Robert Helewka
a967f73d09
Add CLAUDE.md defining the Palladium master notebook conventions and Red Panda Approval criteria, plus a review-notebook slash command for LLM-driven notebook review. Expand .gitignore to block client/engagement documents and generated exports, keeping masters client-clean while allowing text/image sources. Normalize slider widget numeric values from floats to integers in notebook JSON.
63 lines
2.3 KiB
Python
63 lines
2.3 KiB
Python
"""Structured engagement exports — the JSON is the source-of-truth artifact.
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``exports/{engagement_id}.json`` — the full Engagement, serialized.
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``exports/{engagement_id}.csv`` — one row per competency, for
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cross-engagement spreadsheet analysis (build spec §8).
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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import pandas as pd
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from .models import DiagnosticConfig, Engagement
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CSV_COLUMNS = [
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"engagement_id", "client_name", "industry", "workshop_date",
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"competency_id", "dimension", "score", "evidence",
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"is_foundational", "is_binding_constraint",
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]
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def engagement_json(engagement: Engagement) -> str:
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return json.dumps(engagement.model_dump(mode="json"), indent=2,
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ensure_ascii=False)
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def scores_dataframe(engagement: Engagement,
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config: DiagnosticConfig) -> pd.DataFrame:
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binding = set(engagement.computed_value.binding_constraints
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if engagement.computed_value else [])
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foundational = set(config.foundational_competencies)
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rows = [{
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"engagement_id": engagement.engagement_id,
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"client_name": engagement.client_name,
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"industry": engagement.industry_config,
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"workshop_date": engagement.workshop_date.isoformat(),
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"competency_id": s.competency_id,
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"dimension": s.dimension,
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"score": s.score,
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"evidence": s.evidence,
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"is_foundational": s.competency_id in foundational,
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"is_binding_constraint": s.competency_id in binding,
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} for s in engagement.scores]
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return pd.DataFrame(rows, columns=CSV_COLUMNS)
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def write_exports(engagement: Engagement, config: DiagnosticConfig,
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exports_dir: Path) -> tuple[Path, Path]:
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"""Write both artifacts; returns ``(json_path, csv_path)``."""
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exports_dir.mkdir(parents=True, exist_ok=True)
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json_path = exports_dir / f"{engagement.engagement_id}.json"
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csv_path = exports_dir / f"{engagement.engagement_id}.csv"
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json_path.write_text(engagement_json(engagement), encoding="utf-8")
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scores_dataframe(engagement, config).to_csv(csv_path, index=False)
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return json_path, csv_path
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def load_engagement(json_path: Path) -> Engagement:
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"""Reload a saved engagement for review (acceptance §10 nice-to-have)."""
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return Engagement.model_validate_json(json_path.read_text(encoding="utf-8"))
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