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chore: import upstream snapshot with attribution
2026-07-13 12:05:33 +08:00

253 lines
9.9 KiB
Python

import unittest
from lib import normalize
class NormalizeV3Tests(unittest.TestCase):
def test_youtube_evergreen_fallback_keeps_older_items_when_recent_pool_is_empty(self):
items = [
{
"video_id": "vid-1",
"title": "Deploy to Fly.io tutorial",
"url": "https://youtube.com/watch?v=vid-1",
"channel_name": "Example",
"date": "2026-01-10",
"engagement": {"views": 1000, "likes": 50, "comments": 10},
}
]
normalized = normalize.normalize_source_items(
"youtube",
items,
"2026-02-15",
"2026-03-17",
freshness_mode="evergreen_ok",
)
self.assertEqual(1, len(normalized))
self.assertEqual("2026-01-10", normalized[0].published_at)
def test_grounding_still_drops_older_items_in_evergreen_mode(self):
items = [
{
"id": "g-1",
"title": "Fly.io guide",
"url": "https://example.com/fly-guide",
"date": "2026-01-08",
"date_confidence": "high",
"snippet": "Step-by-step guide.",
}
]
normalized = normalize.normalize_source_items(
"grounding",
items,
"2026-02-15",
"2026-03-17",
freshness_mode="evergreen_ok",
)
self.assertEqual([], normalized)
def test_youtube_top_comments_passthrough_with_field_mapping(self):
"""YT comments from enrich_with_comments use likes/text; normalize must
carry them into metadata as the Reddit-compatible {score, excerpt} shape."""
items = [
{
"video_id": "vid-1",
"title": "How to deploy",
"url": "https://youtube.com/watch?v=vid-1",
"channel_name": "Example",
"date": "2026-03-01",
"engagement": {"views": 10000, "likes": 500, "comments": 30},
"top_comments": [
{"author": "Alice", "text": "Best tutorial ever", "likes": 120, "date": "2026-03-02"},
{"author": "Bob", "text": "Helped me ship", "likes": 45, "date": "2026-03-03"},
{"author": "Carol", "text": "Solid walkthrough", "likes": 7, "date": "2026-03-04"},
],
}
]
normalized = normalize.normalize_source_items(
"youtube", items, "2026-02-15", "2026-03-17",
)
self.assertEqual(1, len(normalized))
top = normalized[0].metadata.get("top_comments")
self.assertIsNotNone(top)
self.assertEqual(3, len(top))
# First comment: likes->score, text->excerpt
self.assertEqual(120, top[0]["score"])
self.assertEqual("Best tutorial ever", top[0]["excerpt"])
self.assertEqual("Alice", top[0]["author"])
self.assertEqual("2026-03-02", top[0]["date"])
# Preserves ordering from input (already sorted desc upstream)
self.assertEqual(45, top[1]["score"])
self.assertEqual(7, top[2]["score"])
def test_instagram_comment_like_count_maps_to_score(self):
"""U2: IG comments use comment_like_count as the vote; normalize must
carry it into the shared `score` field so it participates in ranking."""
items = [
{
"video_id": "ig-1",
"text": "reel caption",
"url": "https://www.instagram.com/reel/ABC/",
"author_name": "example",
"date": "2026-03-01",
"engagement": {"views": 10000, "likes": 500, "comments": 30},
"top_comments": [
{"author": "alice", "text": "gold take", "comment_like_count": 120, "date": "2026-03-02"},
{"author": "bob", "text": "mid", "comment_like_count": 5, "date": "2026-03-03"},
],
}
]
normalized = normalize.normalize_source_items(
"instagram", items, "2026-02-15", "2026-03-17",
)
self.assertEqual(1, len(normalized))
top = normalized[0].metadata.get("top_comments")
self.assertIsNotNone(top)
self.assertEqual(120, top[0]["score"])
self.assertEqual("gold take", top[0]["excerpt"])
self.assertEqual("alice", top[0]["author"])
def test_youtube_top_comments_empty_list_passes_through_cleanly(self):
items = [
{
"video_id": "vid-2",
"title": "Short clip",
"url": "https://youtube.com/watch?v=vid-2",
"channel_name": "Example",
"date": "2026-03-01",
"engagement": {"views": 50, "likes": 2},
"top_comments": [],
}
]
normalized = normalize.normalize_source_items(
"youtube", items, "2026-02-15", "2026-03-17",
)
self.assertEqual(1, len(normalized))
# Empty list is fine; metadata may have empty top_comments or omit it.
top = normalized[0].metadata.get("top_comments", [])
self.assertEqual([], top)
def test_youtube_without_top_comments_key_does_not_crash(self):
items = [
{
"video_id": "vid-3",
"title": "No comments fetched",
"url": "https://youtube.com/watch?v=vid-3",
"channel_name": "Example",
"date": "2026-03-01",
"engagement": {"views": 100, "likes": 5},
}
]
normalized = normalize.normalize_source_items(
"youtube", items, "2026-02-15", "2026-03-17",
)
self.assertEqual(1, len(normalized))
self.assertEqual([], normalized[0].metadata.get("top_comments", []))
def test_youtube_top_comments_feed_top_comment_score_signal(self):
"""Integration: after normalize, signals._top_comment_score should
return log1p(first comment score) for YT, proving the full chain."""
from lib import signals
import math
items = [
{
"video_id": "vid-4",
"title": "Viral comment thread",
"url": "https://youtube.com/watch?v=vid-4",
"channel_name": "Example",
"date": "2026-03-01",
"engagement": {"views": 1000, "likes": 50, "comments": 10},
"top_comments": [
{"author": "A", "text": "Legendary", "likes": 9999, "date": "2026-03-02"},
],
}
]
normalized = normalize.normalize_source_items(
"youtube", items, "2026-02-15", "2026-03-17",
)
self.assertAlmostEqual(math.log1p(9999), signals._top_comment_score(normalized[0]), places=4)
def test_tiktok_top_comments_passthrough_with_digg_count_mapping(self):
"""TikTok comments from enrich_with_comments use digg_count/text;
normalize must map to the shared {score, excerpt} shape."""
items = [
{
"id": "tt-1",
"text": "POV: shipping on Friday",
"url": "https://www.tiktok.com/@u/video/tt-1",
"author_name": "u",
"date": "2026-03-01",
"engagement": {"views": 50000, "likes": 2000, "comments": 300},
"top_comments": [
{"author": "Alice", "text": "dead", "digg_count": 1200, "date": "2026-03-02"},
{"author": "Bob", "text": "so real", "digg_count": 400, "date": "2026-03-03"},
],
}
]
normalized = normalize.normalize_source_items(
"tiktok", items, "2026-02-15", "2026-03-17",
)
self.assertEqual(1, len(normalized))
top = normalized[0].metadata.get("top_comments")
self.assertEqual(2, len(top))
self.assertEqual(1200, top[0]["score"])
self.assertEqual("dead", top[0]["excerpt"])
self.assertEqual("Alice", top[0]["author"])
self.assertEqual(400, top[1]["score"])
def test_tiktok_without_top_comments_does_not_crash(self):
items = [
{
"id": "tt-2",
"text": "plain clip",
"url": "https://www.tiktok.com/@u/video/tt-2",
"author_name": "u",
"date": "2026-03-01",
"engagement": {"views": 1000, "likes": 20},
}
]
normalized = normalize.normalize_source_items(
"tiktok", items, "2026-02-15", "2026-03-17",
)
self.assertEqual([], normalized[0].metadata.get("top_comments", []))
def test_tiktok_top_comments_feed_top_comment_score_signal(self):
from lib import signals
import math
items = [
{
"id": "tt-3",
"text": "viral",
"url": "https://www.tiktok.com/@u/video/tt-3",
"author_name": "u",
"date": "2026-03-01",
"engagement": {"views": 100000, "likes": 5000, "comments": 500},
"top_comments": [
{"author": "A", "text": "this aged well", "digg_count": 50000, "date": "2026-03-02"},
],
}
]
normalized = normalize.normalize_source_items(
"tiktok", items, "2026-02-15", "2026-03-17",
)
self.assertAlmostEqual(math.log1p(50000), signals._top_comment_score(normalized[0]), places=4)
def test_grounding_requires_a_usable_date(self):
items = [
{
"id": "g-1",
"title": "Undated result",
"url": "https://example.com/undated",
"snippet": "No date attached.",
}
]
normalized = normalize.normalize_source_items(
"grounding",
items,
"2026-02-15",
"2026-03-17",
)
self.assertEqual([], normalized)
if __name__ == "__main__":
unittest.main()