1. Is Python a compiled language or an interpreted language?

Python is a language that combines elements of both compilation and interpretation. When we run our code, the compilation process occurs first, generating bytecode internally. This bytecode is then converted by the Python virtual machine (PVM) to run on the specific platform, which includes the combination of the machine and operating system.

• What is the difference between a Mutable datatype and an Immutable data type?

Mutable data types are capable of being modified during runtime, meaning they can be changed or updated. Examples of mutable data types include lists, dictionaries, and similar structures.

On the other hand, immutable data types cannot be edited or altered once they are created. They remain unchanged throughout the runtime. Immutable data types include strings, tuples, and similar constructs.

• What is a lambda function?

A lambda function is a type of function that is anonymous, meaning it doesn’t have a specific name. It can accept any number of parameters, but it is limited to having only one statement within its body.

Example:

a = lambda x, y : x*y

print(a(7, 19))

• How is Exceptional handling done in Python?

There are three primary keywords in Python: try, except, and finally. These keywords are used to handle exceptions and implement error recovery mechanisms.

The try block is where a specific section of code is monitored for errors. If an error occurs, the except block is executed to handle the error and perform necessary actions.

The finally block is a powerful feature that allows the execution of code regardless of whether an error occurred or not. It is commonly used for performing cleanup activities, such as releasing resources or cleaning up objects/variables.

• Can we Pass a function as an argument in Python?

A function in Python can receive multiple arguments, which can include objects, variables of various data types, and even other functions. Functions are treated as objects in Python, allowing them to be passed as parameters to other functions. This ability to pass functions as arguments to other functions is a characteristic of higher-order functions.

• What are *args and *kwargs?

To pass a variable number of arguments to a function in Python, you can utilize the special syntax *args and **kwargs in the function definition. This approach allows you to pass a flexible, keyword-free list of arguments to the function. By using the asterisk (*) before the variable name, it becomes an iterable object, enabling operations such as iteration, mapping, and filtering on the arguments.

• What is docstring in Python?

Python documentation strings, also known as docstrings, offer a convenient means of associating documentation with various elements in Python, such as modules, functions, classes, and methods.

To declare docstrings, triple single quotes (”’) or triple double quotes (“””) are placed just below the declaration of a class, method, or function. It is recommended that all functions should have a docstring to provide clear and concise documentation.

To access docstrings, you can use the __doc__ method of the object in question or utilize the help function. These methods allow you to retrieve the docstring and obtain information about the purpose and usage of the associated object.

• What is the difference between xrange and range functions?

The xrange() function offers a significant advantage compared to the range() function in terms of memory optimization. While the range() function generates a list of integers and supports arithmetic operations, the xrange() function, which returns a generator object, does not support arithmetic operations.

• Differentiate between List and Tuple?

In Python, lists and tuples are different classes of data structures. While lists are dynamic and can be modified, tuples have static characteristics and cannot be modified once created. This means that lists can have elements added, removed, or modified, while tuples remain fixed. Additionally, tuples are generally faster than lists due to their static nature.

1. Which sorting technique is used by sort() and sorted() functions of python?

Timsort is an algorithm that combines the strengths of Insertion Sort and Mergesort. It is utilized in Java’s Arrays.sort(), as well as in Python’s sorted() and sort() functions. In Timsort, smaller parts of the data are sorted using Insertion Sort, and then these sorted parts are merged together using Mergesort.

1. What are Iterators in Python?

Iterators in Python are objects that enable iteration over a collection of elements or values. They provide a way to access the elements of a container one by one, without the need to know the underlying structure or implementation details of the container.

1. Does Python support multiple Inheritance?

Python is one of the few modern programming languages that allows for multiple inheritance, which is the ability to derive a class from multiple base classes simultaneously. However, it should be noted that multiple inheritance has gained a somewhat negative reputation, to the point that many contemporary programming languages choose not to support it.

1. How do you do data abstraction in Python?

Data abstraction in Python can be achieved through the use of classes and objects. By defining classes, you can encapsulate data and functionality into objects, hiding the internal implementation details and providing a simplified interface for interacting with the data.

1. What is slicing in Python?

The slice() function in Python extracts a subset of elements from a collection. There are two variations of the slice() function available. The first variation accepts a single argument, while the second variation takes three arguments and returns a slice object. This slice object can then be used to retrieve a specific section of the collection.

Eg.

s=”hello world”

print(s[slice(0,4,2)])

Output: hl

1. What is monkey patching in Python?

Monkey patching in Python refers to the act of altering or updating code, classes, or modules during runtime. In simpler terms, it allows us to modify the behavior or functionality of a class or module without having to modify the entire Python codebase.

1. Write a code to display the current time?

from datetime import datetime

now = datetime.now()

current_time = now.strftime(“%H:%M:%S”)

print(“Current Time =”, current_time)

1. What are Access Specifiers in Python?

There are 3 types of access specifiers for a class in Python. These access specifiers define how the members of the class can be accessed

Public: The members declared as Public are accessible from outside the Class through an object of the class.

Private: These members are only accessible from within the class. No outside Access is allowed.

Protected: The members declared as Protected are accessible from outside the class but only in a class derived from it that is in the child or subclass.

1. What are Function Annotations in Python?

Function annotations in Python are expressions associated with functions that provide additional information about the function’s parameters and return values. These annotations are typically evaluated at compile time and do not have inherent meaning within the Python language itself. They exist primarily for external use by third-party libraries or tools, which can interpret and utilize these annotations as needed. During runtime, Python itself does not actively use or process these annotations.

1. What is the swapcase function in Python?

The swapcase method is used for converting uppercase letters of a string to lowercase and lowercase letters of a string to uppercase.

• What is the difference between / and // in Python?

In Python, the “/” and “//” operators are used for division, but they have different behaviors depending on the operand types:

“/” (Forward Slash): The forward slash operator (“/”) performs regular division. When both operands are of integer or floating-point types, it returns the exact division result as a floating-point number, including the decimal portion if present.

“//” (Double Forward Slash): The double forward slash operator (“//”) performs floor division or integer division. It returns the largest integer that is less than or equal to the division result. This means that the decimal portion is truncated, and the result is always an integer.

• What is the difference between a Set and Dictionary?

A set is a data structure in Python that stores a collection of unique elements. It can contain elements of different types, and the elements are stored in an unordered manner. Sets ensure that each element appears only once, and they are commonly used for tasks like removing duplicates or testing membership.

On the other hand, a dictionary is another data structure in Python that stores key-value pairs. It allows for the storage and retrieval of values based on unique keys. Unlike sets, dictionaries allow duplicate values but require unique keys. Dictionaries provide efficient access to values based on their associated keys, making them useful for tasks like fast lookups and mappings.

• How will you perform Static Analysis on a Python Script?

Mypy is widely recognized as the leading static type checker for Python. It serves as a linter that enables the writing of statically typed code and ensures the correctness of types within your project. To utilize mypy effectively, it is necessary to annotate your code using Python 3 function annotation syntax as defined in PEP 484. By incorporating these annotations, mypy can perform thorough type checking and provide valuable feedback on type-related issues in your Python code.

• What is a Namespace in Python?

A namespace in Python is a container that holds a collection of currently defined names (symbols) and the corresponding objects they reference. It can be conceptualized as a dictionary-like structure, where the names serve as keys and the objects they represent are the corresponding values. Namespaces provide a way to organize and manage the availability and scope of names within a program, allowing for distinct and separate areas of name resolution.

• What is the use of a Pass statement in Python?

The pass statement in Python is utilized as a placeholder for future code that will be added later. When the pass statement is encountered, it essentially acts as a no-op, causing no action to be taken. It is primarily used to avoid syntax errors when empty code blocks are not permitted, such as in loops, function definitions, class definitions, or if statements. By using the pass statement, you can indicate that there will be code in those sections at a later stage without causing any issues during the initial development phase.

• What is the difference between an Iterator and an Iterable in Python?

An iterable in Python refers to an object that can be iterated over, meaning it can be used in a loop or other iteration processes. It provides a way to access its elements one by one. Examples of iterables include lists, tuples, strings, dictionaries, and sets.

On the other hand, an iterator is an object that enables iteration over an iterable object. It maintains the state of the iteration and provides a way to fetch the next element from the iterable. To obtain an iterator, you can use the iter() function and pass the iterable object as an argument. The iter() function returns an iterator object that can then be used with the next() function to retrieve the next element in the iteration sequence.

• What is the significance of functions that start with _ symbol?

In Python, functions that start with an underscore (_) symbol follow a naming convention indicating that they are intended for internal use and should be treated as private. It suggests that these functions are not part of the public interface and may undergo changes. While not enforced by the language, it is considered good practice to respect this convention and avoid accessing or calling these functions directly from outside the module or class they are defined in.

• What is a metaclass in Python?

A metaclass in Python can be described as a class that defines the behavior of other classes. It is responsible for creating and defining the behavior of classes, similar to how a class defines the behavior of instances.

• What is Python Flask?

Flask is a lightweight Python web framework that allows developers to quickly create web applications using a single Python file. It provides useful tools and features while remaining flexible and accessible to new developers.

• What is the use of the zip() function in Python?

The zip() function in Python combines multiple iterables, such as dictionaries, into a single iterable by pairing corresponding elements together as tuples. With dictionaries, zip() pairs the keys and values based on their position in the dictionary.

• What is a Module in Python?

In Python, a module is a file that contains Python definitions, statements, functions, classes, variables, and even runnable code. Modules are used to group related code together, making it easier to understand, use, and logically organize the code.

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

Python issubclass() is a built-in function used to check if a class is a subclass of another class or not. This function returns True if the given class is the subclass of the given class else it returns False

• What is the difference between append() and extend() functions of a list?

The method append() is used to add a single element at the end of a list, while extend() is used to add multiple individual elements to the end of the list.

• How will you handle an error condition in Python code?

In Python, the most straightforward approach to handle exceptions is through the try and except block. The code within the try block is executed, and if an exception occurs, the code within the except block is executed to handle the exception.

• How will you share variables across modules in Python?

To share global variables across modules or scripts in Python, one approach is to create a config file where the entire set of global variables is stored. By importing this config file, the global variables defined within it become accessible for use in other modules or scripts.

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

When working with iterators in Python, it is common to need a count of iterations. To simplify this task, Python offers the built-in function enumerate(). This function adds a counter to an iterable and returns it as an enumerating object, making it easier for programmers to track the iteration count.

• What are the popular Python libraries used in Data analysis?

There are several popular Python libraries widely used in data analysis. Some of them include:

NumPy: A fundamental library for numerical computing in Python, providing support for large, multi-dimensional arrays and mathematical functions.

Pandas: A powerful library for data manipulation and analysis, offering data structures like DataFrames for efficient handling and analysis of structured data.

Matplotlib: A comprehensive plotting library that enables the creation of a wide variety of static, animated, and interactive visualizations.

SciPy: A library built on top of NumPy, providing additional functionality for scientific computing, such as optimization, integration, interpolation, and more.

Scikit-learn: A versatile library for machine learning, offering tools for classification, regression, clustering, dimensionality reduction, and model selection.

• What are some features of the Python language?

Python is a versatile programming language known for its simplicity, readability, and extensive range of features. Some notable features of the Python language include:

Easy to Read and Write: Python emphasizes code readability with its clean and straightforward syntax, making it easier for developers to write and understand code.

Dynamic and Interpreted: Python is dynamically typed, allowing flexible variable assignments and avoiding the need for explicit type declarations. It is also interpreted, which means code can be executed directly without the need for compilation.

Multi-paradigm: Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Developers have the flexibility to choose the best approach for their specific needs.

Large Standard Library: Python comes with a vast standard library, providing ready-to-use modules and functions for a wide range of tasks, such as file I/O, networking, regular expressions, and more. It saves developers time and effort by offering built-in solutions for common programming challenges.

Platform Independence: Python is highly portable and runs on various operating systems, including Windows, macOS, Linux, and more. Code written in Python can be executed on different platforms without requiring major modifications.

• What is PEP8?

PEP 8, also referred to as PEP8 or PEP-8, is a document that offers a set of guidelines and recommended practices for writing Python code.

• How does Python manage memory?

In Python, memory management involves a private heap that stores all Python objects and data structures. The Python memory manager handles the management of this private heap internally.

• What is the purpose of the PYTHONPATH variable?

PythonPath is an environment variable utilized to designate the location of Python libraries. It is commonly employed by developers to ensure that their code can locate the necessary Python libraries during runtime.

• What is the purpose of the PYTHONSTARTUP variable?

The environment variable PYTHONSTARTUP allows you to specify the path to a Python file. This Python script is executed by the Python interpreter before entering the interactive mode, enabling you to run custom code or define variables that will be available in the interactive session.

• How would you get a user’s home directory (~) in Python?

In Python, the os module offers the os.path.expanduser(‘~’) function to retrieve the home directory. This method can be used to obtain the home directory, even if it is part of a longer path, such as ~/Documents/my_folder/.

• What is a Python decorator?

In Python, a decorator is a design pattern that enables users to enhance the functionality of an existing object without altering its structure. It provides a flexible way to add additional features or behavior to an object dynamically.

• What is pickling/unpickling in Python?

In Python, “pickling” refers to the process of converting a hierarchy of Python objects into a byte stream. On the other hand, “unpickling” is the reverse operation where a byte stream, obtained from a binary file or bytes-like object, is converted back into the original object hierarchy.

• How are global and local variables defined in Python?

In Python, global variables are variables that are defined outside of any function and have a global scope, meaning they can be accessed from anywhere in the code. On the other hand, local variables are defined within a function and are limited to that specific function’s scope, meaning they can only be accessed within the function where they are defined.

• Describe a few ways to generate a random number in Python.

Generating a Single Random Number

The random() method in the random module generates a float number between 0 and 1.

Example:

import random

n = random.random()

print(n)

Generating Number in a Range

The randint() method generates a integer between a given range of numbers.

Example:

import random

n = random.randint(0,22)

print(n)

Generating a List of numbers Using For Loop

We can use the above randint() method along with a for loop to generate a list of numbers. We first create an empty list and then append the random numbers generated to the empty list one by one.

Example

import random

randomlist = []

for i in range(0,5):

n = random.randint(1,30)

randomlist.append(n)

print(randomlist)

• How would you get all the keys in a Python dictionary?

We can get the list of all the keys from a Python dictionary using the following methods −

• Using dict.keys() method
• Using list() & dict.keys() function
• Using List comprehension
• Using the Unpacking operator(*)
• Using append() function & For loop

• How do you convert a string to an integer in Python?

To convert a string to an integer in Python, you can utilize the built-in function int(). This function accepts a string as a parameter and returns the corresponding integer value. The syntax for using int() is as follows: int(“str”).

• How do you convert an object to a string in Python?

In Python, objects can be converted into strings using methods such as str() and repr(). The str() method is used to convert built-in objects into strings, providing a human-readable representation of the object. On the other hand, the repr() method is used to convert an object back to a string, producing a string representation that can be used to recreate the object.

• What does the ** operator do in Python?

In Python, the ** operator is used for exponentiation or raising a number to a power. It is referred to as the exponentiation operator.

• What does the Python is operator do?

In Python, the is operator is used to check if two variables refer to the same object in memory. It compares the identity of the objects rather than their values.

• What are Python dictionaries and list comprehensions?

List comprehensions and dictionary comprehensions in Python are indeed powerful alternatives to traditional for-loops and lambda functions. They allow for concise and readable code while providing performance benefits.

List comprehensions provide a compact syntax for creating lists based on existing lists or other iterable objects. They eliminate the need for explicit for-loops when generating new lists, resulting in more concise and expressive code.

• How do you copy an object in Python?

In Python, the assignment operator (=) is used to create a reference to an existing object rather than making a copy of it.

• What is self in Python?

In Python, the keyword self represents the instance of a class. It provides a convenient way to access variables, attributes, and methods within the scope of a defined class. While the parameter is commonly named “self,” it can actually be named using any valid variable name chosen by the developer.

• What is a generator in Python?

In Python, a generator is a special type of function that returns an iterator. When iterated over, the generator produces a sequence of values. Generators are particularly useful when dealing with large sequences where storing all the values in memory simultaneously is not practical.

• What is the difference between .py and .pyc files?

In Python, .py files contain the source code of a program, while .pyc files store the bytecode representation of the program.

• Write Python code to print the length of each line in a particular file, not counting whitespace at the ends.

def get_line_lengths(file_path):

    with open(file_path, ‘r’) as file:

        for line in file:

            cleaned_line = line.strip()

            print(len(cleaned_line))

get_line_lengths(‘your_file_path.txt’)

• Write Python code to remove the whitespace from the following string – ‘abc def geh ijk’.

input_string = ‘abc def geh ijk’

cleaned_string = input_string.replace(‘ ‘, ”)

print(cleaned_string)

• Write Python code to remove duplicate items from a list.

def remove_duplicates(input_list):

    # Convert the list to a set to remove duplicates

    unique_items = set(input_list)

    # Convert the set back to a list

    result_list = list(unique_items)

    return result_list

# Example usage:

input_list = [1, 2, 2, 3, 4, 4, 5, 6, 6]

unique_list = remove_duplicates(input_list)

print(unique_list)

• What is a dynamically typed language?

Dynamically typed languages are those that don’t need explicit data type declarations for variables. Instead, the interpreter determines the data type of a variable during runtime based on its assigned value.

• What are the common built-in data types in Python?

• Numeric data types: int, float, complex.
• String data types: str.
• Sequence types: list, tuple, range.
• Binary types: bytes, byte array, memory view.
• Mapping data type: dict.
• Boolean type: bool.
• Set data types: set, frozenset. Python Numeric Data Type.

• What is break, continue and pass in Python?

Break, continue, and pass are control flow statements in Python that provide different functionalities within loops.

Break: The break statement is used to prematurely terminate a loop (for loop, while loop) when a specific condition is met. Once the break statement is encountered, the loop is immediately exited, and the program continues with the code following the loop.

Continue: The continue statement is used to skip the remaining code inside a loop for the current iteration only. When the continue statement is encountered, the loop moves to the next iteration, skipping any code that comes after the continue statement within that iteration.

Pass: The pass statement is used as a placeholder when a statement or condition needs to be syntactically present in the code but doesn’t require any action. It is typically used for future code implementation or to create an empty code block that will be filled in later.

• Explain how can you make a Python Script executable on Unix.

On Unix systems, you can specify the path to the Python interpreter at the very beginning of your script to enable execution. Place the line #!/usr/bin/env python as the first line of your .py script. This shebang line tells the system which Python interpreter to use when executing the script.

• What is the difference between Python Arrays and lists?

Lists and arrays share common characteristics such as mutability and ordered storage of elements. However, there are key differences between them. Lists in Python are mutable and can hold elements of different types, offering greater flexibility compared to arrays. On the other hand, arrays are also mutable but are constrained to store elements of the same type.

• What is Scope Resolution in Python?

Scope resolution in Python refers to the process of determining the scope or visibility of a variable, function, or other identifiers within a program.

• Explain how to delete a file in Python.

To delete a file in Python, you can use the os.remove() function from the os module.

import os

file_path = “path/to/your/file.txt”

os.remove(file_path)

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

The split() method in Python is used to split a given string into a list of substrings using a specified separator. On the other hand, the join() method is used to concatenate the elements of a sequence, such as a list, into a single string using a provided separator.

Example

sentence = “Hello, how are you doing today?”

words = sentence.split()

print(words)

# Output: [‘Hello,’, ‘how’, ‘are’, ‘you’, ‘doing’, ‘today?’]

words = [‘Hello,’, ‘how’, ‘are’, ‘you’, ‘doing’, ‘today?’]

sentence = ‘ ‘.join(words)

print(sentence)

# Output: ‘Hello, how are you doing today?’

• What are negative indexes and why are they used?

Negative indexes in Python allow you to access elements from the end of a sequence, such as a list or a string, rather than from the beginning.

Negative indexes are useful when you want to access elements from the end of a sequence without knowing its length. They provide a convenient way to work with elements in reverse order or access elements close to the end of the sequence.

Example:

my_list = [10, 20, 30, 40, 50]

print(my_list[-1])  # Output: 50 (last element)

• How do you create a class in Python?

In Python, you create classes using the class keyword, followed by a colon (:) after the class name. A class is a blueprint that defines the structure and behavior of objects. It consists of attributes (data) and methods (functions).

Example:

class Dog:

    # Attribute

    species = “Canine”

    # Method

    def bark(self):

        print(“Woof!”)

# Creating an object of the class

my_dog = Dog()

# Accessing the attribute

print(“Species:”, my_dog.species)  # Output: Species: Canine

# Calling the method

my_dog.bark()  # Output: Woof!

• How does inheritance work in Python? Explain it with an example.

Inheritance in Python allows a class to inherit attributes and methods from another class, known as the base class or superclass. The class that inherits from the base class is called the derived class or subclass. It enables code reuse and promotes a hierarchical structure in object-oriented programming.

Example:

# Base class

class Animal:

    def __init__(self, species):

        self.species = species

    def make_sound(self):

        print(“Some generic sound”)

# Derived class

class Dog(Animal):

    def __init__(self, breed):

        super().__init__(“Dog”)

        self.breed = breed

    def make_sound(self):

        print(“Woof!”)

# Creating objects

animal_obj = Animal(“Unknown”)

dog_obj = Dog(“Labrador”)

# Accessing attributes and calling methods

print(animal_obj.species)  # Output: Unknown

animal_obj.make_sound()    # Output: Some generic sound

print(dog_obj.species)     # Output: Dog (inherited from the Animal class)

print(dog_obj.breed)       # Output: Labrador

dog_obj.make_sound()       # Output: Woof! (overrides the make_sound() method from the Animal class)

• How do you access parent members in the child class?

To access parent class attributes in a child class, you can use the super() method to invoke the parent class’s constructor within the child class. This allows the child class to initialize and access the attributes defined in the parent class.

• Is it possible to call the parent class without its instance creation?

Yes, you can call a static method of a parent class without creating an instance of the class. Static methods are associated with the class itself rather than any specific instance, and they can be called directly using the class name. This is independent of object-oriented programming, as static methods do not rely on object instances and can be accessed without creating objects.

• How is an empty class created in Python?

In Python, an empty class is created using the pass statement. The pass statement is a special keyword that acts as a placeholder and does nothing when executed. It is used to create a class without any attributes or methods. Despite being empty, objects of such empty classes can still be created and used in Python.

• Differentiate between new and override modifiers.

In Python, the __new__ method allows a subclass to provide a different implementation specific to itself. Method overriding happens implicitly when a subclass defines a method with the same name as a method in the parent class, altering its behavior for that subclass.

• Why is Finalize used?

The finalize method in Python offers a straightforward approach to register a cleanup function that will be called when an object is garbage collected.

• How will you check if a class is a child of another class?

The built-in function issubclass() in Python is used to determine if a class is a subclass of another class. It returns True if the first class is a subclass of the second class; otherwise, it returns False. The function takes two parameters: the class to be checked and the potential superclass.

• What are modules and packages in Python?

In Python, a module is a Python file with a .py extension that contains collections of functions and global variables. It serves as an executable file and helps organize related code. To further organize and group modules, Python introduces the concept of a Package. Packages are directories that contain multiple modules and can have nested sub-packages, providing a structured way to manage and organize code in large projects.

• What is the use of help() and dir() functions?

In Python, the help() function is a built-in function that, when executed with an argument (e.g., a module, function, or class), displays the docstring along with the module name, filename, function name, and constants of the specified argument.

On the other hand, the dir() function is another built-in function in Python used to display the properties and methods of the object passed as an argument to it. It provides a list of valid attributes for the specified object, which can be useful for exploring and understanding the available functionalities of an object.

• How Python is interpreted?

Python is an interpreted language, which means that the code is executed line by line by the Python interpreter, without the need for a separate compilation step. The interpreter reads the code, translates it into machine-understandable bytecode, and executes it directly, allowing for quick and easy code testing and debugging.

• Can you easily check if all characters in the given string is alphanumeric?

The isalnum() method in Python returns True if all the characters in a string are alphanumeric, consisting of alphabet letters (a-z) and numbers (0-9). If the string contains any non-alphanumeric characters such as spaces, symbols, or special characters, the method will return False.

• Define GIL.

The Python Global Interpreter Lock (GIL) is a mutex (lock) that ensures only one thread can have control over the Python interpreter at a time. This means that even in multi-threaded Python programs, only one thread can execute Python bytecode at any given moment.

• Define PIP.

PIP is a recursive acronym for “Preferred Installer Program” or “PIP Installs Packages.” It serves as a command-line utility in Python that simplifies the installation, reinstallation, or uninstallation of PyPI packages. With just one simple command, “pip,” users can manage their Python packages effortlessly.

• Are there any tools for identifying bugs and performing static analysis in Python?

Pychecker and Pylint are the static analysis tools that help to find bugs in Python.

• Differentiate between deep and shallow copies.

In a shallow copy, a new object is created, but it only stores references to the elements of the original object. In contrast, a deep copy creates a completely independent copy of the original object, including all its elements and nested objects.

• What is main function in Python? How do you invoke it?

The user defines a main() function in the program, allowing parameters to be passed based on the program’s needs. The use of a main() function is to invoke the programming code at the run time, not at the compile time of a program

• Define encapsulation in Python.

Encapsulation is a concept in object-oriented programming where data (variables) and the methods that operate on that data are bundled together as a single unit. It involves hiding the internal variables of a class from other classes, allowing access to these variables only through the methods of the same class.

• What is polymorphism in Python?

Polymorphism is a concept in programming that refers to the ability of a class or method to take on different forms or behaviors. In Python, polymorphism allows us to define methods in a child class with the same name as methods in its parent class, enabling the child class to override or extend the behavior of the parent class.

• What advantages do NumPy arrays offer over (nested) Python lists?

Advantages of Using Numpy Arrays Over Python Lists

• Uses less memory.
• Faster than the Python List.
• Simple to use.

• How does Python Flask handle database requests?

In Flask, a Python web framework for creating web applications, database requests can be managed using SQLAlchemy. SQLAlchemy is a powerful toolkit that allows Flask to handle database operations for SQL databases such as MySQL, PostgreSQL, SQLite, and more. By combining Flask with SQLAlchemy, developers can efficiently interact with databases and store or retrieve data in their web applications.

• How is multi-threading achieved in Python?

The threading module in Python provides a high-level implementation of multithreading, enabling developers to deploy applications with concurrent execution. To utilize multithreading, the threading module must be imported into the Python program. The start() method is used to initiate the execution of a thread, allowing multiple threads to run concurrently in the application.

• What is functional programming? Does Python follow a functional programming style? If yes, list a few methods to implement functionally oriented programming in Python.

Functional programming is a programming paradigm that revolves around expressing solutions using pure mathematical functions. It is a declarative style of programming, where the emphasis lies on “what to solve” rather than “how to solve.” In contrast to imperative styles, which focus on defining step-by-step instructions, functional programming prioritizes composing functions to achieve the desired outcome. This approach leads to more concise, clear, and often more maintainable code.

Python is not a strictly functional programming language. But it is trivial to write Python in a functional style. There are three basic functions on iterables that allow us to write a powerful program in a very trivial way: filter, map, and reduce.

• Explain split(), sub(), subn() methods of “re” module in Python.

split(): The split() method in the “re” module is used to split a string based on a specified regular expression pattern. It returns a list of substrings obtained by splitting the original string wherever the pattern matches.

sub(): The sub() method in the “re” module is used to perform substitution or replacement of occurrences of a pattern in a given string. It replaces all occurrences of the pattern with a specified replacement string and returns the modified string.

subn(): The subn() method in the “re” module is similar to sub(), but it returns a tuple containing the modified string and the count of substitutions made instead of just the modified string.

• What do you mean by Python literals?

Python literals represent fixed values that are directly used in code without needing to be computed. They can hold various value types, including strings, numbers, booleans, and more.

• What is a map function in Python?

In Python, map() is a built-in function that acts as an iterator, applying a specified function to each element of an iterable (such as tuples, lists, etc.). It is useful when you need to apply the same transformation function to every element in the iterable. The map() function takes the iterable and the function to be applied as arguments, returning an iterator containing the results of the function applied to each element.

• Do we need to declare variables with respective data types in Python?

Python is not “statically typed”. We do not need to declare variables before using them or declare their type.

• How do you write comments in Python?

In Python, comments are indicated using the hash symbol (#), and they continue from the # symbol to the end of the line.

• What do you understand by the word Tkinter?

Tkinter is a Python library used for creating graphical user interfaces (GUI). It provides a set of tools and widgets to build windows, dialogs, buttons, and other elements for desktop applications.

• Explain all file processing modes supported in Python.

In Python, file processing involves four modes: read-only mode, write-only mode, read-write mode, and append mode. These modes are specified using the flags “r” for read, “w” for write, “rw” for read-write, and “a” for append. Each mode allows different operations on files, such as reading, writing, or both.

Python scripting questions

1.  In file handling, what does the term mean “r, a”?

In file handling, “r” stands for Read mode, allowing you to read the file’s contents without modifying it. “a” stands for Append mode, which lets you write new data to the end of the file without overwriting existing content.

• What will be the code we use to open a file c:\scores.txt for reading?

To open a file “c:\scores.txt” for reading in Python, you would use the following code:

file = open(“c:\\scores.txt”, “r”)

• How will you check if all characters in a string are alphanumeric?

The isalnum() method in Python returns a Boolean value of True if all the characters in a given string are alphanumeric, which means they are either alphabet letters (a-z) or numbers (0-9).

Example:

string1 = “Hello123”

result1 = string1.isalnum()

print(result1)  # Output: True

• How will you capitalize the first letter of a string?

The capitalize() function in Python is used to capitalize the first letter of a string. It returns a new string with the first letter as a capital letter. On the other hand, if you want to capitalize the first letter of each word in the entire string, you should use the title() function.

Example:

text = “hello world”

capitalized_text = text.capitalize()

print(capitalized_text)  # Output: “Hello world”

• How do you insert an object at a given index in Python?

In Python, you can utilize the insert() method to add an item to a list at a specific index. Lists are indexed, meaning each item in a list is assigned a numerical index. The indexing starts at zero (0) for the first item, one (1) for the second item, and so forth.

Example:

my_list = [‘one’, ‘two’, ‘three’]

my_list.insert(1, ‘four’)

print(my_list)  # Output: [‘one’, ‘four’, ‘two’, ‘three’]

• How do you reverse a list?

The reverse() method in Python is a built-in list method used to reverse the order of elements in the list. When you apply the reverse() method, it modifies the original list directly, meaning the changes are made to the list itself and no new list is created.

Example:

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

my_list.reverse()

print(my_list)  # Output: [5, 4, 3, 2, 1]

• In one line, show us how you’ll get the max alphabetical character from a string.

max_alphabet = max(filter(str.isalpha, your_string))

• What will the following code output?

                   word=’abcdefghij’

                   Word[:3]+word[3:]

          word[:3]=’abc

          word[3:]=’defghij’

          word[:3]+word[3:]=’abcdefghij’

• How will you convert a list into a string?

To convert a list into a string in Python, you can use the join() method. The join() method is a string method that concatenates the elements of an iterable (like a list) into a single string, using the specified separator.

Example:

my_list = [‘apple’, ‘orange’, ‘banana’]

result_string = ‘, ‘.join(my_list)

print(result_string)  # Output: “apple, orange, banana”

1. How will you remove a duplicate element from a list?

We can remove a duplicate element from a list using the following methods:

• Using set

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

unique_list = list(set(my_list))

print(unique_list)

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

• Using list comprehension

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

unique_list = [item for index, item in enumerate(my_list) if item not in my_list[:index]]

print(unique_list)

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

• Using a loop

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

unique_list = []

for item in my_list:

    if item not in unique_list:

        unique_list.append(item)

print(unique_list)

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

1. What if you want to toggle the case for a Python string?

To toggle the case of a Python string (i.e., convert uppercase letters to lowercase and lowercase letters to uppercase), you can use the swapcase() method. The swapcase() method is a built-in string method that returns a new string with the case of each letter in the original string toggled.

Example:

my_string = “Hello World”

toggled_string = my_string.swapcase()

print(toggled_string)  # Output: “hELLO wORLD”

1. What is the best code you can write to swap two numbers?

To swap two numbers in Python, you can use a simple one-liner using tuple unpacking. This method allows you to swap the values of two variables without using a temporary variable:

a = 5

b = 10

a, b = b, a

print(“a =”, a)  # Output: a = 10

print(“b =”, b)  # Output: b = 5

1. How can you declare multiple assignments in one statement?

When you need to assign multiple variables in a single line in Python, you can use comma-separated variable names on the left side of the assignment operator, and corresponding values separated by commas on the right side. This allows you to assign values to multiple variables simultaneously.

Example:

x, y, z = 10, 20, 30

print(“x =”, x)  # Output: x = 10

print(“y =”, y)  # Output: y = 20

print(“z =”, z)  # Output: z = 30

1. If you are ever stuck in an infinite loop, how will you break out of it?

An infinite loop in Python is a loop that continues to run indefinitely until it is interrupted externally or encounters a break statement. The loop has no built-in termination condition and will continue executing its code repeatedly until stopped with external intervention, such as using the CTRL + C keyboard shortcut.

1. How do you create a text file using Python?

creating a text file with the command function “w”

f = open(“myfile.txt”, “w”)

This “w” command can also be used create a new file but unlike the the “x” command the “w” command will overwrite any existing file found with the same file name.

1. How do you read and write to an existing file in Python?

To read and write to an existing file in Python, you can use the file handling modes “r” for reading and “w” for writing.

# Reading from an existing file

with open(“data.txt”, “r”) as file:

    content = file.read()

    print(“Existing content:”)

    print(content)

# Writing to an existing file

new_content = “This is the new content that will overwrite the existing one.”

with open(“data.txt”, “w”) as file:

    file.write(new_content)

# Reading the updated content

with open(“data.txt”, “r”) as file:

    updated_content = file.read()

    print(“Updated content:”)

    print(updated_content)

1. How can you convert a CSV file to a data frame in Pandas?

To convert a CSV file to a DataFrame in Pandas, you can use the pandas.read_csv() function. The read_csv() function reads data from a CSV file and creates a DataFrame object that allows you to work with the data in a tabular format.

Example:

import pandas as pd

data_frame = pd.read_csv(“data.csv”)

# Display the DataFrame

print(data_frame)

1. Write a statement in Python to perform the following operations

To open a text file “MYPET.TXT” in write mode

To open a text file“MYPET.TXT” in read mode

To open a text file “MYPET.TXT” in write mode:

file_path = “MYPET.TXT”

with open(file_path, “w”) as file:

    # Perform write operations here, e.g., writing data to the file

    file.write(“Hello, this is a test text.”)

To open a text file “MYPET.TXT” in read mode:

file_path = “MYPET.TXT”

with open(file_path, “r”) as file:

    # Perform read operations here, e.g., reading data from the file

    content = file.read()

    print(content)

1. Write a statement in Python to perform the following operations

To open a binary file “LOG.DAT” in read mode

To open a binary file“LOG.DAT” in write mode

To open a binary file “LOG.DAT” in read mode:

file_path = “LOG.DAT”

with open(file_path, “rb”) as file:

    # Perform read operations on the binary file here

    data = file.read()

To open a binary file “LOG.DAT” in write mode:

file_path = “LOG.DAT”

with open(file_path, “wb”) as file:

    # Perform write operations on the binary file here

    # For example, write binary data to the file

    binary_data = b’\x00\x01\x02\x03′  # Replace this with your binary data

    file.write(binary_data)

• How do you find a number of characters in a Python text file?

To find the number of characters in a Python text file, you can use the len() function in combination with reading the contents of the file.

file_path = “example.txt”  # Replace this with the path to your text file

# Open the file in read mode

with open(file_path, “r”) as file:

    # Read the contents of the file

    content = file.read()

# Find the number of characters in the content

num_characters = len(content)

# Print the result

print(f”The number of characters in the file is: {num_characters}”)

• How do you find a number of words in a Python text file?

To find the number of words in a Python text file, you can use the split() method in combination with reading the contents of the file:

file_path = “example.txt”  # Replace this with the path to your text file

# Open the file in read mode

with open(file_path, “r”) as file:

    # Read the contents of the file

    content = file.read()

# Split the content into words

words = content.split()

# Find the number of words in the content

num_words = len(words)

# Print the result

print(f”The number of words in the file is: {num_words}”)

• How do you find a number of lines in a Python text file?

To find the number of lines in a Python text file, you can use a simple loop to iterate through the file’s contents and count the number of lines:

file_path = “example.txt”  # Replace this with the path to your text file

# Open the file in read mode

with open(file_path, “r”) as file:

    # Initialize a line counter

    num_lines = 0

    # Iterate through each line in the file

    for line in file:

        # Increment the line counter for each line

        num_lines += 1

# Print the result

print(f”The number of lines in the file is: {num_lines}”)

• Write a statement to write the string” Welcome! Please have a seat” in the file wel.txt, that has not yet been created.

text_to_write = “Welcome! Please have a seat”

# Open the file in write mode

with open(“wel.txt”, “w”) as file:

    # Write the string to the file

    file.write(text_to_write)

• A text file “PYTHON.TXT” contains the alphanumeric text. Write a program that reads this text file and writes to another file “PYTHON1.TXT” the entire file except for the numbers or digits in the file.
• Write a program to count the words “to” and “the” present in a text file “python.txt”.

file_path = “python.txt”

# Function to count word occurrences in a list of words

def count_word_occurrences(word_list, target_word):

    count = 0

    for word in word_list:

        if word.lower() == target_word:

            count += 1

    return count

# Read the content from the file

with open(file_path, “r”) as file:

    content = file.read()

# Split the content into words

words = content.split()

# Count occurrences of the words “to” and “the”

word_to_count = count_word_occurrences(words, “to”)

word_the_count = count_word_occurrences(words, “the”)

# Print the results

print(f”Occurrences of ‘to’: {word_to_count}”)

print(f”Occurrences of ‘the’: {word_the_count}”)

• Write a program to display all the lines in a file “python.txt” along with the line/record number.

file_path = “python.txt”

# Open the file in read mode

with open(file_path, “r”) as file:

    # Initialize line number counter

    line_number = 1

    # Iterate through each line in the file

    for line in file:

        # Print the line number and the line content

        print(f”Line {line_number}: {line.strip()}”)

        line_number += 1

• Write a program to display all the lines in a file “python.txt” which have the word “to” in it.

file_path = “python.txt”

# Open the file in read mode

with open(file_path, “r”) as file:

    # Iterate through each line in the file

    for line_number, line in enumerate(file, 1):

        # Check if the word “to” is present in the line

        if “to” in line:

            # Print the line number and the line content

            print(f”Line {line_number}: {line.strip()}”)

• How do you print the summation of all the numbers from 1 to 101?

# Initialize the sum to 0

sum_total = 0

# Iterate through the numbers from 1 to 101 (inclusive)

for num in range(1, 102):

    sum_total += num  # Add the current number to the sum

# Print the summation

print(“The summation of all numbers from 1 to 101 is:”, sum_total)

• Write a Python program to reverse a number.

def reverse_number(number):

    # Convert the number to a string

    number_str = str(number)

    # Reverse the string using slicing with step -1

    reversed_str = number_str[::-1]

    # Convert the reversed string back to an integer

    reversed_number = int(reversed_str)

    return reversed_number

# Test the function with an example number

example_number = 12345

reversed_example = reverse_number(example_number)

print(“Original number:”, example_number)

print(“Reversed number:”, reversed_example)

• What is the best way to add items to a Python array?

There are several ways to add items to an array (also known as a list). The best method depends on your specific use case and requirements:-

Using append() method:

The append() method is used to add a single element to the end of the array.

Using extend() method:

The extend() method is used to add multiple elements from an iterable (e.g., list, tuple, string) to the end of the array.

Using the + operator:

You can use the + operator to concatenate two arrays and create a new array with the combined elements.

Using list comprehension:

List comprehension allows you to create a new array with additional elements based on a condition or transformation.

Using insert() method:

The insert() method is used to add an element at a specific index in the array.

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

There are several ways to remove values from an array (also known as a list). The best method to use depends on the specific requirement and the type of removal you want to perform.

Using remove() method:

The remove() method is used to remove the first occurrence of a specified value from the array.

Using pop() method:

The pop() method is used to remove an element at a specific index from the array. If no index is specified, it removes the last element.

Using list comprehension:

List comprehension can be used to create a new array with elements removed based on a condition.

Using del statement:

The del statement can be used to remove elements at specific indices or delete the entire array.

Using slicing assignment:

Slicing assignment can be used to remove elements by replacing a slice of the array with an empty list.

•  In a NumPy array, how do I extract the indices of N maximum values?

In NumPy, We can use the numpy.argpartition() function to find the indices of the N maximum values in an array efficiently. The function performs a partial sort on the array and returns the indices of the N maximum values.

• Using Python/ NumPy, write code to compute percentiles.

import numpy as np

# Example array

data = np.array([10, 20, 30, 40, 50])

# Compute the 25th percentile

percentile_25 = np.percentile(data, 25)

print(“25th percentile:”, percentile_25)

# Compute the 50th percentile (median)

percentile_50 = np.percentile(data, 50)

print(“50th percentile (median):”, percentile_50)

# Compute multiple percentiles at once

percentiles = np.percentile(data, [25, 50, 75])

print(“25th, 50th, and 75th percentiles:”, percentiles)

Output
25th percentile: 20.0

50th percentile (median): 30.0

25th, 50th, and 75th percentiles: [20. 30. 40.]

• Write a Python program that removes vowels from a string.

def remove_vowels(input_string):

    vowels = “aeiouAEIOU”

    result_string = “”

    for char in input_string:

        if char not in vowels:

            result_string += char

    return result_string

# Test the function

input_string = “Hello, World!”

output_string = remove_vowels(input_string)

print(“Original string:”, input_string)

print(“String after removing vowels:”, output_string)

• Write a Python code to reverse a given list.

def reverse_list(input_list):

    return input_list[::-1]

# Test the function

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

reversed_list = reverse_list(original_list)

print(“Original List:”, original_list)

print(“Reversed List:”, reversed_list)

•  Write a Python program to calculate the mean of numbers in a list.

def calculate_mean(numbers):

    if not numbers:

        return None

    total_sum = sum(numbers)

    mean = total_sum / len(numbers)

    return mean

# Test the function

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

mean_value = calculate_mean(numbers_list)

print(“List of numbers:”, numbers_list)

print(“Mean:”, mean_value)

• Write a Python program to determine whether a number is binary.

def is_binary(number):

    binary_digits = set(’01’)

    return set(str(number)).issubset(binary_digits)

# Test the function

number1 = 101010101

number2 = 12345678

print(number1, “is binary:”, is_binary(number1))

print(number2, “is binary:”, is_binary(number2))

• Write a Python program that rotates an array by two positions to the right.

def rotate_array_by_two(arr):

    if not arr:

        return arr

    n = len(arr)

    k = 2  # Number of positions to rotate

    # Calculate the effective number of rotations

    k = k % n

    # Split the array into two parts

    part1 = arr[:n – k]

    part2 = arr[n – k:]

    # Reverse each part separately

    part1 = part1[::-1]

    part2 = part2[::-1]

    # Join the two parts to get the rotated array

    rotated_array = part2 + part1

    return rotated_array

# Test the function

arr = [1, 2, 3, 4, 5, 6]

rotated_arr = rotate_array_by_two(arr)

print(rotated_arr)  # Output: [5, 6, 1, 2, 3, 4]

• How can you initialize a 5*5 numpy array with only zeroes?

We can initialize a 5×5 NumPy array with all zeroes using the numpy.zeros() function.

import numpy as np

# Initialize a 5×5 array with zeroes

array_5x5 = np.zeros((5, 5))

print(array_5x5)

• How to create a data frame from lists? Give the below data frame drop all rows having Nan.

To create a DataFrame from lists in Python using the pandas library and then drop rows containing NaN values, We can follow these steps:

Import the pandas library.

Create a dictionary using lists for each column in the DataFrame.

Convert the dictionary to a DataFrame.

Use the dropna() method to drop rows with NaN values.

Example:

import pandas as pd

# Sample data in lists

names = [‘Alice’, ‘Bob’, ‘Charlie’, ‘David’, ‘Eva’]

ages = [25, 30, 22, None, 28]

scores = [95, None, 80, 60, 75]

# Create DataFrame directly from lists

df = pd.DataFrame({‘Name’: names, ‘Age’: ages, ‘Score’: scores})

# Drop rows with NaN values

df = df.dropna()

print(df)

• How to access the first five entries of a data frame?

We can access the first five entries of a DataFrame in Python using the .head() method. The .head() method returns the first n rows (by default, n=5) of the DataFrame.

• How to access the last five entries of a data frame?

We can access the last five entries of a DataFrame in Python using the .tail() method. The .tail() method returns the last n rows (by default, n=5) of the DataFrame.

• How to fetch a data entry from the pandas data frame using a given value in the index?

To fetch a data entry from a pandas DataFrame using a given value in the index, We can use the .loc[] method. The .loc[] method allows you to access rows by their index labels.

• Find out the mean, the median and standard deviation of this numpy array -> np.array([1,5,3,100,4,48])

import numpy as np

# Given NumPy array

arr = np.array([1, 5, 3, 100, 4, 48])

# Calculate the mean

mean_value = np.mean(arr)

# Calculate the median

median_value = np.median(arr)

# Calculate the standard deviation

std_dev = np.std(arr)

print(“Mean:”, mean_value)

print(“Median:”, median_value)

print(“Standard Deviation:”, std_dev)

• How can you insert an element at a given index in Python?

We can use the insert() method to insert an element at a given index in a list.

Example:

# Create a list

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

# Define the index where you want to insert the element

index_to_insert = 2

# Define the element you want to insert

element_to_insert = 100

# Use the insert() method to insert the element at the specified index

my_list.insert(index_to_insert, element_to_insert)

print(my_list)

• How to create a new column in pandas by using values from other columns?

import pandas as pd

# Sample DataFrame

data = {

    ‘column1’: [10, 20, 30, 40, 50],

    ‘column2’: [5, 10, 15, 20, 25]

}

df = pd.DataFrame(data)

# Create a new column “total” by adding values from “column1” and “column2”

df[‘total’] = df[‘column1’] + df[‘column2’]

print(df)

• How to delete a column or group of columns in pandas? Given the below dataframe drop column “col1”.

We can delete a column or group of columns in pandas using the drop() method of the DataFrame.

Example:

import pandas as pd

# Sample DataFrame

data = {

    ‘col1’: [1, 2, 3, 4, 5],

    ‘col2’: [6, 7, 8, 9, 10],

    ‘col3’: [11, 12, 13, 14, 15]

}

df = pd.DataFrame(data)

# Drop the column “col1”

df.drop(‘col1’, axis=1, inplace=True)

print(df)

• Given the following data frame drop rows having column values as A.

To drop rows from a pandas DataFrame that have a specific value in a certain column (e.g., “A” in column “col1”), We can use the drop() method along with boolean indexing.

Example:

import pandas as pd

# Sample DataFrame

data = {

    ‘col1’: [‘A’, ‘B’, ‘C’, ‘A’, ‘D’],

    ‘col2’: [1, 2, 3, 4, 5],

    ‘col3’: [6, 7, 8, 9, 10]

}

df = pd.DataFrame(data)

# Drop rows where column “col1” has the value “A”

df = df[df[‘col1’] != ‘A’]

print(df)

• Create a lambda function that will print the sum of all the elements in this list -> [5, 8, 10, 20, 50, 100]

my_list = [5, 8, 10, 20, 50, 100]

# Define a lambda function to print the sum of the elements in the list

sum_lambda = lambda lst: print(sum(lst))

# Call the lambda function with the list as an argument

sum_lambda(my_list)

• How can you find the minimum and maximum values present in a tuple?

To find the minimum and maximum values present in a tuple, We can use the min() and max() functions, respectively.

• Write a Python program to reverse each word of a string.

def reverse_words_in_string(input_string):

    # Split the input string into words

    words = input_string.split()

    # Reverse each word in the list

    reversed_words = [word[::-1] for word in words]

    # Join the reversed words back into a new string

    reversed_string = ” “.join(reversed_words)

    return reversed_string

# Test the function

input_string = “Hello World”

reversed_string = reverse_words_in_string(input_string)

print(reversed_string)

• Write a Python program to read text file into a variable and replace all newlines with space.

def read_file_and_replace_newlines(file_path):

    try:

        with open(file_path, ‘r’) as file:

            content = file.read()

            # Replace newlines with spaces

            content_with_spaces = content.replace(‘\n’, ‘ ‘)

        return content_with_spaces

    except FileNotFoundError:

        print(“File not found.”)

        return None

# Example usage

file_path = ‘example.txt’  # Replace ‘example.txt’ with the path to your text file

modified_text = read_file_and_replace_newlines(file_path)

if modified_text is not None:

    print(modified_text)

• How would you confirm that 2 strings have the same identity?

We can use the is keyword to check if two strings have the same identity, which means they refer to the same memory location.

• How would you check if each word in a string begins with a capital letter?

We can check if each word in a string begins with a capital letter by using Python’s split() method to split the string into individual words and then checking the first character of each word.

• How to find the index of the first occurrence of a substring in a string?

We can find the index of the first occurrence of a substring in a string by using the find() method or the index() method. Both methods will return the index of the first occurrence of the substring.

• What is an f-string and how do you use it?

F-strings in Python allow for the embedding of expressions within string literals using a minimal and straightforward syntax. They are not constant values but rather expressions that are evaluated at runtime. When using f-strings in Python source code, they are defined as literal strings with a prefix of ‘f’, and they contain expressions enclosed within braces {}. These expressions are dynamically evaluated, and their values are inserted into the resulting string at runtime. This feature makes f-strings a powerful and convenient way to format strings with dynamic content.

• How to check if a string contains only numbers?

We can check if a string contains only numbers in Python using isdigit() function.

• What is the purpose of using splitlines()?
• How to remove whitespace from the left, right, or both sides of a string?
• How to check if a string begins with or ends with a specific character?
• How to capitalize the first character of each word in a string?