145 lines
3.4 KiB
Python
145 lines
3.4 KiB
Python
import dataclasses
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import datetime
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import enum
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from typing import Self
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from folkugat_web.model.search import NGrams
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from folkugat_web.model.sessions import Session
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from folkugat_web.services import ngrams
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from ._base import IndexedList, WithId
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class ContentType(enum.Enum):
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PARTITURA = "partitura"
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AUDIO = "àudio"
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OTHER = "enllaç"
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class LinkType(enum.Enum):
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# Score
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PDF = "pdf"
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IMAGE = "image"
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# Audio
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SPOTIFY = "spotify"
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YOUTUBE = "youtube"
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@dataclasses.dataclass
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class Link(WithId):
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content_type: ContentType
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link_type: LinkType | None
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url: str
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title: str = ""
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def to_dict(self):
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return dict(
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id=self.id,
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content_type=self.content_type.value,
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link_type=self.link_type.value if self.link_type else None,
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url=self.url,
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title=self.title,
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)
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@classmethod
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def from_dict(cls, d):
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return cls(
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id=d["id"],
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content_type=ContentType(d["content_type"]),
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link_type=LinkType(d["link_type"]) if d["link_type"] else None,
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url=d["url"],
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title=d["title"],
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)
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class PropertyField(enum.Enum):
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AUTOR = "autor"
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TIPUS = "tipus"
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COMPAS = "compàs"
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ORIGEN = "orígen"
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@dataclasses.dataclass
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class Property(WithId):
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field: PropertyField
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value: str
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def to_dict(self):
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return dict(
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id=self.id,
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field=self.field.value,
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value=self.value,
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)
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@classmethod
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def from_dict(cls, d):
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return cls(
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id=d["id"],
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field=PropertyField(d["field"]),
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value=d["value"],
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)
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@dataclasses.dataclass
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class Lyrics(WithId):
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title: str
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content: str
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def to_dict(self):
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return dict(
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id=self.id,
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title=self.title,
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content=self.content,
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)
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@classmethod
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def from_dict(cls, d) -> Self:
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return cls(
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id=d["id"],
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title=d["title"],
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content=d["content"],
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)
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@dataclasses.dataclass
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class Stats:
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times_played: int
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sessions_played: list[Session]
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@dataclasses.dataclass
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class Tema:
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id: int | None = None
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# Info
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title: str = ""
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properties: IndexedList[Property] = dataclasses.field(default_factory=IndexedList)
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links: IndexedList[Link] = dataclasses.field(default_factory=IndexedList)
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lyrics: IndexedList[Lyrics] = dataclasses.field(default_factory=IndexedList)
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# Search related
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alternatives: list[str] = dataclasses.field(default_factory=list)
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ngrams: NGrams = dataclasses.field(default_factory=dict)
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hidden: bool = True
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# Other info
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modification_date: datetime.datetime = dataclasses.field(default_factory=datetime.datetime.now)
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creation_date: datetime.datetime = dataclasses.field(default_factory=datetime.datetime.now)
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# Stats
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stats: Stats | None = None
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def compute_ngrams(self):
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self.ngrams = ngrams.get_text_ngrams(self.title, *self.alternatives)
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def with_ngrams(self):
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self.compute_ngrams()
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return self
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@staticmethod
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def _is_score(link: Link) -> bool:
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if link.content_type is not ContentType.PARTITURA:
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return False
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if link.link_type is LinkType.PDF:
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return link.url.startswith("/")
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return link.link_type is LinkType.IMAGE
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def score(self) -> Link | None:
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return next(filter(self._is_score, self.links), None)
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