10 Good Coding Principles #python #programming #developer #morioh #programmer #coding #coder #softwaredeveloper #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience

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@Python_Dv Nice list, hunter! Old-school devs would say: LURK before you LEAP! Remixing that ethos with some HODL vibes in web3!

@Python_Dv Thanks for sharing! Helpful resources for beginners.

@Python_Dv Does perfect code reflect the soul of its creator?

@Python_Dv Inme se kaun kaun se hai...🤞🏻 I know one thing passion and when the error couldn't solve it, can't sit quite...😏

@Python_Dv Inme se kaun kaun se hai...🤞🏻 I know one thing passion and when the error couldn't solve it, can't sit quite...😏 #coding #programming #programmer #developer

10 Good Coding Principles 1. SOLID Principles: Single Responsibility Principle (SRP): A class should have one reason to change; it should have only one job or responsibility. Open/Closed Principle (OCP): Software entities should be open for extension but closed for modification. Liskov Substitution Principle (LSP): Objects of a superclass should be replaceable with objects of a subclass without affecting the correctness of the program. Interface Segregation Principle (ISP): Clients should not be forced to depend on interfaces they do not use. It's better to have many small interfaces than a few large ones. Dependency Inversion Principle (DIP): High-level modules should not depend on low-level modules; both should depend on abstractions. 2. Security Assurance: SQL Injection Prevention: Use parameterized queries to prevent attackers from executing arbitrary SQL code. Cross-Site Scripting (XSS) Prevention: Validate and sanitize user inputs to avoid the execution of malicious scripts. Data Leakage Prevention: Implement proper access controls and encryption to protect sensitive information. 3. Continuous Refactoring: Regularly improve the design of existing code to enhance readability and maintainability while reducing complexity and dependencies. 4. Code Specification: Adhere to coding standards like PEP 8 for Python or Google Java Style to ensure consistency and readability across the codebase. 5. Documentation and Annotations: Clearly document complex logic and decisions in the code. This includes explaining the rationale behind specific approaches to maintain clarity and aid future developers. 6. Robustness: Design systems to handle various types of failures gracefully, including disk failures, input errors, network overload, and intentional attacks. 7. Design Patterns: Utilize design patterns (like Factory, Singleton, Strategy, Adapter, Proxy) to solve common problems and promote reusable and maintainable code. 8. Abstraction: Aim for moderate to high levels of abstraction, which can help simplify code, enhance scalability, and improve maintainability. 9. Automated Testing: Implement automated testing to ensure code reliability and reduce costs while speeding up the development process. 10. Low Complexity: Strive for low complexity in your code to make it easier to understand, test, and maintain, promoting faster development cycles.