Are you a fresher techie who has just completed a course in Python? Are you looking for a job as a software engineer or a programmer? Are you preparing for an interview to clinch the job? If your answer is yes to any of the above questions (or all of them), you have come to the right place!
Discover some of the most important interview questions about Python (with their answers) you should be prepared to crack the interview in the first attempt.
Q 1. What is Python – a programming language or a scripting language?
Ans. The primary distinction between programming and scripting languages is that they do not require compilation and instead have their code directly interpreted. In programming languages, however, the code is compiled, transformed into minimal byte code, and finally executed. Therefore, Python is classified as a scripting language under the description of programming and scripting language, although in general, Python is classified as an advanced-level programming language.
Q 2. Is there any difference between .py and .pyc files? Explain.
Ans. Yes, there is a difference between .py files and .pyc files. A.py file contains a program’s source code. In contrast, the .pyc file includes your program’s bytecode. After compiling the.py file, we obtain bytecode (source code). Not all of the files you generate .pyc files. It is only used for the files you import. The Python interpreter looks for compiled files before running a Python program. The virtual computer runs the file if it is present. If no.py files are discovered, it looks for them. If it is discovered, it is compiled into a .pyc file and then executed by the Python virtual computer. Having a .pyc file saves you time during compilation.
Q 3. Which is better – NumPy or Python Lists?
Ans. Python’s list data format is highly efficient and can execute various operations. However, they have severe constraints regarding vectorized operations such as element-wise addition and multiplication. Python lists additionally need information about the type of each element, which adds cost because type dispatching code is executed each time an operation is done on any element. This is where NumPy arrays enter the equation, as they manage all Python lists’ restrictions.
Furthermore, when the length of the NumPy arrays grows, NumPy becomes roughly 30x quicker than the Python List. Because of their homogeneous nature, NumPy arrays are tightly packed in memory. This guarantees that memory is freed up as quickly as possible. Hence, NumPy is better than Python Lists.
These three are the most repeatedly asked questions to a fresh techie. However, here’s a list of some more questions you might want to be prepared for:
- What do you mean by a dynamically typed language?
- What is PEP 8? Discuss its significance
- What is slicing? List down its steps.
- Explain the difference between break, continue and pass in Python.
- Differentiate between modules and package
- Differentiate between compiled and interpreted language
- What is PYTHONPATH?
- What do you understand by Namespaces?
- What is scope resolution in Python?
Preparing for an interview for Python can be difficult. However, with constant and consistent practice, you will be able to crack it in no time. Remember to practice the codes on a sheet of paper multiple times so that you are well versed with each one. Don’t get nervous, and you will be just fine. Good luck with the interview!
