Object Oriented Programming (OOP) – Python: Section 4 Notes University-level Python notes covering object-oriented programming concepts like encapsulation, inheritance, and modular code design—essential for AI and software development. Upon purchase, you will be able to digitally download the PDF file containing notes. ...
Python OOP Notes: Encapsulation, Inheritance, Modular Code
More Relevant Posts
-
Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Its simple syntax reduces the complexity of coding and helps developers focus more on solving problems rather than worrying about strict rules. One of Python’s biggest strengths is its vast ecosystem of libraries and frameworks, which enable developers to build a wide range of applications. It is widely used in web development, data analysis, artificial intelligence, machine learning, automation, and scientific computing. Python is platform-independent, meaning programs written in Python can run on different operating systems without modification. It is also open-source, allowing anyone to use, modify, and distribute it freely. Because of its flexibility, strong community support, and wide range of applications, Python has become one of the most popular programming languages in the world.
To view or add a comment, sign in
-
Part 2: Python Programming in One Page --> OOPS concepts. Yesterday, we learned Python in ONE page. Today, let’s level up If Python basics = writing code OOP = structuring code like a pro Simple breakdown Class = Blueprint (Car) Object = Real thing (BMW, Audi) Attributes = Data (color, speed) Methods = Actions (start, stop) 4 Core Ideas: • Encapsulation → keep data safe • Inheritance → reuse code • Polymorphism → same function, different behavior • Abstraction → hide complexity Why it matters? Clean code Reusable Scalable Full guide: https://lnkd.in/gycbAuzj Part 2 of “One Page Learning Series” Next → Data Structures Follow Scooplist for more learning
To view or add a comment, sign in
-
AI tools have transformed fields like software development and data science, and yes, in many cases, they'll write Python for you. But knowing what's actually happening under the hood still matters! Next month, I'm teaching TECH 19: A Practical Introduction to Python through Stanford Continuing Studies. It's an eight-week course designed for professionals who want a solid foundation in one of the world's most widely used programming languages. We'll cover the basics of Python and explore how to build useful tools, leverage powerful packages, and debug code, so you can work confidently alongside the AI tools rather than just depend on them. Enrollment is open now. If you've been meaning to finally understand Python, this is a great place to start! 🔗 https://lnkd.in/eTxm3CyB #Python #ContinuingEducation #DataScience #ProfessionalDevelopment
To view or add a comment, sign in
-
*🎓 Harvard CS50P: Programming with Python – Full Course FREE* *8M+ Views on YouTube* 🔥 Taught by *Dr. David J. Malan* *What you’ll learn:* Learn to read, write, test, and debug Python code from scratch. No experience needed. ✅ Variables, types, conditionals, loops ✅ Functions, arguments, return values ✅ Handle exceptions + fix bugs ✅ Write unit tests ✅ Use third-party libraries ✅ Regular expressions for data ✅ OOP: classes, objects, methods ✅ Read/write files Hands-on projects inspired by real-world problems. No software needed — just your browser. Or use your own PC/Mac. *CS50P vs CS50x?* CS50x = Computer Science + C, Python, SQL, JS CS50P = 100% Python programming Take before, during, or after CS50x. *📺 Watch full course:* `https://lnkd.in/eV6dR9Ax *💻 Slides + Source Code:* `cs50.harvard.edu/python` *⏱️ Course Timeline:* (00:00:00) Introduction (00:04:48) Functions, Variables (01:50:24) Conditionals (02:46:23) Loops (04:07:10) Exceptions (04:51:45) Libraries (06:09:15) Unit Tests (07:00:22) File I/O (08:32:32) Regular Expressions (10:37:35) OOP (13:28:47) Et Cetera ━━━━━━━━━━━━━━━━━━━━━━ This is Harvard quality for $0.
Harvard CS50’s Introduction to Programming with Python – Full University Course
https://www.youtube.com/
To view or add a comment, sign in
-
Synchronous vs Asynchronous Programming in Python In backend development, understanding the difference between synchronous and asynchronous programming is essential for building efficient systems. Synchronous code executes tasks one at a time, meaning each operation must complete before the next one begins. While this approach is simple and easy to understand, it can become inefficient when dealing with operations that take time, such as network requests or database queries. Asynchronous programming allows multiple operations to run concurrently without blocking the execution of other tasks. In Python, frameworks like FastAPI take advantage of asynchronous features using async and await keywords. This allows servers to handle multiple requests at the same time, improving performance and responsiveness. Choosing between synchronous and asynchronous approaches depends on the use case. For simple applications, synchronous code may be sufficient. However, for high-performance APIs or systems handling many concurrent users, asynchronous programming becomes essential. Developers who understand both approaches can design systems that are both efficient and scalable. Question for discussion: Have you worked with asynchronous programming in Python, and what challenges did you face? #PythonDeveloper #BackendDevelopment #AsyncProgramming #FastAPI #SoftwareEngineering
To view or add a comment, sign in
-
-
*🎓 Harvard CS50P: Programming with Python – Full Course FREE* *8M+ Views on YouTube* 🔥 Taught by *Dr. David J. Malan* *What you’ll learn:* Learn to read, write, test, and debug Python code from scratch. No experience needed. ✅ Variables, types, conditionals, loops ✅ Functions, arguments, return values ✅ Handle exceptions + fix bugs ✅ Write unit tests ✅ Use third-party libraries ✅ Regular expressions for data ✅ OOP: classes, objects, methods ✅ Read/write files Hands-on projects inspired by real-world problems. No software needed — just your browser. Or use your own PC/Mac. *CS50P vs CS50x?* CS50x = Computer Science + C, Python, SQL, JS CS50P = 100% Python programming Take before, during, or after CS50x. *📺 Watch full course:* `https://lnkd.in/etc2vQTW *💻 Slides + Source Code:* `cs50.harvard.edu/python` *⏱️ Course Timeline:* (00:00:00) Introduction (00:04:48) Functions, Variables (01:50:24) Conditionals (02:46:23) Loops (04:07:10) Exceptions (04:51:45) Libraries (06:09:15) Unit Tests (07:00:22) File I/O (08:32:32) Regular Expressions (10:37:35) OOP (13:28:47) Et Cetera ━━━━━━━━━━━━━━━━━━━━━━ This is Harvard quality for $0
Harvard CS50’s Introduction to Programming with Python – Full University Course
https://www.youtube.com/
To view or add a comment, sign in
-
🐍 Python Basics – Quick Learning Notes Python is one of the most popular programming languages today, known for its simplicity and versatility. Here are some key fundamentals: 🔹 Interpreted Language Python executes code line by line using an interpreter, making debugging easier and faster. 🔹 Dynamically Typed No need to declare data types explicitly – Python handles it automatically. 🔹 Scripting Language Widely used for automation, data processing, and rapid development. 🔹 Case Sensitive Variables like data and Data are treated differently. 🔹 Memory Management (Private Heap) Python manages memory internally using a private heap, ensuring efficient storage of objects. 🔹 Simple & Readable Syntax Easy to learn and write, making it beginner-friendly. 🔹 Supports Structured Programming Although flexible by default, Python supports structured programming through functions, classes, and OOPS concepts. 💡 Python is not just a language, it's a powerful tool to solve real-world problems efficiently. #Python #Programming #Coding #SoftwareDevelopment #DataScience #Learning #Beginners #Tech
To view or add a comment, sign in
-
🚀 Day 3: Understanding Operators in Python Operators are fundamental elements in programming that allow us to perform operations on variables and values. In Python, operators play a key role in building logic, performing calculations, and making decisions. 🔹 Main Types of Operators: ✔ Arithmetic Operators Used for mathematical calculations (+, -, *, /, %, //, **) ✔ Comparison Operators Used to compare values (==, !=, >, <, >=, <=) ✔ Logical Operators Used to combine conditions (and, or, not) ✔ Assignment Operators Used to assign and update values (=, +=, -=, *=, /=) 💡 Example: x = 10 y = 5 print(x + y) # Output: 15 print(x > y) # Output: True 📌 Why are operators important? Operators are essential for writing any kind of program. From simple calculations to complex decision-making systems, they are used everywhere. Mastering operators means building a strong programming foundation. 📈 Learning step by step, improving every day. #Python #Programming #Developers #Coding #BackendDevelopment #LearningJourney #FullStack #Django
To view or add a comment, sign in
-
-
𝗢𝗯𝗷𝗲𝗰𝘁 𝗢𝗿𝗶𝗲𝗻𝘁𝗲𝗱 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻 Object-oriented programming (OOP) is one of those concepts that separates good developers from great ones. However, it is also one of the most misunderstood topics among beginners and intermediate developers. 𝗧𝗵𝗲 "𝗮𝗵𝗮" 𝗺𝗼𝗺𝗲𝗻𝘁 𝗯𝗲𝗴𝗶𝗻𝘀 𝘄𝗶𝘁𝗵 𝗰𝗹𝗮𝘀𝘀𝗲𝘀. Instead of juggling four loosely related variables, you create your own data types — objects with attributes and behaviors that belong together. 𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿𝘀 (__𝗶𝗻𝗶𝘁__) 𝗮𝗿𝗲 𝘆𝗼𝘂𝗿 𝗯𝗲𝘀𝘁 𝗳𝗿𝗶𝗲𝗻𝗱. They enforce structure when objects are created, so you always know what attributes an instance should have. 𝗧𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗰𝗹𝗮𝘀𝘀 𝗮𝗻𝗱 𝗶𝗻𝘀𝘁𝗮𝗻𝗰𝗲 𝗮𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝘀 is more important than you think. Want to apply a store-wide discount? That's a class attribute. Do you want a specific item to have a custom discount? Override it at the instance level. 𝗖𝗹𝗮𝘀𝘀 𝗮𝗻𝗱 𝘀𝘁𝗮𝘁𝗶𝗰 𝗺𝗲𝘁𝗵𝗼𝗱𝘀 𝘀𝗲𝗿𝘃𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗽𝘂𝗿𝗽𝗼𝘀𝗲𝘀. Use class methods to instantiate objects from structured data, such as CSV or JSON. Use static methods for utility logic related to your class that doesn't depend on instance or class state. 𝗜𝗻𝗵𝗲𝗿𝗶𝘁𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗽𝗼𝗹𝘆𝗺𝗼𝗿𝗽𝗵𝗶𝘀𝗺 𝗹𝗲𝗮𝗱 𝘁𝗼 𝘀𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗰𝗼𝗱𝗲. First, build a parent Item class. Then, extend it with Phone, Laptop, and Keyboard, each of which inherits shared logic while maintaining its own behavior. 💡 In summary, encapsulation and abstraction help you write clean, intentional code that can be maintained at scale. 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 🔗 Python Object Oriented Programming (OOP) - Full Course for Beginners, 29 Jan 2025, https://lnkd.in/dk2cFyYB 🔗 Object Oriented Programming with Python - Full Course for Beginners, 13 Oct 2021, https://lnkd.in/dufrXaBZ #Python #ObjectOrientedProgramming #SoftwareDevelopment #CodingForBeginners #ProgrammingTips
Object Oriented Programming with Python - Full Course for Beginners
https://www.youtube.com/
To view or add a comment, sign in
Explore content categories
- Career
- Productivity
- Finance
- Soft Skills & Emotional Intelligence
- Project Management
- Education
- Technology
- Leadership
- Ecommerce
- User Experience
- Recruitment & HR
- Customer Experience
- Real Estate
- Marketing
- Sales
- Retail & Merchandising
- Science
- Supply Chain Management
- Future Of Work
- Consulting
- Writing
- Economics
- Artificial Intelligence
- Employee Experience
- Workplace Trends
- Fundraising
- Networking
- Corporate Social Responsibility
- Negotiation
- Communication
- Engineering
- Hospitality & Tourism
- Business Strategy
- Change Management
- Organizational Culture
- Design
- Innovation
- Event Planning
- Training & Development