Optimize performance and scalability for increasing loads and data volumes (✓ Sandbox Passed)

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Description

This pull request aims to optimize the performance and scalability of the application by implementing various improvements and enhancements. It includes modifications to the backend/optimization.py, components/PerformanceTracking.js, and personalized_learning_ai.py files.

Summary

• Added imports in backend/optimization.py to components.PerformanceTracking module and other necessary modules.
• Implemented optimization logic in backend/optimization.py to improve algorithms, data structures, and resource allocation based on identified bottlenecks and constraints.
• Utilized the Sweep AI configuration to measure and evaluate performance metrics, code quality score, resource utilization metrics, and scalability benchmarks.
• Continuously monitor performance metrics and resource utilization to adapt optimization strategies based on observed results.
• Removed unnecessary code in components/PerformanceTracking.js.
• Added function calls to optimize algorithms, improve data structures, parallelize, and allocate resources in components/PerformanceTracking.js.
• Modified personalized_learning_ai.py by adding an import statement.

Please review and merge this pull request to enhance the performance and scalability of the application.

Fixes #64.

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Sandbox Executions

• Running GitHub Actions for backend/optimization.py ✓

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• Running GitHub Actions for components/PerformanceTracking.js ✓

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Ran GitHub Actions for 4a3fc8c13b272bc927e74ced3467ecafc683b09b:

• Running GitHub Actions for personalized_learning_ai.py ✓

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Ran GitHub Actions for 83e9b30d0a129c797385998822066ac017f6eb70:

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Rollback Files For Sweep

• Rollback changes to True

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• Apply: All new business logic should have corresponding unit tests.
• Apply: Refactor large functions to be more modular.
• Apply: Add docstrings to all functions and file headers.

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