Add comprehensive C++/Python architect interview preparation guide

[Copilot]

This PR adds a comprehensive interview preparation guide at /docs/interview.md covering essential concepts for C++ and Python architect roles. The guide is designed to help developers prepare for technical interviews with practical examples and detailed explanations.

What's Included

The 1,252-line guide covers eight major areas:

🧠 Core Language Concepts

• C++ fundamentals: Memory management (RAII, smart pointers), modern C++ features (C++11/14/17/20), concurrency and threading
• Python fundamentals: Garbage collection, advanced features (metaclasses, decorators, async/await), type system and hints

🏗️ Design Patterns

Complete implementations of key patterns in both languages:

• Creational: Singleton, Factory patterns with thread-safe C++ and Python examples
• Behavioral: Observer, Strategy patterns with practical use cases
• Structural: Adapter, Decorator pattern explanations

🚀 System Design

Enterprise-level architecture concepts:

• Scalability principles (horizontal vs vertical scaling, load balancing)
• Database design (SQL vs NoSQL, sharding strategies)
• Microservices architecture (benefits, challenges, service discovery)
• Caching strategies (cache-aside, write-through, write-behind)

⚡ Performance Optimization

Language-specific optimization techniques:

• C++: Memory layout optimization, algorithm selection, compiler hints, SFINAE examples
• Python: Profiling with cProfile, memoization, NumPy vectorization, Cython integration

💡 Interview Questions & Solutions

Real interview questions with detailed explanations:

• C++ questions on RAII, new/delete vs malloc/free, const/constexpr differences
• Python questions on GIL implications, decorators, metaclasses with working code examples

📝 Advanced Code Examples

Production-ready implementations:

• C++ template metaprogramming with SFINAE and variadic templates
• Thread-safe queue implementation with condition variables
• Python async web scraper with aiohttp and semaphores
• Advanced data processing pipeline with generators

🎯 Architecture Best Practices

Industry standards and principles:

• SOLID principles with before/after code examples
• Project structure recommendations for both languages
• Error handling strategies (std::expected in C++, Result types in Python)
• Exception safety guarantees

⚠️ Common Pitfalls & Solutions

Critical mistakes and how to avoid them:

• C++: Memory leaks, iterator invalidation, dangling references with fixes
• Python: Mutable default arguments, late binding closures, circular imports, class vs instance variables

Why This Matters

This guide bridges the gap between theoretical knowledge and practical interview performance. Each concept includes:

• Clear explanations suitable for interview discussion
• Working code examples that can be written on a whiteboard or coding platform
• Real-world context showing when and why to use each technique
• Common variations and follow-up questions interviewers might ask

The content follows the existing repository structure and documentation style, providing a valuable resource for the C++/Python architect community.

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