feat(hackernews): add Hacker News as 5th research source
Add HN search via free Algolia API (no key needed). Two-phase approach: search for stories, then enrich top ones with comments. Integrated into the full pipeline (normalize, score, dedupe, render) running in parallel with Reddit/X/YouTube. Source priority: Reddit > X > HN > YouTube > Web. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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"""Tests for Hacker News source 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 hackernews, normalize, schema, score
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class TestDateToUnix(unittest.TestCase):
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def test_known_date(self):
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# 2026-01-01 00:00:00 UTC
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result = hackernews._date_to_unix("2026-01-01")
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self.assertIsInstance(result, int)
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self.assertGreater(result, 0)
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def test_roundtrip(self):
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ts = hackernews._date_to_unix("2026-02-15")
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back = hackernews._unix_to_date(ts)
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self.assertEqual(back, "2026-02-15")
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class TestStripHtml(unittest.TestCase):
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def test_basic_html(self):
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result = hackernews._strip_html("<p>Hello <b>world</b></p>")
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self.assertIn("Hello", result)
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self.assertIn("world", result)
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self.assertNotIn("<", result)
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def test_html_entities(self):
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result = hackernews._strip_html("& test")
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self.assertIn("&", result)
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self.assertIn("test", result)
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def test_empty(self):
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result = hackernews._strip_html("")
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self.assertEqual(result, "")
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class TestParseHackernewsResponse(unittest.TestCase):
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SAMPLE_RESPONSE = {
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"hits": [
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{
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"objectID": "12345",
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"title": "Show HN: A new AI coding assistant",
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"url": "https://example.com/article",
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"author": "pg",
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"points": 350,
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"num_comments": 127,
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"created_at_i": 1739836800, # 2025-02-18
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},
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{
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"objectID": "12346",
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"title": "Ask HN: Best practices for LLM apps?",
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"url": "",
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"author": "dang",
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"points": 80,
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"num_comments": 45,
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"created_at_i": 1739750400, # 2025-02-17
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},
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],
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}
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def test_parses_hits(self):
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items = hackernews.parse_hackernews_response(self.SAMPLE_RESPONSE)
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self.assertEqual(len(items), 2)
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def test_item_fields(self):
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items = hackernews.parse_hackernews_response(self.SAMPLE_RESPONSE)
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item = items[0]
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self.assertEqual(item["object_id"], "12345")
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self.assertEqual(item["title"], "Show HN: A new AI coding assistant")
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self.assertEqual(item["url"], "https://example.com/article")
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self.assertEqual(item["hn_url"], "https://news.ycombinator.com/item?id=12345")
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self.assertEqual(item["author"], "pg")
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self.assertEqual(item["engagement"]["points"], 350)
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self.assertEqual(item["engagement"]["num_comments"], 127)
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def test_date_conversion(self):
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items = hackernews.parse_hackernews_response(self.SAMPLE_RESPONSE)
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self.assertIsNotNone(items[0]["date"])
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# Should be a valid YYYY-MM-DD string
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self.assertRegex(items[0]["date"], r"^\d{4}-\d{2}-\d{2}$")
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def test_hn_url_for_askhn(self):
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"""Ask HN posts have no article URL, but should have hn_url."""
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items = hackernews.parse_hackernews_response(self.SAMPLE_RESPONSE)
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ask_hn = items[1]
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self.assertEqual(ask_hn["url"], "")
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self.assertIn("news.ycombinator.com", ask_hn["hn_url"])
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def test_relevance_range(self):
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items = hackernews.parse_hackernews_response(self.SAMPLE_RESPONSE)
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for item in items:
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self.assertGreaterEqual(item["relevance"], 0.0)
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self.assertLessEqual(item["relevance"], 1.0)
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def test_empty_response(self):
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items = hackernews.parse_hackernews_response({"hits": []})
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self.assertEqual(items, [])
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def test_missing_hits(self):
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items = hackernews.parse_hackernews_response({})
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self.assertEqual(items, [])
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class TestNormalizeHackernewsItems(unittest.TestCase):
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def test_normalize(self):
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raw_items = [
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{
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"object_id": "99999",
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"title": "Test Story",
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"url": "https://example.com",
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"hn_url": "https://news.ycombinator.com/item?id=99999",
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"author": "testuser",
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"date": "2026-02-15",
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"engagement": {"points": 100, "num_comments": 50},
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"relevance": 0.8,
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"why_relevant": "Test",
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}
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]
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result = normalize.normalize_hackernews_items(raw_items, "2026-01-01", "2026-03-01")
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self.assertEqual(len(result), 1)
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self.assertIsInstance(result[0], schema.HackerNewsItem)
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self.assertEqual(result[0].id, "HN1")
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self.assertEqual(result[0].title, "Test Story")
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self.assertEqual(result[0].date_confidence, "high")
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self.assertEqual(result[0].engagement.score, 100)
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self.assertEqual(result[0].engagement.num_comments, 50)
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def test_normalize_with_comments(self):
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raw_items = [
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{
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"object_id": "99999",
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"title": "Test",
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"url": "",
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"hn_url": "",
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"author": "user",
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"date": "2026-02-15",
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"engagement": {"points": 10, "num_comments": 5},
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"relevance": 0.5,
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"why_relevant": "Test",
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"top_comments": [
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{"author": "commenter", "text": "Great post!", "points": 5},
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],
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"comment_insights": ["Great post!"],
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}
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]
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result = normalize.normalize_hackernews_items(raw_items, "2026-01-01", "2026-03-01")
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self.assertEqual(len(result[0].top_comments), 1)
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self.assertEqual(result[0].top_comments[0].author, "commenter")
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self.assertEqual(len(result[0].comment_insights), 1)
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class TestScoreHackernewsItems(unittest.TestCase):
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def test_score_items(self):
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items = [
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schema.HackerNewsItem(
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id="HN1", title="High engagement", url="", hn_url="",
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author="user1", date="2026-02-20",
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engagement=schema.Engagement(score=500, num_comments=200),
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relevance=0.9,
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),
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schema.HackerNewsItem(
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id="HN2", title="Low engagement", url="", hn_url="",
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author="user2", date="2026-02-18",
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engagement=schema.Engagement(score=10, num_comments=3),
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relevance=0.5,
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),
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]
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scored = score.score_hackernews_items(items)
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self.assertEqual(len(scored), 2)
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# High engagement + high relevance should score higher
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self.assertGreater(scored[0].score, scored[1].score)
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def test_score_empty(self):
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result = score.score_hackernews_items([])
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self.assertEqual(result, [])
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def test_engagement_formula(self):
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eng = schema.Engagement(score=100, num_comments=50)
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result = score.compute_hackernews_engagement_raw(eng)
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self.assertIsNotNone(result)
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self.assertGreater(result, 0)
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def test_engagement_none(self):
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result = score.compute_hackernews_engagement_raw(None)
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self.assertIsNone(result)
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def test_engagement_empty(self):
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eng = schema.Engagement()
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result = score.compute_hackernews_engagement_raw(eng)
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self.assertIsNone(result)
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class TestSortItemsWithHN(unittest.TestCase):
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def test_hn_priority_between_x_and_youtube(self):
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"""HN should sort between X and YouTube at same score."""
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x_item = schema.XItem(id="X1", text="test", url="", author_handle="user")
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x_item.score = 50
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hn_item = schema.HackerNewsItem(id="HN1", title="test", url="", hn_url="", author="user")
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hn_item.score = 50
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yt_item = schema.YouTubeItem(id="YT1", title="test", url="", channel_name="ch")
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yt_item.score = 50
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sorted_items = score.sort_items([yt_item, hn_item, x_item])
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# Same score, so sorted by source priority: X > HN > YouTube
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self.assertIsInstance(sorted_items[0], schema.XItem)
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self.assertIsInstance(sorted_items[1], schema.HackerNewsItem)
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self.assertIsInstance(sorted_items[2], schema.YouTubeItem)
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if __name__ == "__main__":
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unittest.main()
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