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1. What is Python?

• Python is a high-level, interpreted, and general-purpose programming language.
• It was created by Guido van Rossum in 1991 and was first released in 1991.
• Python is an open-source language, which means that it is free to use, distribute, and modify.
• It is popular for its simple and easy-to-read syntax, making it a great language for beginners as well as everybody.
• Python is used for a wide range of tasks such as web development, data analysis, machine learning, artificial intelligence, scientific computing, and more.
• Python supports multiple programming paradigms such as object-oriented, functional, and procedural programming.
• It has a large and supportive community, which means that there is a wealth of resources and libraries available for use.
• Python can be used on multiple platforms such as Windows, Mac, and Linux.
• It has a large standard library that provides a wide range of modules for various tasks such as web scraping, regular expressions, and more.
• Python is used by companies like Google, NASA, Dropbox, and more.
• It is an interpreted language which means that it does not need to be compiled before it is executed.
• Python code is executed line by line, which makes debugging easier.
• Python has a garbage collector which automatically frees up memory that is no longer being used.

2. What are the key features of Python?

• Interpreted language: Python is an interpreted language, which means that it does not need to be compiled before it is executed.
• Easy to read and write: Python has a simple and easy-to-read syntax, making it a great language for beginners.
• High-level language: Python is a high-level programming language, which means that it abstracts away many of the low-level details of the computer.
• Object-oriented: Python supports object-oriented programming, which means that it allows for the creation of objects and classes.
• Dynamically-typed: Python is a dynamically-typed language, which means that variables do not need to be declared with a specific data type.
• Cross-platform: Python can be used on multiple platforms such as Windows, Mac, and Linux.
• Large standard library: Python has a large standard library that provides a wide range of modules for various tasks such as web scraping, regular expressions, and more.
• Large and supportive community: Python has a large and supportive community, which means that there is a wealth of resources and libraries available for use.
• Garbage collection: Python has a garbage collector which automatically frees up memory that is no longer being used.
• Modularity: the ability to split the code into modules and reuse it.
• Extensibility: the ability to add low-level modules to the Python interpreter, written in C or C++.
• Portable: Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
• Interactive: support for an interactive mode of testing and debugging the code.
• Embeddable: the ability to add scripting capabilities to your C/C++ programs.

3. What is the difference between Python 2 and Python 3?

• Print statement: In Python 2, the print statement is used for printing, whereas in Python 3, the print() function is used.
• Division operator: In Python 2, the division operator (/) returns an integer if both operands are integers, whereas in Python 3, it returns a float.
• Exception handling: In Python 2, the “as” keyword is used to handle exceptions, whereas in Python 3, the “as” keyword is optional.
• Text and binary data: In Python 3, there is a clear distinction between text (str) and binary data (bytes), whereas in Python 2, there is no such distinction.
• Unicode support: Python 3 uses Unicode for strings by default, whereas in Python 2, strings are in ASCII by default.
• Range function: In Python 2, the range() function returns a list, whereas in Python 3, it returns an iterable object.
• Integer division: In Python 2, the division of integers returns the floor division, whereas in Python 3, the division operator returns a float.
• xrange function: In Python 2, the xrange() function was used to generate a sequence of numbers, whereas in Python 3, this function was removed, and the range() function is used instead.
• raise statement: In Python 2, the raise statement must include the exception type, whereas in Python 3, the exception type is optional.
• Syntax: Some syntax changes were made in Python 3, for example, the use of parentheses in a print statement, and the use of “raise ValueError” instead of “raise ValueError,”
• Iterator methods: In python 2, Iterator methods such as .next() and .iteritems() are used whereas in python 3, it’s replaced by next() and items()
• Standard Library: python 3 has more updated versions of libraries, some libraries like Tkinter in python 2 are not present in python 3.

4. What are the benefits of using Python?

• Easy to learn: Python has a simple and easy-to-read syntax, making it a great language for beginners.
• Versatile: Python can be used for a wide range of tasks, including web development, scientific computing, data analysis, artificial intelligence, and more.
• Large community: Python has a large and active community, which means there are many resources and libraries available to help you solve any problem you encounter.
• Cross-platform: Python can run on a wide range of platforms, including Windows, Mac, and Linux, making it a versatile language for development.
• Plenty of libraries: Python has a large number of libraries and frameworks, such as NumPy, Pandas, Matplotlib, and TensorFlow, which makes it easy to perform complex tasks with minimal code.
• High-demand: Python is a highly demanded language in the industry and one of the most popular programming languages in the world
• Interoperability: Python can easily integrate with other languages and technologies, such as C, C++, Java, and C#.
• Good for prototyping: Python is great for quickly prototyping ideas and experimenting with new technologies.
• Good for Automation: Python can be used to automate repetitive tasks, scraping data from websites, or automate testing.
• Good for Machine Learning: Python has many powerful libraries for machine learning such as TensorFlow, Pytorch, Scikit-learn which makes it a popular choice for data scientists and researchers.

5. What are the data types supported in Python?

Python supports several built-in data types, including:

• Numbers: integers (int), floating-point numbers (float), complex numbers (complex)
• Strings: sequences of characters (str)
• Lists: ordered collections of items (list)
• Tuples: ordered, immutable collections of items (tuple)
• Sets: unordered collections of unique items (set)
• Dictionaries: a collection of key-value pairs (dict)
• Boolean: true or false (bool)
• None: special object representing the absence of a value (None)

Python also allows for the creation of user-defined data types, such as classes and objects.

Python Variables and Data Types (Multiple Choice Questions) MCQ

6. How do you create a variable in Python?

In Python, you can create a variable by assigning a value to it using the assignment operator (=). For example:

x = 5

This creates a variable x and assigns the value 5 to it.

You can also assign a value to a variable when you first declare it, like so:

y = 10

You can also assign different data types like string, boolean, list, etc.

name = "John Doe"
is_student = True
marks = [1, 2, 3, 4]

You can also perform mathematical operations and use them to assign value to variables.

a = 3
b = 5
c = a + b

It’s also important to know that variable names in Python must start with a letter or an underscore and cannot contain spaces or special characters, except for underscores. They also cannot be the same as Python keywords.

7. How do you create a list in Python?

In Python, a list is a collection of items that are ordered and changeable. Lists are written with square brackets, and the items are separated by commas. Here is an example of how to create a list in Python:

# creating a list
fruits = ["apple", "banana", "mango"]

# creating a list using list() method
numbers = list((1, 2, 3, 4, 5))

# creating a list of list
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

#creating empty list
empty_list = []

You can also create a list using list comprehension, which is a more concise way of creating a list with a certain pattern. Here is an example:

squares = [x**2 for x in range(1,11)]

This creates a list of squares of numbers from 1 to 10.

You can also create a list using the * operator, it creates a new list repeating the same element multiple times. For example :

repeated_list = [1]*5

This will create a list [1,1,1,1,1]

You can also create a list using the list() function, it converts any iterable data types such as tuple, set, string, etc into a list.

tuple_list = list((1, 2, 3, 4, 5))

This will convert the tuple into a list.

You can also use the range() function to create a list of numbers within a range.

numbers = list(range(1,10))

This will create a list of numbers from 1 to 9.

8. How do you create a tuple in Python?

In Python, a tuple is a collection of items that are ordered and unchangeable (immutable). Tuples are written with round brackets, and the items are separated by commas. Here is an example of how to create a tuple in Python:

# creating a tuple
fruits = ("apple", "banana", "mango")

# creating a tuple using tuple() method
numbers = tuple((1, 2, 3, 4, 5))

# creating a tuple of tuple
matrix = ((1, 2, 3), (4, 5, 6), (7, 8, 9))

#creating empty tuple
empty_tuple = ()

You can also create a tuple using a single value, this is also called singleton tuple.

singleton_tuple = (1,)

this creates a tuple containing only one element

You can also convert a list, set, or any other iterable data type into a tuple using the tuple() function

list_tuple = tuple([1, 2, 3, 4, 5])
set_tuple = tuple({1, 2, 3, 4, 5})

This will convert the list and set into a tuple

You can also use the * operator to unpack elements from an iterable.

a, b, c = [1, 2, 3]

This will unpack the elements from the list and assign them to variables a,b,c.

You can also use * operator for packing elements into tuple

tup = 1, 2, 3

This will create a tuple containing the elements 1, 2 and 3

9. How do you create a dictionary in Python?

In Python, a dictionary is a collection of key-value pairs. Dictionaries are written with curly brackets, and the key-value pairs are separated by colons. Here is an example of how to create a dictionary in Python:

# creating a dictionary using curly braces
person = {"name": "John", "age": 30, "gender": "male"}

# creating a dictionary using dict() method
marks = dict(maths=95, physics=85, chemistry=90)

# creating a dictionary using keyword arguments
student = dict(name='Sara', age=25, gender='female')

# creating an empty dictionary
empty_dict = {}

You can also create a dictionary by using the dict() constructor and passing in a list of key-value tuples.

# creating a dictionary using key-value tuples
data = dict([("name", "John"), ("age", 30), ("gender", "male")])

You can also create a dictionary by using the dict() constructor and passing in keyword arguments

# creating a dictionary using keyword arguments
data = dict(name="John", age=30, gender="male")

You can also use the dict() constructor and passing in keyword arguments

# creating a dictionary using keyword arguments
data = dict(name="John", age=30, gender="male")

You can also create a dictionary by using the dict() constructor and passing in keyword arguments

# creating a dictionary using keyword arguments
data = dict(name="John", age=30, gender="male")

You can also use a dictionary comprehension to create a dictionary with a specific structure.

squares = {i: i*i for i in range(1, 11)}

This creates a dictionary where the keys are numbers from 1 to 10 and values are their squares.

You can also use the zip() function to create a dictionary from two lists, where the first list is used as the keys and the second list is used as the values.

keys = ['name', 'age', 'gender']
values = ['John', 30, 'male']
person = dict(zip(keys, values))

This creates a dictionary where the keys are ‘name’, ‘age’, ‘gender’ and values are ‘John’, 30, ‘male’ respectively.

10. How do you create a set in Python?

In Python, you can create a set by using curly braces {} or the set() function. For example:

# Using curly braces
my_set = {1, 2, 3}

# Using the set() function
my_set = set([1, 2, 3])

You can also create a set with a set comprehension, similar to a list comprehension:

my_set = {x**2 for x in range(10)}

Note that sets are unordered and do not allow duplicate elements. If you add an element that already exists in the set, it will not be added again.

11. How do you create a string in Python?

In Python, you can create a string by enclosing a set of characters in either single quotes (‘…’) or double quotes (“…”). For example:

my_string = "Hello, world!"
another_string = 'This is also a string.'

You can also use triple quotes for multi-line strings:

my_string = """This is a
multi-line string."""

You can also use string literals f or F for string formatting, for example :

name = "John"
age = 30
f"My name is {name} and I am {age} years old."

This will give you My name is John and I am 30 years old.

12. What is a function in python and how do you create a function in Python?

A function in Python is a block of code that performs a specific task, and can be reused throughout a program. Functions help to organize and structure code, making it more readable, maintainable, and reusable.

You create a function in Python using the def keyword, followed by the name of the function, a set of parentheses (which may include parameters), and a colon. The code block that follows the definition is indented and forms the body of the function.

For example:

def greet(name):
    print(f"Hello, {name}!")

This creates a function called greet that takes one parameter, name, and prints a greeting using that name.

You can then call the function by using its name followed by parentheses containing any necessary arguments:

greet("Ram")

This will output Hello, Ram!

Functions can also include a return statement which is used to return a value from the function to the calling code. For example:

def add(a, b):
    return a + b

This creates a function called add that takes two parameters, a and b, and returns the sum of those two values.

You can then call the function and assign the return value to a variable:

result = add(3, 4)
print(result)

This will output 7.

13. What is a python class? How do you create a class in Python?

A class in Python is a blueprint for creating objects (a particular data structure), providing initial values for state (member variables or attributes), and implementations of behavior (member functions or methods). Classes are a fundamental part of object-oriented programming (OOP) and they are used to represent real-world objects and entities.

You create a class in Python using the class keyword, followed by the name of the class, and a colon. The code block that follows the definition is indented and forms the body of the class. The class definition typically includes a constructor method, named __init__, which is called when a new object of the class is created. The constructor method is used to initialize the attributes of the class.

For example:

class Dog:
    def __init__(self, name, breed):
        self.name = name
        self.breed = breed
    def bark(self):
        print("Woof!")

This creates a class called Dog that has two attributes, name and breed, and one method bark that prints “Woof!”.

You can then create an instance (object) of the class by calling the class name followed by parentheses.

dog = Dog("Fido", "Golden Retriever")
dog.bark()

This will output Woof!.

You can also access the attributes of the class directly:

print(dog.name)
print(dog.breed)

This will output Fido and Golden Retriever respectively.

14. What is an object in python and how do you create an object in Python?

An object in Python is an instance of a class. It is a specific realization of the blueprint defined by a class, with its own set of data and behavior. In other words, an object is a specific example of a class, with its own unique state and methods.

You create an object (or instance) of a class in Python by calling the class name followed by parentheses. The parentheses can be used to pass any necessary arguments to the class’s constructor method, __init__.

For example:

class Dog:
    def __init__(self, name, breed):
        self.name = name
        self.breed = breed
    def bark(self):
        print("Woof!")

dog = Dog("Fido", "Golden Retriever")

This creates an object called dog which is an instance of the Dog class. The dog object has a name attribute set to “Fido” and a breed attribute set to “Golden Retriever” and a bark method which prints “Woof!” when called.

Once an object is created, you can access its attributes and methods by using the dot notation.

print(dog.name)
dog.bark()

This will output Fido and Woof! respectively.

You can also create multiple instances of the same class, each with their own unique state.

dog1 = Dog("Fido", "Golden Retriever")
dog2 = Dog("Buddy", "Beagle")
print(dog1.name)
print(dog2.name)

This will output Fido and Buddy respectively.

Another example

class Car:
    def __init__(self, make, model,year):
        self.make = make
        self.model = model
        self.year = year
    def honk(self):
        print("Beep Beep!")

car = Car("Toyota", "Corolla",2022)

This creates an object called car which is an instance of the Car class. The car object has make attribute set to “Toyota” and a model attribute set to “Corolla” and a year attribute set to 2022, and a honk method which prints “Beep Beep!” when called.

Once an object is created, you can access its attributes and methods by using the dot notation.

print(car.make)
print(car.year)
car.honk()

This will output Toyota, 2022 and Beep Beep! respectively.

You can also create multiple instances of the same class, each with their own unique state.

car1 = Car("Honda", "Civic",2022)
car2 = Car("Mercedes", "Benz",2022)
print(car1.make)
print(car2.make)

This will output Honda and Mercedes respectively.

In this way, you can create an object in python for a class.

15. What is the use of the ‘self’ keyword in Python?

The self keyword in Python is used to refer to the current instance of a class. It is used inside the class methods to refer to the attributes and methods of the class. The self keyword is used as the first parameter in the class method definition.

When you create a method in a class, the first parameter passed to the method is always self. For example:

class MyClass:
    def my_method(self):
        print("Hello World")

In this example, self is the first parameter of the my_method() function.

When you call this method from an instance of the class, Python automatically passes the instance as the first argument to the method. For example:

my_object = MyClass()
my_object.my_method() # Hello World

In this example, my_object is passed as the self parameter to the my_method() function.

self is used to access the attributes and methods of the class within the class’s methods. For example:

class Dog:
    def __init__(self, name, breed):
        self.name = name
        self.breed = breed
    def bark(self):
        print(f"{self.name} says Woof!")

dog = Dog("Fido", "Golden Retriever")
dog.bark()  # Fido says Woof!

Here, the bark() method uses the self.name attribute to access the name of the dog instance, and print it out.

In short, self is used to refer to the current instance of a class and can be used to access the attributes and methods of the class.

Project Management MCQ Questions And Answers

16. What is inheritance in Python? How many types of inheritance are in python?

Inheritance in Python is a mechanism by which a child class can inherit the properties and methods of a parent class. This allows for code reuse and a way to organize and structure your code more effectively.

When a class inherits from another class, it can use all the attributes and methods of the parent class, but it can also add new attributes and methods, or override the ones inherited from the parent class. This allows the child class to have its own unique behavior while still sharing common functionality with the parent class.

In Python, there are several types of inheritance that can be used to create a new class based on an existing class:

1. Single Inheritance: A child class inherits properties and methods from a single parent class. This is the most basic form of inheritance.

class Parent:
    def __init__(self, name):
        self.name = name
    def speak(self):
        print("Hello")
        
class Child(Parent):
    pass

c = Child("John")
c.speak() #Hello

2. Multi-level Inheritance: A child class inherits properties and methods from a parent class, which in turn inherits from another parent class.

class GrandParent:
    def __init__(self, name):
        self.name = name
    def speak(self):
        print("Hello")

class Parent(GrandParent):
    pass

class Child(Parent):
    pass

c = Child("John")
c.speak() #Hello

3. Multiple Inheritance: A child class inherits properties and methods from multiple parent classes.

class Parent1:
    def __init__(self, name):
        self.name = name
    def speak(self):
        print("Hello")
        
class Parent2:
    def __init__(self, age):
        self.age = age
    def run(self):
        print("Running")

class Child(Parent1,Parent2):
    pass

c = Child("John",25)
c.speak() #Hello
c.run()  #Running

4. Hierarchical Inheritance: A parent class is inherited by multiple child classes.

class Parent:
    def __init__(self, name):
        self.name = name
    def speak(self):
        print("Hello")

class Child1(Parent):
    pass

class Child2(Parent):
    pass

c1 = Child1("John")
c1.speak() #Hello
c2 = Child2("Jane")
c2.speak() #Hello

5. Hybrid Inheritance: A combination of any of the above types of inheritance.

class GrandParent:
    def __init__(self, name):
        self.name = name
    def speak(self):
        print("Hello")

class Parent(GrandParent):
    def __init__(self, name,age):
        super().__init__(name)
        self.age = age
    def run(self):
        print("Running")
        
class Child(Parent):
    pass
class Child1(Parent):
    pass

c = Child("John",25)
c.speak() #Hello
c.run()  #Running
c1 = Child1("Jane",28)
c1.speak() #Hello
c1.run()  #Running

It’s important to note that multiple inheritance can be tricky and may lead to issues such as the diamond problem (when a class has multiple superclasses that have a common superclass) but can be resolved by using the method resolution order (MRO) in python.

17. What is polymorphism in Python?

Polymorphism is a concept in object-oriented programming that allows objects of different types to be treated as objects of a common base type. In Python, polymorphism allows you to define methods in a base class that can be overridden by subclasses, and to use those methods interchangeably for objects of different types.

There are two types of polymorphism in Python:

1. Duck typing: This refers to the ability of an object to respond to a certain method or attribute, regardless of its type. For example, in Python, it’s common to check if an object is iterable by using the iter() function, which will return an iterator for the object if it is iterable, and raise a TypeError otherwise.

def print_items(items):
    for item in items:
        print(item)

print_items([1,2,3])
print_items("Hello")

2. Method overloading: Method overloading is not supported by python directly, but we can achieve this by using the *args, **kwargs in the function definition. For example:

class A:
    def add(self,*args):
        total = 0
        for i in args:
            total +=i
        return total
a = A()
print(a.add(1))
print(a.add(1,2))
print(a.add(1,2,3))

In both examples, different types of objects (a list and a string) are used with the same function, and the function is able to handle them correctly because they both support the necessary methods or attributes.

18. What is encapsulation in Python?

Encapsulation in Python refers to the practice of binding the data (attributes) and the methods (functions) that operate on that data within a single unit, such as a class. This allows for the creation of objects that have a defined set of attributes and methods, and which hide the implementation details of those attributes and methods from the outside world.

By encapsulating data and methods within a class, developers can define a clear and consistent public interface for interacting with objects, while hiding the implementation details and preventing external code from directly modifying the internal state of the object. This allows for greater flexibility and maintainability of code, as changes to the implementation of an object do not affect code that uses the object.

Encapsulation in Python can be achieved by using the __init__ method to define the attributes of an object, and by using methods to define the behavior of an object. Additionally, the use of private attributes and methods (prefixed with an underscore) can further restrict access to the internal implementation of an object.

19. What is data abstraction in python?

Data abstraction in Python refers to the process of hiding the implementation details of an object, and instead providing a simplified, higher-level view of the object’s data and behavior. This allows the developer to work with objects at a more general, abstract level, without needing to understand the underlying implementation details.

Data abstraction is closely related to encapsulation, which also involves hiding the implementation details of an object. However, data abstraction specifically focuses on providing a simplified view of the object’s data, whereas encapsulation includes both data and behavior.

In Python, data abstraction can be achieved through the use of classes and objects. A class defines the blueprint for an object, including its attributes and methods, while an object is an instance of a class. By hiding the implementation details of a class within the class definition, and only exposing a simplified interface through the object, data abstraction can be achieved.

For example, a class called BankAccount can have a private variable _balance and a public method get_balance() which can be used to access the balance but can not access or modify the value of the private variable ‘_balance’ directly, this is the example of data abstraction.

20. What is the use of the ‘__init__’ method in Python?

The __init__ method in Python is a special method that is automatically called when an object is created from a class. It is used to initialize the attributes of the object and set them to their initial state. The __init__ method is defined in the class definition and takes the first argument as self which refers to the instance of the class being created.

The basic syntax for the __init__ method is as follows:

class MyClass:
    def __init__(self, attribute1, attribute2, ...):
        self.attribute1 = attribute1
        self.attribute2 = attribute2
        ...

Here, self refers to the instance of the class being created, and the attributes passed as arguments to the __init__ method are set to the corresponding values passed to the constructor when an object is created.

The __init__ method is called automatically when a new object is created from a class, so you don’t need to call it explicitly.

object = MyClass(value1, value2)

In this example, the __init__ method is called automatically when the MyClass object is created, and the value1 and value2 values passed as arguments are used to set the attribute1 and attribute2 attributes of the object.

In short, the __init__ method is used to initialize the attributes of an object and set them to their initial state when the object is created.