"""效能分析服务 — 个人能力图谱 + 设备流转对比（ECharts 数据源）

数据来源：
  - Task      工序/任务节点，携带 assignee_id、received_at、completed_at → 计算单台耗时。
  - Product   设备身份证(sn)、规格型号(spec_model)、物料名，用于筛选与展示。
  - TaskRecord 备注时间线（本模块当前仅作耗时主数据补充，可按需在后续下钻中引入）。

耗时口径：
  - 单台真实耗时 = (completed_at or now) - (received_at or created_at)，单位小时。
  - naive datetime 按 UTC 处理，统一换算北京时间。
"""
from datetime import datetime, timezone

from sqlalchemy import select, func
from sqlalchemy.ext.asyncio import AsyncSession
from pydantic import BaseModel


# ============================================================
# Schemas（与前端 src/services/analyticsApi.ts 对齐）
# ============================================================

class CapabilityDataPoint(BaseModel):
    value: float | None      # 该人员在该设备上的总耗时（未触及为 None，真实 0 为 0.0）
    spec_model: str          # 规格型号
    status: str              # 该设备当前状态 WIP/PENDING/COMPLETED/—
    first_received_at: str   # 最早接收时间 YYYY-MM-DD HH:mm
    last_completed_at: str   # 最后完成时间 YYYY-MM-DD HH:mm（无则空串）


class CapabilityDevice(BaseModel):
    product_sn: str              # 身份证
    external_serial: str | None  # 产品序列号（业务序列号）
    spec_model: str              # 规格型号
    material_name: str           # 物料名称


class CapabilitySeries(BaseModel):
    name: str          # 人员姓名
    assignee_id: str   # 人员ID
    data: list[CapabilityDataPoint]   # 与 categories 严格对齐，未触及设备补 0


class CapabilityResponse(BaseModel):
    categories: list[str]              # X 轴：设备身份证（按时间升序）
    devices: list[CapabilityDevice]    # 与 categories 对齐的设备元数据
    series: list[CapabilitySeries]


class FlowDevice(BaseModel):
    product_sn: str
    external_serial: str | None
    material_name: str
    spec_model: str
    lead_time: float   # 设备生命周期总时长（小时）= max_end - min_start
    started_at: str    # 设备最早介入时间（T0），格式 MM-DD HH:mm
    total_days: int = 0       # 设备生产总天数（自然天，自最早介入至今）
    total_workdays: int = 0   # 设备生产总天数（工作日，排除周末/节假日）


class FlowSeries(BaseModel):
    name: str          # 人员姓名
    data: list[list]   # 每项 = [device_index, start_offset, end_offset, task_name, duration]（小时）


class FlowResponse(BaseModel):
    devices: list[FlowDevice]
    series: list[FlowSeries]


class AssigneeOption(BaseModel):
    id: str
    name: str


class SpecModelOption(BaseModel):
    spec_model: str
    material_name: str


class DeviceOption(BaseModel):
    product_sn: str
    external_serial: str | None
    material_name: str
    spec_model: str


class AnalyticsOptions(BaseModel):
    assignees: list[AssigneeOption]
    spec_models: list[SpecModelOption]
    devices: list[DeviceOption]


class DeviceRecord(BaseModel):
    task_name: str          # 工序名
    assignee_name: str      # 负责人姓名
    status: str             # 任务状态
    remark: str | None      # 备注
    images: list[str]       # 图片 URL 列表
    created_at: str         # 记录时间 ISO


# ============================================================
# 时间工具
# ============================================================

def _to_bj(dt: datetime | None) -> datetime | None:
    """naive datetime 按 UTC 处理，统一换算为北京时间。"""
    from app.core.time_utils import BEIJING_TZ
    if not dt:
        return None
    if dt.tzinfo is None:
        dt = dt.replace(tzinfo=timezone.utc).astimezone(BEIJING_TZ)
    else:
        dt = dt.astimezone(BEIJING_TZ)
    return dt


def _duration_hours(start: datetime | None, end: datetime, holidays: set = None, mode: str = "workdays") -> float:
    """计算单台耗时（小时），无开始时间返回 0。
    mode=workdays: 排除周末/节假日的工作小时；mode=natural: 自然小时。"""
    if not start:
        return 0.0
    if mode == "natural":
        return (end - start).total_seconds() / 3600
    from app.core.time_utils import working_duration_hours
    return working_duration_hours(start, end, holidays)


# ============================================================
# 个人能力图谱 — 单台设备耗时对比（分组柱状图，X=设备身份证）
# ============================================================

async def get_capability_profile(
    db: AsyncSession,
    assignee_ids: list[str] | None = None,
    spec_models: list[str] | None = None,
    since: datetime | None = None,
    until: datetime | None = None,
    mode: str = "workdays",
) -> CapabilityResponse:
    """
    个人能力图谱（单机颗粒度）：X 轴 = 设备身份证，每个负责人一条柱状 series。
    按 (负责人, 设备) 分组，累加该人在该设备所有工序的耗时，
    series.data 与 categories 严格对齐，未触及设备补 0。
    耗时口径：(coalesce(completed_at, now) - coalesce(received_at, created_at))。
    """
    from app.models.task import (
        Task, TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED,
    )
    from app.models.product import Product
    from app.models.holiday import Holiday
    from app.core.time_utils import get_beijing_time

    now = get_beijing_time()

    # 读取节假日（排除非工作日）
    hres = await db.execute(select(Holiday.day))
    holidays = {r[0] for r in hres}

    stmt = (
        select(
            Task.assignee_id, Task.status,
            Task.received_at, Task.created_at, Task.completed_at,
            Product.serial_number, Product.external_serial, Product.spec_model,
            Product.material_name,
        )
        .join(Product, Task.product_id == Product.id)
        .where(
            Task.status.in_([TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED]),
            Task.assignee_id.isnot(None),
        )
    )
    if assignee_ids:
        stmt = stmt.where(Task.assignee_id.in_(assignee_ids))
    if spec_models:
        stmt = stmt.where(Product.spec_model.in_(spec_models))

    # 时间交集（与 people-history 口径一致）
    start_expr = func.coalesce(Task.received_at, Task.created_at)
    end_expr = func.coalesce(Task.completed_at, now)
    if until:
        stmt = stmt.where(start_expr <= until)
    if since:
        stmt = stmt.where(end_expr >= since)

    result = await db.execute(stmt)
    rows = result.all()

    # 设备元数据 + 时间基准；人员×设备 耗时聚合
    device_meta: dict[str, dict] = {}
    agg: dict[tuple[str, str], dict] = {}
    for row in rows:
        assignee = row[0]
        status = row[1]
        start = _to_bj(row[2] or row[3])        # received_at or created_at
        end = _to_bj(row[4]) if row[4] else now  # completed_at or now
        sn = row[5]
        ext = row[6]
        spec = row[7] or "未知型号"
        mat = row[8] or ""

        meta = device_meta.setdefault(sn, {"external_serial": ext, "spec_model": spec, "material_name": mat, "earliest": None})
        if start and (meta["earliest"] is None or start < meta["earliest"]):
            meta["earliest"] = start

        entry = agg.setdefault((assignee, sn), {
            "hours": 0.0, "prio": 9,
            "first_start": None, "last_completed": None,
        })
        entry["hours"] += _duration_hours(start, end, holidays, mode)
        if start and (entry["first_start"] is None or start < entry["first_start"]):
            entry["first_start"] = start
        completed_dt = _to_bj(row[4]) if row[4] else None
        if completed_dt and (entry["last_completed"] is None or completed_dt > entry["last_completed"]):
            entry["last_completed"] = completed_dt
        prio = 0 if status == TASK_STATUS_WIP else (1 if status == TASK_STATUS_PENDING else 2)
        entry["prio"] = min(entry["prio"], prio)

    if not agg:
        return CapabilityResponse(categories=[], devices=[], series=[])

    # X 轴：按最早接收/创建时间升序的设备身份证
    categories = sorted(device_meta.keys(), key=lambda s: device_meta[s]["earliest"] or now)
    devices = [
        CapabilityDevice(
            product_sn=sn,
            external_serial=device_meta[sn]["external_serial"],
            spec_model=device_meta[sn]["spec_model"],
            material_name=device_meta[sn]["material_name"],
        )
        for sn in categories
    ]

    # 人员姓名映射
    raw_ids = list({a for (a, _) in agg.keys()})
    name_map: dict[str, str] = {}
    if raw_ids:
        from app.services.mom_cache import get_display_names
        name_map = get_display_names(raw_ids)

    STATUS_CODE = {0: "WIP", 1: "PENDING", 2: "COMPLETED"}

    by_assignee: dict[str, dict[str, dict]] = {}
    for (a, sn), entry in agg.items():
        by_assignee.setdefault(a, {})[sn] = entry

    series: list[CapabilitySeries] = []
    for a in sorted(by_assignee.keys()):
        sn_entries = by_assignee[a]
        data: list[CapabilityDataPoint] = []
        for sn in categories:
            e = sn_entries.get(sn)
            if e:
                data.append(CapabilityDataPoint(
                    value=round(e["hours"], 1),
                    spec_model=device_meta[sn]["spec_model"],
                    status=STATUS_CODE[e["prio"]],
                    first_received_at=e["first_start"].strftime("%Y-%m-%d %H:%M") if e["first_start"] else "",
                    last_completed_at=e["last_completed"].strftime("%Y-%m-%d %H:%M") if e["last_completed"] else "",
                ))
            else:
                data.append(CapabilityDataPoint(
                    value=None,
                    spec_model=device_meta[sn]["spec_model"],
                    status="—",
                    first_received_at="",
                    last_completed_at="",
                ))
        series.append(CapabilitySeries(
            name=name_map.get(a, a),
            assignee_id=a,
            data=data,
        ))
    series.sort(key=lambda s: s.name)
    return CapabilityResponse(categories=categories, devices=devices, series=series)


# ============================================================
# 流转对比 — 设备各工序耗时（堆叠柱状）
# ============================================================

async def get_flow_compare(
    db: AsyncSession,
    product_sns: list[str] | None = None,
    spec_models: list[str] | None = None,
    mode: str = "natural",
) -> FlowResponse:
    """
    查询每台设备上各操作人的任务时间区间，拼装为「生命周期时间轴」区间图：
    x 轴 = 设备身份证，y 轴 = 相对该设备 T0（最早介入时间）的小时偏移。
    每个任务一根悬空区间柱（start_offset -> end_offset），并行任务可并排显示。

    设备来源：
      - 传 product_sns：按给定身份证；
      - 仅传 spec_models：这些型号下最近有流转的 20 台设备；
      - 都未传：返回空。

    data 每项 = [device_index, start_offset, end_offset, task_name, duration]（单位小时）。
    """
    from app.models.task import Task, TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED
    from app.models.product import Product
    from app.core.time_utils import get_beijing_time

    now = get_beijing_time()

    if product_sns:
        product_rows = (await db.execute(
            select(
                Product.id, Product.serial_number, Product.external_serial,
                Product.material_name, Product.spec_model,
            ).where(Product.serial_number.in_(product_sns))
        )).all()
    elif spec_models:
        latest_subq = (
            select(
                Task.product_id,
                func.max(func.coalesce(Task.received_at, Task.created_at)).label("latest"),
            )
            .group_by(Task.product_id)
            .subquery()
        )
        product_rows = (await db.execute(
            select(
                Product.id, Product.serial_number, Product.external_serial,
                Product.material_name, Product.spec_model,
            )
            .join(latest_subq, latest_subq.c.product_id == Product.id)
            .where(Product.spec_model.in_(spec_models))
            .order_by(latest_subq.c.latest.desc())
            .limit(20)
        )).all()
    else:
        return FlowResponse(devices=[], series=[])

    if not product_rows:
        return FlowResponse(devices=[], series=[])

    devices = [
        FlowDevice(
            product_sn=r[1], external_serial=r[2],
            material_name=r[3] or "", spec_model=r[4] or "",
            lead_time=0.0,
            started_at="",
        )
        for r in product_rows
    ]
    # 显式传入身份证时按输入顺序排列
    if product_sns:
        order = {sn: i for i, sn in enumerate(product_sns)}
        devices.sort(key=lambda d: order.get(d.product_sn, len(order)))

    id_to_sn = {r[0]: r[1] for r in product_rows}
    sn_to_index = {d.product_sn: i for i, d in enumerate(devices)}
    product_ids = [r[0] for r in product_rows]

    # ── 这些设备的全部任务（含工序名，用于区间图） ──
    task_rows = (await db.execute(
        select(
            Task.product_id, Task.assignee_id, Task.task_name,
            Task.received_at, Task.created_at, Task.completed_at,
            Task.task_type,
        )
        .where(
            Task.product_id.in_(product_ids),
            Task.status.in_([TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED]),
            Task.assignee_id.isnot(None),
        )
    )).all()

    # ── 解析为区间记录，并计算每台设备的 T0（最早）与 max_end（最晚） ──
    intervals: list[dict] = []
    t0_by_device: dict[int, datetime] = {}
    max_end_by_device: dict[int, datetime] = {}
    for row in task_rows:
        pid, assignee_id, task_name, received_at, created_at, completed_at, task_type = row
        sn = id_to_sn.get(pid)
        if sn is None or sn not in sn_to_index:
            continue
        idx = sn_to_index[sn]
        start = _to_bj(received_at or created_at)
        end = _to_bj(completed_at) if completed_at else now
        if start is None:
            continue
        is_main = 0 if task_type == "SPAWN" else 1
        intervals.append({
            "idx": idx,
            "assignee_id": assignee_id,
            "task_name": (task_name or "").strip() or "未命名工序",
            "start": start,
            "end": end,
            "is_main": is_main,
        })
        if idx not in t0_by_device or start < t0_by_device[idx]:
            t0_by_device[idx] = start
        if idx not in max_end_by_device or end > max_end_by_device[idx]:
            max_end_by_device[idx] = end

    # ── 计算每台设备 lead_time（最大 end - 最小 start，小时），重建 devices ──
    lead_time_by_index = {
        idx: round((max_end_by_device[idx] - t0_by_device[idx]).total_seconds() / 3600, 1)
        for idx in t0_by_device
    }
    # 🔧 设备生产总天数（自然天 + 工作日，自最早介入至今）
    import math
    from app.core.time_utils import to_beijing as _tb, working_duration_hours as _wdh
    from app.models.holiday import Holiday as _Holiday
    hres = await db.execute(select(_Holiday.day))
    _holidays = {r[0] for r in hres}

    def _total_days(t0):
        t0_bj = _tb(t0)
        if not t0_bj:
            return 1, 1
        natural = max(1, math.ceil((now - t0_bj).total_seconds() / 86400))
        workdays = max(1, math.ceil(_wdh(t0_bj, now, _holidays) / 24))
        return natural, workdays

    days_map = {i: _total_days(t0_by_device[i]) for i in t0_by_device}
    devices = [
        FlowDevice(
            product_sn=d.product_sn, external_serial=d.external_serial,
            material_name=d.material_name, spec_model=d.spec_model,
            lead_time=lead_time_by_index.get(i, 0.0),
            started_at=t0_by_device[i].strftime("%m-%d %H:%M") if i in t0_by_device else "",
            total_days=days_map.get(i, (1, 1))[0],
            total_workdays=days_map.get(i, (1, 1))[1],
        )
        for i, d in enumerate(devices)
    ]

    # ── 按人分组，转为相对 T0 的小时偏移区间 ──
    by_assignee: dict[str, list[list]] = {}
    # 工作日模式：把时间偏移换算为「排除周末/节假日的工作小时」，压缩休息日
    if mode == "workdays":
        from app.core.time_utils import working_duration_hours as _wdh
        from app.models.holiday import Holiday as _Holiday
        hres = await db.execute(select(_Holiday.day))
        _holidays = {r[0] for r in hres}
    for it in intervals:
        t0 = t0_by_device[it["idx"]]
        if mode == "workdays":
            start_offset = _wdh(t0, it["start"], _holidays)
            end_offset = _wdh(t0, it["end"], _holidays)
        else:
            start_offset = round((it["start"] - t0).total_seconds() / 3600, 1)
            end_offset = round((it["end"] - t0).total_seconds() / 3600, 1)
        duration = round(end_offset - start_offset, 1)
        by_assignee.setdefault(it["assignee_id"], []).append(
            [it["idx"], start_offset, end_offset, it["task_name"], duration, it["is_main"]]
        )

    # 翻译人员姓名
    raw_ids = list(by_assignee.keys())
    name_map: dict[str, str] = {}
    if raw_ids:
        from app.services.mom_cache import get_display_names
        name_map = get_display_names(raw_ids)

    series = [
        FlowSeries(name=name_map.get(a, a), data=by_assignee[a])
        for a in sorted(by_assignee.keys())
    ]
    return FlowResponse(devices=devices, series=series)


# ============================================================
# 设备备注记录 — 单台设备的全部备注/照片（弹窗下钻）
# ============================================================

async def get_device_records(
    db: AsyncSession,
    product_sn: str,
    assignee_ids: list[str] | None = None,
) -> list[DeviceRecord]:
    """查询某台设备（身份证）的所有任务备注记录，含图片，按时间倒序。
    可选按负责人过滤（assignee_ids）。"""
    import json
    from app.models.task import Task, TaskRecord
    from app.models.product import Product

    product_id = await db.scalar(
        select(Product.id).where(Product.serial_number == product_sn)
    )
    if not product_id:
        return []

    stmt = (
        select(
            TaskRecord.remark, TaskRecord.images, TaskRecord.created_at,
            Task.task_name, Task.assignee_id, Task.status,
        )
        .join(Task, TaskRecord.task_id == Task.id)
        .where(Task.product_id == product_id)
    )
    if assignee_ids:
        stmt = stmt.where(Task.assignee_id.in_(assignee_ids))
    stmt = stmt.order_by(TaskRecord.created_at.desc())
    result = await db.execute(stmt)
    rows = result.all()

    raw_ids = list({r[4] for r in rows if r[4]})
    name_map: dict[str, str] = {}
    if raw_ids:
        from app.services.mom_cache import get_display_names
        name_map = get_display_names(raw_ids)

    records: list[DeviceRecord] = []
    for row in rows:
        remark, images_raw, created, task_name, assignee, status = row
        try:
            images = json.loads(images_raw) if images_raw else []
        except (json.JSONDecodeError, TypeError):
            images = []
        if not isinstance(images, list):
            images = []
        records.append(DeviceRecord(
            task_name=task_name or "",
            assignee_name=name_map.get(assignee or "", assignee or ""),
            status=status or "",
            remark=remark,
            images=images,
            created_at=_to_bj(created).isoformat() if created else "",
        ))
    return records


# ============================================================
# 下拉选项 — 负责人 + 规格型号
# ============================================================

async def get_analytics_options(
    db: AsyncSession,
    assignee_ids: list[str] | None = None,
    spec_models: list[str] | None = None,
) -> AnalyticsOptions:
    """返回筛选栏选项，支持动态联动：
      - 传入 spec_models：只返回碰过这些型号的人；
      - 传入 assignee_ids：只返回这些人处理过的型号；
      - devices：根据筛选条件返回关联设备（无筛选则返回最近流转的设备）。"""
    from app.models.task import Task
    from app.models.product import Product

    # ── 负责人：从 tasks 去重（可选按 spec_models 过滤） ──
    if spec_models:
        assignee_stmt = (
            select(Task.assignee_id)
            .join(Product, Task.product_id == Product.id)
            .where(
                Task.assignee_id.isnot(None),
                Product.spec_model.in_(spec_models),
            )
            .distinct()
        )
    else:
        assignee_stmt = (
            select(Task.assignee_id)
            .where(Task.assignee_id.isnot(None))
            .distinct()
        )
    assignee_rows = (await db.execute(assignee_stmt)).all()
    distinct_assignees = sorted({r[0] for r in assignee_rows if r[0]})

    name_map: dict[str, str] = {}
    if distinct_assignees:
        from app.services.mom_cache import get_display_names
        name_map = get_display_names(distinct_assignees)

    assignees = [
        AssigneeOption(id=aid, name=name_map.get(aid, aid))
        for aid in distinct_assignees
    ]

    # ── 规格型号 + 物料名（可选按 assignee_ids 过滤；同型号取首个非空物料名） ──
    if assignee_ids:
        spec_stmt = (
            select(Product.spec_model, Product.material_name)
            .join(Task, Task.product_id == Product.id)
            .where(
                Product.spec_model.isnot(None),
                func.trim(Product.spec_model) != "",
                Task.assignee_id.in_(assignee_ids),
            )
            .distinct()
        )
    else:
        spec_stmt = (
            select(Product.spec_model, Product.material_name)
            .where(Product.spec_model.isnot(None), func.trim(Product.spec_model) != "")
            .distinct()
        )
    spec_rows = (await db.execute(spec_stmt)).all()
    spec_map: dict[str, str] = {}
    for row in spec_rows:
        sm = row[0]
        mn = (row[1] or "").strip()
        if sm not in spec_map:
            spec_map[sm] = mn
        elif mn and not spec_map[sm]:
            spec_map[sm] = mn
    spec_model_opts = [
        SpecModelOption(spec_model=sm, material_name=spec_map[sm])
        for sm in sorted(spec_map.keys())
    ]

    # ── 设备字典（可选按 assignee_ids / spec_models 过滤；无筛选返回最近流转 100 台） ──
    if assignee_ids or spec_models:
        device_stmt = select(
            Product.serial_number, Product.external_serial,
            Product.material_name, Product.spec_model,
        )
        if assignee_ids:
            device_stmt = device_stmt.join(
                Task, Task.product_id == Product.id
            ).where(Task.assignee_id.in_(assignee_ids))
        if spec_models:
            device_stmt = device_stmt.where(Product.spec_model.in_(spec_models))
        device_stmt = device_stmt.distinct()
    else:
        latest_subq = (
            select(
                Task.product_id,
                func.max(func.coalesce(Task.received_at, Task.created_at)).label("latest"),
            )
            .group_by(Task.product_id)
            .subquery()
        )
        device_stmt = (
            select(
                Product.serial_number, Product.external_serial,
                Product.material_name, Product.spec_model,
            )
            .join(latest_subq, latest_subq.c.product_id == Product.id)
            .order_by(latest_subq.c.latest.desc())
            .limit(100)
        )
    device_rows = (await db.execute(device_stmt)).all()
    devices = [
        DeviceOption(
            product_sn=r[0] or "",
            external_serial=r[1] or None,
            material_name=r[2] or "",
            spec_model=r[3] or "",
        )
        for r in device_rows
    ]

    return AnalyticsOptions(assignees=assignees, spec_models=spec_model_opts, devices=devices)