mirror of
https://github.com/Horizontal42/Sort_YM.git
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187c30b4ab
Aggregates liked tracks into top artists, genres, decades and top albums with fixed size ceilings instead of a per-track dump, so it can be pasted into an LLM chat regardless of library size. Fully offline - reads only the existing cache, no Client/network needed. Adds album_title/year to the track cache (one-time re-fetch) to support the decade and album views.
42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
from __future__ import annotations
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import tomllib
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from dataclasses import dataclass
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent.parent
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@dataclass(frozen=True)
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class Config:
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fetch_batch_delay: float
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lyrics_request_delay: float
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apply_request_delay: float
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request_timeout: float
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batch_size: int
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small_group_min: int
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digest_top_artists: int
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digest_top_albums: int
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token_file: Path
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cache_dir: Path
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out_dir: Path
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def load_config(path: Path | None = None) -> Config:
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path = path or ROOT / "config.toml"
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with path.open("rb") as f:
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data = tomllib.load(f)
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return Config(
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fetch_batch_delay=data["throttle"]["fetch_batch_delay"],
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lyrics_request_delay=data["throttle"]["lyrics_request_delay"],
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apply_request_delay=data["throttle"]["apply_request_delay"],
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request_timeout=data["throttle"]["request_timeout"],
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batch_size=data["fetch"]["batch_size"],
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small_group_min=data["classify"]["small_group_min"],
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digest_top_artists=data["digest"]["top_artists"],
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digest_top_albums=data["digest"]["top_albums"],
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token_file=ROOT / data["paths"]["token_file"],
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cache_dir=ROOT / data["paths"]["cache_dir"],
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out_dir=ROOT / data["paths"]["out_dir"],
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)
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