causal-priority-queue 1.0.0

A dynamically adjusting priority queue with causal influences.

Causal Priority Queue (CPQ)

Overview

Causal Priority Queue (CPQ) is a dynamically adjusting priority queue where:

• Priorities are not static but dynamically change based on causal influences.
• Items in the queue influence each other based on relationships.
• Designed for AI scheduling, intelligent load balancing, and real-time prioritization.

How It Works

Unlike traditional priority queues where elements have fixed priorities, CPQ:

1. Stores influences as a graph where tasks affect each other.
2. Adjusts priorities dynamically when tasks are processed.
3. Ensures efficient priority updates using a heap-based structure.

Installation

You can install CPQ by cloning the repository:

git clone https://github.com/mukerjeejoy-github/causal-priority-queue.git
cd CausalPriorityQueue

Usage Example

from causal_priority_queue.cpq import CausalPriorityQueue

cpq = CausalPriorityQueue()
cpq.add_task("Task A", priority=3, influences=["Task B"], influence_weight=2)
cpq.add_task("Task B", priority=5)
cpq.add_task("Task C", priority=8)

print("Before popping:", cpq.get_tasks())
print("Popped:", cpq.pop_task())
print("After popping:", cpq.get_tasks())

🔍 Benchmarks

Data Structure	Time Taken (10,000 tasks)
Causal Priority Queue (CPQ)	0.019 sec
Standard Priority Queue (heapq)	0.009 sec
SortedDict Priority Queue	0.006 sec

🤝 Contributing

1. Fork the repository.
2. Create a feature branch.
3. Commit changes and create a pull request.

📜 License

This project is licensed under the MIT License. See LICENSE for details.