Python Practice on HackerRank Improves Problem Solving Skills

If Python variables still confuse you sometimes — lists behaving oddly, a global that won't update, `is` returning results that don't match `==` — it's almost always the same issue. You're thinking of variables as boxes that hold values. Python treats them as name tags attached to objects. Once that click happens, most of Python's "strange" behavior stops being strange. You can find a tutorial on PythonCodeCrack at the link below built entirely around that single idea. It starts from your first assignment and walks all the way through scope, mutability, type conversion, and even the CPython implementation details that surprise senior developers. Every section ends with a "thread marker" tying the concept back to the core model, and there are predict-before-you-run prompts at the moments where beginner intuition sometimes fails. Ends with a 10-question exam and a downloadable certificate for anyone who wants to mark the milestone and share their progress in building their Python programming skillset. Free. No signup. Just a solid foundation. https://lnkd.in/gA6nnmSJ #Python #LearnPython #PythonForBeginners #Coding #Programming

Mastering Conditional Logic in Python As part of my Python practice, I worked on a problem that strengthens decision-making using conditional statements. n = int(input()) if n % 2 != 0: print("Weird") elif n % 2 == 0 and 2 <= n <= 5: print("Not Weird") elif n % 2 == 0 and 6 <= n <= 20: print("Weird") else: print("Not Weird") ->What this program does: Takes an integer as input Checks whether the number is odd or even Applies multiple conditions to decide the output -> Logic Breakdown: Odd numbers → Weird Even numbers (2 to 5) → Not Weird Even numbers (6 to 20) → Weird Even numbers (>20) → Not Weird -> Example: Input: 3 → Output: Weird Input: 24 → Output: Not Weird -> Key Takeaways: Understanding if-elif-else is essential for real-world problem solving Combining conditions using and improves control over logic Writing clean conditional code builds strong programming fundamentals #Python #CodingJourney #ProblemSolving #100DaysOfCode #LearningPython #ProgrammingBasics

🚀 Learning Python OOP – Encapsulation in Action! Today I practiced a simple Bank Account example to understand the concept of Encapsulation in Python. In this example, I created a Bank class where sensitive data like PIN and balance are kept private using double underscores (__pin, __balance). This ensures that the data cannot be accessed directly from outside the class and can only be used through defined methods like checking balance or updating the PIN. This concept helps in: ✔ Protecting sensitive data ✔ Improving code security ✔ Controlling how data is accessed and modified This example was taught in our class, and implementing it on my own really helped me understand how encapsulation works in real scenarios. Excited to keep building more concepts as part of my Data Science learning journey 📊🐍 #Python #PythonLearning #ObjectOrientedProgramming #Encapsulation #DataScienceJourney #Coding #LearningByDoing #BeginnerProgrammer

🐍 Documenting my Python learnings for Data Engineering use cases I’ve been working on strengthening my Python understanding specifically from a Data Engineering perspective. To keep things structured, I’ve been documenting my learnings in a GitHub repository — focusing only on concepts and use-cases that are relevant for working with data. The idea was to build something that: • Organizes key Python concepts in one place • Connects them to practical data-related use cases • Serves as a quick reference while revising If you already have some familiarity with Python and want a concise, organized way to revisit important concepts in a data-focused context, feel free to check it out 👇 🔗https://lnkd.in/gYdG3R7V Open to feedback and suggestions 🙂 #Python #DataEngineering #LearningInPublic

Handling Files in Python: Best Practices for Opening Opening files in Python is a foundational skill for data manipulation and processing. The code above demonstrates how to open a file safely using a context manager, represented by the `with` statement. This approach ensures that the file is properly closed after its block of code is executed, even if an error occurs. Without the context manager, you might leave the file open after reading it, leading to potential memory leaks or file corruption. By using `with`, Python takes care of closing the file automatically, making your code cleaner and safer. It also helps handle exceptions gracefully. For instance, if the specified file is not found, a `FileNotFoundError` will trigger the exception block, allowing you to inform the user without crashing the program. This becomes critical when working on projects that involve multiple files or external resources. The need for efficient resource management cannot be overstated, especially in larger applications where multiple files may be opened. Quick challenge: How would you modify this code to open a file for writing, ensuring that it creates the file if it doesn't exist? #WhatImReadingToday #Python #PythonProgramming #FileHandling #LearnPython #Programming

Day 1 — Starting My Python Journey Today I practiced the basics of Python 🔹 Working with variables 🔹 Using the print() function 🔹 Performing basic operations Here’s a simple snippet I tried: name = "Ankaj" age = 34 print(name, age) a = 20 b = 10 print(a + b) # Addition print(a - b) # Subtraction print(a / b) # Division What I learned: Python makes it really easy to work with variables and perform operations without complex syntax. I’m documenting my journey as I learn every day Follow Ankaj Python Hub to grow with me https://lnkd.in/gx2yF2vF #Python #LearnPython #CodingJourney #100DaysOfCode #Beginner

🚀 Day 12 of Python Coding Challenge 📌 Problem: Count Total Number of Characters in a File Understanding file handling is a fundamental skill in Python. Today’s task is to count the total number of characters in a given file. 💡 Approach: Open the file in read mode Read the file content Use len() to count characters 🧠 Python Code: def count_characters(file_path): try: with open(file_path, 'r') as file: content = file.read() return len(content) except FileNotFoundError: return "File not found." # Example usage file_path = "sample.txt" result = count_characters(file_path) print("Total characters in file:", result) ✅ Sample Output: Total characters in file: 12 🔍 Key Learnings: File handling using open() Using with statement for safe file operations Applying len() on strings 📢 Pro Tip: If you want to exclude spaces or newline characters, you can filter them before counting! 🔥 Keep Learning, Keep Growing! Follow along for more daily Python problems. #Python #CodingChallenge #Day12 #LearningJourney #30DaysOfCode

🚀 Ever wondered how to efficiently use loops in Python? Let's dive in and unravel the power of Python loops! 🐍 Python loops are used to iterate over sequences like lists, tuples, and dictionaries, executing the same block of code repeatedly. This simplifies tasks like calculations, data processing, and repetitive actions in your programs. Developers benefit greatly from mastering loops as they streamline code, improve efficiency, and help automate repetitive tasks. By understanding how loops work, developers can write cleaner code, reduce errors, and enhance their problem-solving skills. Plus, loops are fundamental in programming and are widely used in various applications. Step by Step Breakdown: 1. Initialize a list of items. 2. Use a "for" loop to iterate over each item. 3. Perform an action on each item within the loop. 💡 Pro Tip: Remember to choose the appropriate loop (for or while) based on the specific task and data structure you are working with for optimal performance and readability. ⚠️ Common Mistake Alert: Forgetting to update the loop control variable correctly can lead to infinite loops, causing your program to hang or crash. 🤔 What's your favorite application of loops in Python? Share with us in the comments below! 🌐 View my full portfolio and more dev resources at tharindunipun.lk #PythonLoops #CodeEfficiency #Programming101 #DeveloperTips #AutomationInCoding #LearnToCode #PythonProgramming #TechSkills #ProblemSolving #CodeMastery

Evaluating Expressions in Python using eval() While practicing on HackerRank, I explored the power of Python’s built-in eval() function. *Problem Statement: Read a mathematical expression from input and evaluate its result. Solution: # Enter your code here. Read input from STDIN. Print output to STDOUT expression = input() print(eval(expression)) * How it works: input() takes the expression as a string (e.g., "3 + 5 * 2") eval() evaluates the string as a Python expression The result is printed directly Example: Input: 3 + 5 * 2 Output: 13 *Important Note: eval() is powerful but should be used carefully, as it can execute arbitrary code. It’s safe in controlled environments like coding platforms, but not recommended for untrusted input in real-world applications. -> Always exciting to learn how Python simplifies complex tasks with minimal code! #Python #HackerRank #CodingPractice #Programming #LearnToCode #100DaysOfCode