"""数据库表定义"""

from sqlalchemy import (
    MetaData, Table, Column, Integer, Float, Text, Boolean, DateTime,
    func
)

metadata = MetaData()

recommendations_table = Table(
    "recommendations", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("ts_code", Text, nullable=False),
    Column("name", Text, nullable=False),
    Column("sector", Text),
    Column("score", Float),
    Column("market_temp_score", Float),
    Column("sector_score", Float),
    Column("capital_score", Float),
    Column("technical_score", Float),
    Column("supply_demand_score", Float, default=0),
    Column("price_action_score", Float, default=0),
    Column("position_score", Float),
    Column("valuation_score", Float),
    Column("signal", Text),
    Column("entry_price", Float),
    Column("target_price", Float),
    Column("stop_loss", Float),
    Column("reasons", Text),
    Column("risk_note", Text, default=""),
    Column("action_plan", Text, default="观察"),
    Column("trigger_condition", Text, default=""),
    Column("invalidation_condition", Text, default=""),
    Column("suggested_position_pct", Float, default=0),
    Column("review_after_days", Integer, default=3),
    Column("lifecycle_status", Text, default="candidate"),
    Column("data_freshness", Text, default=""),
    Column("llm_analysis", Text, default=""),
    Column("strategy", Text, default="trend_breakout"),
    Column("entry_signal_type", Text, default="none"),
    Column("entry_timing", Text, default=""),
    Column("llm_score", Float, default=None),
    Column("recall_tags", Text, default="[]"),
    Column("prefilter_decision", Text, default=""),
    Column("prefilter_reason", Text, default=""),
    Column("focus_points", Text, default="[]"),
    Column("scan_session", Text),
    Column("created_at", DateTime, server_default=func.now()),
)

sector_heat_table = Table(
    "sector_heat", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("sector_code", Text, nullable=False),
    Column("sector_name", Text, nullable=False),
    Column("pct_change", Float),
    Column("capital_inflow", Float),
    Column("limit_up_count", Integer),
    Column("heat_score", Float),
    Column("stage", Text),
    Column("days_continuous", Integer),
    Column("member_count", Integer),
    Column("leading_stocks", Text),   # JSON string
    Column("pct_trend", Text),        # JSON string
    Column("turnover_avg", Float),
    Column("main_force_ratio", Float),
    Column("trade_date", Text, nullable=False),
    Column("created_at", DateTime, server_default=func.now()),
)

market_temperature_table = Table(
    "market_temperature", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("trade_date", Text, nullable=False, unique=True),
    Column("up_count", Integer),
    Column("down_count", Integer),
    Column("limit_up_count", Integer),
    Column("limit_down_count", Integer),
    Column("max_streak", Integer),
    Column("broken_rate", Float),
    Column("temperature", Float),
    Column("created_at", DateTime, server_default=func.now()),
)

recommendation_tracking_table = Table(
    "recommendation_tracking", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("recommendation_id", Integer),
    Column("track_date", Text, nullable=False),
    Column("current_price", Float),
    Column("pct_from_entry", Float),
    Column("max_price", Float),
    Column("min_price", Float),
    Column("max_return_pct", Float),
    Column("max_drawdown_pct", Float),
    Column("days_since_recommendation", Integer, default=0),
    Column("hit_target", Boolean, default=False),
    Column("hit_stop_loss", Boolean, default=False),
    Column("close_reason", Text, default=""),
    Column("review_note", Text, default=""),
    Column("status", Text, default="active"),
    Column("created_at", DateTime, server_default=func.now()),
)

users_table = Table(
    "users", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("username", Text, nullable=False, unique=True),
    Column("password_hash", Text, nullable=False),
    Column("role", Text, default="user"),
    Column("is_active", Boolean, default=True),
    Column("created_at", DateTime, server_default=func.now()),
    Column("updated_at", DateTime, server_default=func.now()),
)

stock_diagnoses_table = Table(
    "stock_diagnoses", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("ts_code", Text, nullable=False),
    Column("name", Text, nullable=False),
    Column("diagnosis_mode", Text, default="entry"),
    Column("diagnosis", Text, nullable=False),
    Column("created_at", DateTime, server_default=func.now()),
)

user_watchlists_table = Table(
    "user_watchlists", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("user_id", Integer, nullable=False),
    Column("ts_code", Text, nullable=False),
    Column("name", Text, nullable=False),
    Column("note", Text, default=""),
    Column("watch_group", Text, default="observe"),
    Column("cost_price", Float, default=None),
    Column("is_active", Boolean, default=True),
    Column("created_at", DateTime, server_default=func.now()),
    Column("updated_at", DateTime, server_default=func.now()),
)

watchlist_analyses_table = Table(
    "watchlist_analyses", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("user_id", Integer, nullable=False),
    Column("watchlist_id", Integer, nullable=False),
    Column("ts_code", Text, nullable=False),
    Column("name", Text, nullable=False),
    Column("conclusion", Text, default="观察"),
    Column("advice", Text, default=""),
    Column("trigger_condition", Text, default=""),
    Column("risk_note", Text, default=""),
    Column("summary", Text, default=""),
    Column("full_analysis", Text, default=""),
    Column("score_reference", Float, default=0),
    Column("analysis_mode", Text, default="scheduled"),
    Column("created_at", DateTime, server_default=func.now()),
)

error_logs_table = Table(
    "error_logs", metadata,
    Column("id", Integer, primary_key=True, autoincrement=True),
    Column("source", Text, nullable=False),      # 模块来源，如 "recommender", "screener"
    Column("level", Text, default="error"),       # error / warning
    Column("message", Text, nullable=False),      # 错误消息
    Column("detail", Text, default=""),           # 完整异常信息（traceback）
    Column("created_at", DateTime, server_default=func.now()),
)