Potential employers may ask appropriate advanced Python interview questions to find the right Python developer for a team. However, have you ever tried to exactly pin the interview questions that could be asked during your interviews? The best advanced Python interview questions for your technical hiring procedures are provided here. You can use them as it is or as a source of ideas for your own queries.
Advanced Python Interview Questions in 2022
Understanding Python First
Guido van Rossum created and launched Python on February 20th, 1991. It allows the incorporation of dynamic semantics. It is a free and open-source programming language with clear and straightforward syntax. Python is simple for developers to learn and comprehend because of all these factors. Python is mostly used for general-purpose programming and supports object-based programming as well.
Python’s popularity is skyrocketing due to its ease of use and ability to accomplish various features with fewer lines of code. Due to its capability to handle strong calculations through sophisticated libraries, it is also utilized in artificial intelligence, machine learning, web scraping, web building, and other disciplines. Python developers are, therefore, in great demand internationally.
Here is a list of some advanced Python interview questions:
1. How to Access a Module Written in Python from C?
Any Python developer must be familiar with how Python functions. However, there is no purpose in attempting to acquire an exact match. Instead, keep an eye out for first-hand accounts of candidates’ use of particular features.
The following is how to obtain a pointer to the module object:
module = PyImport_ImportModule("");
It’s key to note that it doesn’t enter the module into any namespace. It only ensures it has been initialized and is saved in sys modules.
2. How to Get the Res_set from the Train_set and the Test_set from Below?
>>train_set=np.array([1, 2, 3]) >>test_set=np.array([[0, 1, 2], [1, 2, 3]) Res_set [[1, 2, 3], [0, 1, 2], [1, 2, 3]]
Select the right option:
- res_set = train_set.append(test_set)
- res_set = np.concatenate([train_set, test_set]))
- resulting_set = np.vstack([train_set, test_set])
- None of these
resulting_set = np.vstack([train_set, test_set])
We want vertical stacking in this situation, although choices a and b would both do horizontal stacking. As a result, statement option c is correct.
3. In Python, How Do You Reverse A List? When Is It Beneficial?
Python’s reverse() and reversed() functions can be used to reverse a list. They reverse the list around but don’t make a new one.
The technique, for instance, can be applied to sort a list. A list of names in reverse alphabetical order would need to be reversed to be organized alphabetically, which can be achieved through the reverse functionality.
4. What Is the Output of The Following Code:
list = [‘alfa’, ‘bravo’, ‘charlie’, ‘delta’. ‘echo’] print list[10:]
You can learn more about applicants’ working methods by asking them to review sample code. The goal is to observe applicants’ reasoning, not to obtain faultless answers, as most questions can be answered by searching on Google. But keep in mind that “brainteasers” and “gotcha” questions mostly serve to waste everyone’s time.
There won’t be an IndexError; the output will be . The 10th object in the list that the code attempts to access does not exist, so it will output .
5. When Using Pandas to Read A File, You See The “Temp.Csv” Error. Which of The Following Can Fix It?
Traceback (most recent call last): File "<input>", line 1, in<module> UnicodeEncodeError:
‘ascii’ codec can’t encode a character.
Select the Right Answer:
- read_csv(“temp.csv”, compression=’gzip’)
- read_csv(“temp.csv”, dialect=’str’)
- read_csv(“temp.csv”, encoding=’utf-8′)
- None of these
pd.read_csv(“temp.csv”, encoding=’utf-8′) can correct it.
The discrepancy between utf-8 coding and Unicode is the cause of the problem.
6. Can You Use Continue and Break Together?
A follow-up query following the initial query, you can combine the words break and continue. While “continue” will instantly start the next iteration of the loop, “break” will end the current loop’s execution.
7. Explain the Difference Between Generators and Iterators.
Before returning the first result, an iterator has the entire sequence stored in memory. Iterators use the return key. A generator computes each result as it is required. An unknown outcome follows. Yield is what a generator uses.
In summary, you would utilize a generator to handle streams or when memory usage is crucial. Iterators are not generators; they are only iterators.
8. Is Python Call by Reference or Call by Value? How Are Arguments Passed by Value or By Reference?
In Python, everything is an object, and every variable has a reference to an object. You cannot alter the value of the references because they are set according to the functions. However, if an object is malleable, you can alter it.
9. How Would You Reset a Dataframe’s Index to a Specific List? Select the Appropriate Option.
- None of these
10. Explain What is GIL in Python?
Regarding memory management, Python does not adhere to thread safety. Therefore, the GIL is a bottleneck if you’re running several threads because it only permits one thread at the moment to access memory. You’re alright if everything takes place in a single thread. The GIL, however, pauses all other threads when one thread accesses memory in a multi-threaded environment.
Python scripts with several threads have difficulty with this. Python does not have a problem with it because each process has its own memory. See if your candidate discusses “bottleneck,” “multi-threading,” and “memory management.” Multi-processing, C extensions, or other Python implementations like IronPython or Cython are possible fixes.
11. What Is Mutable Vs. Immutable Types?
An immutable type cannot be altered. Examples include strings, floats, integers, and tuples. A changeable type is also adaptable—dictionaries, sets, classes, and lists.
In the follow-up, you want the applicant to clarify how immutable types are liable to change, whereas immutable types point to memory locations rather than real values.
12. How Can You Copy Objects in Python?
The function used to copy objects in Python are copy.copy for shallow copy and copy.deepcopy() for a deep copy.
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While you may be aware of some of the advanced python interview questions, it’s also important to understand that it takes much more than this to prepare for a technical interview.
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