Yong-yuan-X
e74b0e1e93
Add a pytest-discovered tests/conftest.py for the last30days scripts path and remove duplicate per-file sys.path.insert boilerplate from tests. Normalize affected imports to rely on the shared scripts path and remove the now-unneeded E402 suppressions.
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
import unittest
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from lib import relevance
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class RelevanceCoreV3Tests(unittest.TestCase):
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def test_tokenize_removes_stopwords_and_expands_synonyms(self):
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tokens = relevance.tokenize("How to use JS for hip hop apps")
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self.assertIn("js", tokens)
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self.assertIn("javascript", tokens)
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self.assertIn("hiphop", tokens)
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self.assertNotIn("how", tokens)
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def test_token_overlap_relevance_returns_neutral_for_stopword_only_query(self):
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self.assertEqual(0.5, relevance.token_overlap_relevance("how to", "anything at all"))
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def test_token_overlap_relevance_returns_zero_for_no_overlap(self):
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self.assertEqual(0.0, relevance.token_overlap_relevance("openclaw", "corsair gaming mouse"))
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def test_token_overlap_relevance_rewards_exact_phrase_matches(self):
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phrase_score = relevance.token_overlap_relevance(
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"openclaw nanoclaw",
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"A detailed openclaw nanoclaw comparison for agents.",
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)
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partial_score = relevance.token_overlap_relevance(
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"openclaw nanoclaw",
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"A detailed openclaw comparison for agents.",
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)
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self.assertGreater(phrase_score, partial_score)
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def test_token_overlap_relevance_caps_generic_only_matches(self):
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score = relevance.token_overlap_relevance(
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"anthropic odds",
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"Latest odds and prediction updates for markets",
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)
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self.assertLessEqual(score, 0.24)
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def test_token_overlap_relevance_splits_concatenated_hashtags(self):
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score = relevance.token_overlap_relevance(
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"claude code",
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"Agent workflow discussion",
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hashtags=["ClaudeCode", "BuildInPublic"],
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)
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self.assertGreater(score, 0.0)
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if __name__ == "__main__":
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unittest.main()
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