"Uttam Singh's Tech and Science Odyssey"

  The ' yield' keyword is used in Python to define a generator function. A generator function is a special type of function that generates a sequence of values, one at a time, instead of returning a single value. The main difference between a generator function and a regular function is that a generator function uses the ' yield' keyword to return a value, instead of the ' return' keyword. When a generator function is called, it returns a generator object, which can be iterated over using a ' for' loop or other iteration tools. Here is an example of a simple generator function: When you run this code, it will output the numbers 1 through 5, one at a time. The generator function ' count_up_to' is called once, and each time it hits a yield statement, it returns the current value of ' count' and pauses its execution until the next iteration. This allows the generator to produce values one at a time, which can be useful for processing ...

A decorator is a special type of function in Python that is used to modify or extend the behavior of another function, method, or class. They are often used to add additional functionality to existing functions or classes, such as logging, timing, or access control. In Python, decorators are applied to functions or classes using the "@" symbol, followed by the name of the decorator function. For example:   When you run this code, calling the ' say_hello()' function will first print "Something is happening before the function is called", then "Hello!", and then "Something is happening after the function is called". Decorators can also accept arguments and preserve the original function's metadata, such as its name, docstring, and arguments. The use of decorators provides a convenient and reusable way to add additional functionality to your functions and classes, making your code cleaner and more maintainable.

  Classes in Python are a blueprint for creating objects, providing structure for data and methods that operate on that data. Objects are instances of a class, and each object has its own set of data and methods. To define a class in Python, you use the class keyword followed by the name of the class, with the class definition inside a block of indented code: An object is created from a class using the class name followed by parentheses: To add data to a class, you can use class variables, which are defined within the class definition but outside of any methods. For example: To add behavior to a class, you can define class methods, which are functions that operate on the class variables. The first argument of a class method is always self, which refers to the instance of the object being operated on.

  Handling errors and exceptions in Python is an important aspect of writing reliable and robust code. In Python, exceptions are raised when something unexpected happens during the execution of the program. You can handle exceptions in Python using a try-except block. The try block contains the code that might raise an exception, and the ' except' block contains the code that will handle the exception if it is raised. Here is an example of how to handle a division by zero error: In this example, we attempt to divide 5 by 0, which raises a ZeroDivisionError exception. The ' except' block catches the exception and prints a message to the console indicating what went wrong. You can also handle multiple exceptions by using multiple ' except' blocks: In this example, the ' try' block raises a ' ValueError' exception because "abc" cannot be converted to an integer. The first ' except' block catches this exception and prints a...

  Python arrays and lists are both used to store collections of items, but there are some key differences between the two. An array is a more efficient data structure compared to a list because arrays are fixed-size and all elements are of the same type, while lists are dynamic and can contain elements of different types. This means that arrays use less memory and are faster when it comes to accessing elements, making them ideal for numerical computations. Here is an example in Python to demonstrate the difference between arrays and lists: In the example above, we import the array module and create an array of integers. We also create a list of integers. When we print both the array and the list, we can see that they both store the same values, but the array is declared with a specific data type (integer) while the list can contain elements of different types.

  To make a Python script executable on Unix, you need to add a shebang line at the beginning of the script, which tells the system what interpreter to use to run the script. The shebang line should be in the following format: #!/usr/bin/env python3 Next, you need to make the script file executable by running the following command in the terminal: chmod +x script.py This allows the file to be executed as a program. You can now run the script by typing ./script.py in the terminal.

  Slicing in Python is a way to extract a portion or subset of a sequence, such as a string, list, or tuple. It is done by specifying two indices separated by a colon (:). The first index is the starting position, and the second index is the ending position. For example, if you have a list of numbers called ' numbers' , you can extract the first three elements like this: This will output ' [1, 2, 3]' , which is the first three elements of the numbers list. You can also omit the starting index to start from the beginning, or omit the ending index to go to the end, like this: This will output ' [2, 3, 4, 5]' , which is all the elements of the numbers list except for the first one. Slicing is a powerful and flexible tool that allows you to work with sublists, substrings, and sub-arrays in an efficient and concise way.