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 logging —
configure_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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