Tutorial Playlist

Python Tutorial for Beginners

Overview

The Best Tips for Learning Python

Lesson - 1

How to Install Python on Windows?

Lesson - 2

Top 10 Python IDEs in 2022: Choosing The Best One

Lesson - 3

A Beginner’s Guide To Python Variables

Lesson - 4

Understanding Python If-Else Statement

Lesson - 5

Python Numbers: Integers, Floats, Complex Numbers

Lesson - 6

Python Strings | Simplilearn Python Tutorial

Lesson - 7

The Basics of Python Loops

Lesson - 8

Python For Loops Explained With Examples

Lesson - 9

Introduction to Python While Loop

Lesson - 10

Everything You Need to Know About Python Arrays

Lesson - 11

All You Need To Know About Python List

Lesson - 12

How to Easily Implement Python Sets and Dictionaries

Lesson - 13

A Handy Guide to Python Tuples

Lesson - 14

Everything You Need to Know About Python Slicing

Lesson - 15

Python Regular Expression (RegEX)

Lesson - 16

Learn A to Z About Python Functions

Lesson - 17

Objects and Classes in Python: Create, Modify and Delete

Lesson - 18

Python OOPs Concept: Here's What You Need to Know

Lesson - 19

An Introduction to Python Threading

Lesson - 20

Getting Started With Jupyter Network

Lesson - 21

PyCharm Tutorial: Getting Started with PyCharm

Lesson - 22

The Best NumPy Tutorial for Beginners

Lesson - 23

The Best Python Pandas Tutorial

Lesson - 24

An Introduction to Matplotlib for Beginners

Lesson - 25

The Best Guide to Time Series Analysis In Python

Lesson - 26

An Introduction to Scikit-Learn: Machine Learning in Python

Lesson - 27

A Beginner's Guide To Web Scraping With Python

Lesson - 28

Python Django Tutorial: The Best Guide on Django Framework

Lesson - 29

Top 10 Reason Why You Should Learn Python

Lesson - 30

10 Cool Python Project Ideas For Beginners in 2021

Lesson - 31

The Best Ideas for Python Automation Projects

Lesson - 32

12 Tips On How To Become a Python Developer

Lesson - 33

The Best Guide for RPA Using Python

Lesson - 34

Comprehending Web Development With PHP vs. Python

Lesson - 35

The Best Tips for Learning Python - REMOVE

Lesson - 36

The Best Way to Learn About Box and Whisker Plot

Lesson - 37

An Interesting Guide to Visualizing Data Using Python Seaborn

Lesson - 38

The Complete Guide to Data Visualization in Python

Lesson - 39

Everything You Need to Know About Game Designing With Pygame in Python

Lesson - 40

The Complete Simplified Guide to Python Bokeh

Lesson - 41

Top 150 Python Interview Questions and Answers for 2022

Lesson - 42

The Supreme Guide to Understand the Workings of CPython

Lesson - 43
Top 150 Python Interview Questions and Answers for 2022

Python was developed by Guido van Rossum and was introduced first on 20 February 1991. It is one of the most widely used programming languages which provides flexibility to incorporate dynamic semantics. It is an open-source and free language having clean and simple syntax. All these things make it easy for developers to learn and understand Python. Python also supports object-based programming and is mainly used for doing general-purpose programming.

Due to its simplicity and the capacity to achieve numerous functionalities in fewer lines of code, the popularity of Python is increasing exponentially. It is also used in artificial intelligence, machine learning, web scraping, web development and different other domains due to its ability to support powerful computations through powerful libraries. As a result, Python Developers are in high demand in India and around the world. Companies provide these Developers incredible remunerations and bonuses.

Learn data operations in Python, strings, conditional statements, error handling, and the commonly used Python web framework Django with the Python Training course.

Python Interview Questions For Freshers

In this article, we will look at some of the most commonly asked Python interview questions with answers which will help you prepare for your upcoming job interviews.

1. What is the Difference Between a Shallow Copy and Deep Copy?

Deepcopy creates a different object and populates it with the child objects of the original object. Therefore, changes in the original object are not reflected in the copy.

copy.deepcopy() creates a Deep Copy.

Shallow copy creates a different object and populates it with the references of the child objects within the original object. Therefore, changes in the original object are reflected in the copy.

copy.copy creates a Shallow Copy.

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2. How Is Multithreading Achieved in Python?

Multithreading usually implies that multiple threads are executed concurrently. The Python Global Interpreter Lock doesn't allow more than one thread to hold the Python interpreter at that particular point of time. So multithreading in python is achieved through context switching. It is quite different from multiprocessing which actually opens up multiple processes across multiple threads.

3. Discuss Django Architecture.

Here you can also find a comprehensive guide on Python Django Tutorial that is very easy to understand.

Django is a web service used to build your web pages. Its architecture is as shown:

  • Template: the front end of the web page 
  • Model: the back end where the data is stored 
  • View: It interacts with the model and template and maps it to the URL
  • Django: serves the page to the user 

4. What Advantage Does the Numpy Array Have over a Nested List?

Numpy is written in C so that all its complexities are backed into a simple to use a module. Lists, on the other hand, are dynamically typed. Therefore, Python must check the data type of each element every time it uses it. This makes Numpy arrays much faster than lists.

Numpy has a lot of additional functionality that list doesn’t offer; for instance, a lot of things can be automated in Numpy.

5. What are Pickling and Unpickling?

Pickling 

Unpickling 

  • Converting a Python object hierarchy to a byte stream is called pickling
  • Pickling is also referred to as serialization
  • Converting a byte stream to a Python object hierarchy is called unpickling
  • Unpickling is also referred to as deserialization 

If you just created a neural network model, you can save that model to your hard drive, pickle it, and then unpickle to bring it back into another software program or to use it at a later time.

6. How is Memory managed in Python?

Python has a private heap space that stores all the objects. The Python memory manager regulates various aspects of this heap, such as sharing, caching, segmentation, and allocation. The user has no control over the heap; only the Python interpreter has access.

7. Are Arguments in Python Passed by Value or by Reference?

Arguments are passed in python by a reference. This means that any changes made within a function are reflected in the original object.

Consider two sets of code shown below:

Python Function

In the first example, we only assigned a value to one element of ‘l’, so the output is [3, 2, 3, 4].

In the second example, we have created a whole new object for ‘l’. But, the values [3, 2, 3, 4] doesn’t show up in the output as it is outside the definition of the function.

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8. How Would You Generate Random Numbers in Python?

To generate random numbers in Python, you must first import the random module. 

The random() function generates a random float value between 0 & 1.

> random.random()

The randrange() function generates a random number within a given range.

Syntax: randrange(beginning, end, step)

Example - > random.randrange(1,10,2)

9. What Does the // Operator Do?

In Python, the / operator performs division and returns the quotient in the float.

For example: 5 / 2 returns 2.5

The // operator, on the other hand, returns the quotient in integer.

For example: 5 // 2 returns 2

10. What Does the ‘is’ Operator Do?

The ‘is’ operator compares the id of the two objects. 

list1=[1,2,3]

list2=[1,2,3]

list3=list1

list1 == list2 🡪 True

list1 is list2 🡪 False

list1 is list3 🡪 True

11. What Is the Purpose of the Pass Statement?

The pass statement is used when there's a syntactic but not an operational requirement. For example - The program below prints a string ignoring the spaces.

var="Si mplilea rn"

for i in var:

  if i==" ":

    pass

  else:

    print(i,end="")

Here, the pass statement refers to ‘no action required.’

12. How Will You Check If All the Characters in a String Are Alphanumeric?

Python has an inbuilt method isalnum() which returns true if all characters in the string are alphanumeric. 

Example - 

>> "abcd123".isalnum()

Output: True

>>”abcd@123#”.isalnum()

Output: False

Another way is to use regex as shown.

>>import re

>>bool(re.match(‘[A-Za-z0-9]+$','abcd123’))

Output: True

>> bool(re.match(‘[A-Za-z0-9]+$','abcd@123’))

Output: False

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13. How Will You Merge Elements in a Sequence?

There are three types of sequences in Python:

  • Lists 
  • Tuples 
  • Strings

Example of Lists - 

>>l1=[1,2,3]

>>l2=[4,5,6]

>>l1+l2

Output: [1,2,3,4,5,6]

Example of Tuples - 

>>t1=(1,2,3)

>>t2=(4,5,6)

>>t1+t2

Output: (1,2,3,4,5,6)

Example of String - 

>>s1=“Simpli”

>>s2=“learn”

>>s1+s2

Output: ‘Simplilearn’

14. How Would You Remove All Leading Whitespace in a String?

Python provides the inbuilt function lstrip() to remove all leading spaces from a string.

>>“      Python”.lstrip

Output: Python

15. How Would You Replace All Occurrences of a Substring with a New String?

The replace() function can be used with strings for replacing a substring with a given string. Syntax: 

str.replace(old, new, count)

replace() returns a new string without modifying the original string.

Example - 

>>"Hey John. How are you, John?".replace(“john",“John",1)

Output: “Hey John. How are you, John?

16. What Is the Difference Between Del and Remove() on Lists?

del

remove()

  • del removes all elements of a list within a given range 
  • Syntax: del list[start:end]
  • remove() removes the first occurrence of a particular character 
  • Syntax: list.remove(element)

Here is an example to understand the two statements - 

>>lis=[‘a’, ‘b’, ‘c’, ‘d’]

>>del lis[1:3]

>>lis

Output: [“a”,”d”]

>>lis=[‘a’, ‘b’, ‘b’, ‘d’]

>>lis.remove(‘b’)

>>lis

Output: [‘a’, ‘b’, ‘d’]

Note that in the range 1:3, the elements are counted up to 2 and not 3.

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17. How Do You Display the Contents of a Text File in Reverse Order?

You can display the contents of a text file in reverse order using the following steps:

  • Open the file using the open() function 
  • Store the contents of the file into a list 
  • Reverse the contents of the list
  • Run a for loop to iterate through the list

18. Differentiate Between append() and extend().

append()

extend()

  • append() adds an element to the end of the list
  • Example - 

>>lst=[1,2,3]

>>lst.append(4)

>>lst

Output:[1,2,3,4]

  • extend() adds elements from an iterable to the end of the list
  • Example - 

>>lst=[1,2,3]

>>lst.extend([4,5,6])

>>lst

Output:[1,2,3,4,5,6]

19. What Is the Output of the below Code? Justify Your Answer.

>>def addToList(val, list=[]):

>> list.append(val)

>> return list

>>list1 = addToList(1)

>>list2 = addToList(123,[])

>>list3 = addToList('a’)

>>print ("list1 = %s" % list1)

>>print ("list2 = %s" % list2)

>>print ("list3 = %s" % list3)

Output: 

list1 = [1,’a’]

list2 = [123]

lilst3 = [1,’a’]

Note that list1 and list3 are equal. When we passed the information to the addToList, we did it without a second value. If we don't have an empty list as the second value, it will start off with an empty list, which we then append. For list2, we appended the value to an empty list, so its value becomes [123].

For list3, we're adding ‘a’ to the list. Because we didn't designate the list, it is a shared value. It means the list doesn’t reset and we get its value as [1, ‘a’].

Remember that a default list is created only once during the function and not during its call number.

20. What Is the Difference Between a List and a Tuple?

Lists are mutable while tuples are immutable.

Example:

List 

>>lst = [1,2,3]

>>lst[2] = 4

>>lst

Output:[1,2,4]

Tuple 

>>tpl = (1,2,3)

>>tpl[2] = 4

>>tpl

Output:TypeError: 'tuple'

the object does not support item

assignment

There is an error because you can't change the tuple 1 2 3 into 1 2 4. You have to completely reassign tuple to a new value.

21. What Is Docstring in Python?

Docstrings are used in providing documentation to various Python modules, classes, functions, and methods. 

Example - 

def add(a,b):

" " "This function adds two numbers." " "

sum=a+b

return sum

sum=add(10,20)

print("Accessing doctstring method 1:",add.__doc__)

print("Accessing doctstring method 2:",end="")

help(add)

Output - 

Accessing docstring method 1: This function adds two numbers.

Accessing docstring method 2: Help on function add-in module __main__:

add(a, b)

This function adds two numbers.

22. How Do You Use Print() Without the Newline?

The solution to this depends on the Python version you are using. 

Python v2

>>print(“Hi. ”),

>>print(“How are you?”)

Output: Hi. How are you?

Python v3

>>print(“Hi”,end=“ ”)

>>print(“How are you?”)

Output: Hi. How are you?

23. How Do You Use the Split() Function in Python?

The split() function splits a string into a number of strings based on a specific delimiter. 

Syntax - 

string.split(delimiter, max)

Where:

the delimiter is the character based on which the string is split. By default it is space. 

max is the maximum number of splits 

Example - 

>>var=“Red,Blue,Green,Orange”

>>lst=var.split(“,”,2)

>>print(lst)

Output:

[‘Red’,’Blue’,’Green, Orange’]

Here, we have a variable var whose values are to be split with commas. Note that ‘2’ indicates that only the first two values will be split.

24. Is Python Object-oriented or Functional Programming?

Python is considered a multi-paradigm language.

Python follows the object-oriented paradigm 

  • Python allows the creation of objects and their manipulation through specific methods 
  • It supports most of the features of OOPS such as inheritance and polymorphism

Python follows the functional programming paradigm

  • Functions may be used as the first-class object 
  • Python supports Lambda functions which are characteristic of the functional paradigm 

25. Write a Function Prototype That Takes a Variable Number of Arguments.

The function prototype is as follows:

def function_name(*list)

>>def fun(*var):

>> for i in var:

print(i)

>>fun(1)

>>fun(1,25,6)

In the above code, * indicates that there are multiple arguments of a variable.

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26. What Are *args and *kwargs?

*args 

  • It is used in a function prototype to accept a varying number of arguments.
  • It's an iterable object. 
  • Usage - def fun(*args)

*kwargs 

  • It is used in a function prototype to accept the varying number of keyworded arguments.
  • It's an iterable object
  • Usage - def fun(**kwargs):

fun(colour=”red”.units=2)

27. “in Python, Functions Are First-class Objects.” What Do You Infer from This?

It means that a function can be treated just like an object. You can assign them to variables, or pass them as arguments to other functions. You can even return them from other functions.

28. What Is the Output Of: Print(__name__)? Justify Your Answer.

__name__ is a special variable that holds the name of the current module. Program execution starts from main or code with 0 indentations. Thus, __name__ has a value __main__ in the above case. If the file is imported from another module, __name__ holds the name of this module.

29. What Is a Numpy Array?

A numpy array is a grid of values, all of the same type, and is indexed by a tuple of non-negative integers. The number of dimensions determines the rank of the array. The shape of an array is a tuple of integers giving the size of the array along each dimension.

30. What Is the Difference Between Matrices and Arrays?

Matrices

Arrays

  • A matrix comes from linear algebra and is a two-dimensional representation of data 
  • It comes with a powerful set of mathematical operations that allow you to manipulate the data in interesting ways
  • An array is a sequence of objects of similar data type 
  • An array within another array forms a matrix

Python Interview Questions For Experienced

31. How Do You Get Indices of N Maximum Values in a Numpy Array?

>>import numpy as np

>>arr=np.array([1, 3, 2, 4, 5])

>>print(arr.argsort( ) [ -N: ][: : -1])

32. How Would You Obtain 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]]

Choose the correct option:

  1. res_set = train_set.append(test_set)
  2. res_set = np.concatenate([train_set, test_set]))
  3. resulting_set = np.vstack([train_set, test_set])
  4. None of these

Here, options a and b would both do horizontal stacking, but we want vertical stacking. So, option c is the right statement.

resulting_set = np.vstack([train_set, test_set])

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33. How Would You Import a Decision Tree Classifier in Sklearn? Choose the Correct Option.

  1. from sklearn.decision_tree import DecisionTreeClassifier
  2. from sklearn.ensemble import DecisionTreeClassifier
  3. from sklearn.tree import DecisionTreeClassifier
  4. None of these

Answer - 3. from sklearn.tree import DecisionTreeClassifier

34. You Have Uploaded the Dataset in Csv Format on Google Spreadsheet and Shared It Publicly. How Can You Access This in Python?

We can use the following code:

>>link = https://docs.google.com/spreadsheets/d/...

>>source = StringIO.StringIO(requests.get(link).content))

>>data = pd.read_csv(source)

35. What Is the Difference Between the Two Data Series given Below?

df[‘Name’] and df.loc[:, ‘Name’], where:

df = pd.DataFrame(['aa', 'bb', 'xx', 'uu'], [21, 16, 50, 33], columns = ['Name', 'Age'])

Choose the correct option:

  1. 1 is the view of original dataframe and 2 is a copy of original dataframe
  2. 2 is the view of original dataframe and 1 is a copy of original dataframe
  3. Both are copies of original dataframe
  4. Both are views of original dataframe

Answer - 3. Both are copies of the original dataframe.

36. You Get the Error “temp.Csv” While Trying to Read a File Using Pandas. Which of the Following Could Correct It?

Error:

Traceback (most recent call last): File "<input>", line 1, in<module> UnicodeEncodeError:

'ascii' codec can't encode character.

Choose the correct option:

  1. pd.read_csv(“temp.csv”, compression=’gzip’)
  2. pd.read_csv(“temp.csv”, dialect=’str’)
  3. pd.read_csv(“temp.csv”, encoding=’utf-8′)
  4. None of these

The error relates to the difference between utf-8 coding and a Unicode. 

So option 3. pd.read_csv(“temp.csv”, encoding=’utf-8′) can correct it.

37. How Do You Set a Line Width in the Plot given Below?

Matplot

>>import matplotlib.pyplot as plt

>>plt.plot([1,2,3,4])

>>plt.show()

Choose the correct option:

  1. In line two, write plt.plot([1,2,3,4], width=3)
  2. In line two, write plt.plot([1,2,3,4], line_width=3
  3. In line two, write plt.plot([1,2,3,4], lw=3)
  4. None of these

Answer - 3. In line two, write plt.plot([1,2,3,4], lw=3)

38. How Would You Reset the Index of a Dataframe to a given List? Choose the Correct Option.

  1. df.reset_index(new_index,)
  2. df.reindex(new_index,)
  3. df.reindex_like(new_index,)
  4. None of these

Answer - 3. df.reindex_like(new_index,)

39. 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 deep copy

40. What Is the Difference Between range() and xrange() Functions in Python?

range()

xrange()

  • range returns a Python list object
  • xrange returns an xrange object

41. How Can You Check Whether a Pandas Dataframe Is Empty or Not?

The attribute df.empty is used to check whether a pandas data frame is empty or not. 

>>import pandas as pd

>>df=pd.DataFrame({A:[]})

>>df.empty

Output: True

42. Write a Code to Sort an Array in Numpy by the (N-1)Th Column.

This can be achieved by using argsort() function. Let us take an array X; the code to sort the (n-1)th column will be x[x [: n-2].argsoft()]

The code is as shown below:

>>import numpy as np

>>X=np.array([[1,2,3],[0,5,2],[2,3,4]])

>>X[X[:,1].argsort()]

Output:array([[1,2,3],[0,5,2],[2,3,4]])

43. How Do You Create a Series from a List, Numpy Array, and Dictionary?

The code is as shown:

>> #Input

>>import numpy as np

>>import pandas as pd

>>mylist = list('abcedfghijklmnopqrstuvwxyz’)

>>myarr = np.arange(26)

>>mydict = dict(zip(mylist, myarr))

>> #Solution

>>ser1 = pd.Series(mylist)

>>ser2 = pd.Series(myarr)

>>ser3 = pd.Series(mydict)

>>print(ser3.head())

44. How Do You Get the Items Not Common to Both Series a and Series B?

>> #Input

>>import pandas as pd

>>ser1 = pd.Series([1, 2, 3, 4, 5])

>>ser2 = pd.Series([4, 5, 6, 7, 8])

>> #Solution

>>ser_u = pd.Series(np.union1d(ser1, ser2)) # union

>>ser_i = pd.Series(np.intersect1d(ser1, ser2)) # intersect

>>ser_u[~ser_u.isin(ser_i)]

45. How Do You Keep Only the Top Two Most Frequent Values as It Is and Replace Everything Else as ‘other’ in a Series?

>> #Input

>>import pandas as pd

>>np.random.RandomState(100)

>>ser = pd.Series(np.random.randint(1, 5, [12]))

>> #Solution

>>print("Top 2 Freq:", ser.value_counts())

>>ser[~ser.isin(ser.value_counts().index[:2])] = 'Other’

>>ser

46. How Do You Find the Positions of Numbers That Are Multiples of Three from a Series?

>> #Input

>>import pandas as pd

>>ser = pd.Series(np.random.randint(1, 10, 7))

>>ser

>> #Solution

>>print(ser)

>>np.argwhere(ser % 3==0)

47. How Do You Compute the Euclidean Distance Between Two Series?

The code is as shown:

>> #Input

>>p = pd.Series([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

>>q = pd.Series([10, 9, 8, 7, 6, 5, 4, 3, 2, 1])

>> #Solution

>>sum((p - q)**2)**.5

>> #Solution using func

>>np.linalg.norm(p-q)

You can see that the Euclidean distance can be calculated using two ways.

48. How Do You Reverse the Rows of a Data Frame?

>> #Input

>>df = pd.DataFrame(np.arange(25).reshape(5, -1))

>> #Solution

>>df.iloc[::-1, :]

49. If You Split Your Data into Train/Test Splits, Is It Possible to over Fit Your Model?

Yes. One common beginner mistake is re-tuning a model or training new models with different parameters after seeing its performance on the test set. 

50. Which Python Library Is Built on Top of Matplotlib and Pandas to Ease Data Plotting?

Seaborn is a Python library built on top of matplotlib and pandas to ease data plotting. It is a data visualization library in Python that provides a high-level interface for drawing statistical informative graphs.

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51. What are the important features of Python?

  • Python is a scripting language. Python, unlike other programming languages like C and its derivatives, does not require compilation prior to execution.
  • Python is dynamically typed, which means you don't have to specify the kinds of variables when declaring them or anything.
  • Python is well suited to object-oriented programming since it supports class definition, composition, and inheritance.

52. What type of language is Python?

Although Python can be used to write scripts, it is primarily used as a general-purpose programming language.

53. Explain how Python is an interpreted language.

Any programming language that is not in machine-level code before runtime is called an interpreted language. Python is thus an interpreted language.

54. What is PEP 8?

PEP denotes Python Enhancement Proposal. It's a collection of guidelines for formatting Python code for maximum readability.

55. Explain Python namespace.

In Python, a namespace refers to the name that is assigned to each object.

56. What are decorators in Python?

Decorators are used for changing the appearance of a function without changing its structure. Decorators are typically defined prior to the function they are enhancing.

57. How to use decorators in Python?

Decorators are typically defined prior to the function they are enhancing. To use a decorator, we must first specify its function. Then we write the function to which it is applied, simply placing the decorator function above the function to which it must be applied.

58. Differentiate between .pyc and .py.

The .py files are the source code files for Python. The bytecode of the python files are stored in .pyc files, which are created when code is imported from another source. The interpreter saves time by converting the source .py files to .pyc files.

59. What is slicing in Python?

Slicing is a technique for gaining access to specific bits of sequences such as strings, tuples, and lists.

60. How to use the slicing operator in Python?

Slicing is a technique for gaining access to specific bits of sequences such as lists, tuples, and strings. The slicing syntax is [start:end:step]. This step can also be skipped. [start:end] returns all sequence items from the start (inclusive) to the end-1 element. It means the ith element from the end of the start or end element is negative i. The step represents the jump or the number of components that must be skipped.

61. What are keywords in python?

In Python, keywords are reserved words with a specific meaning. They are commonly used to specify the type of variables. Variable and function names cannot contain keywords. Following are the 33 keywords of Python:

  • Yield
  • For
  • Else
  • Elif
  • If
  • Not
  • Or
  • And
  • Raise
  • Nonlocal
  • None
  • Is
  • In
  • Import
  • Global
  • From
  • Finally
  • Except
  • Del
  • Continue
  • Class
  • Assert
  • With
  • Try
  • False
  • True
  • Return
  • Pass
  • Lambda
  • Def
  • As
  • Break
  • While

62. How to combine dataframes in Pandas?

The following are the ways through which the data frames in Pandas can be combined:

  • Concatenating them by vertically stacking the two dataframes.
  • Concatenating them by horizontally stacking the two dataframes.
  • Putting them together in a single column. 

63. What are the key features of the Python 3.9.0.0 version?

  • Zoneinfo and graphlib are two new modules.
  • Improved modules such as asyncio and ast.
  • Optimizations include improved idiom for assignment, signal handling, and Python built-ins.
  • Removal of erroneous methods and functions.
  • Instead of LL1, a new parser is based on PEG.
  • Remove Prefixes and Suffixes with New String Methods.
  • Generics with type hinting in standard collections.

64. In Python, how is memory managed?

  • Python's private heap space is in charge of memory management. A private heap holds all Python objects and data structures. This secret heap is not accessible to the programmer. Instead, the Python interpreter takes care of it.
  • Python also includes a built-in garbage collector, which recycles all unused memory and makes it available to the heap space.
  • Python's memory management is in charge of allocating heap space for Python objects. The core API allows programmers access to some programming tools.

65. Explain PYTHONPATH.

It's an environment variable that is used when you import a module. When a module is imported, PYTHONPATH is checked to see if the imported modules are present in various folders. It is used by the interpreter to determine which module to load.

66. Explain global variables and local variables in Python.

Local Variables:

A local variable is any variable declared within a function. This variable exists only in local space, not in global space.

Global Variables:

Global variables are variables declared outside of a function or in a global space. Any function in the program can access these variables.

67. Is Python case sensitive?

Yes, Python is case sensitive.

68. How to install Python on Windows and set path variables?

  • Download Python from https://www.python.org/downloads/
  • Install it on your computer. Using your command prompt, look for the location where PYTHON is installed on your computer by typing cmd python.
  • Then, in advanced system settings, create a new variable called PYTHON_NAME and paste the copied path into it.
  • Search the path variable, choose its value and select ‘edit’.
  • If the value doesn't have a semicolon at the end, add one, and then type %PYTHON HOME%.

69. Is it necessary to indent in Python?

Indentation is required in Python. It designates a coding block. An indented block contains all of the code for loops, classes, functions, and so on. Typically, four space characters are used. Your code will not execute correctly if it is not indented, and it will also generate errors.

70. On Unix, how do you make a Python script executable?

Script file should start with #!/usr/bin/env python.

71. What is the use of self in Python?

Self is used to represent the class instance. In Python, you can access the class's attributes and methods with this keyword. It connects the attributes to the arguments. Self appears in a variety of contexts and is frequently mistaken for a term. Self is not a keyword in Python, unlike in C++.

72. What are the literals in Python?

For primitive data types, a literal in Python source code indicates a fixed value.

73. What are the types of literals in Python?

For primitive data types, a literal in Python source code indicates a fixed value. Following are the 5 types of literal in Python:

  • String Literal: A string literal is formed by assigning some text to a variable that is contained in single or double-quotes. Assign the multiline text encased in triple quotes to produce multiline literals.
  • Numeric Literal: They may contain numeric values that are floating-point values, integers, or complex numbers.
  • Character Literal: It is made by putting a single character in double-quotes.
  • Boolean Literal: True or False
  • Literal Collections: There are four types of literals such as list collections, tuple literals, set literals, dictionary literals, and set literals.

74. What are Python modules? Name a few Python built-in modules that are often used.

Python modules are files that contain Python code. Functions, classes, or variables can be used in this code. A Python module is a .py file that contains code that may be executed. The following are the commonly used built-in modules:

  • JSON
  • data time
  • random
  • math
  • sys
  • OS

75. What is _init_?

_init_ is a constructor or method in Python. This method is used to allocate memory when a new object is created.

76. What is the Lambda function?

A lambda function is a type of anonymous function. This function can take as many parameters as you want, but just one statement.

77. Why Lambda is used in Python?

Lambda is typically utilized in instances where an anonymous function is required for a short period of time. Lambda functions can be applied in two different ways:

  • Assigning Lambda functions to a variable
  • Wrapping Lambda function into another function

78. How does continue, break, and pass work?

Continue

When a specified condition is met, the control is moved to the beginning of the loop, allowing some parts of the loop to be transferred.

Break

When a condition is met, the loop is terminated and control is passed to the next statement.

Pass

When you need a piece of code syntactically but don't want to execute it, use this. This is a null operation. 

79. What are Python iterators?

Iterators are things that can be iterated through or traversed.

80. Differentiate between range and xrange.

In terms of functionality, xrange and range are essentially the same. They both provide you the option of generating a list of integers to use whatever you want. The sole difference between range and xrange is that range produces a Python list object whereas x range returns an xrange object. This is especially true if you are working with a machine that requires a lot of memory, such as a phone because range will utilize as much memory as it can to generate your array of numbers, which can cause a memory error and crash your program. It is a beast with a memory problem.

81. What are unpickling and pickling?

The Pickle module takes any Python object and converts it to a string representation, which it then dumps into a file using the dump method. This is known as pickling. Unpickling is the process of recovering original Python objects from a stored text representation.

82. What are generators in Python?

Functions which return an iterable set of items are known as generators.

83. How do you copy an object in Python?

The assignment statement (= operator) in Python does not copy objects. Instead, it establishes a connection between the existing object and the name of the target variable. The copy module is used to make copies of an object in Python. Furthermore, the copy module provides two options for producing copies of a given object –

Deep Copy: Deep Copy recursively replicates all values from source to destination object, including the objects referenced by the source object.

from copy import copy, deepcopy

list_1 = [1, 2, [3, 5], 4]

## shallow copy

list_2 = copy(list_1) 

list_2[3] = 7

list_2[2].append(6)

list_2    # output => [1, 2, [3, 5, 6], 7]

list_1    # output => [1, 2, [3, 5, 6], 4]

## deep copy

list_3 = deepcopy(list_1)

list_3[3] = 8

list_3[2].append(7)

list_3    # output => [1, 2, [3, 5, 6, 7], 8]

list_1    # output => [1, 2, [3, 5, 6], 4]

Shallow Copy: A bit-wise copy of an object is called a shallow copy. The values in the copied object are identical to those in the original object. If one of the values is a reference to another object, only its reference addresses are copied.

84. In Python, are arguments provided by value or reference?

Pass by value: The actual item's copy is passed. Changing the value of the object's copy has no effect on the original object's value.

Pass by reference: The actual object is passed as a reference. The value of the old object will change if the value of the new object is changed.

Arguments are passed by reference in Python.

def appendNumber(arr):

   arr.append(4)

arr = [1, 2, 3]

print(arr)  #Output: => [1, 2, 3]

appendNumber(arr)

print(arr)  #Output: => [1, 2, 3, 4]

85. How to delete a file in Python?

Use command os.remove(file_name) to delete a file in Python.

86. Explain join() and split() functions in Python.

The join() function can be used to combine a list of strings based on a delimiter into a single string.

The split() function can be used to split a string into a list of strings based on a delimiter.

string = "This is a string."

string_list = string.split(' ') #delimiter is ‘space’ character or ‘ ‘

print(string_list) #output: ['This', 'is', 'a', 'string.']

print(' '.join(string_list)) #output: This is a string.

87. Explain **kwargs and *args.

*args

  • The function definition uses the *args syntax to pass variable-length parameters.
  • "*" denotes variable length, while "args" is the standard name. Any other will suffice.

**kwargs

  • **kwargs is a special syntax for passing variable-length keyworded arguments to functions.
  • When a variable is passed to a function, it is called a keyworded argument.
  • "Kwargs" is also used by convention here. You are free to use any other name.

88. What are negative indexes and why are they used?

  • The indexes from the end of the list, tuple, or string are called negative indexes.
  • Arr[-1] denotes the array's last element. Arr[]

89. How will you capitalize the first letter of string?

The capitalize() function in Python capitalizes a string's initial letter. It returns the original text if the string already contains a capital letter at the beginning.

90. What method will you use to convert a string to all lowercase?

The lower() function can be used to convert a string to lowercase.

91. In Python, how do you remark numerous lines?

Comments that involve multiple lines are known as multi-line comments. A # must prefix all lines that will be commented. You can also use a convenient shortcut to remark several lines. All you have to do is hold down the ctrl key and left-click anywhere you want a # character to appear, then input a # once. This will add a comment to every line where you put your cursor.

92. What are docstrings?

Docstrings are documentation strings. Within triple quotations are these docstrings. They are not allocated to any variable and, as a result, they can also be used as comments.

93. What is the purpose of ‘not’, ‘is’, and ‘in’ operators?

Special functions are known as operators. They take one or more input values and output a result.

not- returns the boolean value's inverse

is- returns true when both operands are true

in- determines whether a certain element is present in a series

94. What are the functions help() and dir() used for in Python?

Both help() and dir() are available from the Python interpreter and are used to provide a condensed list of built-in functions.

dir() function: The defined symbols are displayed using the dir() function.

help() function: The help() function displays the documentation string and also allows you to access help for modules, keywords, attributes, and other items.

95. Why isn't all the memory de-allocated when Python exits?

  • When Python quits, some Python modules, especially those with circular references to other objects or objects referenced from global namespaces, are not necessarily freed or deallocated.
  • Python would try to de-allocate/destroy all other objects on exit because it has its own efficient cleanup mechanism.
  • It is difficult to de-allocate memory that has been reserved by the C library.

96. What is a dictionary in Python?

Dictionary is one of Python's built-in datatypes. It establishes a one-to-one correspondence between keys and values. Dictionary keys and values are stored in pairs in dictionaries. Keys are used to index dictionaries.

97. In Python, how do you utilize ternary operators?

The Ternary operator is the operator for displaying conditional statements. This is made of true or false values and a statement that must be evaluated.

98. Explain the split(), sub(), and subn() methods of the Python "re" module.

Python's "re" module provides three ways for modifying strings. They are:

split (): a regex pattern is used to "separate" a string into a list

subn(): It works similarly to sub(), returning the new string as well as the number of replacements.

sub(): identifies all substrings that match the regex pattern and replaces them with a new string

99. What are negative indexes and why do we utilize them?

Python sequences are indexed, and they include both positive and negative values. Positive numbers are indexed with '0' as the first index and '1' as the second index, and so on.

The index for a negative number begins with '-1,' which is the last index in the sequence, and ends with '-2,' which is the penultimate index, and the sequence continues like a positive number. The negative index is used to eliminate all new-line spaces from the string and allow it to accept the last character S[:-1]. The negative index can also be used to represent the correct order of the string.

100. Explain Python packages.

Packages in Python are namespaces that contain numerous modules.

101. What are built-in types of Python?

Given below are the built-in types of Python:

  • Built in functions
  • Boolean
  • String
  • Complex numbers
  • Floating point
  • Integers

102. What are the benefits of NumPy arrays over (nested) Python lists?

  • Lists in Python are useful general-purpose containers. They allow for (relatively) quick insertion, deletion, appending, and concatenation, and Python's list comprehensions make them simple to create and operate.
  • They have some limitations: they don't enable "vectorized" operations like elementwise addition and multiplication, and because they can include objects of different types, Python must maintain type information for each element and execute type dispatching code while working on it.
  • NumPy arrays are faster, and NumPy comes with a number of features, including histograms, algebra, linear, basic statistics, fast searching, convolutions, FFTs, and more.

103. What is the best way to add values to a Python array?

The append(), extend(), and insert (i,x) procedures can be used to add elements to an array.

104. What is the best way to remove values from a Python array?

The pop() and remove() methods can be used to remove elements from an array. The difference between these two functions is that one returns the removed value while the other does not.

105. Is there an object-oriented Programming (OOps) concept in Python?

Python is a computer language that focuses on objects. This indicates that by simply constructing an object model, every program can be solved in Python. Python, on the other hand, may be used as both a procedural and structured language.

106. Differentiate between deep and shallow copy.

When a new instance type is formed, a shallow copy is used to maintain the values that were copied in the previous instance. Shallow copy is used to copy reference pointers in the same way as values are copied. These references refer to the original objects, and any modifications made to any member of the class will have an impact on the original copy. Shallow copy enables faster program execution and is dependent on the size of the data being utilized.

Deep copy is a technique for storing previously copied values. The reference pointers to the objects are not copied during deep copy. It creates a reference to an object and stores the new object that is referenced to by another object. The changes made to the original copy will have no effect on any subsequent copies that utilize the item. Deep copy slows down program performance by creating many copies of each object that is called.

107. What are Python libraries?

A Python library is a group of Python packages. Numpy, Pandas, Matplotlib, Scikit-learn, and many other Python libraries are widely used.

108. Why split is used?

In Python, the split() function is used to split a string.

109. How multithreading is achieved in Python?

  • Although Python includes a multi-threading module, it is usually not a good idea to utilize it if you want to multi-thread to speed up your code.
  • As this happens so quickly, it may appear to the human eye that your threads are running in parallel, but they are actually sharing the same CPU core.
  • The Global Interpreter Lock is a Python concept (GIL). Only one of your 'threads' can execute at a moment, thanks to the GIL. A thread obtains the GIL, performs some work, and then passes the GIL to the following thread.

110. How are classes created in Python?

The class keyword in Python is used to construct a class.

111. What is pandas dataframe?

A dataframe is a 2D changeable and tabular structure for representing data with rows and columns labelled.

112. Explain monkey patching in Python.

Monkey patches are solely used in Python to run-time dynamic updates to a class or module.

113. How Python module is imported?

The import keyword can be used to import modules.

114. What is inheritance in Python?

Inheritance allows one class to gain all of another class's members (for example, attributes and methods). Inheritance allows for code reuse, making it easier to develop and maintain applications.

115. What are the different types of inheritance in Python?

The following are the various types of inheritance in Python:

  • Single inheritance: The members of a single super class are acquired by a derived class.
  • Multiple inheritance: More than one base class is inherited by a derived class.
  • Muti-level inheritance: D1 is a derived class inherited from base1 while D2 is inherited from base2.
  • Hierarchical Inheritance: You can inherit any number of child classes from a single base class.

116. Is multiple inheritance possible in Python?

A class can be inherited from multiple parent classes, which is known as multiple inheritance. In contrast to Java, Python allows multiple inheritance.

117. Explain polymorphism in Python.

The ability to take various forms is known as polymorphism. For example, if the parent class has a method named ABC, the child class can likewise have a method named ABC with its own parameters and variables. Python makes polymorphism possible.

118. What is encapsulation in Python?

Encapsulation refers to the joining of code and data. Encapsulation is demonstrated through a Python class.

119. In Python, how do you abstract data?

Only the necessary details are provided, while the implementation is hidden from view. Interfaces and abstract classes can be used to do this in Python.

120. Is access specifiers used in Python?

Access to an instance variable or function is not limited in Python. To imitate the behavior of protected and private access specifiers, Python introduces the idea of prefixing the name of the variable, function, or method with a single or double underscore.

121. How to create an empty class in Python?

A class that has no code defined within its block is called an empty class. The pass keyword can be used to generate it. You can, however, create objects of this class outside of the class. When used in Python, the PASS command has no effect.

122. What does an object() do?

It produces a featureless object that serves as the foundation for all classes. It also does not accept any parameters.

123. Write a Python program to generate a Star triangle.

1

2

3

4

def pyfunc(r):

    for x in range(r):

        print(' '*(r-x-1)+'*'*(2*x+1))

pyfunc(9)

Output:

        *

       ***

      *****

     *******

    *********

   ***********

  *************

 ***************

*****************

124. Write a program to produce the Fibonacci series in Python.

1

2

3

4

5

6

7

8

9

10

11

12

# Enter number of terms needednbsp;#0,1,1,2,3,5....

a=int(input("Enter the terms"))

f=0;#first element of series

s=1#second element of series

if a=0:

   print("The requested series is",f)

else:

  print(f,s,end=" ")

   for x in range(2,a):

         print(next,end=" ")

         f=s

         s=next

Output: Enter the terms 5 0 1 1 2 3

125. Make a Python program that checks if a sequence is a Palindrome.

a=input("enter sequence")

b=a[::-1]

if a==b:

  print("palindrome")

else:

  print("Not a Palindrome")

Output: enter sequence 323 palindrome

126. Make a one-liner that counts how many capital letters are in a file. Even if the file is too large to fit in memory, your code should work.

1

2

3

4

5

6

with open(SOME_LARGE_FILE) as fh:

count = 0

text = fh.read()

for character in text:

    if character.isupper():

count += 1

Let us transform this into a single line

1

count sum(1 for line in fh for character in line if character.isupper())

 

127. Can you write a sorting algorithm with a numerical dataset?

1

2

3

4

list = ["1", "4", "0", "6", "9"]

list = [int(i) for i in list]

list.sort()

print (list)

128. Check code given below, list the final value of A0, A1 …An.

1

2

3

4

5

6

7

A0 = dict(zip(('a','b','c','d','e'),(1,2,3,4,5)))

A1 = range(10)A2 = sorted([i for i in A1 if i in A0])

A3 = sorted([A0[s] for s in A0])

A4 = [i for i in A1 if i in A3]

A5 = {i:i*i for i in A1}

A6 = [[i,i*i] for i in A1]

print(A0,A1,A2,A3,A4,A5,A6)

Here’s the answer:

A0 = {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4} # the order may vary

A1 = range(0, 10) 

A2 = []

A3 = [1, 2, 3, 4, 5]

A4 = [1, 2, 3, 4, 5]

A5 = {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}

A6 = [[0, 0], [1, 1], [2, 4], [3, 9], [4, 16], [5, 25], [6, 36], [7, 49], [8, 64], [9, 81]]

129. What is Flask and explain its benefits.

Flask is a Python web microframework based on the BSD license. Two of its dependencies are Werkzeug and Jinja2. This means it will have few, if any, external library dependencies. It lightens the framework while reducing update dependencies and security vulnerabilities.

A session is just a way of remembering information from one request to the next. A session in a flask employs a signed cookie to allow the user to inspect and edit the contents of the session. If the user only has the secret key, he or she can change the session. Flask.secret key.

130. Is Django better as compared to Flask?

Django and Flask map URLs or addresses entered into web browsers into Python functions.

Flask is easier to use than Django, but it doesn't do much for you, so you will have to specify the specifics, whereas Django does a lot for you and you won't have to do anything. Django has prewritten code that the user must examine, whereas Flask allows users to write their own code, making it easier to grasp. Both are technically excellent and have their own set of advantages and disadvantages.

131. Differentiate between Pyramid, Django, and Flask.

  • Pyramid is designed for larger apps. It gives developers flexibility and allows them to utilize the appropriate tools for their projects. The database, URL structure, templating style, and other options are all available to the developer. Pyramid can be easily customized.
  • Flask is a "microframework" designed for small applications with straightforward needs. External libraries are required in a flask. The flask is now ready for use.
  • Django, like Pyramid, may be used for larger applications. It has an ORM in it.

132. In NumPy, how will you read CSV data into an array?

This may be accomplished by utilizing the genfromtxt() method with a comma as the delimiter.

133. What is GIL?

The term GIL stands for Global Interpreter Lock. This is a mutex that helps thread synchronization by preventing deadlocks by limiting access to Python objects. GIL assists with multitasking (and not parallel computing).

134. What is PIP?

PIP denotes Python Installer Package. It is used to install various Python modules. It's a command-line utility that creates a unified interface for installing various Python modules. It searches the internet for the package and installs it into the working directory without requiring any user intervention.

135. What is the use of sessions in the Django framework?

Django has a session feature that allows you to store and retrieve data for each site visitor. Django isolates the process of sending and receiving cookies by keeping all necessary data on the server-side and inserting a session ID cookie on the client-side.

136. Write a program that checks if all of the numbers in a sequence are unique.

def check_distinct(data_list):

 if len(data_list) == len(set(data_list)):

   return True

 else:

   return False;

print(check_distinct([1,6,5,8]))     #Prints True

print(check_distinct([2,2,5,5,7,8])) #Prints False

137. What is an operator in Python?

An operator is a symbol that is applied to a set of values to produce a result. An operator manipulates operands. Numeric literals or variables that hold values are known as operands. Unary, binary, and ternary operators are all possible. The unary operator, which requires only one operand, the binary operator, which requires two operands, and the ternary operator, which requires three operands.

138. What are the various types of operators in Python?

  • Bitwise operators
  • Identity operators
  • Membership operators
  • Logical operators
  • Assignment operators
  • Relational operators
  • Arithmetic operators

139. How to write a Unicode string in Python?

The old Unicode type has been replaced with the "str" type in Python 3, and the string is now considered Unicode by default. Using the art.title.encode("utf-8") function, we can create a Unicode string.

140. Explain the differences between Python 2.x and Python 3.x?

Python 2.x is an older version of the Python programming language. Python 3.x is the most recent version. Python 2.x is no longer supported. Python 3.x is the language's present and future.

In Python2, a string is inherently ASCII, while in Python 3, it is Unicode.

141. How to send an email in Python language?

Python includes the smtplib and email libraries for sending emails. Import these modules into the newly generated mail script and send mail to users who have been authenticated.

142. Create a program to add two integers >0 without using the plus operator.

def add_nums(num1, num2):

   while num2 != 0:

       data = num1 & num2

       num1 = num1 ^ num2

       num2 = data << 1

   return num1

print(add_nums(2, 10))

143. Create a program to convert dates from yyyy-mm-dd to dd-mm-yyyyy.

We can use this module to convert dates:

import re

def transform_date_format(date):

   return re.sub(r'(\d{4})-(\d{1,2})-(\d{1,2})', '\\3-\\2-\\1', date)

date_input = "2021-08-01"

print(transform_date_format(date_input))

The datetime module can also be used, as demonstrated below:

from datetime import datetime

new_date = datetime.strptime("2021-08-01", "%Y-%m-%d").strftime("%d:%m:%Y")

print(new_data)

144. Create a program that combines two dictionaries. If you locate the same keys during combining, you can sum the values of these similar keys. Create a new dictionary.

from collections import Counter

d1 = {'key1': 50, 'key2': 100, 'key3':200}

d2 = {'key1': 200, 'key2': 100, 'key4':300}

new_dict = Counter(d1) + Counter(d2)

print(new_dict)

145. Is there an inherent do-while loop in Python?

No.

146. What kind of joins are offered by Pandas?

There are four joins in Pandas: left, inner, right, and outer.

147. How are dataframes in Pandas merged?

The type and fields of the dataframes being merged determine how they are merged. If the data has identical fields, it is combined along axis 0, otherwise, it is merged along axis 1.

148. What is the best way to get the first five entries of a data frame?

We may get the top five entries of a data frame using the head(5) method. df.head() returns the top 5 rows by default. df.head(n) will be used to fetch the top n rows.

149. How can you access the data frame's latest five entries?

We may get the top five entries of a dataframe using the tail(5) method. df.tail() returns the top 5 rows by default. df.tail(n) will be used to fetch the last n rows.

150. Explain classifier.

Any data point's class is predicted using a classifier. Classifiers are hypotheses that are used to assign labels to data items based on their classification. 

Step-By-Step Guide to Become a Python Developer

If you are an experienced or fresher developer who is looking out for a way to become a Python Developer, you have to learn Python. This may seem obvious, but there are a few things to keep in mind when learning or mastering Python and its frameworks, such as Django and Flask.

Follow the “Do Approach”

If you have started learning a new language and you have completed it, you know that it is not something you learn once and become a master of. It requires constant practice and patience. You always have to do a basic revision. Make sure to do your coding practice and work on the development part. Try everything which will help you learn Python effectively.

Be a Part of the Programming Community

When you limit yourself to only learning, you will never learn to grow, accept new viewpoints, or see things from a different perspective. This is not meant to compel you to enroll in professional programming lessons, but rather to emphasize the need of communicating even if you are a self-learner. You will not believe how much you will learn if you become an active member of the community. You can even share codes, learn new ideas, and discuss queries to start meaningful conversations.

Work for Learning

One of the best ways to learn starts with action. You have to take action to bring your knowledge into practice. Take freelance projects or work for startups, as they are a great way to accumulate knowledge and skills. The advantages of working on the job are plenty such as you can learn to handle various responsibilities, manage your studies and time, and get opinions on your positives and negatives through your clients. Another option is to begin teaching your juniors. This will provide a two-fold benefit— you will have the opportunity to practice your work while also passing on the material to pupils at the same level as you were a year ago.

Attend Seminars and Webinars

There are numerous contents available on the internet which you can go through. From detailed webinars to small workshops, make sure to attend those to brush up on your basic skills. You can also become a part of a concept which you have never heard of in programming. This way you can reinvent your ways of learning.

Things to Learn in Python

  • Learn the basics of Python, its history, installations, syntax and other basic constructs such as operators, variables, and statements.
  • Understand the applications of Python and the difference between Python 2 and Python 3.
  • Learn the important concepts such as loops and decision making.
  • Understand the basic data structure such as dictionaries, sets, and lists.
  • Learn how to develop a virtual environment.
  • Get started with functions as well as recursion.
  • Understand object-based concepts such as classes, methods, overloading, and inheritance.
  • Gain experience with modules like calendar, namedruple, and OS.
  • Know how to do file handling and understand other complex concepts such as generators, decorators, and shallow and deep copying.
  • Get started with building GUIs with Python.
  • Know how to generate and use random numbers as well as regular expressions.
  • Understand more complicated topics such as XML processing, networking, and multiprocessing.
  • Know how to use Pandas, NumPy, and SciPy.
  • Know how to debug log, unit test, serialize and access the database.

Things You Need to Master in Python

Frameworks

You should start working on a framework. Django, Flask, and CherryPy are three of Python's most powerful frameworks. Start using Django, a robust framework that adheres to the DRY (Don't Repeat Yourself) concept. It simplifies your work and takes care of the little details.

ORM Libraries

ORM denotes Object Relational Mapping. This is a way to manipulate data from a database through an object-oriented paradigm. You can learn to operate ORM libraries such as Django ORM and SQLAlchemy. It is easier and faster as compared to writing SQL.

Front End Technologies

Learning technologies and languages such as Javascript, jQuery, CSS3, and HTML5 are not required to become a Python Developer. However, if you can try to have a basic understanding of these, you will come to know how things work. You may need to work with the front-end team as a Python Developer.

Version Control

Multiple people making changes to a code can eventually break it. If you wish to use version control, you should learn GitHub and its basic terminology such as pull, push, fork, and commit.

Python is progressing consistently and is used in various industries and purposes such as data science, web application development, GUI and much more. The progress of the programming language is shaped by the dynamic needs of businesses. Any Python programming business in India can succeed if it keeps up with current developments and responds to market demands.

Now let us have a look at the top Python development trends in the year 2022:

Artificial Intelligence

Artificial Intelligence will most likely be the paramount trend for Python in 2022. Python is great for creating a variety of AI systems that require a lot of data. It is the ideal platform for AI since it allows Developers to work with both structured and unstructured data.

Framework Upgrades

Organizations hire Python Developers to match the pace of change and frameworks in Python and the upgraded technologies. Thus, companies would have to keep an eye on the latest upgrades that these frameworks receive over a period of time. TurboGears, Django, Pyramid and CherryPy are some of the top Python frameworks which will witness major updates in the coming year.

Web App Development

Despite the fact that Python web development services are at the top of the charts everywhere, 2022 will witness massive growth in this sector. Python is a strong programming language that can be used to create high-quality applications in a variety of frameworks.

Academic Growth

Python is becoming the most popular and widely taught programming language in colleges and universities. There are certain Python classes that are very popular all over the world. Python courses will become more popular in 2022 as schools focus on teaching the language to pupils in order to improve their job prospects.

Cloud Computing

Python is becoming the most popular programming language in colleges and universities. Python courses will become more popular in 2022, with schools focusing on teaching the language to pupils in order to improve their job prospects. These days many cloud computing providers like DigitalOcean, Google Cloud and AWS use Python to develop and manage their platforms.

Job Opportunities in Python

If you have Python on your resume, you may end with the following positions in leading companies:

Software Engineer

  • Write and test codes
  • Study user needs
  • Write operational documentation
  • Communicate with clients and collaborate with the team
  • Build existing programs

Senior Software Engineer

  • Build strong software architecture
  • Automate tasks through scripting or other tools
  • Debug codes
  • Conduct validation and verification testing
  • Implementing version control
  • Design patterns

Data Scientist

  • Identify data sources
  • Automate the collection
  • Preprocess data
  • Analyze data to invent trends
  • Design predictive models
  • Conduct data visualization
  • Propose solutions by overcoming business challenges

DevOps Engineer

  • Deploy fixes and updates
  • Analyze and solve technical glitches
  • Design processes for maintenance and troubleshooting
  • Create scripts for automating visualization
  • Deliver Level 2 technical support

Python Developer Salary in India

Python has increased in popularity among developers with each passing year since its introduction. We observed above how, according to studies, Python may not be at the top, but it will undoubtedly be the programming language of the future in 3-4 years. The future of Python appears to be bright and promising. This expansion has resulted in a large increase in the salary of Python Developers in India.

The average salary of a Python Developer in India is Rs.5,28,500 per annum. The starting  salary could be lower than that i.e. Rs. 4 lakhs per annum in some places. However, this salary figure can go up to Rs.10 lakhs per annum with time depending on your performance, experience and your expertise in the language. The salaries of Python Developers are affected by different factors like skills, location, job role, and experience.

Salary of Python Developers Based on Experience

Since this language is new, experience plays a significant role in determining the average salary for a Python Developer in India. As a result, the more experience you have on your Python Developer resume, the higher the income you can expect. The average salary of a fresher Python Developer in India is Rs. 4,18,662 per annum. On the other hand, the average salary of a Python Developer having 1 to 4 years of experience is Rs. 6,48,990.

The average salary of a Python Developer having 5 to 9 years of experience can range between Rs. 9 lakhs to Rs.10 lakhs per annum, whereas the average salary of a Python Developer with more than 10 years of experience is Rs.13 lakhs per annum.

Python Developer Salary Based on Location

Did you wonder why places like Bengaluru, Gurugram, New Delhi, and Pune are full of working crowds? These are some of the places where the job opportunity rate is higher than the other cities. So, location also plays a significant role to finalize the pay structure of a Python Developer. Let us take a look at the salary structure of a Python Developer in various cities in India:

  • Bengaluru: Rs.9,20,860 per annum
  • Hyderabad: Rs.7,77,351 per annum
  • Gurugram: Rs.7,19,064 per annum
  • Pune: Rs.7,07,764 per annum
  • Mumbai: Rs.6,59,912 per annum

Python Developer Salary on the Basis of Company

The following are the top companies which offer lucrative salaries to Python Developers in India:

  • Amazon: Rs.12,41000
  • Accenture: Rs.5,64,105
  • Cognizant: Rs.5,55,014
  • Capgemini: Rs.5,25,924
  • Tech Mahindra: Rs.5,29,000
  • TCS: Rs.4,30,837
  • Infosys: Rs.4,25,742
  • Wipro: Rs.4,00,000

Python Developer Salary on the Basis of Skills

The demand for Python is clear. However, a Python Developer's income is never exclusively determined by his or her command of the language. It is also dependent on the Developer's skill set. The competition in the field is fierce, and as the language's popularity grows, so does the community. However, the salary of a Python Developer is also determined on the basis of the skills given below:

  • Test Automation: Rs,1,099,268
  • API Development: Rs.1,000,000
  • GIT: Rs.8,62,500
  • SVN: Rs.8,58,000
  • SQL: Rs.4,89,032
Looking forward to make a move to programming? Take up the Python Training Course and begin your career as a professional Python programmer.

Conclusion

There is a vast career scope in Python. Moreover, if you pursue a course like the Full Stack Web Developer Mean Stack program, you can work for reputed multinational companies across the world. As a MEAN stack Developer, this training will help you progress your career. Throughout this Full Stack MEAN Developer curriculum, you will study top skills like MongoDB, Express.js, Angular, and Node.js ("MEAN"), as well as GIT, HTML, CSS, and JavaScript, to develop and deploy interactive applications and services. 

To fast track your career in Data Science to the next level and become industry-ready for top data jobs, dive deep into the complexities of data interpretation, master technologies like Machine Learning, and master powerful programming abilities. You can enroll in Simplilearn’s Data Science Certification Course developed in conjunction with IBM, which will help you further your career in Data Science by providing world-class training and abilities. The system provides in-depth instruction on the most in-demand Data Science and Machine Learning abilities and hands-on experience with essential tools and technologies such as Python, R, Tableau, Hadoop, Spark, and Machine Learning ideas.

About the Author

John TerraJohn Terra

John Terra lives in Nashua, New Hampshire and has been writing freelance since 1986. Besides his volume of work in the gaming industry, he has written articles for Inc.Magazine and Computer Shopper, as well as software reviews for ZDNet. More recently, he has done extensive work as a professional blogger. His hobbies include running, gaming, and consuming craft beers. His refrigerator is Wi-Fi compliant.

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