75 lines
2.2 KiB
Python
75 lines
2.2 KiB
Python
"""Utilities that drive the modern Textual UI menus and presets."""
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from __future__ import annotations
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import sys
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any, Dict, Iterable, List, Optional, Sequence
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BASE_DIR = Path(__file__).resolve().parent
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ROOT_DIR = BASE_DIR.parent
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for path in (ROOT_DIR, BASE_DIR):
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str_path = str(path)
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if str_path not in sys.path:
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sys.path.insert(0, str_path)
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import metadata
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@dataclass(slots=True)
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class PipelinePreset:
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"""Simple descriptor for a reusable pipeline."""
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label: str
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description: str
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pipeline: str
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PIPELINE_PRESETS: List[PipelinePreset] = [
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PipelinePreset(
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label="Download → Merge → Local",
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description="Use download-data with playlist auto-selection, merge the pieces, tag, then import into local storage.",
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pipeline='download-data "<url>" | merge-file | add-tag | add-file -storage local',
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),
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PipelinePreset(
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label="Download → Hydrus",
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description="Fetch media, auto-tag, and push directly into Hydrus.",
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pipeline='download-data "<url>" | merge-file | add-tag | add-file -storage hydrus',
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),
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PipelinePreset(
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label="Search Local Library",
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description="Run search-file against the local library and emit a result table for further piping.",
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pipeline='search-file -library local -query "<keywords>"',
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),
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]
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def load_tags(file_path: Path) -> List[str]:
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"""Read tags for a file using metadata.py as the single source of truth."""
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try:
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return metadata.read_tags_from_file(file_path)
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except Exception:
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return []
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def group_tags_by_namespace(tags: Sequence[str]) -> Dict[str, List[str]]:
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"""Return tags grouped by namespace for quick UI summaries."""
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grouped: Dict[str, List[str]] = {}
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for tag in metadata.normalize_tags(list(tags)):
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namespace, value = metadata.split_tag(tag)
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key = namespace or "_untagged"
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grouped.setdefault(key, []).append(value)
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for items in grouped.values():
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items.sort()
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return grouped
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def normalize_tags(tags: Iterable[str]) -> List[str]:
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"""Expose metadata.normalize_tags for callers that imported the old helper."""
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return metadata.normalize_tags(list(tags))
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