Encapsulation and Access Modifiers in Python OOP

🐍 The Lightest Way to Run Python from .NET Need to execute Python code from your C# application without complex setup and boilerplate? I built DotNetPy: ✅ Zero Boilerplate - No GIL management or Source Generator required ✅ AOT-Friendly - Explicitly designed for Native AOT scenarios ✅ Minimal Learning Curve - Execute Python in just a few lines ✅ Apache 2.0 Licensed From evaluating Python expressions to complex data marshaling, it's a much lighter alternative to pythonnet or CSnakes. Example: Python.Initialize(pythonLibraryPath); var executor = Python.GetInstance(); var result = executor.Evaluate("sum([1,2,3,4,5])"); Console.WriteLine(result?.GetInt32()); // 15 🔗 GitHub: https://lnkd.in/g23PEys8 ⭐ Apache 2.0 | AOT-Compatible | Lightweight ⚠️ Note: Experimental - extensive testing needed before production use Feedback & contributions welcome! #dotnet #python #csharp #opensource #interop #nativeaot #programming #developers

Python OOP Concept 7/15: Polymorphism - Method Overriding Polymorphism allows objects of different classes to be treated uniformly. In my Django, Flask, and FastAPI applications, polymorphism enables flexible, extensible architectures. Method overriding is a key aspect - child classes can redefine parent methods with specialized behavior. In Django, I use polymorphism with model inheritance. In Flask, different authentication backends implement the same interface. In FastAPI, various data sources conform to unified schemas. 💡 Key Benefits: 📌 Flexibility: Swap implementations without changing client code 📌 Extensibility: Add new variants without modifying existing code 📌 Testability: Mock services easily for unit tests 🎯 Key Takeaway: Polymorphism enables interchangeable components. Override methods to specialize behavior while maintaining consistent interfaces. Follow winston mhango for the next concept: "Abstract Classes and Interfaces" #Python #OOP #Polymorphism #FastAPI #Django #Flask #SoftwareDesign

Python: My Go-To Language for Clean & Powerful Code Core & OOP: Mastered Python fundamentals and object-oriented programming Web Development: Built APIs with Flask and FastAPI Data Handling: Worked with CSV, JSON, and automation scripts Libraries: Explored pandas, requests, BeautifulSoup for practical projects Best Practices: Focused on writing clean, readable, and maintainable code. Python has strengthened my problem-solving mindset and expanded my development toolkit. #Python #Programming #WebDevelopment #Automation #CleanCode #LearningJourney

Python OOP: Concept 6/15: Inheritance Basics - Reusing Code Inheritance lets classes inherit attributes and methods from parent classes. With 7+ years using Django, Flask, and FastAPI, I rely heavily on inheritance for code reuse and extensibility. 📌 A child class inherits from a parent class, gaining its functionality while adding or overriding as needed. In Flask, I create base API classes with common error handling. In FastAPI, I inherit from base models for shared validation logic. 🚀 Benefits: 📍 Code reuse: Avoid duplicating common functionality 📍 Extensibility: Add specialized behavior in child classes 📍 Maintainability: Changes to parent affect all children 🎯 Key Takeaway: Inheritance promotes DRY principles and hierarchical organization. Use super() to properly initialize parent classes. Follow along for the next concept: "Polymorphism - Method Overriding" #Python #OOP #Django #Flask #FastAPI #Inheritance #SoftwareEngineering

🔧 Everyone's using monkey-patching in Python, but these alternatives are 10x safer Here are 3 game-changing tools for modifying Python code at runtime that most developers don't know about: 1. Modshim (New!) → Surgical precision code modification without the mess → 70% less likely to cause runtime errors vs traditional monkey-patching → Free & open source 2. pytest-mock → Clean mocking with automatic cleanup → Prevents test pollution and memory leaks → Free community edition 3. unittest.mock → Built-in solution that's seriously underrated → Zero dependencies, works out of the box → Native Python support 💡 Pro tip: Modshim's isolated execution context means your patches won't leak into other parts of your codebase. No more mysterious bugs! 🔥 Why this matters: • Safer code modifications • Better testing isolation • Cleaner debugging • Production-ready stability Save this before it becomes mainstream! 📌 Which tool are you trying first? 📖 Read full article: https://lnkd.in/eUbnh4AU #Python #Programming #SoftwareEngineering #DevTools #CodeQuality #Testing #PythonDevelopment #TechTips

💡 Why OOP Still Matters in Modern Python Even with the rise of functional and data-driven programming, Object-Oriented Programming (OOP) continues to be the backbone of scalable, maintainable, and readable Python code. Here’s why it’s still powerful today 👇 🔹 Helps model real-world entities easily 🔹 Promotes code reusability through inheritance 🔹 Ensures data safety with encapsulation 🔹 Enables flexibility via polymorphism 🔹 Simplifies complexity using abstraction 🔹 Keeps large projects organized (like Django & Flask) OOP isn’t outdated — it’s a timeless design approach that helps developers build better, cleaner, and smarter software. ✨ Master the fundamentals. Structure your logic. Build like a pro. #Python #OOP #Programming #SoftwareDevelopment #CleanCode #Django #TechLearning

Concept 3/15: Understanding Attributes and Methods In Python OOP, attributes store data and methods define behavior. After years building with Django and FastAPI, I've learned that proper attribute/method design is critical for clean code. Attributes come in two types: 📌 Instance attributes: Unique to each object 📌 Class attributes: Shared across all instances Methods define what objects can do: 📌 Instance methods: Operate on instance data 📌 Class methods: Work with class data 📌 Static methods: Independent utility functions In Django models, I use instance attributes for field values and class attributes for metadata. In FastAPI, class attributes store configuration shared across endpoints. 🎯 Key Takeaway: Distinguish between instance (per-object) and class (shared) data. This affects memory usage and behavior consistency. Follow winston mhango for the next concept: "The Role of self and init" #Python #OOP #Flask #Django #FastAPI #SoftwareEngineering #CodingTips

Build a Daily Report Generator Using Python + Notion API (Minimal Working Example) For my first Dev.to post, I wanted to share something small, useful, and immediately applicable — a minimal Python script that automatically generates a daily report into Notion. This is part of my ongoing effort to build in public while constructing my one-person company’s automation stack. If you want a simple, beginner-friendly example of how to interact with the Notion API using Python, this is a great place to start. A tiny script that: Reads your Notion API key Writes a new entry into a Notion database Automatically fills in today’s date Adds a default “Daily Report” template text No frameworks, no advanced tooling — just pure Python and a few lines of code. You'll need: A Notion API integration A database in Notion The database’s ID Python 3.8+ The requests library Install the dependency: pip install requests import requests import datetime NOTION_API_KEY = "YOUR_NOTION_SECRET_KEY" DATABASE_ID = "YOUR_DATABASE_ID" url = "https://lnkd.in/gB3pFQVi" headers = { "Auth https://lnkd.in/gY2kCf9D

Day 10 of sharing 💪 ! You have Python scripts running on your system. They analyze data. Make predictions. Process information. Now you need to use that same inside Node-RED. The simple way: Use the Exec node. It runs your Python script directly from your flow. Send data in. Get results out. Keep building your flow. Test in your instance. Deploy to edge devices. Your flows and Python scripts stay together. Check it out: https://lnkd.in/dbvFWfci

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