CoreB

CoreB is a library for managing concurrent function execution and control in Python applications. This library includes capabilities for managing ThreadPoolExecutor, controlling processes with Controller, handling function outputs with Return, and executing tasks with Agent.

Features ✨

• Manage concurrent function execution using ThreadPoolExecutor
• Pause and resume function execution with Controller
• Handle function outputs with Return
• Manage and execute tasks in the processing core with Agent
• Optimized structure for executing tasks in a processing loop with Loop

Installation 📦

Run the pip install -r requirements.txt command and add the CoreB file to your project.

Usage 📖

import time
from CoreB import Controller, Agent, Core

# Create a controller
controller = Controller(name="event")

def func(name, size=6, delay=1):
    for i in range(size):
        if controller.is_pause():
            controller.wait_until_pause()
        print(f"{i + 1} from {name}")
        time.sleep(delay)

# Define tasks
tasks = [Agent(func, name="func1", size=10, _return_name="func1"), Agent(func, name="func2", _return_name="func2")]
core = Core(list_of_agents=tasks)
core.set_controller(controller)
core.run()

# Pause and resume execution
time.sleep(3)
core.pause("event")
core.add_task(Agent(func, name="func3 added", _return_name="func3"))
time.sleep(7)
core.resume("event")

Classes and Descriptions 🔍

1. Controller

A class for controlling function execution throughout the program.

• pause(): Pause execution
• resume(): Resume function execution
• wait_until_pause(timeout): Wait until the controller resumes execution
• is_pause() -> bool: Check the pause status

2. Agent

This class represents a function to be executed in CoreB.

• Takes a function, arguments, and a unique name for storing output as input.

3. Core

The main class responsible for executing tasks.

• run(): Execute added functions
• pause(controller_name): Pause execution of functions associated with a specific controller
• resume(controller_name): Resume execution of functions
• add_task(*agents): Add new tasks while running

4. Return

Stores the outputs of executed functions in CoreB.

5. Loop

Manages task execution within a processing loop.

TODO 🛠️

• Implementing advanced logging
• Implementing better methods for computing the number of Workers based on CPU conditions
• Add documentation for all classes and methods.
• Implement unit tests for core functionalities.
• Create examples demonstrating usage of the core.
• Optimize performance for large-scale tasks.
• Ensure compatibility with projects that have a main loop.

License 📜

This project is released under the MIT license. Usage, modification, and distribution are permitted.

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🚀 CoreB is a simple and powerful solution for managing concurrent processing in Python!