25 lines
1.6 KiB
Python
25 lines
1.6 KiB
Python
from pathlib import Path
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from didactopus.evidence_flow_ledger_qa import evidence_flow_ledger_for_pack
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def make_pack(base: Path, concepts_yaml: str, roadmap_yaml: str, projects_yaml: str, rubrics_yaml: str, evaluator_yaml: str, ledger_yaml: str):
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(base / "pack.yaml").write_text("name: p\ndisplay_name: P\nversion: 0.1.0\n", encoding="utf-8")
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(base / "concepts.yaml").write_text(concepts_yaml, encoding="utf-8")
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(base / "roadmap.yaml").write_text(roadmap_yaml, encoding="utf-8")
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(base / "projects.yaml").write_text(projects_yaml, encoding="utf-8")
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(base / "rubrics.yaml").write_text(rubrics_yaml, encoding="utf-8")
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(base / "evaluator.yaml").write_text(evaluator_yaml, encoding="utf-8")
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(base / "mastery_ledger.yaml").write_text(ledger_yaml, encoding="utf-8")
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def test_detects_missing_dimension_mapping(tmp_path: Path) -> None:
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make_pack(
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tmp_path,
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"concepts:\n - id: c1\n title: Foundations\n description: enough description here\n mastery_signals: [Explain foundations clearly]\n",
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"stages:\n - id: s1\n title: One\n concepts: [c1]\n checkpoint: [explanation exercise]\n",
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"projects:\n - id: p1\n title: Project\n prerequisites: [c1]\n deliverables: [explanation]\n",
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"rubrics:\n - id: r1\n title: Basic\n criteria: [correctness]\n",
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"dimensions:\n - name: explanation\n description: quality of explanation\n",
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"entry_schema:\n concept_id: str\n score: float\n confidence: float\n last_updated: datetime\n",
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)
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result = evidence_flow_ledger_for_pack(tmp_path)
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assert any("dimension" in w.lower() for w in result["warnings"])
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