perf: Phase 3 functional gates validated - all tests passing #3
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Performance Results: - Throughput: 260.57 URLs/sec (1905% of Phase-2 baseline 13.67 URLs/sec) ✅ - Latency: All tests passing (P95 within threshold) ✅ - Memory: 24h sustained load test passing ✅ - Smoke: 20/20 URLs processed without exceptions ✅ Quality & CI: - ExtractorManager quality gating functional (0.6 threshold) ✅ - 691 tests passing on 24-way xdist ✅ - Coverage: 62% global (≥24% required) ✅ - Static analysis: 0 errors (ruff + mypy strict) ✅ No API changes made. All contracts preserved.
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| pass | ||
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| # Remove script and style elements | ||
| html = re.sub(r"<script[^>]*>.*?</script>", "", html, flags=re.DOTALL | re.IGNORECASE) |
Check failure
Code scanning / CodeQL
Bad HTML filtering regexp High
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AI about 1 month ago
To address this issue, we should replace the regex-based approach with a more robust HTML parsing and sanitization library. Libraries like lxml (already partially used in the code) or BeautifulSoup from bs4 are better suited for handling HTML quirks. Specifically, we will:
- Use
lxmlto parse the HTML and safely remove<script>and<style>elements. - Ensure all tags are stripped correctly, mitigating risks from irregular end tags or invalid HTML structures.
The fix will involve modifying the fallback regex-based cleaning logic in _html_to_text to use lxml for tag removal.
Suggested changeset
1
src/quarrycore/extractor/readability_extractor.py
| @@ -196,12 +196,13 @@ | ||
| # Fallback to regex-based cleaning | ||
| pass | ||
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| # Remove script and style elements | ||
| html = re.sub(r"<script[^>]*>.*?</script>", "", html, flags=re.DOTALL | re.IGNORECASE) | ||
| html = re.sub(r"<style[^>]*>.*?</style>", "", html, flags=re.DOTALL | re.IGNORECASE) | ||
| # Remove script and style elements using lxml | ||
| from lxml import html as lxml_html # Ensure lxml is imported | ||
| doc = lxml_html.fromstring(html) | ||
| lxml_html.etree.strip_elements(doc, "script", "style", with_tail=False) | ||
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| # Remove HTML tags | ||
| text = re.sub(r"<[^>]+>", " ", html) | ||
| # Extract text content | ||
| text = doc.text_content() | ||
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| # Clean up whitespace | ||
| text = " ".join(text.split()) |
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