103 lines
4.4 KiB
Python
103 lines
4.4 KiB
Python
import json
|
|
from pathlib import Path
|
|
from didactopus.document_adapters import adapt_document
|
|
from didactopus.document_adapters import adapt_documents
|
|
from didactopus.topic_ingest import document_to_course, build_topic_bundle, merge_courses_into_topic_course, extract_concept_candidates
|
|
|
|
|
|
def test_cross_course_merge(tmp_path: Path) -> None:
|
|
a = tmp_path / "a.md"
|
|
b = tmp_path / "b.docx"
|
|
a.write_text("# T\n\n## M\n### L1\nBody A", encoding="utf-8")
|
|
b.write_text("# T\n\n## M\n### L1\nBody B", encoding="utf-8")
|
|
|
|
docs = [adapt_document(a), adapt_document(b)]
|
|
courses = [document_to_course(doc, "Topic") for doc in docs]
|
|
topic = build_topic_bundle("Topic", courses)
|
|
merged = merge_courses_into_topic_course(topic)
|
|
assert len(merged.modules) >= 1
|
|
assert len(merged.modules[0].lessons) == 1
|
|
|
|
|
|
def test_extract_concepts(tmp_path: Path) -> None:
|
|
a = tmp_path / "a.md"
|
|
a.write_text("# T\n\n## M\n### Lesson A\nObjective: Explain Topic A.\nBody.", encoding="utf-8")
|
|
doc = adapt_document(a)
|
|
course = document_to_course(doc, "Topic")
|
|
concepts = extract_concept_candidates(course)
|
|
assert len(concepts) >= 1
|
|
|
|
|
|
def test_document_to_course_skips_empty_sections(tmp_path: Path) -> None:
|
|
a = tmp_path / "a.md"
|
|
a.write_text("# T\n\n## Empty\n\n### Filled\nBody.", encoding="utf-8")
|
|
doc = adapt_document(a)
|
|
course = document_to_course(doc, "Topic")
|
|
assert [lesson.title for lesson in course.modules[0].lessons] == ["Filled"]
|
|
|
|
|
|
def test_document_to_course_parses_bulleted_objectives_and_exercises(tmp_path: Path) -> None:
|
|
a = tmp_path / "a.md"
|
|
a.write_text(
|
|
"# T\n\n## M\n### Shannon Entropy\n- Objective: Explain uncertainty.\n- Exercise: Compute entropy.\nBody.",
|
|
encoding="utf-8",
|
|
)
|
|
doc = adapt_document(a)
|
|
course = document_to_course(doc, "Topic")
|
|
lesson = course.modules[0].lessons[0]
|
|
assert lesson.objectives == ["Explain uncertainty."]
|
|
assert lesson.exercises == ["Compute entropy."]
|
|
|
|
|
|
def test_extract_concepts_retains_lessons_but_filters_generic_terms(tmp_path: Path) -> None:
|
|
a = tmp_path / "a.md"
|
|
a.write_text(
|
|
"# T\n\n## M\n### MIT OCW 6.050J Information and Entropy: Syllabus\n- Objective: Explain the course.\nBody.\n\n### Channel Capacity\n- Objective: Explain noisy channels.\n- Exercise: State a capacity limit.\nChannel Capacity links reliable communication to noise and coding.",
|
|
encoding="utf-8",
|
|
)
|
|
doc = adapt_document(a)
|
|
course = document_to_course(doc, "Topic")
|
|
concepts = extract_concept_candidates(course)
|
|
titles = {concept.title for concept in concepts}
|
|
assert "MIT OCW 6.050J Information and Entropy: Syllabus" in titles
|
|
assert "Explain" not in titles
|
|
assert "Channel Capacity" in titles
|
|
|
|
|
|
def test_adapt_documents_from_doclift_bundle(tmp_path: Path) -> None:
|
|
bundle = tmp_path / "bundle"
|
|
doc_dir = bundle / "documents" / "lesson-a"
|
|
doc_dir.mkdir(parents=True)
|
|
(bundle / "manifest.json").write_text(
|
|
json.dumps(
|
|
{
|
|
"documents": [
|
|
{
|
|
"title": "Lecture 1. Example",
|
|
"document_kind": "lecture",
|
|
"output_dir": str(doc_dir),
|
|
"layout_path": str(doc_dir / "document.layout.json"),
|
|
"tables_path": str(doc_dir / "document.tables.json"),
|
|
"figures_path": str(doc_dir / "document.figures.json"),
|
|
"table_count": 1,
|
|
"figure_reference_count": 0,
|
|
}
|
|
]
|
|
}
|
|
),
|
|
encoding="utf-8",
|
|
)
|
|
(doc_dir / "document.md").write_text("# Lecture 1. Example\n\n## Module\n### Lesson A\nBody.", encoding="utf-8")
|
|
(doc_dir / "document.layout.json").write_text("[]", encoding="utf-8")
|
|
(doc_dir / "document.tables.json").write_text(json.dumps({"source_path": "/tmp/source.doc", "tables": []}), encoding="utf-8")
|
|
(doc_dir / "document.figures.json").write_text(json.dumps({"source_path": "/tmp/source.doc", "figure_references": []}), encoding="utf-8")
|
|
|
|
docs = adapt_documents(bundle)
|
|
|
|
assert len(docs) == 1
|
|
assert docs[0].source_type == "doclift_bundle"
|
|
assert docs[0].title == "Lecture 1. Example"
|
|
assert docs[0].metadata["document_kind"] == "lecture"
|
|
assert docs[0].metadata["doclift_bundle"] is True
|
|
assert docs[0].source_path == "/tmp/source.doc"
|