Python Questions and Answers for Viva

Answer-1: Python is a high-level, interpreted programming language known for its simplicity and readability. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming.

Answer-2: Key features of Python include:
Easy-to-read syntax
Dynamic typing
Automatic memory management (garbage collection)
Extensive standard library
Interpreted nature
Portability

Answer-3: The main differences between Python 2 and Python 3 are
Python 2 has reached its end of life and is no longer maintained, while Python 3 is actively developed and supported.
Python 3 has several syntactical and feature improvements over Python 2, such as print function, integer division, and Unicode support.

Answer-4: PEP 8 is the style guide for Python code. It defines the recommended coding conventions to ensure consistency and readability in Python code.

Answer-5: Comments in Python start with the '#' symbol and continue until the end of the line. They are used to add explanatory notes or documentation to the code.

Answer-6: Indentation is used in Python to define blocks of code. It is crucial for maintaining the structure and readability of the code, as Python relies on indentation to denote scope.

Answer-7: Python supports various data types, including integers, floats, strings, lists, tuples, dictionaries, sets, and booleans.

Answer-8: Variables in Python are declared by simply assigning a value to a name using the assignment operator '='. For example, 'x = 10'.

Answer-9: Type inference in Python refers to the ability of the interpreter to automatically determine the data type of a variable based on the value assigned to it. Python is dynamically typed, so variables do not have explicit types.

Answer-10:
The '==' operator is used to compare the values of two objects for equality.
The 'is' operator is used to compare the identities of two objects, i.e., whether they refer to the same object in memory.

Answer-11: Strings in Python can be concatenated using the '+' operator or by using string formatting methods like 'str.format()' or f-strings (formatted string literals).

Answer-12: Mutable data types in Python can be modified after creation (e.g., lists, dictionaries), while immutable data types cannot be modified once created (e.g., integers, strings, tuples).

Answer-13: List comprehension is a concise way to create lists in Python by applying an expression to each item in an iterable. It consists of square brackets containing an expression followed by a 'for' loop.

Answer-14:
Lists are mutable, meaning their elements can be modified after creation, while tuples are immutable.
Lists are enclosed in square brackets '[ ]', while tuples are enclosed in parentheses '( )'.

Answer-15: A dictionary in Python is an unordered collection of key-value pairs. It is mutable, iterable, and can contain elements of different data types.

Answer-16: You can iterate over a dictionary using a 'for' loop. By default, the loop iterates over the keys of the dictionary, but you can access both keys and values using the '.items()' method.

Answer-17:
Sets are unordered collections of unique elements, while dictionaries are unordered collections of key-value pairs.
Sets are enclosed in curly braces '{ }', while dictionaries are enclosed in curly braces '{ }' with key-value pairs separated by colons ':'.

Answer-18: A module in Python is a file containing Python code, typically containing functions, classes, and variables. Modules allow for code reuse and organization.

Answer-19:
'import module' imports the entire module namespace, requiring the use of the module name to access its contents.
'from module import *' imports all names from the module into the current namespace, allowing direct access to the module's contents without using the module name.

Answer-20: A package in Python is a directory containing multiple modules and a special file called '__init__.py'. Packages allow for hierarchical organization of modules.

Answer-21: Exceptions in Python are handled using 'try', 'except', and 'finally' blocks. Code that may raise an exception is placed inside the 'try' block, and exception handling logic is defined in the 'except' block.

Answer-22: The 'finally' block in exception handling is used to define cleanup code that should be executed regardless of whether an exception occurs or not. It is often used to release resources or perform cleanup tasks.

Answer-23: The '__init__' method is a special method in Python classes that is called automatically when a new instance of the class is created. It is used to initialize the object's state and perform any necessary setup tasks.

Answer-24: Inheritance is the mechanism in object-oriented programming where a class (subclass) inherits attributes and methods from another class (superclass). It allows for code reuse and promotes modularity.

Answer-25: Method overriding is the ability of a subclass to provide a specific implementation of a method that is already defined in its superclass. The overridden method in the subclass takes precedence over the method in the superclass.

Answer-26: Method overloading is not directly supported in Python. However, you can achieve similar behavior by using default parameter values or variable-length argument lists.

Answer-27: Lambda functions, also known as anonymous functions, are small, inline functions defined using the 'lambda' keyword. They are typically used for short, simple operations where defining a named function would be overkill.

Answer-28: Decorators are functions that modify the behavior of other functions or methods. They allow you to add functionality to existing functions dynamically, without modifying their source code.

Answer-29: A generator in Python is a special type of iterator that generates values on-the-fly using the 'yield' keyword. Generators are memory-efficient and allow for lazy evaluation of data.

Answer-30: The 'yield' keyword is used in generator functions to yield a value to the caller without terminating the function. It allows for the creation of iterators and enables lazy evaluation.

Answer-31: Files in Python are typically opened using the 'open()' function, specifying the file path and mode (e.g., ''r'' for read, ''w'' for write). They should be closed using the 'close()' method or by using a 'with' statement, which automatically closes the file when the block is exited.

Answer-32: The 'with' statement in Python is used to create a context manager that automatically handles resource management (e.g., file closing, database connections) within a specific block of code.

Answer-33: File reading and writing in Python are typically done using the 'read()', 'readline()', 'readlines()', 'write()', and 'writelines()' methods of file objects, depending on the desired operation.

Answer-34: Common file modes in Python include:
''r'': Read mode
''w'': Write mode (creates a new file or truncates an existing file)
''a'': Append mode (appends data to the end of an existing file)
''b'': Binary mode (for handling binary files)
''+'': Read and write mode

Answer-35: The 'os' module in Python provides functions for interacting with the operating system, such as file management, directory operations, process management, and environment variables.

Answer-36: The 'sys' module in Python provides access to system-specific parameters and functions, such as command-line arguments, Python runtime environment, and interpreter settings.

Answer-37: The 're' module in Python provides support for regular expressions, allowing you to search, match, and manipulate text patterns in strings.

Answer-38: Third-party packages in Python can be installed using package managers like pip ('pip install package_name'). They can also be installed manually by downloading the package source code and using setup tools ('python setup.py install').

Answer-39: A virtual environment in Python is a self-contained directory that contains a Python interpreter and a set of installed packages. It allows you to isolate project dependencies and avoid conflicts between different projects.

Answer-40: The 'unittest' module in Python provides a framework for writing and running unit tests. It allows you to define test cases, test suites, and assertions to verify the correctness of your code.

Answer-41: The 'logging' module in Python provides a flexible and customizable framework for logging messages from your Python programs. It allows you to control the verbosity, formatting, and destination of log messages.

Answer-42: The 'datetime' module in Python provides classes and functions for working with dates, times, and time intervals. It allows you to perform various operations, such as date arithmetic, formatting, and parsing.

Answer-43: The 'json' module in Python provides functions for encoding and decoding JSON (JavaScript Object Notation) data. It allows you to convert Python objects to JSON strings and vice versa.

Answer-44: The 'requests' module in Python provides a simple and elegant way to make HTTP requests and handle responses. It allows you to send GET, POST, PUT, DELETE, and other types of requests, and supports features like session management, cookies, and authentication.

Answer-45: The 'BeautifulSoup' library in Python is a popular web scraping library that allows you to extract data from HTML and XML documents. It provides a simple interface for navigating and manipulating the document tree.

Answer-46: The 'numpy' library in Python provides support for numerical computing and array manipulation. It introduces the 'ndarray' data structure, which allows for efficient storage and manipulation of multidimensional arrays.

Answer-47: The 'pandas' library in Python provides high-performance, easy-to-use data structures and data analysis tools. It introduces the 'DataFrame' data structure, which allows for efficient manipulation and analysis of structured data.

Answer-48: The 'matplotlib' library in Python provides functions for creating static, interactive, and animated visualizations. It allows you to generate various types of plots, including line plots, scatter plots, bar plots, and histograms.

Answer-49: The 'scikit-learn' library in Python provides machine learning algorithms, preprocessing techniques, and evaluation metrics for building and evaluating predictive models. It supports various tasks, such as classification, regression, clustering, and dimensionality reduction.

Answer-50: The 'tensorflow' library in Python is an open-source machine learning framework developed by Google. It provides a flexible and scalable platform for building and deploying machine learning models, particularly deep learning models.