test: add tests for entity_extract module
Covers _extract_x_handles (8 cases), _extract_x_hashtags (5 cases), _extract_subreddits (6 cases), and extract_entities integration (4 cases). Follows existing test patterns from test_dedupe.py.
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"""Tests for entity_extract module."""
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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 import entity_extract
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class TestExtractXHandles(unittest.TestCase):
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def test_basic_author_handle(self):
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items = [{"author_handle": "techguru", "text": ""}]
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result = entity_extract._extract_x_handles(items)
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self.assertEqual(result, ["techguru"])
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def test_mentions_in_text(self):
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items = [{"text": "Great thread by @airesearcher and @mldev"}]
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result = entity_extract._extract_x_handles(items)
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self.assertIn("airesearcher", result)
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self.assertIn("mldev", result)
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def test_generic_handles_filtered(self):
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items = [
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{"author_handle": "@openai", "text": ""},
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{"author_handle": "@elonmusk", "text": ""},
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{"author_handle": "realexpert", "text": ""},
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]
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result = entity_extract._extract_x_handles(items)
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self.assertEqual(result, ["realexpert"])
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def test_case_normalization(self):
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items = [{"author_handle": "@CamelCase", "text": ""}]
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result = entity_extract._extract_x_handles(items)
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self.assertEqual(result, ["camelcase"])
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def test_frequency_ranking(self):
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items = [
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{"author_handle": "popular", "text": ""},
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{"author_handle": "popular", "text": ""},
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{"author_handle": "popular", "text": ""},
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{"author_handle": "rare", "text": ""},
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]
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result = entity_extract._extract_x_handles(items)
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self.assertEqual(result[0], "popular")
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def test_leading_at_stripped(self):
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items = [{"author_handle": "@withatsign", "text": ""}]
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result = entity_extract._extract_x_handles(items)
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self.assertEqual(result, ["withatsign"])
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def test_empty_input(self):
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result = entity_extract._extract_x_handles([])
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self.assertEqual(result, [])
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def test_mixed_items(self):
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items = [
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{"author_handle": "poster1", "text": "Check @mentioned"},
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{"text": "No author here"},
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{"author_handle": "", "text": ""},
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]
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result = entity_extract._extract_x_handles(items)
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self.assertIn("poster1", result)
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self.assertIn("mentioned", result)
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self.assertEqual(len(result), 2)
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class TestExtractXHashtags(unittest.TestCase):
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def test_basic_hashtag(self):
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items = [{"text": "Exciting news #AI"}]
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result = entity_extract._extract_x_hashtags(items)
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self.assertEqual(result, ["#ai"])
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def test_multiple_tags(self):
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items = [{"text": "#Python and #MachineLearning are trending"}]
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result = entity_extract._extract_x_hashtags(items)
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self.assertIn("#python", result)
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self.assertIn("#machinelearning", result)
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def test_frequency_ranking(self):
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items = [
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{"text": "#ai is great"},
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{"text": "#ai again"},
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{"text": "#rare tag"},
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]
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result = entity_extract._extract_x_hashtags(items)
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self.assertEqual(result[0], "#ai")
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def test_single_char_tag_filtered(self):
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items = [{"text": "#X is not enough chars but #AI is"}]
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result = entity_extract._extract_x_hashtags(items)
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# #X is only 1 char, filtered by \w{2,30} regex
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self.assertNotIn("#x", result)
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self.assertIn("#ai", result)
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def test_empty_input(self):
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result = entity_extract._extract_x_hashtags([])
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self.assertEqual(result, [])
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class TestExtractSubreddits(unittest.TestCase):
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def test_basic_subreddit_field(self):
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items = [{"subreddit": "MachineLearning"}]
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result = entity_extract._extract_subreddits(items)
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self.assertEqual(result, ["MachineLearning"])
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def test_cross_ref_in_comment_insights(self):
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items = [{"subreddit": "AI", "comment_insights": ["Check out r/localLLaMA for more"]}]
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result = entity_extract._extract_subreddits(items)
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self.assertIn("localLLaMA", result)
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def test_cross_ref_in_top_comments(self):
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items = [{"subreddit": "tech", "top_comments": [{"excerpt": "Also see r/programming"}]}]
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result = entity_extract._extract_subreddits(items)
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self.assertIn("programming", result)
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def test_frequency_ranking(self):
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items = [
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{"subreddit": "popular"},
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{"subreddit": "popular"},
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{"subreddit": "rare"},
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]
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result = entity_extract._extract_subreddits(items)
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self.assertEqual(result[0], "popular")
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def test_leading_r_slash_stripped(self):
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items = [{"subreddit": "r/stripped"}]
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result = entity_extract._extract_subreddits(items)
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self.assertEqual(result, ["stripped"])
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def test_empty_input(self):
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result = entity_extract._extract_subreddits([])
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self.assertEqual(result, [])
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class TestExtractEntities(unittest.TestCase):
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def test_integration(self):
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reddit = [{"subreddit": "AI", "comment_insights": ["r/localLLaMA"]}]
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x = [{"author_handle": "researcher", "text": "#deeplearning @colleague"}]
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result = entity_extract.extract_entities(reddit, x)
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self.assertIn("researcher", result["x_handles"])
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self.assertIn("#deeplearning", result["x_hashtags"])
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self.assertIn("AI", result["reddit_subreddits"])
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def test_max_limits(self):
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x = [
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{"author_handle": f"user{i}", "text": ""}
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for i in range(10)
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]
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result = entity_extract.extract_entities([], x, max_handles=2)
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self.assertLessEqual(len(result["x_handles"]), 2)
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def test_empty_inputs(self):
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result = entity_extract.extract_entities([], [])
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self.assertEqual(result["x_handles"], [])
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self.assertEqual(result["x_hashtags"], [])
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self.assertEqual(result["reddit_subreddits"], [])
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def test_return_keys(self):
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result = entity_extract.extract_entities([], [])
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self.assertSetEqual(set(result.keys()), {"x_handles", "x_hashtags", "reddit_subreddits"})
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if __name__ == "__main__":
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unittest.main()
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