Python’s adaptable features and ease of use have made it one of the most popular programming languages in the world today. It has a broad range of applications in domains like data research, backend programming, and machine learning. If you’re preparing for a Python developer interview, you can expect questions ranging from basic syntax and data types to advanced concepts. But with constant revision and practice, you can ace an Advanced Python interview with ease.
In the blog below, we have prepared a set of advanced Python interview questions along with their answers to help candidates prepare for their interview with confidence.
Top 10 Python Interview Questions You Must Prepare For
1. In the context of Python, what is the Global Interpreter Lock (GIL)?
Answer: The Global Interpreter Lock (GIL) is a mute function feature that is primarily responsible for protecting any access to Python objects. It also prevents various threads from executing Python bytecode simultaneously. This also explains how Python threads are not completely parallel on multi-core processors. The GIL limits any true multi-threaded execution, but at the same time also makes memory management easier. For tasks that are CPU-bound, multiprocessing is preferred over threading in Python.
2. Define Python decorators, and mention how they are useful.
Answer: To modify the behaviour of other functions or classes that do not involve changing of their source code, Decorator functions are used. These are very commonly used for tasks like caching or to measure the execution time. These functions follow the major principle of higher-order functions, which makes code more reusable.
3. Can you explain Python’s memory management system?
Answer: The Python Memory Manager handles the memory allocation, and Python uses a private store heap to keep objects. The Python Memory manager also has a garbage collector that is built in. This collector uses reference counting and generational garbage collection to reclaim all unused memory. Usually, memory management is not done manually by the developers, but there are certain tools, such as the gc module, that help in debugging and precise monitoring of memory usage.
4. State the difference between a shallow copy and a deep copy.
Answer:
- Shallow Copy- A shallow copy references the same elements as the original but also creates a new object. Any changes are shown in both copies.
- Deep Copy- In a Deep copy, a new object is created, and it repeatedly copies all the previous copies, making sure that there is complete independence between the copies.
5. How are multi-threading and multiprocessing handled differently by Python?
Answer:
- Multi-threading– This feature is limited in Python due to GIL. Since GIL only allows one thread execution at a time, it is very useful for I/O bound operations such as network requests or file handling.
- Multiprocessing– It is suitable for CPU-bound operations as it allows true parallelism. It creates separate processes with independent memory space.
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6. What are Python metaclasses?
Answer: A Python metaclass is defined as a class of classes. Classes define behavior, and Metaclasses define class behavior. Metaclasses enable various customizations of class creation, introduce new design rules, or facilitate automatic modification methods. By default, the Python classes are type Metaclass.
7. How does Python handle exceptions internally?
Answer: Whenever an exception occurs, Python creates an exception object and searches for a similar except block. When the block is found, it is executed; if not, Python ends with an error message. Python follows an array of exception classes that allow developers to hunt for a specific or general exception.
8. Explain Python’s garbage collection process.
Answer: To track objects in Python, reference counting is used, so when the reference count drops to 0, it gets deallocated. However, repeated reference to the country or cycles can prevent cleaning. To solve it, Python also uses a cyclic garbage collector that identifies such cycles and reclaims them.
9. Define Python namespaces, and why are they important?
Answer: Defined as a roadmap between objects and names, Python features various namespaces, for example, local, global, and built-in. These prevent naming errors by making sure that each name points to the correct object.
10. How does Python implement dynamic typing?
Answer: Python implements dynamic typing by ensuring that variable types are committed at runtime, and not during compilation time. The type of any variable can change during its execution. Though this flexibility increases productivity, it requires careful error handling.
Final Thoughts
The Python interview questions are a test to judge the skills and knowledge of candidates in the Python language. Various topics such as GIL, memory management, etc, are very often discussed in the technical interviews. Constantly revising such concepts is beneficial to polish your knowledge, and with this, a candidate can absolutely stand out and get hired.
All the best!