Mastering Python List Comprehensions with Python

If you’ve ever used `@property` in Python, you’ve already used descriptors. Most developers rely on them every day without realizing what’s actually happening under the hood. And once you understand how descriptors work, a lot of “Python magic” suddenly becomes much easier to reason about. In today’s video, I build descriptors step by step. I recreate a simple version of `@property`, explore why assigning to `__dict__` sometimes overrides attributes and sometimes doesn’t, and use descriptors to implement reusable validation and lazy cached properties. If you want to deepen your understanding of Python and write cleaner, more expressive code, descriptors are a feature worth learning. 👉 Watch here: https://lnkd.in/exgSHj2q. #python #softwaredesign #cleancode #pythoninternals #developers

11 Useful Python List Methods Working with lists is common in almost every Python project. Understanding these built-in methods makes your code cleaner and more efficient. Here are 11 essential list methods: 1) append() → Add a single item to the list. 2) extend() → Add multiple items individually. 3) insert() → Add an item at a specific index. 4) remove() → Remove the first matching item. 5) pop() → Remove and return an item. 6) index() → Find the position of an item. 7) count() → Count how many times an item appears. 8) sort() → Sort the list in place. 9) reverse() → Reverse the order of elements. 10) clear() → Remove all items from the list. 11) reverse() → Reverse the order of elements. These small methods are simple, but they appear frequently in real-world code. Mastering them improves readability and reduces unnecessary logic. Comment below, Which list method do you use the most? Comment below. Save this for quick revision later. 📌 I share simple Python and backend learnings here. #Python #LearnPython #Programming #Coding #SoftwareEngineering #PythonDeveloper

If you’ve ever used `@property` in Python, you’ve already used descriptors. Most developers rely on them every day without realizing what’s actually happening under the hood. And once you understand how descriptors work, a lot of “Python magic” suddenly becomes much easier to reason about. In today’s video, I build descriptors step by step. I recreate a simple version of `@property`, explore why assigning to `__dict__` sometimes overrides attributes and sometimes doesn’t, and use descriptors to implement reusable validation and lazy cached properties. If you want to deepen your understanding of Python and write cleaner, more expressive code, descriptors are a feature worth learning. 👉 Watch here: https://lnkd.in/eXDTNvPg. #python #softwaredesign #cleancode #pythoninternals #developers

Day 46 : Python Conditional Statements – If/Else Today I understood the conditional statements used in Python. Hands-on : - Today I learned about conditional statements in Python, which are used to control the flow of a program based on conditions. - I started with the basic syntax of the if statement, understanding how Python evaluates conditions and executes code blocks. -I then explored the if/else statement, which allows execution of alternate code when a condition is false. - Moving forward, I practiced if/elif/else statements to handle multiple conditions efficiently. - I also learned how to write if/else in a single line (ternary operator), which makes simple conditions more concise. - Finally, I explored nested if/else statements, where one condition is placed inside another to handle more complex logic. Result : - Successfully understood how to implement conditional logic in Python using different forms of if/else statements. Key Takeaways : - If statement executes code only when a condition is true. - If/Else provides an alternative execution path. - If/Elif/Else helps handle multiple conditions efficiently. - One-line if/else (ternary) makes code concise for simple conditions. - Nested conditions allow handling complex decision-making scenarios. #Python #Programming #DataAnalytics #LearningJourney #ConditionalStatements #CodingBasics #DataScience #BeginnerPython #AnalyticsSkills

Just last week, I discovered common Python errors in student submissions: • Modifiable default arguments 🤦♂️ • Simple "except" clauses 🚨 • Iterating while making changes to a list 🔁 To be honest, these appear every single semester. When I started studying Python, I recall wishing someone had given me a concise, useful manual. I created one for my pupils, and I'm sharing it with you now. 📌"10 Python Mistakes Novices Must Avoid" • Why they occur • How to correct them • Examples of clean code for each This will save hours of frustrating troubleshooting, whether you're learning Python yourself or mentoring someone who is. 🔗 Go here: https://lnkd.in/gGni7aS7 ♻️ Share this with a student or junior developer you know; it could save them weeks of confusion. #Python #ProgrammingTips #Coding #ComputerScienceEducation #LearnPython

🚀 Ever wondered how to efficiently organize your code using modules in Python? Let's break it down! 🐍 Modules are simply Python files that consist of functions and variables for specific tasks. They help keep your code organized, manageable, and reusable. 👨💻 Why does this matter for developers? By using modules, you can effectively break down your code into smaller, logical components, making it easier to collaborate with others, maintain and scale your projects. 🔍 Here's the step-by-step breakdown: 1️⃣ Create a Python file for your module, e.g., "my_module.py". 2️⃣ Define functions and variables within the module. 3️⃣ Import the module in your main Python script. 4️⃣ Access functions and variables using dot notation. 🧩 Full code example: ``` # my_module.py def greet(name): return "Hello, " + name ``` ``` # main.py import my_module print(my_module.greet("Alice")) ``` 💡 Pro tip: Keep your module names meaningful and descriptive to enhance code readability and maintainability. ❌ Common mistake to avoid: Forgetting to add an empty "__init__.py" file in the module folder, which is required for Python to recognize it as a package. 🤔 What creative ways have you used modules in your Python projects? Share in the comments below! 👨💼💬 🌐 View my full portfolio and more dev resources at tharindunipun.lk 🚀 #PythonModules #CodeOrganization #DeveloperTips #PythonCoding #CodingLife #CodeReuse #TechSkills #SoftwareDevelopment #LearnToCode

🚀 Learning Python the Practical Way: Understanding Virtual Environments Over the past few days, I started learning Python and decided to focus on building instead of just reading syntax. Today, I explored one of the most important concepts for any developer: Virtual Environments (venv) Here’s what I understood: 🔹 A virtual environment is an isolated Python setup for a specific project 🔹 It prevents version conflicts between different projects 🔹 Each project can have its own dependencies without affecting others 💡 Why it matters: While working on multiple projects, different versions of the same library can break things. Virtual environments solve this by keeping everything separate and controlled. 🛠️ What I practiced: Creating a virtual environment Activating and deactivating it Installing packages inside it Understanding how Python uses project-specific paths This concept is very similar to how we manage dependencies in Node.js projects, but implemented differently in Python. Next step: Building a simple backend server using FastAPI to apply this knowledge in real projects. #Python #BackendDevelopment #FastAPI #WebDevelopment #LearningInPublic

I was memorizing Python keywords… and realized something important. Most beginners try to remember everything at once but Python doesn’t work like that. It works on logic, not memorization. What I learned: Python has reserved keywords words you can’t change because they already have a meaning in the language. Examples: if, else, elif → decision making for, while → loops def, return → functions True, False, None → core values and, or, not → logic 💡 Instead of memorizing 30+ keywords… I started grouping them like this: 🔹 Decision → if, else, elif 🔹 Loops → for, while, break, continue 🔹 Functions → def, return 🔹 Logic → and, or, not 🔹 Structure → class, try, except And suddenly… everything made sense. Big realization: Programming is not about remembering keywords. It’s about understanding how they work together. If you’re learning Python right now: Don’t memorize. Connect concepts. That’s when coding becomes easy. #Python #Coding #LearnToCode #DataAnalytics #Programming

🚀 **Day 7 of Learning Python** Today I learned about **Functions** in Python — a major step toward writing cleaner and reusable code! 🔧 A function is a block of code that performs a specific task and can be reused whenever needed. Instead of repeating code, we can simply call a function. 👉 **Basic syntax:** `def function_name(parameters):`     `# code block` 💡 **Example:** ``` def myfunction(name): return f"Hello, {name}!" print(myfunction("Prathap")) ``` ✨ **What I learned:** ✅ Functions help organize code better ✅ They improve readability ✅ They save time by avoiding repetition ✅ You can pass data using parameters and get results using return values 🔥 It feels great to move from just writing code to structuring it properly! 📌 **Key takeaway:** Good programmers don’t just write code — they write reusable code. #Python #LearningJourney #30DaysOfCode #Functions #Coding #Programming #DeveloperJourney

10 Python Built-in Functions You Should Know: If you’re learning Python or writing code daily, these built-in functions will save you time and make your code cleaner: 🔹 len() → Count items in a list or string. 🔹 zip() → Combine two lists into pairs. 🔹 map() → Apply a function to every item. 🔹 filter() → Filter items based on a condition. 🔹 any() → Returns True if any item is True. 🔹 all() → Returns True if all items are True. 🔹 sum() → Adds up elements in an iterable. 🔹 sorted() → Sorts items. 🔹 enumerate() → Adds index to items. 🔹 range() → Generates a sequence of numbers. Mastering these small functions is very helpful in writing clean code. Which one do you use the most? #Python #Programming #Developers #Coding #SoftwareEngineering #CodingInterview #PythonDeveloper