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Shared Pydantic contracts for spark-advisor microservices

Project description

spark-advisor-models

Shared Pydantic models and configuration for the spark-advisor ecosystem.

Install

pip install spark-advisor-models

What's inside

  • Spark job metrics — stages, executors, tasks, quantile distributions (model/metrics.py)
  • Analysis output — recommendations, severity levels, causal chains (model/output.py)
  • AI tool schemas — input/output models for Claude API, generated from Pydantic (model/input.py)
  • Spark config wrapper — typed access to spark.* properties (model/spark_config.py)
  • Shared configuration — rule thresholds, AI settings, NATS settings (config.py, settings.py)
  • Structured loggingconfigure_logging(), bind_nats_context(), nats_handler_context() (logging.py)
  • Distributed tracing — OpenTelemetry W3C Traceparent propagation via NATS headers (tracing.py)
  • Utilities — byte formatting, statistics helpers (util/)

Usage

from spark_advisor_models.model.metrics import JobAnalysis, StageMetrics
from spark_advisor_models.config import Thresholds, AiSettings

Links

License

Apache 2.0

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