feat(weights): implementation and testing

[grantdfoster]

Summary of Changes

1. Makefile Enhancements

• New Test Targets: Added test-weights-unit and test-weights-e2e targets to the Makefile for running unit and end-to-end tests related to weights management.

2. New Data Class in interfaces/types.py

• NodeData Class: Introduced a new NodeData class with attributes hotkey, posts, uptime, and latency. This class is designed to encapsulate node-related data and is marked as JSONSerializable.

3. Version Update in neurons/__init__.py

• Version Bump: Updated the version from 0.3.0 to 2.0.0, indicating significant changes or improvements in the codebase.

4. Validator Enhancements in neurons/validator.py

• New Managers: Integrated WeightsManager and NodeDataScorer into the Validator class.
• Background Task: Added a new asynchronous task set_weights_loop to periodically set weights using the WeightsManager.

5. New Tests for Weights Management

• End-to-End Test (tests/test_weights_e2e.py): Created a test to verify the end-to-end functionality of the weights management system, including weight calculation and setting.
• Unit Test (tests/test_weights_unit.py): Developed unit tests for the WeightsManager, focusing on weight calculation and setting logic with mocked dependencies.

6. Background Task in validator/background_tasks.py

• Set Weights Loop: Implemented a new background task set_weights_loop to continuously update node weights based on data from NodeDataScorer.

7. Node Data Scoring in validator/scorer.py

• NodeDataScorer Class: Introduced a class to score node data, currently using a stub for node data. This class is intended to be expanded to fetch real data in the future.

8. Weights Management in validator/weights.py

• WeightsManager Class: Added a class to manage node weights, including methods to calculate and set weights on the blockchain.
  • Weight Calculation: Weights are calculated based on node post counts, normalized across the range of posts.
  • Blockchain Interaction: Ensures weights are set on the blockchain, respecting minimum intervals between updates and handling retries on failure.

Key Features and Improvements

• Modular Design: The introduction of WeightsManager and NodeDataScorer promotes a modular approach, making the system more maintainable and extensible.
• Automated Testing: New tests ensure the reliability of the weights management system, facilitating future development and refactoring.
• Background Processing: The addition of background tasks for syncing and setting weights enhances the system's efficiency and responsiveness.

This pull request significantly enhances the functionality related to node weight management, providing a robust framework for future developments in this area.