"""Schémas d'entrée/sortie de l'import.

Le rapport ne contient que des **codes** de traduction + des paramètres
structurés, jamais de phrase (voir `locales/fr.json`).
"""

import datetime as dt
import uuid
from typing import Literal

from pydantic import BaseModel, Field

Severity = Literal["ERROR", "WARNING"]
RowAction = Literal["CREATED", "UPDATED", "SKIPPED"]


class ColumnMapping(BaseModel):
    first_name: str
    last_name: str
    email: str | None = None
    phone: str | None = None
    tshirt_size: str | None = None
    diet: str | None = None
    comment: str | None = None
    skills: str | None = None


class AvailabilityColumnMapping(BaseModel):
    header: str
    date: dt.date
    day_part_code: str


class ImportMapping(BaseModel):
    dry_run: bool = True
    columns: ColumnMapping
    availability_columns: list[AvailabilityColumnMapping] = Field(
        default_factory=list
    )


class Issue(BaseModel):
    code: str
    severity: Severity
    field: str | None = None
    params: dict[str, str | int | None] = Field(default_factory=dict)


class RowReport(BaseModel):
    line: int
    action: RowAction
    volunteer_id: uuid.UUID | None = None
    issues: list[Issue] = Field(default_factory=list)


class ImportReport(BaseModel):
    dry_run: bool
    total_rows: int
    created: int = 0
    updated: int = 0
    skipped: int = 0
    availabilities_written: int = 0
    skills_created: list[str] = Field(default_factory=list)
    rows: list[RowReport] = Field(default_factory=list)


class PreviewRow(BaseModel):
    line: int
    values: dict[str, str]


class DayPartInfo(BaseModel):
    code: str
    label: str
    start_time: dt.time
    end_time: dt.time
    order: int


class AnalyzeResponse(BaseModel):
    filename: str
    format: Literal["csv", "xlsx"]
    headers: list[str]
    row_count: int
    preview: list[PreviewRow]
    suggested_mapping: dict[str, str]
    edition_dates: list[dt.date]
    day_parts: list[DayPartInfo]