Philip Guzman
42 lines
1.5 KiB
Python
42 lines
1.5 KiB
Python
from collections import defaultdict
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from typing import DefaultDict, Iterable, List, Tuple
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from serato_doctor.matching import cloud_conflict_name, normalize
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from serato_doctor.models.duplicate import DuplicateGroup, DuplicateKind
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from serato_doctor.models.track import DiskTrack
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def find_duplicate_groups(
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tracks: Iterable[DiskTrack],
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) -> Tuple[DuplicateGroup, ...]:
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"""Find exact-name duplicates and suspected numeric conflict copies."""
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track_tuple = tuple(tracks)
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by_name: DefaultDict[str, List[DiskTrack]] = defaultdict(list)
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by_conflict_name: DefaultDict[str, List[DiskTrack]] = defaultdict(list)
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for track in track_tuple:
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by_name[normalize(track.filename)].append(track)
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by_conflict_name[cloud_conflict_name(track.filename)].append(track)
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groups = []
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for key, matches in by_name.items():
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if len(matches) > 1:
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groups.append(_group(DuplicateKind.EXACT_NAME, key, matches))
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for key, matches in by_conflict_name.items():
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distinct_names = {normalize(track.filename) for track in matches}
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if len(distinct_names) > 1:
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groups.append(_group(DuplicateKind.CLOUD_CONFLICT, key, matches))
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return tuple(
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sorted(groups, key=lambda group: (group.kind.value, group.comparison_key))
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)
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def _group(
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kind: DuplicateKind, key: str, tracks: Iterable[DiskTrack]
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) -> DuplicateGroup:
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ordered = tuple(sorted(tracks, key=lambda track: str(track.path)))
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return DuplicateGroup(kind, key, ordered)
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