exploring DSAs in detail in a while , hoping to make a separate series for them as well 🫡 Until my next post! Happy Coding Fellow Pythonists! ‼️My Python DSAs Repo is up on my GitHub! Check it out for curiousity purposes! -------------------------- ☺️ Here are Python (Beginner to Intermediate) GitHub Repos for you: 📁Python Variables: https://lnkd.in/e9rjz-_D 📁Python Operators: https://lnkd.in/e6hzgHSn 📁Python Conditionals: https://lnkd.in/egQNGZBF 📁Python Loops: https://lnkd.in/eezUg_-y 📁Python Functions: https://lnkd.in/eKdU6nex 📁Python Lists & Tuples: https://lnkd.in/eZ8KiQNs 📁Python Dictionaries & Sets: https://lnkd.in/eDmgj7pc 📁Python OOP: https://lnkd.in/eJFupCiK 📁Python DSAs: https://lnkd.in/ebR3rjkt ------------------------- ⚡ Follow my learning journey: 📎 GitHub: https://lnkd.in/ehu8wX85 🔗 GitLab: https://lnkd.in/eiiQP2gw 💬 Feedback: I’d love your thoughts and tips! 🤝 Collab: If you’re also exploring Python, DM me! Let’s grow together! -------------------------- 📞Book A Call With Me: https://lnkd.in/e23BtnR9 -------------------------- #pythondatastructures #pythontrees #binarytree #binarysearchtree #avltree #pythonforbeginners

#Day21 of #120DaysChallenge Python Functions Today, I learned about functions in Python — one of the most powerful features that help make code reusable, organized, and easier to understand. Here’s what I covered: What functions are and why we use them The basic syntax using the def keyword How to pass parameters to a function How to use the return statement to send back results Here’s a simple example I practiced def add(a,b): print(a+b) add(1,2) output: 3 ex2 : def calculate():   a=   print('Sum is',a+b)   print('Difference is',a-b)   calculate() calculate() def calculate():   a=   print('Sum is',a+b)   print('Difference is',a-b)   calculate() calculate() ''' ''' def add():   a=input('enter fname:')   b=input('enter lname:')   print(a+b) add()    ''' ''' def add():   a=input('enter fname:')   b=input('enter lname:')   print((a+''+b).title()) add()   ''' #using While loop while True:     def cal():         a=int(input('enter a value:'))         b=int(input('enter b value:'))         print('The sume is',a+b)         cal() # a function call itself its recursive     cal() #recursive function : a function call itself def cal():     a=int(input('enter a value:'))     b=int(input('enter b value:'))     print('The sume is',a+b)     cal() # a function call itself its recursive cal() #return def mul(a,b):     return a*b print(mul(1,3)) ''' #Difference Between Print and return ->Print just show the human user output in a console ->return is used to terminate the function and gives back a value from function ''' Key takeaway: Functions help break big problems into smaller, manageable pieces — and make code cleaner and reusable! Excited to keep learning and building step by step. #Python #LearningJourney #Coding #Functions #100DaysOfCode Pooja Chinthakayala Day 22 Challenge done Mam

Python Iteration Using iter() and next() 🤔What is Iteration in Python? 👉 Iteration in Python is the process of accessing elements of a collection one by one 🌀 When using iter() and next(): 👉iter() → creates an iterator object from an iterable (like a list, tuple, or string). 👉next() → retrieves the next element from the iterator, one at a time. ‼️When the iterator has no more elements, next() raises StopIteration, signaling the end. ------------------------- ☺️ Here are Python (Beginner to Intermediate) GitHub Repos for you: 📁Python Variables: https://lnkd.in/e9rjz-_D 📁Python Operators: https://lnkd.in/e6hzgHSn 📁Python Conditionals: https://lnkd.in/egQNGZBF 📁Python Loops: https://lnkd.in/eezUg_-y 📁Python Functions: https://lnkd.in/eKdU6nex 📁Python Lists & Tuples: https://lnkd.in/eZ8KiQNs 📁Python Dictionaries & Sets: https://lnkd.in/eDmgj7pc 📁Python OOP: https://lnkd.in/eJFupCiK 📁Python DSAs: https://lnkd.in/ebR3rjkt ------------------------- ⚡ Follow my learning journey: 📎 GitHub: https://lnkd.in/ehu8wX85 🔗 GitLab: https://lnkd.in/eiiQP2gw 💬 Feedback: I’d love your thoughts and tips! 🤝 Collab: If you’re also exploring Python, DM me! Let’s grow together! -------------------------- 📞Book A Call With Me: https://lnkd.in/e23BtnR9 -------------------------- #iteration #pythonprogramming #iterationinpython #pythonforbeginners

#AI #ML #Post8🧠 Invoke Python from C# using Python.Runtime ✅️Python.Runtime is the core library of Python.NET, a bridge between C# (.NET) and Python. It allows your C# code to embed the Python interpreter, run Python code, and interact with Python objects just like native C# objects. Think of it as a “translator” between C# and Python. --- ⚙️ Installation You can install it via NuGet: ✅️dotnet add package Python.Runtime --- 🧩 Key Components of Python.Runtime Let’s break down the main classes and methods you’ll use: 1. PythonEngine This is the core interface for controlling the embedded Python interpreter. Common methods: ✅️PythonEngine.Initialize() Starts the Python interpreter ✅️PythonEngine.Shutdown() Stops the interpreter and frees resources ✅️PythonEngine.Exec(string code) Executes a block of Python code ✅️PythonEngine.RunString(string code) Runs a single Python expression and returns the result ✅️PythonEngine.ImportModule("module_name") Imports a Python module --- 2. Py.GIL() In Python, the Global Interpreter Lock (GIL) ensures only one thread executes Python bytecode at a time. ✅ Example: using (Py.GIL()) { // Interact with Python here } When the using block ends, the GIL is automatically released. --- 3. PyObject A wrapper around Python objects. You can use PyObject to reference, call, or convert Python data. --- 4. Py.Import() Used to import Python modules from C# just like import in Python. --- 🧠 Example: Calling a Python function from C# Let’s say you have this Python file (myscript.py): # myscript.py def multiply(a, b): return a * b Here’s the C# code that uses Python.Runtime to call it: using System; using Python.Runtime; class Program { static void Main() { // Initialize Python interpreter PythonEngine.Initialize(); using (Py.GIL()) { // Import your Python script (make sure it's in the same folder or on sys.path) dynamic script = Py.Import("myscript"); // Call the function dynamic result = script.multiply(5, 10); Console.WriteLine($"Result from Python: {result}"); } PythonEngine.Shutdown(); } } --- ⚙️ How It Works Internally 1. PythonEngine.Initialize() loads the Python C API into your .NET process. 2. The embedded interpreter behaves exactly like a normal Python runtime (you can import any installed package). 3. Objects are wrapped as PyObject so you can use them in C#. 4. Python.NET automatically converts between basic .NET and Python types: int ↔ int double ↔ float string ↔ str List<T> ↔ list --- 💡 Tips & Notes ✅️Python must be installed on your system (and PYTHONHOME or PYTHONPATH should be correctly set if needed). ✅️You can specify a specific Python version with: Environment.SetEnvironmentVariable("PYTHONNET_PYDLL", @"C:\Python311\python311.dll");

🚀 Python Just Got 20x Faster with Mojo Integration For years, developers accepted a trade-off: Python gives us simplicity, but C/C++ deliver raw speed. That line just blurred. A recent test using Mojo, the new superset of Python, produced jaw-dropping results: 🔥 Mandelbrot Set Calculations • 20x faster than pure Python • 5x faster than NumPy • Zero compromise on readability ⚡ Sigmoid Function Processing • 12x faster than Python • 2x faster than NumPy • Same Python-like syntax we already love But here's the twist: NumPy still wins at some tasks. In numerical integration, its vectorized operations outperformed Mojo. This isn't a replacement-it's a new weapon in the toolkit. 💡 The secret sauce? Mojo lets you write high-performance code without leaving the Python ecosystem. Offload the heavy lifting to Mojo, keep the rest in Python, and you get the best of both worlds. 👉 Pro tip: Minimize Python↔Mojo crossings and stick to native Mojo types for peak performance. With 20x more speed at your fingertips, the question isn't if you'll use Mojo-it's what you'll build with it. #Python #Mojo #Programming #TechInnovation #Developers 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/d6uc43xX

🌟 Day 19 of my Python Full Stack Journey Topic: List Comprehensions Today I learned List Comprehension, which is a short and fast way to create lists in Python. Instead of writing long for loops, we can create lists in one line. #Python #ListComprehension #CodingJourney #FullStackDeveloper #DailyLearning #Consistency #PracticeEveryday #LearningByDoing Pooja Chinthakayala mam Saketh Kallepu sir Uppugundla Sairam sir Codegnan #List comprehensions or Linear comprehensions #every 'LC' can be rewritten as a for loop but every for loop cannot be rewritten in list comprehension. a=["codegnan","python","course"] b=str(a) print(b) #syntax #a=[expre for var in collection/range] a = ["codegnan","python","course"] a = [i.upper() for i in a] print(a) a=["vja","hyd","vzg"] a=[i.title() for i in a] print(a) a=[1,2,4,5,6,8,12,13] a=[i*i for i in a] print(a) a=[i**2 for i in a] print(a) a=[pow(1,2) for i in a] print(a) #if usage in list comprehension #even numbers  for i in range(16):   if i%2==0:     print(i) a=[i for i in range(16) if i%2==0] print(a) #even number square a=[i*i for i in range(21) if i%2==0] print(a) fruits=["apple", "mango","kiwi","dragon","berry","banana"] fruits=[i for i in fruits if "a" in i] print(fruits) fruits=["apple", "mango","kiwi","dragon","berry","banana"] fruits=[i for i in fruits if "a" not in i] print(fruits) #no-elif usage in "Lc" #if -else usage in "LC" #even numbers square odd*5 a=[i*i if i%2==0 else i*5 for i in range(31)] print(a) #add a+b a=[1,2,3,4,5] b=[5,4,3,2,1] c=[a[i] + b[i] for i in range(len(a))] print(c) a=[1,2,3,4,5] b=[5,4,3,2,1] c=[a[i] + b[i] for i in range(5)] print(c)

🧠 String Methods in Python — Master Text Manipulation Brought to you by programmingvalley.com Credit: @allinpython Strings are one of the most common data types in Python — and mastering them can make your code cleaner and faster. Here are some must-know string methods every developer should learn: → "HELlo".lower() → converts to lowercase → hello → "hello".upper() → converts to uppercase → HELLO → "hello world".capitalize() → makes first letter uppercase → Hello world → "hello world".title() → capitalizes each word → Hello World → " hello ".strip() → removes spaces → hello → "Hello".startswith("He") → checks if string starts with “He” → True → "Hello".endswith("lo") → checks if string ends with “lo” → True → "one,three".replace(",", "|") → replaces characters → one|three → "one,three".split(", ") → splits string → ['one', 'three'] → "-".join(["a", "b", "c"]) → joins list into string → a-b-c → "hello".find("e") → returns position → 1 → "hello".index("e") → similar to find() but raises error if not found → "hello world".count("o") → counts occurrences → 2 → "12345".isnumeric() → checks if all characters are numeric → True 🎓 Learn Python the right way: Python for Data Science → https://lnkd.in/d5iyumu4 Google IT Automation with Python → https://lnkd.in/dyJ4mYs9 Microsoft Python Development Certificate → https://lnkd.in/dDXX_AHM #Python #Coding #DataScience #LearnPython #ProgrammingValley #PythonTips

🐍📰 How to Group Data Using Polars .group_by() Start using Polars .group_by() to make sense of your data. This tutorial shows you how to group, aggregate, and reveal hidden insights with hands-on examples #python