import uuid
from datetime import datetime, timezone
from typing import Protocol

from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession

from ..entities.vocab_entities import LearnableWordBankEntryEntity, UserLanguagePairEntity
from ....domain.models.vocab import LearnableWordBankEntry, UserLanguagePair


class VocabRepository(Protocol):
    async def get_or_create_language_pair(
        self, user_id: uuid.UUID, source_lang: str, target_lang: str
    ) -> UserLanguagePair: ...

    async def get_language_pair(self, language_pair_id: uuid.UUID) -> UserLanguagePair | None: ...

    async def add_entry(
        self,
        user_id: uuid.UUID,
        language_pair_id: uuid.UUID,
        surface_text: str,
        entry_pathway: str,
        is_phrase: bool = False,
        sense_id: uuid.UUID | None = None,
        wordform_id: uuid.UUID | None = None,
        source_article_id: uuid.UUID | None = None,
        disambiguation_status: str = "pending",
    ) -> LearnableWordBankEntry: ...

    async def get_entries_for_user(
        self, user_id: uuid.UUID, language_pair_id: uuid.UUID
    ) -> list[LearnableWordBankEntry]: ...

    async def set_sense(
        self, entry_id: uuid.UUID, sense_id: uuid.UUID
    ) -> LearnableWordBankEntry: ...

    async def get_pending_disambiguation(self, user_id: uuid.UUID) -> list[LearnableWordBankEntry]: ...


def _pair_to_model(entity: UserLanguagePairEntity) -> UserLanguagePair:
    return UserLanguagePair(
        id=str(entity.id),
        user_id=str(entity.user_id),
        source_lang=entity.source_lang,
        target_lang=entity.target_lang,
    )


def _entry_to_model(entity: LearnableWordBankEntryEntity) -> LearnableWordBankEntry:
    return LearnableWordBankEntry(
        id=str(entity.id),
        user_id=str(entity.user_id),
        language_pair_id=str(entity.language_pair_id),
        sense_id=str(entity.sense_id) if entity.sense_id else None,
        wordform_id=str(entity.wordform_id) if entity.wordform_id else None,
        surface_text=entity.surface_text,
        is_phrase=entity.is_phrase,
        entry_pathway=entity.entry_pathway,
        source_article_id=str(entity.source_article_id) if entity.source_article_id else None,
        disambiguation_status=entity.disambiguation_status,
        created_at=entity.created_at,
    )


class PostgresVocabRepository:
    def __init__(self, db: AsyncSession) -> None:
        self.db = db

    async def get_or_create_language_pair(
        self, user_id: uuid.UUID, source_lang: str, target_lang: str
    ) -> UserLanguagePair:
        result = await self.db.execute(
            select(UserLanguagePairEntity).where(
                UserLanguagePairEntity.user_id == user_id,
                UserLanguagePairEntity.source_lang == source_lang,
                UserLanguagePairEntity.target_lang == target_lang,
            )
        )
        entity = result.scalar_one_or_none()
        if entity is None:
            entity = UserLanguagePairEntity(
                user_id=user_id,
                source_lang=source_lang,
                target_lang=target_lang,
            )
            self.db.add(entity)
            await self.db.flush()
        return _pair_to_model(entity)

    async def get_language_pair(self, language_pair_id: uuid.UUID) -> UserLanguagePair | None:
        result = await self.db.execute(
            select(UserLanguagePairEntity).where(UserLanguagePairEntity.id == language_pair_id)
        )
        entity = result.scalar_one_or_none()
        return _pair_to_model(entity) if entity else None

    async def add_entry(
        self,
        user_id: uuid.UUID,
        language_pair_id: uuid.UUID,
        surface_text: str,
        entry_pathway: str,
        is_phrase: bool = False,
        sense_id: uuid.UUID | None = None,
        wordform_id: uuid.UUID | None = None,
        source_article_id: uuid.UUID | None = None,
        disambiguation_status: str = "pending",
    ) -> LearnableWordBankEntry:
        entity = LearnableWordBankEntryEntity(
            user_id=user_id,
            language_pair_id=language_pair_id,
            surface_text=surface_text,
            entry_pathway=entry_pathway,
            is_phrase=is_phrase,
            sense_id=sense_id,
            wordform_id=wordform_id,
            source_article_id=source_article_id,
            disambiguation_status=disambiguation_status,
            created_at=datetime.now(timezone.utc),
        )
        self.db.add(entity)
        await self.db.commit()
        await self.db.refresh(entity)
        return _entry_to_model(entity)

    async def get_entries_for_user(
        self, user_id: uuid.UUID, language_pair_id: uuid.UUID
    ) -> list[LearnableWordBankEntry]:
        result = await self.db.execute(
            select(LearnableWordBankEntryEntity)
            .where(
                LearnableWordBankEntryEntity.user_id == user_id,
                LearnableWordBankEntryEntity.language_pair_id == language_pair_id,
            )
            .order_by(LearnableWordBankEntryEntity.created_at.desc())
        )
        return [_entry_to_model(e) for e in result.scalars().all()]

    async def set_sense(
        self, entry_id: uuid.UUID, sense_id: uuid.UUID
    ) -> LearnableWordBankEntry:
        result = await self.db.execute(
            select(LearnableWordBankEntryEntity).where(
                LearnableWordBankEntryEntity.id == entry_id
            )
        )
        entity = result.scalar_one()
        entity.sense_id = sense_id
        entity.disambiguation_status = "resolved"
        await self.db.commit()
        await self.db.refresh(entity)
        return _entry_to_model(entity)

    async def get_pending_disambiguation(self, user_id: uuid.UUID) -> list[LearnableWordBankEntry]:
        result = await self.db.execute(
            select(LearnableWordBankEntryEntity)
            .where(
                LearnableWordBankEntryEntity.user_id == user_id,
                LearnableWordBankEntryEntity.disambiguation_status == "pending",
            )
            .order_by(LearnableWordBankEntryEntity.created_at.desc())
        )
        return [_entry_to_model(e) for e in result.scalars().all()]