Python technical interview questions and answers are widely asked in software development, data science, automation, and machine learning roles. Python is one of the most popular languages due to its simplicity and power, so companies expect candidates to understand core topics like variables, loops, functions, OOP, modules, file handling, exceptions, and libraries. Companies like TCS, Infosys, Cognizant, Capgemini, and Wipro frequently include Python questions in interviews and online tests. This guide provides clear explanations for the most important Python questions, making it useful for freshers preparing for placement interviews as well as experienced developers. You can also download Python interview PDFs and practice coding exercises to strengthen your preparation.
Python developers can enhance their capabilities by exploring data science applications and machine learning implementations
Showing 10 of 69 questions
31. Discuss how the Global Interpreter Lock (GIL) affects multi-threading in Python
The GIL ensures that only one thread executes Python bytecode at a time, which can lead to performance limitations in CPU-bound multi-threaded programs, encouraging the use of multiprocessing instead.
32. Detail how to implement a custom iterator in Python
To create a custom iterator, define a class with __iter__() returning self and __next__() providing the next value, raising StopIteration when done.
33. Describe Python coroutines and their differences from functions
Coroutines are defined with async def, allowing them to pause execution and yield control back to the event loop, facilitating asynchronous programming.
34. Discuss the principles and implementation of context managers
Context managers are implemented using __enter__ and __exit__ methods, utilizing the with statement to ensure resource management and cleanup after use.
35. What is the role of descriptors in Python
Descriptors control attribute access by defining methods __get__, __set__, and __delete__, enabling property-like behavior in class attributes.
36. Explain the differences between *args and **kwargs in function definitions
*args allows for variable-length non-keyword arguments, while **kwargs allows for variable-length keyword arguments, providing flexibility in function calls.
37. Discuss how Python's functools module can optimize function calls
The functools module includes lru_cache to cache results of expensive function calls, improving performance for repeated calls with the same attributes.
38. Outline the advantages and drawbacks of using Python's asyncio library
asyncio allows for writing concurrent code using async/await, improving I/O-bound task performance, but adds complexity and is not suitable for CPU-bound tasks.
39. Describe how to implement a singleton pattern in Python
A singleton can be implemented by overriding __new__ in a class, ensuring that only one instance is created, thus controlling the object’s instantiation.
40. Explain the difference between deep copy and shallow copy in Python
A shallow copy creates a new object but inserts references into it to the objects found in the original. A deep copy creates a new object and recursively adds copies of nested objects found in the original, making it completely independent of the original.