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chore: import upstream snapshot with attribution
2026-07-13 12:46:28 +08:00

144 lines
4.9 KiB
Python

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