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What are mixins in Python? How can they be used for code reuse?

Mixins in Python enable code reuse across class hierarchies, offering flexibility and modularity over traditional inheritance. They help avoid deep inheritance and the diamond problem.Character count: 159

Mar 26, 2025 pm 01:21 PM

Explain the concept of "duck typing" in Python. What are its advantages and disadvantages?

The article discusses duck typing in Python, which allows objects to be used based on their behavior rather than their type. It examines the advantages like flexibility and disadvantages like runtime errors, and provides best practices for effective

Mar 26, 2025 pm 01:20 PM

What are abstract base classes (ABCs) in Python? How do they enforce interfaces?

Article discusses abstract base classes (ABCs) in Python, their role in enforcing interfaces, and benefits like code reusability and type checking.

Mar 26, 2025 pm 01:19 PM

Explain the difference between shallow copy and deep copy in Python. How can you create deep copies?

The article discusses shallow and deep copies in Python, focusing on their differences and usage scenarios. Shallow copies reference nested objects, while deep copies recursively duplicate them. Use copy.deepcopy() for deep copies.

Mar 26, 2025 pm 01:18 PM

How does Python's property decorator work? How can you use it to create managed attributes?

The article discusses Python's property decorator, which allows methods to be accessed like attributes, enabling managed attributes with getter, setter, and deleter functions. It highlights benefits like encapsulation, validation, and improved code r

Mar 26, 2025 pm 01:16 PM

Explain the use of functools.lru_cache. How does it work, and when is it beneficial?

The article discusses functools.lru_cache, a Python decorator for memoization using an LRU cache. It explains its operation, benefits, performance improvements, argument handling, limitations, and ideal application scenarios.Main issue: Understanding

Mar 26, 2025 pm 01:15 PM

What are Python's slots? What are their benefits and drawbacks?

Python's slots optimize memory and speed by pre-allocating attribute storage. Benefits include reduced memory use and faster access, but drawbacks involve limited flexibility and added complexity. Best for large instance counts or fixed attributes.[1

Mar 26, 2025 pm 01:14 PM

Describe how Python handles memory management. How can you use tools like memory_profiler to diagnose memory issues?

Python's memory management relies on garbage collection, featuring reference counting, cycle detection, and generational collection. memory_profiler aids in diagnosing memory issues by providing line-by-line usage, snapshots, and detailed reports.

Mar 26, 2025 pm 01:13 PM

What is the Global Interpreter Lock (GIL) in Python? What are its limitations, and how can you work around them for CPU-bound tasks?

The article discusses the Global Interpreter Lock (GIL) in Python, its limitations for CPU-bound tasks, and workarounds like multiprocessing and alternative implementations to bypass the GIL.

Mar 26, 2025 pm 01:10 PM

Explain the difference between mutable and immutable data types in Python. Give examples of each.

Abstract: The article discusses mutable and immutable data types in Python, highlighting their differences and use cases. Key points include memory management, benefits of immutability, and scenarios favoring mutable types.

Mar 26, 2025 pm 01:08 PM

What are generators and iterators in Python? How do they differ, and when would you use each?

Article discusses generators and iterators in Python, their differences, and usage scenarios. Generators are favored for memory efficiency and lazy evaluation, while iterators suit custom iteration needs.

Mar 26, 2025 pm 01:07 PM

Explain the concept of method resolution order (MRO) in Python. How does it work with multiple inheritance?

The article discusses Python's Method Resolution Order (MRO) in multiple inheritance, focusing on the C3 linearization algorithm to solve the diamond problem. It explains how MRO ensures consistent method resolution and demonstrates the use of super(

Mar 26, 2025 pm 01:05 PM

Explain the purpose and usage of context managers (the with statement). How do you create a custom context manager?

Abstract: The article discusses context managers in Python, focusing on their purpose in resource management and how to create custom ones. It highlights benefits like automatic cleanup and improved code readability.(159 characters)

Mar 26, 2025 pm 01:04 PM

What are decorators in Python? Give an example of a decorator you might use in a real-world scenario (e.g., caching, logging).

Article discusses Python decorators, their uses like caching, and benefits for code efficiency. It also covers common pitfalls and how decorators add functionality without modifying source code.Character count: 159

Mar 26, 2025 pm 01:03 PM

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What are mixins in Python? How can they be used for code reuse?

Explain the concept of "duck typing" in Python. What are its advantages and disadvantages?

What are abstract base classes (ABCs) in Python? How do they enforce interfaces?

Explain the difference between shallow copy and deep copy in Python. How can you create deep copies?

How does Python's property decorator work? How can you use it to create managed attributes?

Explain the use of functools.lru_cache. How does it work, and when is it beneficial?

What are Python's slots? What are their benefits and drawbacks?

Describe how Python handles memory management. How can you use tools like memory_profiler to diagnose memory issues?

What is the Global Interpreter Lock (GIL) in Python? What are its limitations, and how can you work around them for CPU-bound tasks?

Explain the difference between mutable and immutable data types in Python. Give examples of each.

What are generators and iterators in Python? How do they differ, and when would you use each?

Explain the concept of method resolution order (MRO) in Python. How does it work with multiple inheritance?

Explain the purpose and usage of context managers (the with statement). How do you create a custom context manager?

What are decorators in Python? Give an example of a decorator you might use in a real-world scenario (e.g., caching, logging).

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