Questions for Python Interview – Guide To Crack Interview

1. Latest Questions for Python Interview

In our last Python guide, we discussed important Questions for Python Interview part 5. Today, we will move towards some practical and technical Questions for Python Interview. Both freshers and experienced can refer these Questions for Python Interview. We recommend you to check all the parts of Python Interview Questions, surely you will crack the interview in just one go.
So, let’s start exploring Questions for Python Interview.
Let’s first revise the Python Tutorial.

Questions for Python Interview - Guide To Crack Interview

Questions for Python Interview – Guide To Crack Interview

2. Tricky Questions for Python Interview

Following are the Practical Questions for Python Interview, which will help you to boost your confidence. Let’s discuss these Questions for Python Interview in detail:
Q.1. Are these statements optimal? If not, optimize them.
word=’word’
print(word.__len__())
Ans. No, these are not optimal. Let’s check the manual for this.

>>> help(str.__len__)

Help on wrapper_descriptor:
__len__(self, /)
Return len(self).
__len__ is a wrapper descriptor which in turn makes a call to len(). So why not skip the work and do just that instead?
The optimal solution:

>>> word='word'
>>> len(word)

4
Q.2. Have you heard of the yield keyword in Python?
Ans. Yes, I have. This keyword bears the ability to turn any function into a generator. Much like the standard return keyword, but returns a generator object. It is also true that one function may observe multiple yields.

>>> def odds(n):
      odd=[i for i in range(n+1) if i%2!=0]
      for i in odd:
               yield i
>>> for i in odds(8):
      print(i)

1
3
5
7
Q.3. How will you print the contents of a file?
Ans.

>>> try:
       with open('tabs.txt','r') as f:
              print(f.read())
except IOError:
       print("File not found")

Q.4. How will you convert a list into a string?
Ans. We will use the join() method for this.

>>> nums=['one','two','three','four','five','six','seven']
>>> s=' '.join(nums)
>>> s

‘one two three four five six seven’
Let’s revise the Python string in detail
Q.5. What will the following code output?
>>> a=1
>>> a,b=a+1,a+1
>>> a,b
Ans. The output is (2, 2). This code increments the value of a by 1 and assigns it to both a and b. This is because this is a simultaneous declaration. The following code gives us the same:

>>> a=1
>>> b,a=a+1,a+1
>>> a,b

(2, 2)
Have a look at Python Built-in Functions
Q.6. Explain different ways to create an empty NumPy array in Python.
Ans. We’ll talk about two methods to create NumPy array-

  1. First method-
>>> import numpy
>>> numpy.array([])

array([], dtype=float64)

  1. Second method-
>>> numpy.empty(shape=(0,0))

array([], shape=(0, 0), dtype=float64)
Q.7. How will you remove a duplicate element from a list?
Ans. We can turn it into a set to do that.

>>> list=[1,2,1,3,4,2]
>>> set(list)

{1, 2, 3, 4}
Let’s revise the Python List
Q.8. How many types of objects does Python support?
Ans. Objects in Python are mutable and immutable. Let’s talk about these.

  • Immutable objects- Those which do not let us modify their contents. Examples of these will be tuples, booleans, strings, integers, floats, and complexes. Iterations on such objects are faster.
>>> tuple=(1,2,4)
>>> tuple

(1, 2, 4)

>>> 2+4j

(2+4j)

  • Mutable objects- Those that let you modify their contents. Examples of these are lists, sets, and dicts. Iterations on such objects are slower.
>>> [2,4,9]

[2, 4, 9]

>>> dict1={1:1,2:2}
>>> dict1

{1: 1, 2: 2}
While two equal immutable objects’ reference variables share the same address, it is possible to create two mutable objects with the same content.
Q.9. What is a control flow statement?
Ans. A Python program usually starts to execute from the first line. From there, it moves through each statement just once and as soon as it’s done with the last statement, it transactions the program. However, sometimes, we may want to take a more twisted path through the code. Control flow statements let us disturb the normal execution flow of a program and bend it to our will.
Q.10. Create a new list to convert the following list of number strings to a list of numbers.
nums=[‘22’,’68’,’110’,’89’,’31’,’12’]
Ans. We will use the int() function with a list comprehension to convert these strings into integers and put them in a list.

>>> [int(i) for i in nums]

[22, 68, 110, 89, 31, 12]
Questions for Python Interview for freshers – Q. 2,3,6,7,8,9
Questions for Python Interview for experienced – Q. 1,4,5,10
Q.11. What is the MRO in Python?
Ans. MRO stands for Method Resolution Order. Talking of multiple inheritances, whenever we search for an attribute in a class, Python first searches in the current class. If found, its search is satiated. If not, it moves to the parent class. It follows an approach that is left-to-right and depth-first. It goes Child, Mother, Father, Object.
We can call this order a linearization of the class Child; the set of rules applied are the Method Resolution Order (MRO). We can borrow the __mro__ attribute or the mro() method to get this.
Q.12. Are methods and constructors the same thing?
Ans. No, there are subtle but considerable differences-

  • We must name a constructor in the name of the class; a method name can be anything.
  • Whenever we create an object, it executes a constructor; whenever we call a method, it executes a method.
  • For one object, a constructor executes only once; a method can execute any number of times for one object.
  • We use constructors to define and initialize non-static variables; we use methods to represent business logic to perform operations.

Q.13. Can you explain the life cycle of a thread?
Let’s revise Python Multithreading

  • To create a thread, we create a class that we make override the run method of the thread class. Then, we instantiate it.
  • A thread that we just created is in the new state. When we make a call to start() on it, it forwards the threads for scheduling. These are in the ready state.
  • When execution begins, the thread is in the running state.
  • Calls to methods like sleep() and join() make a thread wait. Such a thread is in the waiting/blocked state.
  • When a thread is done waiting or executing, other waiting threads are sent for scheduling.
  • A running thread that is done executing terminates and is in the dead state.
Questions for Python Interview

Questions for Python Interview – Life Cycle of a Thread

Q.14. Below, we give you code to remove numbers smaller than 5 from the list nums. However, it does not work as expected. Can you point out the bug for us?
>>> nums=[1,2,5,10,3,100,9,24]
>>> for i in nums:
 if i<5:
 nums.remove(i)
>>> nums
[2, 5, 10, 100, 9, 24]
Ans. This code checks for each element in nums- is it smaller than 5? If it is, it removes that element. In the first iteration, 1 indeed is smaller than 5. So it removes that from this list. But this disturbs the indices. Hence, it checks the element 5, but not the element 2. For this situation, we have three workarounds:

  1. Create an empty array and append to that-
>>> nums=[1,2,5,10,3,100,9,24]
>>> newnums=[]
>>> for i in nums:
        if i>=5:
               newnums.append(i)
>>> newnums

[5, 10, 100, 9, 24]

  1. Using a list comprehension-
>>> nums=[1,2,5,10,3,100,9,24]
>>> newnums=[i for i in nums if i>=5]
>>> newnums

[5, 10, 100, 9, 24]

  1. Using the filter() function-
>>> nums=[1,2,5,10,3,100,9,24]
>>> newnums=list(filter(lambda x:x>=5, nums))
>>> newnums

[5, 10, 100, 9, 24]
Q.15. What is the best code you can write to swap two numbers?
Ans. I can perform the swapping in one statement.

>>> a,b=b,a

Here’s the entire code, though-

>>> a,b=2,3
>>> a,b=b,a
>>> a,b

(3, 2)
Q.16. Explain the problem with the following piece of code-
>>> def func(n=[]):
 #playing around
 pass
>>> func([1,2,3])
>>> func()
>>> n
Ans. The request for n raises a NameError. This is since n is a variable local to func and we cannot access it elsewhere. It is also true that Python only evaluates default parameter values once; every invocation shares the default value. If one invocation modifies it, that is what another gets. This means you should only ever use primitives, strings, and tuples as default parameters, not mutable objects.
Best Python Interview Preparation
Q.17. Can you remove the whitespaces from the string “aaa bbb ccc ddd eee”?
Ans. I can think of two ways to do this.

  1. Using join-
>>> s='aaa bbb ccc ddd eee'
>>> s1=''.join(s.split())
>>> s1

‘aaabbbcccdddeee’

  1. Using a list comprehension-
>>> s='aaa bbb ccc ddd eee'
>>> s1=str(''.join(([i for i in s if i!=' '])))
>>> s1

‘aaabbbcccdddeee’
Q.18. Given the first and last names of all employees in your firm, what data type will you use to store it?
Ans. I can use a dictionary to store that. It would be something like this-
{‘first_name’:’Ayushi’,’second_name’:’Sharma’}
Q.19. What do you see below?
s = a + ‘[‘ + b + ‘:’ + c + ‘]’
Ans. This is string concatenation. If a, b, and c are strings themselves, then it works fine and concatenates the strings around the strings ‘[‘, ‘:’, and ‘]’ as mentioned. If even one of these isn’t a string, this raises a TypeError.
Q.20. If a function does not have a return statement, is it valid?
Ans. Very conveniently. A function that doesn’t return anything returns a None object. Not necessarily does the return keyword mark the end of a function; it merely ends it when present in the function. Normally, a block of code marks a function and where it ends, the function body ends.
Questions for Python Interview for freshers – Q. 11,12,13,15,18,20
Questions for Python Interview for experienced – Q. 14,16,17,19
Q.21. What good is recursion?
Ans. With recursion, we observe the following:

  • Need to put in less efforts.
  • Smaller code than that by loops.
  • Easier-to-understand code.

Q.22. So does recursion cause any trouble?
Ans. Sure does:

  • Needs more function calls.
  • Each function call stores a state variable to the program stack- consumes memory, can cause memory overflow.
  • Calling a function consumes time.

Q.23. How do you get the current working directory using Python?
Ans. Working on software with Python, you may need to read and write files from various directories. To find out which directory we’re presently working under, we can borrow the getcwd() method from the os module.

>>> import os
>>> os.getcwd()

‘C:\\Users\\Ayushi\\AppData\\Local\\Programs\\Python\\Python37-32’
Q.24. What is tuple unpacking?
Ans. Suppose we have a tuple nums=(1,2,3). We can unpack its values into the variables a, b, and c. Here’s how:
Have a look at Python tuple

>>> nums=(1,2,3)
>>> a,b,c=nums
>>> a

1

>>> b

2

>>> c

3
Q.25. What does the following code give us?
>>> b=(1)
Ans. Not a tuple. This gives us a plain integer.

>>> type(b)

<class ‘int’>
To let it be a tuple, we can declare so explicitly with a comma after 1:

>>> b=(1,)
>>> type(b)

<class ‘tuple’>
Q.26. What is the iterator protocol?
Ans. The iterator protocol for Python declares that we must make use of two functions to build an iterator- iter() and next().

  • iter()- To create an iterator
  • next()- To iterate to the next element
>>> a=iter([2,4,6,8,10])
>>> next(a)

2

>>> next(a)

4

>>> next(a)

6

>>> next(a)

8

>>> next(a)

10

>>> next(a)

Traceback (most recent call last):
 File “<pyshell#31>”, line 1, in <module>
next(a)
StopIteration
Q.27. Why do we need to overload operators?
Ans. To compare two objects, we can overload operators in Python. We understand 3>2. But what is orange>apple? Let’s compare apples and oranges now.

>>> class fruit:
       def __init__(self,type,size):
               self.type='fruit'
               self.type=type
               self.size=size
       def __gt__(self,other):
               if self.size>other.size:
                        return True
               return False
>>> orange=fruit('orange',7)
>>> apple=fruit('apple',8)
>>> apple>orange

True

>>> orange>apple

False
Q.28. What is the enumerate() function in Python?
Ans. enumerate() iterates through a sequence and extracts the index position and its corresponding value too.
Let’s take an example.

>>> for i,v in enumerate(['Python','C++','Scala']):
         print(i,v)

0 Python
1 C++
2 Scala
Q.29. How do we make forms in Python?
Ans. We use the cgi module for this; we borrow the FieldStorage class from it. It has the following attributes:

  • form.name: Name of field.
  • form.filename: Client-side filename for FTP transactions.
  • form.value: Value of field as string.
  • form.file: File object from which to read data.
  • form.type: Content type.
  • form.type_options: Options of ‘content-type’ line of HTTP request, returned as dictionary.
  • form.disposition: The field ‘content-disposition’.
  • form.disposition_options: Options for ‘content-disposition’.
  • form.headers: All HTTP headers returned as dictionary.

Q.30. How will you create the following pattern using Python?
*
**
***
****
*****
Ans. We will use two for-loops for this.

>>> for i in range(1,6):
        for j in range(1,i+1):
                  print('*',end='')
        print()

Questions for Python Interview for freshers – Q. 21,22,23,27,28,29
Questions for Python Interview for experienced – Q. 24,25,26,30
Get Python Developer’s Job with the Best Practices
So, this was all the Questions for Python Interview. Hope you like our explanation.

3. Conclusion – Python Interview Questions

So, you have completed the last part of Python Interview Questions. These Questions for Python Interview proves beneficial for both Python fresher and experienced. Do you have Questions for Python Interview to add? Hey, leave it in the comments below.
See also – 
Questions for Python Interview – Part 4
Questions for Python Interview – Part 3
For reference

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