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AI Bot 22d80f3d94 test(wave129): asset_scoring资产评分+64单测
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- 覆盖8大模块:权重/分辨率评分/时长评分/码率评分/加权总分/单素材评分/分桶/多样性选择/候选过滤/数据类
- 边界值全覆盖:0/None/负数/临界值/最佳区间
- 多样性选择验证:多桶分布/去重/配额/不足时回退
2026-07-27 18:26:45 +08:00
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"""资产评分纯逻辑单元测试 — wave129."""
from __future__ import annotations
from dataclasses import dataclass
import pytest
from packages.domain.asset_scoring import (
AssetScoreDetail,
SmartSelectResult,
_bucket_by_duration,
calculate_total_score,
diverse_selection,
filter_candidates,
score_asset_detail,
score_bitrate,
score_duration,
score_resolution,
WEIGHT_QUALITY,
WEIGHT_RESOLUTION,
WEIGHT_DURATION,
WEIGHT_BITRATE,
)
# ── 常量与权重 ──────────────────────────────────────────────────────────────
class TestWeights:
def test_weights_sum_to_one(self):
total = WEIGHT_QUALITY + WEIGHT_RESOLUTION + WEIGHT_DURATION + WEIGHT_BITRATE
assert abs(total - 1.0) < 0.001
def test_quality_is_highest_weight(self):
assert WEIGHT_QUALITY > WEIGHT_RESOLUTION
assert WEIGHT_QUALITY > WEIGHT_DURATION
assert WEIGHT_QUALITY > WEIGHT_BITRATE
# ── 分辨率评分 ──────────────────────────────────────────────────────────────
class TestScoreResolution:
def test_exact_target_full_score(self):
assert score_resolution(1920, 1080) == 1.0
def test_higher_than_target_full_score(self):
"""4K 等高于目标分辨率也给满分."""
assert score_resolution(3840, 2160) == 1.0
assert score_resolution(2560, 1440) == 1.0
def test_seventytwop_less_than_one(self):
score = score_resolution(1280, 720)
assert 0.5 < score < 1.0
def test_fourheightyp_even_lower(self):
score_480 = score_resolution(854, 480)
score_720 = score_resolution(1280, 720)
assert score_480 < score_720
def test_none_returns_medium(self):
assert score_resolution(None, None) == 0.5
assert score_resolution(None, 1080) == 0.5
assert score_resolution(1920, None) == 0.5
def test_zero_or_negative_returns_medium(self):
assert score_resolution(0, 1080) == 0.5
assert score_resolution(-100, 1080) == 0.5
assert score_resolution(1920, 0) == 0.5
def test_custom_target_resolution(self):
score = score_resolution(1280, 720, target_width=1280, target_height=720)
assert score == 1.0
def test_score_between_zero_one(self):
score = score_resolution(320, 240)
assert 0.0 < score < 1.0
def test_very_low_resolution_not_zero(self):
"""低分也不会低于 0.1."""
score = score_resolution(160, 120)
assert score >= 0.1
# ── 时长评分 ────────────────────────────────────────────────────────────────
class TestScoreDuration:
def test_optimal_range_full_score(self):
"""3-30秒最佳区间满分."""
assert score_duration(3.0) == 1.0
assert score_duration(10.0) == 1.0
assert score_duration(30.0) == 1.0
def test_very_short_lower_score(self):
score_1s = score_duration(1.0)
assert 0.3 <= score_1s < 1.0
def test_shorter_than_optimal_lower(self):
"""越短分越低."""
score_1 = score_duration(1.0)
score_2 = score_duration(2.0)
assert score_1 < score_2
def test_just_below_optimal(self):
score = score_duration(2.9)
assert score < 1.0
assert score > 0.8 # 接近满分
def test_too_long_penalty(self):
score_30 = score_duration(30.0)
score_60 = score_duration(60.0)
assert score_60 < score_30
def test_very_long_minimum_floor(self):
"""超长素材最低 0.2 分."""
score = score_duration(1000.0)
assert score >= 0.2
def test_none_returns_medium(self):
assert score_duration(None) == 0.5
def test_zero_returns_medium(self):
assert score_duration(0) == 0.5
assert score_duration(0.0) == 0.5
def test_negative_returns_medium(self):
assert score_duration(-5.0) == 0.5
# ── 码率评分 ────────────────────────────────────────────────────────────────
class TestScoreBitrate:
def test_optimal_bitrate_full_score(self):
"""2-8 Mbps 区间满分."""
# 5 Mbps, 10秒 = 50Mbit = 6.25MB = 6,250,000 字节
size_5mbps_10s = int(5_000_000 * 10 / 8)
assert score_bitrate(size_5mbps_10s, 10.0) == 1.0
# 3 Mbps, 5秒
size_3mbps_5s = int(3_000_000 * 5 / 8)
assert score_bitrate(size_3mbps_5s, 5.0) == 1.0
def test_low_bitrate_lower_score(self):
"""码率低得分低."""
# 500 Kbps
size_low = int(500_000 * 10 / 8)
score = score_bitrate(size_low, 10.0)
assert 0.3 <= score < 1.0
def test_high_bitrate_moderate_penalty(self):
"""码率过高适度扣分,最低0.5."""
# 50 Mbps,远超 8Mbps
size_high = int(50_000_000 * 10 / 8)
score = score_bitrate(size_high, 10.0)
assert 0.5 <= score < 1.0
def test_none_duration_returns_medium(self):
assert score_bitrate(1_000_000, None) == 0.5
def test_zero_file_size_returns_medium(self):
assert score_bitrate(0, 10.0) == 0.5
def test_zero_duration_returns_medium(self):
assert score_bitrate(1_000_000, 0) == 0.5
assert score_bitrate(1_000_000, -5.0) == 0.5
# ── 加权总分 ────────────────────────────────────────────────────────────────
class TestCalculateTotalScore:
def test_all_perfect(self):
assert calculate_total_score(1.0, 1.0, 1.0, 1.0) == 1.0
def test_all_zero(self):
assert calculate_total_score(0.0, 0.0, 0.0, 0.0) == 0.0
def test_weighted_calculation(self):
"""手动验证加权计算."""
q, r, d, b = 0.8, 0.6, 0.4, 0.2
expected = WEIGHT_QUALITY * q + WEIGHT_RESOLUTION * r + WEIGHT_DURATION * d + WEIGHT_BITRATE * b
assert calculate_total_score(q, r, d, b) == pytest.approx(expected, rel=1e-3)
def test_quality_dominates(self):
"""质量分权重最高,质量分变化影响最大."""
score_high_quality = calculate_total_score(1.0, 0.5, 0.5, 0.5)
score_low_quality = calculate_total_score(0.0, 0.5, 0.5, 0.5)
diff_quality = score_high_quality - score_low_quality
score_high_res = calculate_total_score(0.5, 1.0, 0.5, 0.5)
score_low_res = calculate_total_score(0.5, 0.0, 0.5, 0.5)
diff_res = score_high_res - score_low_res
assert diff_quality > diff_res
def test_rounded_to_4_decimals(self):
result = calculate_total_score(0.3333, 0.3333, 0.3333, 0.3333)
assert result == round(result, 4)
# ── 单个素材评分详情 ────────────────────────────────────────────────────────
class TestScoreAssetDetail:
def test_normal_asset(self):
detail = score_asset_detail(
asset_id="asset_001",
quality=80.0,
width=1920,
height=1080,
duration=10.0,
file_size=5_000_000,
)
assert detail.asset_id == "asset_001"
assert 0.0 <= detail.total_score <= 1.0
assert detail.quality_score == pytest.approx(0.8)
assert detail.resolution_score == 1.0
assert detail.duration_score == 1.0
assert detail.duration == 10.0
def test_unknown_quality_defaults(self):
detail = score_asset_detail(
asset_id="a1",
quality=None,
width=1920,
height=1080,
duration=10.0,
file_size=5_000_000,
)
assert detail.quality_score == 0.5
def test_quality_hundred_is_one(self):
detail = score_asset_detail(
asset_id="a1",
quality=100.0,
width=1920,
height=1080,
duration=10.0,
file_size=1_000_000,
)
assert detail.quality_score == 1.0
def test_quality_zero_is_zero(self):
detail = score_asset_detail(
asset_id="a1",
quality=0.0,
width=1920,
height=1080,
duration=10.0,
file_size=1_000_000,
)
assert detail.quality_score == 0.0
def test_custom_target_resolution(self):
detail = score_asset_detail(
asset_id="a1",
quality=50.0,
width=1280,
height=720,
duration=10.0,
file_size=1_000_000,
target_width=1280,
target_height=720,
)
assert detail.resolution_score == 1.0
# ── 时长分桶 ────────────────────────────────────────────────────────────────
def _make_detail(asset_id: str, duration: float | None, score: float = 0.8) -> AssetScoreDetail:
return AssetScoreDetail(
asset_id=asset_id,
total_score=score,
quality_score=score,
resolution_score=score,
duration_score=score,
bitrate_score=score,
duration=duration,
)
class TestBucketByDuration:
def test_short_bucket(self):
item = _make_detail("s1", duration=3.0)
assert _bucket_by_duration(item) == "short"
def test_short_boundary(self):
item = _make_detail("s1", duration=4.9)
assert _bucket_by_duration(item) == "short"
def test_medium_bucket(self):
item = _make_detail("m1", duration=10.0)
assert _bucket_by_duration(item) == "medium"
def test_medium_boundary(self):
item = _make_detail("m1", duration=14.9)
assert _bucket_by_duration(item) == "medium"
def test_long_bucket(self):
item = _make_detail("l1", duration=20.0)
assert _bucket_by_duration(item) == "long"
def test_long_at_boundary(self):
""">=15s 为长素材."""
item = _make_detail("l1", duration=15.0)
assert _bucket_by_duration(item) == "long"
def test_unknown_bucket(self):
item = _make_detail("u1", duration=None)
assert _bucket_by_duration(item) == "unknown"
# ── 多样性选择 ──────────────────────────────────────────────────────────────
class TestDiverseSelection:
def _make_scored_list(self) -> list[AssetScoreDetail]:
"""构造一个包含各时长桶的测试列表,按分数降序."""
items = [
_make_detail("high_short", duration=3.0, score=0.95),
_make_detail("high_medium", duration=8.0, score=0.9),
_make_detail("high_long", duration=30.0, score=0.85),
_make_detail("mid_short", duration=2.0, score=0.8),
_make_detail("mid_medium", duration=10.0, score=0.75),
_make_detail("mid_long", duration=20.0, score=0.7),
_make_detail("low_short", duration=4.0, score=0.6),
_make_detail("low_medium", duration=12.0, score=0.5),
_make_detail("low_long", duration=60.0, score=0.4),
]
items.sort(key=lambda x: x.total_score, reverse=True)
return items
def test_empty_list_returns_empty(self):
assert diverse_selection([], 5) == []
def test_zero_count_returns_empty(self):
items = self._make_scored_list()
assert diverse_selection(items, 0) == []
def test_negative_count_returns_empty(self):
items = self._make_scored_list()
assert diverse_selection(items, -1) == []
def test_selects_from_multiple_buckets(self):
items = self._make_scored_list()
result = diverse_selection(items, 6)
assert len(result) == 6
# 应该包含来自不同桶的素材
durations = [r.duration for r in result]
has_short = any(d and d < 5.0 for d in durations)
has_medium = any(d and 5.0 <= d < 15.0 for d in durations)
has_long = any(d and d >= 15.0 for d in durations)
assert has_short and has_medium and has_long
def test_no_duplicate_ids(self):
items = self._make_scored_list()
result = diverse_selection(items, 9)
ids = [r.asset_id for r in result]
assert len(ids) == len(set(ids))
def test_not_more_than_count(self):
items = self._make_scored_list()
result = diverse_selection(items, 3)
assert len(result) <= 3
def test_fewer_assets_than_count(self):
items = [_make_detail("a1", duration=3.0, score=0.9)]
result = diverse_selection(items, 10)
assert len(result) == 1
def test_only_short_bucket(self):
items = [
_make_detail("s1", duration=1.0, score=0.9),
_make_detail("s2", duration=2.0, score=0.8),
_make_detail("s3", duration=3.0, score=0.7),
]
result = diverse_selection(items, 3)
assert len(result) == 3
# 只有短素材,应该都返回
assert all(r.duration and r.duration < 5.0 for r in result)
def test_highest_scores_priority(self):
"""分数最高的素材应该优先被选中."""
items = self._make_scored_list()
result = diverse_selection(items, 3)
# 最高分的那个应该在结果里
assert result[0].asset_id == "high_short"
def test_contains_top_scoring_items(self):
"""结果中应该包含全局最高分的素材."""
items = self._make_scored_list()
result = diverse_selection(items, 6)
result_ids = {r.asset_id for r in result}
# 全局最高分的应该在结果中
assert "high_short" in result_ids
assert "high_medium" in result_ids
# ── 候选过滤 ────────────────────────────────────────────────────────────────
@dataclass
class MockAsset:
asset_id: str
status: str = "ready"
mime_type: str = "video/mp4"
quality_score: float | None = None
class TestFilterCandidates:
def test_ready_video_passes(self):
assets = [MockAsset("a1", status="ready", mime_type="video/mp4")]
candidates, filtered = filter_candidates(assets)
assert len(candidates) == 1
assert filtered == 0
def test_not_ready_filtered(self):
assets = [
MockAsset("a1", status="processing"),
MockAsset("a2", status="failed"),
MockAsset("a3", status="ready"),
]
candidates, filtered = filter_candidates(assets)
assert len(candidates) == 1
assert candidates[0].asset_id == "a3"
assert filtered == 0 # 状态不对的不算质量过滤
def test_non_video_filtered(self):
assets = [
MockAsset("a1", mime_type="image/jpeg"),
MockAsset("a2", mime_type="audio/mp3"),
MockAsset("a3", mime_type="video/mp4"),
]
candidates, filtered = filter_candidates(assets)
assert len(candidates) == 1
assert filtered == 0
def test_video_mime_prefix(self):
"""所有以 video 开头的 MIME 都通过."""
assets = [
MockAsset("a1", mime_type="video/mp4"),
MockAsset("a2", mime_type="video/webm"),
MockAsset("a3", mime_type="video/x-matroska"),
]
candidates, _ = filter_candidates(assets)
assert len(candidates) == 3
def test_low_quality_filtered_counted(self):
"""质量分低于门槛的计入 filtered_out."""
assets = [
MockAsset("good", quality_score=80.0),
MockAsset("bad", quality_score=20.0),
]
candidates, filtered = filter_candidates(assets, min_quality_score=30.0)
assert len(candidates) == 1
assert candidates[0].asset_id == "good"
assert filtered == 1
def test_none_quality_passes(self):
"""quality_score 为 None 的不做质量检查,通过."""
assets = [MockAsset("a1", quality_score=None)]
candidates, filtered = filter_candidates(assets, min_quality_score=30.0)
assert len(candidates) == 1
assert filtered == 0
def test_quality_at_threshold_passes(self):
"""刚好等于门槛值的通过."""
assets = [MockAsset("a1", quality_score=30.0)]
candidates, filtered = filter_candidates(assets, min_quality_score=30.0)
assert len(candidates) == 1
assert filtered == 0
def test_empty_list(self):
candidates, filtered = filter_candidates([])
assert candidates == []
assert filtered == 0
def test_none_mime_type_treated_as_empty(self):
assets = [MockAsset("a1", mime_type=None)] # type: ignore
candidates, _ = filter_candidates(assets)
assert len(candidates) == 0
# ── 数据类 ──────────────────────────────────────────────────────────────────
class TestDataClasses:
def test_score_detail_defaults(self):
detail = AssetScoreDetail(
asset_id="test",
total_score=0.5,
quality_score=0.5,
resolution_score=0.5,
duration_score=0.5,
bitrate_score=0.5,
duration=None,
)
assert detail.asset_id == "test"
assert detail.total_score == 0.5
assert detail.duration is None
def test_smart_select_result_defaults(self):
result = SmartSelectResult(
selected_ids=["a1", "a2"],
total_candidates=10,
filtered_out=3,
avg_score=0.75,
)
assert len(result.selected_ids) == 2
assert result.total_candidates == 10
assert result.filtered_out == 3
assert result.details == [] # 默认空列表