"""
Schema 提取器 —— 只提取表结构，不碰数据
"""
import sqlite3
from typing import Any


def extract_schema(db_path: str) -> dict[str, Any]:
    """从数据库提取 Schema，只返回结构信息"""
    conn = sqlite3.connect(db_path)
    conn.row_factory = sqlite3.Row
    cur = conn.cursor()

    cur.execute("SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%'")
    tables = [row["name"] for row in cur.fetchall()]

    schema = {"tables": []}

    for table in tables:
        cur.execute(f"PRAGMA table_info('{table}')")
        columns = []
        for col in cur.fetchall():
            columns.append({
                "name": col["name"],
                "type": col["type"],
                "nullable": col["notnull"] == 0,
                "is_primary_key": col["pk"] == 1,
            })

        cur.execute(f"PRAGMA foreign_key_list('{table}')")
        fks = [
            {"column": fk["from"], "references_table": fk["table"], "references_column": fk["to"]}
            for fk in cur.fetchall()
        ]

        cur.execute(f"SELECT COUNT(*) AS cnt FROM '{table}'")
        row_count = cur.fetchone()["cnt"]

        data_profile = {}
        for col in columns:
            col_name = col["name"]
            col_type = (col["type"] or "").upper()

            if any(t in col_type for t in ("VARCHAR", "TEXT", "CHAR")):
                cur.execute(f'SELECT DISTINCT "{col_name}" FROM "{table}" WHERE "{col_name}" IS NOT NULL LIMIT 20')
                vals = [row[0] for row in cur.fetchall()]
                if len(vals) <= 20:
                    data_profile[col_name] = {"type": "enum", "distinct_count": len(vals), "values": vals}
            elif any(t in col_type for t in ("INT", "REAL", "FLOAT", "DOUBLE", "DECIMAL", "NUMERIC")):
                cur.execute(f'''
                    SELECT MIN("{col_name}") AS min_val, MAX("{col_name}") AS max_val,
                           AVG("{col_name}") AS avg_val, COUNT(DISTINCT "{col_name}") AS distinct_count
                    FROM "{table}" WHERE "{col_name}" IS NOT NULL
                ''')
                row = cur.fetchone()
                if row and row["min_val"] is not None:
                    data_profile[col_name] = {
                        "type": "numeric",
                        "min": round(row["min_val"], 2), "max": round(row["max_val"], 2),
                        "avg": round(row["avg_val"], 2), "distinct_count": row["distinct_count"],
                    }

        schema["tables"].append({
            "name": table, "columns": columns, "foreign_keys": fks,
            "row_count": row_count, "data_profile": data_profile,
        })

    conn.close()
    return schema


def schema_to_text(schema: dict) -> str:
    """将 Schema 转为可读文本，供 LLM 理解"""
    lines = ["=== 数据库 Schema ===\n"]
    for table in schema["tables"]:
        lines.append(f"📋 表: {table['name']} (共 {table['row_count']} 行)")
        lines.append("  列:")
        for col in table["columns"]:
            pk = " [PK]" if col["is_primary_key"] else ""
            null = " NULL" if col["nullable"] else " NOT NULL"
            lines.append(f'    - {col["name"]}: {col["type"]}{pk}{null}')
        if table["foreign_keys"]:
            lines.append("  外键:")
            for fk in table["foreign_keys"]:
                lines.append(f'    - {fk["column"]} → {fk["references_table"]}.{fk["references_column"]}')
        if table["data_profile"]:
            lines.append("  数据画像:")
            for col_name, profile in table["data_profile"].items():
                if profile["type"] == "enum":
                    vals = ", ".join(str(v) for v in profile["values"][:10])
                    lines.append(f'    - {col_name}: 枚举值({profile["distinct_count"]}个) = [{vals}]')
                elif profile["type"] == "numeric":
                    lines.append(
                        f'    - {col_name}: 范围[{profile["min"]} ~ {profile["max"]}], '
                        f'均值{profile["avg"]}, {profile["distinct_count"]}个不同值'
                    )
        lines.append("")
    return "\n".join(lines)