Python Interview Questions Preparation Course

Q.    How will you improve the performance of a program in Python?

There are many ways to improve the performance of a Python program. Some of these are as follows:

1. Data Structure: We have to select the right data structure for our purpose in a Python program.
2. Standard Library: Wherever possible, we should use methods from standard library. Methods implemented in standard library have much better performance than user implementation.
3. Abstraction: At times, a lot of abstraction and indirection can cause slow performance of a program. We should remove the redundant abstraction in code.
4. Algorithm: Use of right algorithm can make a big difference in a program. We have to find and select the suitable algorithm to solve our problem with high performance.

Q.    What are the benefits of using Python?

Python is so much powerful that even Google uses it. Some of the benefits of using Python are as follows:

1. Efficient: Python is very efficient in memory management. For a large data set like Big Data, it is much easier to program in Python.
2. Faster: Though Python code is interpreted, still Python has very fast performance.
3. Wide usage: Python is widely used among different organizations for different projects. Due to this wide usage, there are thousands of add-ons available for use with Python.
4. Easy to learn: Python is quite easy to learn. This is the biggest benefit of using Python. Complex tasks can be very easily implemented in Python.

Q.    How will you specify source code encoding in a Python source file?

By default, every source code file in Python is in UTF-8 encoding. But we can also specify our own encoding for source files. This can be done by adding following line after #! line in the source file.

# -*- coding: encoding -*-

In the above line we can replace encoding with the encoding that we want to use.

Q.   What is the use of PEP 8 in Python?

PEP 8 is a style guide for Python code. This document provides the coding conventions for writing code in Python. Coding conventions are about indentation, formatting, tabs, maximum line length, imports organization, line spacing etc. We use PEP 8 to bring consistency in our code. With consistency it is easier for other developers to read the code.

Q.    What is Pickling in Python?

Pickling is a process by which a Python object hierarchy can be converted into a byte stream. The reverse operation of Pickling is Unpickling. 

Python has a module named pickle. This module has the implementation of a powerful algorithm for serialization and de-serialization of Python object structure.

Some people also call Pickling as Serialization or Marshalling.  With Serialization we can transfer Python objects over the network. It is also used in persisting the state of a Python object. We can write it to a file or a database.

Q.    What is a Python Decorator?

A Python Decorator is a mechanism to wrap a Python function and modify its behavior by adding more functionality to it. We can use @ symbol to call a Python Decorator function.

Q.    How are arguments passed in a Python method? By value or by reference?

Every argument in a Python method is an Object. All the variables in Python have reference to an Object. Therefore arguments in Python method are passed by Reference.

Since some of the objects passed as reference are mutable, we can change those objects in a method. But for an Immutable object like String, any change done within a method is not reflected outside. 

Q.    What is the difference between List and Dictionary data types in Python?

Main differences between List and Dictionary data types in Python are as follows:

• Syntax: In a List we store objects in a sequence. In a Dictionary we store objects in key-value pairs.
• Reference: In List we access objects by index number. It starts from 0 index. In a Dictionary we access objects by key specified at the time of Dictionary creation.
• Ordering: In a List objects are stored in an ordered sequence. In a Dictionary objects are not stored in an ordered sequence.
• Hashing: In a Dictionary, keys have to be hashable. In a List there is no need for hashing.

Q.    What is the use of Pass statement in Python?

The use of Pass statement is to do nothing. It is just a placeholder for a statement that is required for syntax purpose. It does not execute any code or command.

Some of the use cases for pass statement are as follows:

• Syntax purpose:
• Minimal Class: It can be used for creating minimal classes:
• Place-holder for TODO work:

>>> while True:

...     pass  # Wait till user input is received

>>> class MyMinimalClass:

...     pass

We can also use it as a placeholder for TODO work on a function or code that needs to be implemented at a later point of time.

>>> def initialization(): ...     pass   # TODO

Q.    How do you perform unit testing for Python code?

We can use the unit testing modules unittest or unittest2 to create and run unit tests for Python code.

We can even do automation of tests with these modules. Some of the main components of unittest are as follows:

• Test fixture: We use test fixture to create preparation methods required to run a test. It can even perform post-test cleanup.
• Test case: This is main unit test that we run on a piece of code. We can use Testcase base class to create new test cases.
• Test suite: We can aggregate our unit test cases in a Test suite.
• Test runner: We use test runner to execute unit tests and produce reports of the test run.

Q.    What are the main benefits of using Python?

Some of the main benefits of using Python are as follows:

• Easy to learn: Python is simple language. It is easy to learn for a new programmer.
• Large library: There is a large library for utilities in Python that can be used for different kinds of applications.
• Readability: Python has a variety of statements and expressions that are quite readable and very explicit in their use. It increases the readability of overall code.
• Memory management: In Python, memory management is built into the Interpreter. So a developer does not have to spend effort on managing memory among objects.
• Complex built-in Data types: Python has built-in Complex data types like list, set, dict etc. These data types give very good performance as well as save time in coding new features.

Q.    What is a metaclass in Python?

A metaclass in Python is also known as class of a class. A class defines the behavior of an instance. A metaclass defines the behavior of a class.

One of the most common metaclass in Python is type. We can subclass type to create our own metaclass.

We can use metaclass as a class-factory to create different types of classes.

Q.   What is the use of frozenset in Python?

A frozenset is a collection of unique values in Python. In addition to all the properties of set, a frozenset is immutable and hashable.

Once we have set the values in a frozenset, we cannot change. So we cannot use and update methods from set on frozenset. Being hashable, we can use the objects in frozenset as keys in a Dictionary.

Q.    What is Python Flask?

Python Flask is a micro-framework based on Python to develop a web application.

It is a very simple application framework that has many extensions to build an enterprise level application.

Flask does not provide a data abstraction layer or form validation by default. We can use external libraries on top of Flask to perform such tasks.

Q.   What is None in Python?

None is a reserved keyword used in Python for null objects. It is neither a null value nor a null pointer. It is an actual object in Python. But there is only one instance of None in a Python environment.

We can use None as a default argument in a function. During comparison we have to use “is” operator instead of “==” for None.

Q.    What is a Module in Python?

A Module is a script written in Python with import statements, classes, functions etc. We can use a module in another Python script by importing it or by giving the complete namespace.

With Modules, we can divide the functionality of our application in smaller chunks that can be easily managed.

Q.   How can we create a dictionary with ordered set of keys in Python?

In a normal dictionary in Python, there is no order maintained between keys. To solve this problem, we can use OrderDict class in Python. This class is available for use since version 2.7. It is similar to a dictionary in Python, but it maintains the insertion order of keys in the dictionary collection.

Q.    Python is an Object Oriented programming language or a functional programming language?

Python uses most of the Object Oriented programming concepts. But we can also do functional programming in Python. As per the opinion of experts, Python is a multi-paradigm programming language.

We can do functional, procedural, object-oriented and imperative programming with the help of Python.

Q.    How will you handle an error condition in Python code?

We can implement exception handling to handle error conditions in Python code. If we are expecting an error condition that we cannot handle, we can raise an error with appropriate message.

E.g.

>>> if student_score < 0: raise ValueError(“Score can not be negative”) 

If we do not want to stop the program, we can just catch the error condition, print a message and continue with our program.

 E.g. In following code snippet we are catching the error and continuing with the default value of age.

#!/usr/bin/python

try:

        age=18+'duration'

except:

        print("duration has to be a number")

age=18 print(age)

Q.    How will you check in Python, if a class is subclass of another class?

Python provides a useful method issubclass(a,b) to check whether class a is a subclass of b.

E.g. int is not a subclass of long

>>> issubclass(int,long)

False

bool is a subclass of int

>>> issubclass(bool,int)

True

Q.   How will you debug a piece of code in Python?

In Python, we can use the debugger pdb for debugging the code. To start debugging we have to enter following lines on the top of a Python script.

import pdb

pdb.set_trace()

After adding these lines, our code runs in debug mode. Now we can use commands like breakpoint, step through, step into etc for debugging.

Q.    How do you profile a Python script?

Python provides a profiler called cProfile that can be used for profiling Python code.

We can call it from our code as well as from the interpreter.

It gives use the number of function calls as well as the total time taken to run the script.

We can even write the profile results to a file instead of standard out.

Q.   What is the difference between ‘is’ and ‘==’ in Python?

We use ‘is’ to check an object against its identity.

We use ‘==’ to check equality of two objects.

E.g.

>>> lst = [10,20, 20]

>>> lst == lst[:]

True

>>> lst is lst[:]

False

Q.    How will you share variables across modules in Python?

We can create a common module with variables that we want to share.

This common module can be imported in all the modules in which we want to share the variables.

In this way, all the shared variables will be in one module and available for sharing with any new module as well.

Q.   How can we do Functional programming in Python?

In Functional Programming, we decompose a program into functions. These functions take input and after processing give an output. The function does not maintain any state.

Python provides built-in functions that can be used for Functional programming. Some of these functions are:

• Map()
• reduce()
• filter()

Event iterators and generators can be used for Functional programming in Python.

Q.    What is the improvement in enumerate() function of Python?

In Python, enumerate() function is an improvement over regular iteration. The enumerate() function returns an iterator that gives (0, item[0]).

E.g.

>>> thelist=['a','b']

>>> for i,j in enumerate(thelist):

...    print i,j

...

0 a

1 b

Q.   How will you execute a Python script in Unix?

To execute a Python script in Unix, we need to have Python executor in Unix environment.

In addition to that we have to add following line as the first line in a Python script file.

#!/usr/local/bin/python

This will tell Unix to use Python interpreter to execute the script.

Q.    What are the popular Python libraries used in Data analysis?

Some of the popular libraries of Python used for Data analysis are:

• Pandas: Powerful Python Data Analysis Toolkit
• SciKit: This is a machine learning library in Python.
• Seaborn: This is a statistical data visualization library in Python. SciPy: This is an open source system for science, mathematics and engineering implemented in Python.