Matt Van Horn
0591f55f0e
YouTube videos now get real relevance scores based on token overlap between the search query and video title (was hardcoded at 0.7). Uses ratio overlap with stopword removal, floored at 0.1. Cross-source linking annotates items that discuss the same story across different platforms (e.g., Reddit + HN + X). Items get bidirectional cross_refs displayed as [xref: R3, HN5] in compact output so Claude can triangulate multi-platform coverage. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
111 lines
3.6 KiB
Python
111 lines
3.6 KiB
Python
"""Tests for YouTube relevance scoring."""
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import sys
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import unittest
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from pathlib import Path
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# Add lib to path
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sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
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from lib.youtube_yt import _compute_relevance, _tokenize
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class TestTokenize(unittest.TestCase):
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def test_basic(self):
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tokens = _tokenize("Claude Code Tutorial")
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self.assertIn("claude", tokens)
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self.assertIn("code", tokens)
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self.assertIn("tutorial", tokens)
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def test_removes_stopwords(self):
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tokens = _tokenize("how to use Claude Code for beginners")
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self.assertNotIn("how", tokens)
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self.assertNotIn("to", tokens)
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self.assertNotIn("for", tokens)
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self.assertIn("claude", tokens)
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self.assertIn("code", tokens)
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self.assertIn("beginners", tokens)
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def test_strips_punctuation(self):
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tokens = _tokenize("What's new in Claude?")
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self.assertIn("claude", tokens)
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self.assertNotIn("what's", tokens)
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def test_drops_single_char(self):
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tokens = _tokenize("a b c Claude")
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self.assertNotIn("a", tokens)
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self.assertNotIn("b", tokens)
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self.assertIn("claude", tokens)
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def test_empty(self):
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tokens = _tokenize("")
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self.assertEqual(tokens, set())
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def test_all_stopwords(self):
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tokens = _tokenize("the a an to for how")
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self.assertEqual(tokens, set())
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class TestComputeRelevance(unittest.TestCase):
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def test_exact_match(self):
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result = _compute_relevance("Claude Code", "Claude Code")
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self.assertEqual(result, 1.0)
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def test_full_match_in_longer_title(self):
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result = _compute_relevance("Claude Code", "Claude Code Tutorial")
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self.assertEqual(result, 1.0)
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def test_partial_match(self):
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result = _compute_relevance("Claude Code Tips", "Claude Tips for Beginners")
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self.assertGreater(result, 0.5)
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self.assertLess(result, 1.0)
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def test_no_match(self):
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result = _compute_relevance("Claude Code", "Python Web Scraping")
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self.assertEqual(result, 0.1) # Floor
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def test_empty_query_returns_neutral(self):
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result = _compute_relevance("", "Some Video Title")
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self.assertEqual(result, 0.5)
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def test_stopword_only_query(self):
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result = _compute_relevance("how to the", "Some Video Title")
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self.assertEqual(result, 0.5)
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def test_empty_title(self):
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result = _compute_relevance("Claude Code", "")
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self.assertEqual(result, 0.1) # Floor
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def test_case_insensitive(self):
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result = _compute_relevance("claude code", "CLAUDE CODE Tutorial")
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self.assertEqual(result, 1.0)
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def test_stopwords_in_title_dont_inflate(self):
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# "Claude Code" query against a title with lots of stopwords
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# Should still match well since Claude and Code are present
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result = _compute_relevance(
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"Claude Code",
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"How To Use Claude Code For Complete Beginners"
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)
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self.assertEqual(result, 1.0)
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def test_floor_at_0_1(self):
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result = _compute_relevance("quantum computing", "cat videos compilation")
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self.assertEqual(result, 0.1)
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def test_cap_at_1_0(self):
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result = _compute_relevance("AI", "AI AI AI AI AI")
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self.assertLessEqual(result, 1.0)
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def test_single_word_query(self):
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result = _compute_relevance("Seedance", "Seedance AI Video Generator Review")
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self.assertEqual(result, 1.0)
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def test_single_word_no_match(self):
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result = _compute_relevance("Seedance", "Random cooking video")
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self.assertEqual(result, 0.1)
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if __name__ == "__main__":
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unittest.main()
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