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README.md

Python AMR Guides

These guides are the Python equivalent of R-package vignettes plus maintainer-focused system documentation.

Port Status

  • Port Status — R AMR port overview, critical gaps (all resolved), parity references

Guide Index

  1. Getting Started
  2. Core Workflows (SIR, antibiogram, metrics)
  3. API, Async Persistence, and Observability
  4. Datasets and Breakpoints
  5. Data Pipeline Architecture
  6. Reproduction Parity Matrix
  7. Data QA Copilot
  8. System Architecture
  9. Runtime Sequences
  10. Storage Architecture
  11. Data Contracts
  12. Data Pipeline Deep Dive
  13. Transforms Reference
  14. Parity and Reproducibility
  15. External Ingest Playbook
  16. API Reference
  17. CLI Reference
  18. Contracts Index
  19. Analytics Semantics
  20. Breakpoints and Guidelines
  21. Prediction Methodology
  22. Operations Runbook
  23. Incident Response
  24. Observability Metrics
  25. Configuration Reference
  26. Security and Data Handling
  27. Testing Strategy
  28. Performance Guardrails
  29. Release Process
  30. Migration Guide
  31. Docs Contribution Guide
  32. Glossary
  33. Diagram Index

Start Here by Role

  • Contributor/Maintainer: 10_system_architecture.md -> 20_data_contracts.md -> 50_operations_runbook.md
  • Data Engineer: 24_external_ingest_playbook.md -> 21_data_pipeline_deep_dive.md -> 23_parity_and_reproducibility.md
  • API/CLI Integrator: 30_api_reference.md + 31_cli_reference.md + 53_configuration_reference.md
  • Reviewer: 32_contracts_index.md + 60_testing_strategy.md + 61_performance_guardrails.md

Scope

  • Native Python implementation (no R bridge)
  • R AMR port complete — all critical gaps resolved (veterinary breakpoints, translation)
  • Async-first persistence pipeline
  • DuckDB + SQLAlchemy-backed run storage
  • CLI and FastAPI interfaces