Python Interview Questions and Answers- Part 4

Answer:

Unlike several other languages, Python does not directly support method overloading. However, using default parameters or variable-length arguments will allow you to accomplish a comparable level of functionality.

Answer:

A decorator in Python is a design pattern that allows adding functionality to an existing function or class dynamically, without modifying its source code. Decorators use the @decorator_name syntax and can modify or extend the behavior of the decorated object. They are often used for tasks like logging, timing, and access control.

Answer:

Python supports the following built-in data types:

• Immutable data types: Number, String, Tuple
• Mutable data types: List, Dictionary, Set

Answer:

Descriptors are a powerful feature in Python that allow you to define how attribute access is handled in a class. They are defined using special methods such as `__get__()`, `__set__()`, and `__delete__()`. Descriptors enable you to customize the behavior of attribute access, allowing you to implement computed properties, data validation, or custom behavior.

Answer:

`__getattr__()` is called when an attribute is not found via normal lookup. It allows you to define custom behavior when accessing non-existent attributes. `__getattribute__()` is called for every attribute access, regardless of whether the attribute exists or not. It is typically used for implementing attribute interception or logging.

Answer:

`__new__()` is a static method that is called to create an instance of a class. It is responsible for object creation and can return a new object of the class. `__init__()` is an instance method that is called after the object has been created. It initializes the object’s attributes and performs any necessary setup.

Answer:

To make a Python script executable on Unix/Linux systems, you need to add a shebang line at the top of the script, specifying the path to the Python interpreter. For example, `#!/usr/bin/env python3` indicates that the script should be run with the `python3` interpreter. Additionally, you need to set the script’s file permissions to allow execution using the `chmod` command.

Answer:

`*args` helps pass a variable number of non-keyword arguments to a function. Using it, you can pass any number of positional arguments, which are then accessible as a tuple inside the function. `**kwargs`, on the other hand, helps to pass a variable number of keyword arguments to a function. It allows you to pass any number of keyword arguments, which are then accessible as a dictionary inside the function.

Answer:

The `__slots__` attribute in Python classes is used to explicitly define the list of allowed attributes for instances of the class. By using `__slots__`, you can optimize memory usage and improve attribute access speed. However, it restricts the creation of additional attributes on instances.

Answer:

Method chaining is a programming technique that allows you to call multiple methods on an object in a single line, by returning the object itself from each method call. It enables a more concise and readable syntax for performing a series of operations on an object.

Answer:

Python’s type conversion functionality helps convert one form of data type into the needed one. Type Conversion is classified into two types:

1. Implicit Type Conversion: When python interpreter helps to automatically convert the data type into another data type without involving any User.
2. Explicit Type Conversion: In this form of Type conversion, the user changes the data type inn into a required type.

Answer:

Yes, Python programming is a case sensitive language, so, both Function and function will have different meanings in pythons like SQL and Pascal.

Answer:

Python provides various profiling tools, such as `cProfile` and `line_profiler`, to identify performance bottlenecks in code. Optimizations can be done by using efficient data structures, algorithmic improvements, caching, or utilizing built-in functions and libraries optimized for specific tasks.

Answer:

The `async` and `await` keywords are used in asynchronous programming with Python’s `asyncio` module. They allow you to define coroutines, which are functions that can be paused and resumed while waiting for I/O or other tasks to complete. `async` is used to declare a coroutine function, and `await` is used to suspend execution until the awaited coroutine is complete.

Answer:

Context managers in Python are objects that define the methods `__enter__()` and `__exit__()`. They allow you to manage resources, such as file handles or database connections, in a clean and efficient way. The `with` statement is used to create a context and automatically handle the setup and teardown of resources.

Answer:

The split(), sub(), and subn() methods are part of Python’s “re” module, which is used for working with regular expressions. These methods offer string manipulation capabilities.

• The split() method is utilized to split a given string into a list based on a specified pattern.
• The sub() method searches for occurrences of a regular expression pattern in a string and replaces them with a different string.
• The subn() method is similar to sub(), but it also returns the modified string along with the count of replacements made.

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Answer:

In Python, literals are the specific values that are assigned to variables or used as constants in a program. Python supports different types of literals, including:

String Literals:

These are represented by enclosing text in single (”) or double quotes (“”). For example: “Intellipaat”, ‘45879’.

Numeric Literals:

Python supports three types of numeric literals:

Integer: Whole numbers without decimal points. For example: i = 10.

Float: Numbers with decimal points. For example: f = 5.2.

Complex: Numbers in the form a + bj, where a and b are real numbers and j represents the imaginary unit. For example: c = 1.73j.

Boolean Literals:

Boolean literals represent the boolean values True or False. For example: x = True.

These literals provide specific values that can be used within a Python program for various purposes.

Answer:

Dict and list comprehensions are concise ways to create new dictionaries or lists by performing operations on existing ones. They provide a compact syntax for transforming and filtering data without the need for explicit loops.

Dict comprehensions allow you to create new dictionaries by specifying key-value pairs and optional conditions in a single line of code. They are enclosed in curly braces ({}) and follow the format {key_expression: value_expression for item in iterable if condition}.

List comprehensions work similarly but create new lists instead. They are enclosed in square brackets ([]) and have the format [expression for item in iterable if condition].

Comprehensions are useful in scenarios where you want to perform operations on an entire list or dictionary, apply conditional filtering, combine multiple lists, or flatten a multi-dimensional list. They offer a more concise and efficient alternative to traditional loop constructs.

Answer:

Comments in Python are used by programmers to provide explanatory notes and increase code readability. There are two ways to write comments in Python:

Single-line comments: Single-line comments are created using the hash symbol (#). Any text after the # symbol on the same line is considered a comment. For example:

# This is a comment in Python

print(“This is not a comment”)

Multi-line comments: Multi-line comments, also known as docstrings, are enclosed within triple quotes (”’ ”’). They can span multiple lines and are commonly used for function or class documentation. For example:

”’

This is a multi-line comment in Python.

It can span multiple lines and is often used for documentation.

”’

print(“This is not a comment”)

Both single-line and multi-line comments are ignored by the Python interpreter and do not affect the execution of the code. They are solely meant to provide information to developers and make the code more understandable.

Answer:

Tkinter is a module that comes bundled with Python and is used for creating graphical user interface (GUI) applications. It serves as the standard GUI toolkit for Python and provides a set of functions, classes, and methods that allow developers to build interactive and visually appealing applications.

Tkinter provides access to the Tk GUI toolkit, which is based on the Tkinter library originally developed for the Tcl programming language. With Tkinter, developers can create windows, buttons, menus, dialogs, and other GUI components to build desktop applications. Tkinter’s integration with Python makes it a popular choice for creating cross-platform GUI applications.