Python & Django
Interview Guide.
Python has evolved from a simple scripting language into a high-performance architectural powerhouse. With the advent of PEP 703 and Django 5.x, the landscape of scalable web development has shifted. This guide covers the deep technical internals required for senior engineering roles.
1Core Python Internals
Explain the Global Interpreter Lock (GIL) and the impact of PEP 703.
The GIL prevents multiple native threads from executing Python bytecodes at once. PEP 703 (Java-style 'No-GIL') allows for true parallel execution in multi-core systems, making Python a much stronger contender for high-performance computing without relying on multiprocessing.
What are Decorators and how are they implemented under the hood?
Decorators are higher-order functions that take a function as an argument and return a modified version of it. Under the hood, they leverage Python's first-class function objects and closures to wrap functionality without changing the original source code.
Deep Dive: Generators vs. Iterators.
All generators are iterators, but not all iterators are generators. Generators use the 'yield' keyword to produce values lazily, which is significantly more memory-efficient than creating a full list in memory for large datasets.
2Asynchronous Programming (AsyncIO)
How does the AsyncIO Event Loop manage concurrency?
Unlike threading, AsyncIO uses 'Cooperative Multitasking'. A single thread switches between tasks when they hit an 'await' point (like I/O wait). This avoids the overhead of context switching and locking required in multi-threaded environments.
Async vs. Multiprocessing: When to use which?
Use AsyncIO for I/O-bound tasks (web scraping, database queries) where you are waiting on external sources. Use Multiprocessing for CPU-bound tasks (data processing, encryption) to leverage multiple CPU cores simultaneously.
3Django Architectural Mastery
Explain the execution order of Django Middleware.
Middleware follows a 'Onion' structure. On the request phase, it executes from top to bottom. On the response phase (after the view), it executes in reverse order from bottom to top.
ORM Optimization: 'select_related' vs 'prefetch_related'.
Use 'select_related' for foreign keys (one-to-one/many-to-one) to do a SQL JOIN in a single query. Use 'prefetch_related' for many-to-many or many-to-one reverse lookups, which performs separate queries and joins them in Python.
What is the N+1 problem in Django and how do you solve it?
The N+1 problem occurs when you fetch a list of objects and then perform a separate query for each object's related data. It is solved by using 'select_related' or 'prefetch_related' to fetch all required data in as few queries as possible.
4Modern Features & POO (OOP)
Explain Method Resolution Order (MRO) and C3 Linearization.
MRO is the order in which Python looks for a method in a class hierarchy. Python uses the C3 Linearization algorithm to ensure that 'super()' calls are predictable and avoid the 'Diamond Problem' in multiple inheritance.
What are 'Dunder' (Magic) methods?
Dunder methods (e.g., __init__, __str__, __call__) allow you to overload operators and define built-in behaviors for your objects. For example, __call__ makes an instance of a class callable like a function.
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