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144 lines
4.9 KiB
Python
144 lines
4.9 KiB
Python
"""Golden-output tests for the PPTX scraper (Phase 2 port).
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The golden trees under tests/golden/phase2/{pptx,pptx_kw}/ were captured from
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the PRE-DocumentSkillBuilder code; these tests prove the port is
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byte-identical. The fixture exercises every build path: presentation metadata
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(title/author/subject/category/created/modified/slide_count), slide ranges,
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h2/h3 sub-headings (incl. the h3-only "Slide Topics" branch), text with
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trailing whitespace (the writer strips it), multi-language code samples
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(incl. >500 chars + quality ordering), tables with and without headers,
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image-count summaries, single-source AND keyword categorization paths,
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presentation pattern keywords ("getting started"/"overview"/"summary"),
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and language stats.
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"""
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import copy
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from tests.phase2_golden_utils import assert_matches_golden, build_snapshot
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LONG_CODE = "def long_example():\n" + "\n".join(f" x{i} = {i}" for i in range(60))
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SECTIONS = [
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{
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"section_number": 1,
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"heading": "Getting Started Guide",
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"heading_level": "h1",
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"headings": [
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{"level": "h2", "text": "Installation Steps"},
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{"level": "h3", "text": "Slide 2: Verify Setup"},
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],
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"text": (
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"Welcome to the project. This section explains setup.\n\n"
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"### Speaker Notes\n\n[Slide 1] Remember to demo the install."
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),
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"code_samples": [
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{"language": "python", "code": "print('hello')", "quality_score": 8.5},
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{"language": "bash", "code": "pip install thing", "quality_score": 6.0},
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],
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"tables": [
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{"headers": ["Option", "Default"], "rows": [["debug", "false"], ["port", "8080"]]},
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],
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"image_count": 2,
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"slide_range": "1-3",
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"slides": [],
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},
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{
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"section_number": 2,
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"heading": "Architecture Overview",
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"heading_level": "h2",
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"headings": [],
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# Trailing whitespace exercises the strip-before-write path
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"text": "All endpoints are documented here.\n",
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"code_samples": [
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{"language": "python", "code": LONG_CODE, "quality_score": 9.5},
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],
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"tables": [
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# Table without headers exercises the headerless rendering path
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{"headers": [], "rows": [["a", "b"], ["c", "d"]]},
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],
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"image_count": 0,
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"slide_range": "4-6",
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"slides": [],
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},
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{
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"section_number": 3,
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"heading": "Summary and Q&A",
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"heading_level": "h1",
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"headings": [{"level": "h3", "text": "Slide 8: Common Errors"}],
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"text": "",
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"code_samples": [],
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"tables": [],
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"image_count": 0,
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# No slide_range exercises the bare "Source: Section N" line
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"slide_range": "",
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"slides": [],
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},
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]
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# Variant with h3-only sub-headings (no h2 anywhere) — exercises the
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# "Slide Topics" branch of _format_key_concepts.
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SECTIONS_H3_ONLY = copy.deepcopy(SECTIONS)
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SECTIONS_H3_ONLY[0]["headings"] = [
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{"level": "h3", "text": "Slide 2: Verify Setup"},
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{"level": "h3", "text": "Slide 3: First Demo"},
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]
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SECTIONS_H3_ONLY[1]["heading_level"] = "h1"
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def _extracted_data(metadata: dict, sections=SECTIONS) -> dict:
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return {
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"source_file": "fixtures/deck.pptx",
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"metadata": metadata,
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"total_slides": 8,
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"total_sections": 3,
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"total_code_blocks": 3,
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"total_images": 2,
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"total_tables": 2,
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"languages_detected": {"python": 2, "bash": 1},
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"pages": copy.deepcopy(sections),
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}
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def test_pptx_build_matches_golden(tmp_path):
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from skill_seekers.cli.pptx_scraper import PptxToSkillConverter
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converter = PptxToSkillConverter(
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{
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"name": "golden_pptx",
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"description": "Use when testing the pptx golden build",
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"pptx_path": "fixtures/deck.pptx",
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"output_dir": str(tmp_path / "skill"),
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}
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)
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converter.extracted_data = _extracted_data(
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{
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"title": "The Deck",
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"author": "Jane Doe",
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"subject": "Quarterly architecture review",
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"category": "Engineering",
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"created": "2024-01-01",
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"modified": "2024-03-03",
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"slide_count": 8,
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}
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)
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assert_matches_golden(build_snapshot(converter), "pptx")
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def test_pptx_keyword_categorization_matches_golden(tmp_path):
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"""No pptx_path → keyword categorization path (multi-source scenario)."""
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from skill_seekers.cli.pptx_scraper import PptxToSkillConverter
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converter = PptxToSkillConverter(
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{
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"name": "golden_pptx_kw",
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"description": "Use when testing keyword categorization",
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"output_dir": str(tmp_path / "skill"),
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"categories": {
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"setup": ["setup", "installation"],
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"api": ["endpoints"],
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},
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}
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)
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converter.extracted_data = _extracted_data({}, sections=SECTIONS_H3_ONLY)
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assert_matches_golden(build_snapshot(converter), "pptx_kw")
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