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Contributing to Predictive-ML-Core

Thank you for your interest in contributing! This project is maintained as a community resource for learning and using predictive analytics in cloud infrastructure.

Before You Contribute

Please read COMMUNITY.md to understand the project's purpose and boundaries.

Contribution Guidelines

Types of Contributions We Accept ✅

  • Bug fixes in existing code
  • Performance improvements with synthetic data benchmarks
  • Documentation updates (clarifications, examples, typos)
  • Example scenarios using synthetic/public data
  • Tests with synthetic telemetry data
  • Algorithm improvements (if generalizable to any infrastructure)

Types We Don't Accept ❌

  • Real production telemetry or logs
  • Customer data or anonymized customer data without explicit consent
  • CloudSealed-specific implementations
  • Credentials, API keys, or tokens in any form
  • Changes to remove/modify MIT license

Process

  1. Check existing issues/PRs to avoid duplicates
  2. Open an issue first for significant changes (discuss before implementing)
  3. Fork and branch: git checkout -b feature/your-feature-name
  4. Keep data synthetic: All examples use generated data
  5. Update docs: Explain what your change does
  6. Add tests: Use synthetic data; all tests must be reproducible
  7. Run locally: Ensure dotnet build and tests pass
  8. Create PR: Link the issue, describe changes clearly

Data Policy

You MUST NOT commit:

  • Real telemetry or logs
  • Customer/company-specific data (even anonymized)
  • Cloud credentials (keys, tokens, connection strings)
  • Production configuration

You CAN use:

  • Synthetic data generated with Random seeded values
  • Public datasets (cite source, respect license)
  • Realistic but fake scenarios (e.g., "Company A" with made-up metrics)

Quick Check Before Committing

# Ensure no secrets are committed
git-secrets --scan

# Verify no real company/customer names in data
grep -r "YOUR_COMPANY\|customer\|client" src/

Code Style

  • Follow standard C# conventions (PascalCase for public members)
  • XML comments for public APIs
  • Meaningful variable names
  • Keep functions focused and testable

Documentation

When adding a feature:

  1. Update README.md if it's user-facing
  2. Add inline comments explaining the "why"
  3. Include example usage in docstrings
  4. Document inputs/outputs clearly

Testing

  • Write tests for any new algorithms
  • Use synthetic data only
  • Tests must be reproducible (fixed seeds)
  • Verify tests pass: dotnet test

Licensing

By contributing, you agree that your work will be distributed under the MIT license. You confirm you have the right to contribute and that you're not violating any third-party licenses.

Questions?

  • Check COMMUNITY.md FAQ
  • Open an issue with [question] tag
  • Review existing PRs for examples

Thank you for contributing to the community! 🙏