Save each module with a .py extension, then import them into whichever modules require them, including the main module.
MODULES ALSO REDUCE THE DUPLICATION OF CODE WITHIN A PROGRAM..THIS BENEFIT OF USING MODULES IS KNOWN AS code reuse BECAUSE YOU ARE WRITING THE CODE TO PERFORM A TASK ONCE AND THEN REUSING IT EACH TIME YOU NEED TO PERFORM A TASK.
Python parallel processing within a for loop can be implemented using the concurrent.futures module. By creating a ThreadPoolExecutor and using the map function, you can execute multiple tasks concurrently within the for loop. This allows for faster execution of the loop iterations by utilizing multiple CPU cores.
MODULES ALSO REDUCE THE DUPLICATION OF CODE WITHIN A PROGRAM..THIS BENEFIT OF USING MODULES IS KNOWN AS code reuse BECAUSE YOU ARE WRITING THE CODE TO PERFORM A TASK ONCE AND THEN REUSING IT EACH TIME YOU NEED TO PERFORM A TASK.
Modules refer to individual units or sections within a course that cover specific topics or concepts, whereas curriculum is the overall plan or framework that outlines the goals, content, and sequence of a course or educational program. Modules are like building blocks that make up the curriculum as a whole.
Parallel processing in Python can be implemented using the multiprocessing module. By creating multiple processes within a for loop, each process can execute a task concurrently, allowing for parallel processing.
Answer: Function "A function is a group of statements that exist within a program for the purpose of performing a specific task." (Source: Starting out with Python - Second Edition, Tony Graddis, Page 81)
Assuming you only intend executing your code on your own machine and you have some version of Python installed, you can execute a Python script from within your code in the same way you can execute a Python script via the command line: python script.py infile outfile -o
Modular programming is the technique which divides the entire program into smaller modules, which perform a specific task. Even though the simple program structure works well for simple examples, it is counter-productive for longer programs, leading to lack of clarity and slowing code maintenance and modification. The programmer designs the program in levels, where a level consists of one or more modules. The first level is a complete main program and modules at successive levels consist of sub modules referenced in the prior levels. A module is a set of program statements which, when acting together complete a specific task. In practice a module can be a function and the main program can consist of a sequence of calls to the functions that represent the modules of the next levels down. The order in which the modules are executed by the computer is controlled by the main program. This describes fully the procedures required in the solution to a problem. The procedures are written in the order of the machine execution. Modules should be structured within themselves by incorporating the constructs of sequencing, selection and repetition. Every program can and should be written using only these constructs.
Py2app for the Mac, or Py2exe for Windows, create a standalone executable file from a Python program, which can run without the Python interpreter. You can always run the application within the Python interpreter. If you want to create an executable file, Python includes no built-in tools to do this; you need an application such as Py2app or Py2exe. Of course, you might search for alternative tools, that do the same thing.
The SSD 1 Module 3 covers topics related to the Defense Equal Opportunity Program (DEOMI) and cultural awareness. These modules aim to educate military personnel on diversity, inclusion, and equal opportunity within the armed forces.
Ditto code refers to code that is repeated or duplicated in multiple places within a program. This can lead to maintenance issues and make it more difficult to make changes or fix bugs. It is generally considered a best practice to refactor ditto code into reusable functions or modules to improve code maintainability.
In Python, a namespace is a system that organizes and manages the names (identifiers) used in a program. It serves as a container that keeps track of the mappings between names and the objects they refer to. Namespaces help prevent naming conflicts and provide a way to access and manage variables, functions, classes, modules, and other objects within a program. Here are a few key points about Python namespaces: Namespace Hierarchy: Namespaces are organized in a hierarchical structure known as the namespace hierarchy. At the top level, there is the built-in namespace that contains Python's built-in functions and types. Below it, there are global namespaces for each module or script, and within each module, there can be nested local namespaces for functions or classes. Scope: Each namespace has a specific scope, which defines the visibility and lifetime of the names within it. The scope determines where a particular name can be accessed or referenced in the code. Names can be either local to a specific function or class, or they can be global, visible throughout the module or script. Name Resolution: When a name is referenced in Python, the interpreter looks for that name within the available namespaces following a specific order called the "LEGB" rule. It checks the Local namespace first, then the Enclosing (nested) namespaces, followed by the Global namespace, and finally the Built-in namespace. This order determines which object a name refers to, and if the name is not found in any of the namespaces, a NameError is raised. Creating and Modifying Namespaces: Namespaces are created implicitly as you define variables, functions, classes, or import modules. You can also create namespaces explicitly using the `namespace` or `dict` objects. By organizing names into separate namespaces, Python provides a structured and manageable approach to name resolution and prevents naming conflicts, allowing for more organized and modular code. Understanding namespaces is essential for writing and maintaining Python programs effectively.