'''
NeuralBridge Adapter for Snowflake Data Warehouse.

This adapter provides a unified interface to interact with Snowflake, allowing
users to execute queries, manage database objects, and perform administrative
tasks programmatically.

Configuration (YAML)
--------------------
.. code-block:: yaml

    adapters:
      my_snowflake_db:
        adapter: snowflake
        config:
          account: "your_account.snowflakecomputing.com"
          user: "your_username"
          password: "your_password"
          warehouse: "your_warehouse"
          database: "your_database"
          schema: "your_schema"
          role: "your_role"

Supported Operations
--------------------
- **query**: Execute a SELECT statement and retrieve results.
- **list_schemas**: List all schemas in the current database.
- **list_tables**: List all tables within a specific schema.
- **describe_table**: Retrieve the column metadata for a given table.
- **execute_sql**: Execute a non-query SQL statement (e.g., DDL, DML).

'''

from __future__ import annotations

import asyncio
from typing import Any

import structlog

from neuralbridge.adapters.base import AdapterResponse, BaseAdapter

logger = structlog.get_logger(__name__)


class SnowflakeAdapter(BaseAdapter):
    '''
    Connects to and interacts with a Snowflake Data Warehouse.

    This adapter uses mock implementations for database interactions to allow for
    development and testing without a live Snowflake connection. In a production
    environment, it would use the official snowflake-connector-python library.
    '''

    # --- Adapter Metadata ---
    adapter_type: str = "snowflake"
    category: str = "databases"
    description: str = "Adapter for Snowflake Data Warehouse."
    version: str = "0.1.1"
    supported_operations: list[str] = [
        "query",
        "list_schemas",
        "list_tables",
        "describe_table",
        "execute_sql",
    ]

    def __init__(self, config: dict[str, Any] | None = None) -> None:
        '''Initializes the Snowflake adapter instance.'''
        super().__init__(config)
        self._connection: Any = None

    # --- Configuration Schema ---

    def _get_config_schema(self) -> dict[str, Any]:
        '''
        Returns the JSON Schema for the Snowflake adapter's configuration.

        This schema defines the required and optional parameters for connecting
        to a Snowflake instance.
        '''
        return {
            "type": "object",
            "properties": {
                "account": {"type": "string", "description": "Snowflake account identifier."},
                "user": {"type": "string", "description": "Username for authentication."},
                "password": {"type": "string", "description": "Password for authentication."},
                "warehouse": {"type": "string", "description": "Default warehouse to use."},
                "database": {"type": "string", "description": "Default database to use."},
                "schema": {"type": "string", "description": "Default schema to use."},
                "role": {"type": "string", "description": "Default role to use."},
            },
            "required": ["account", "user", "password", "warehouse", "database"],
        }

    # --- Abstract Method Implementations ---

    async def _do_connect(self) -> None:
        '''
        Establishes a connection to the Snowflake database.

        This is a mock implementation. In a real-world scenario, this method
        would use the snowflake-connector-python library to create a live
        connection object.
        '''
        logger.info(
            "snowflake_adapter_connecting",
            account=self.config.get("account"),
            database=self.config.get("database"),
        )
        # MOCK: In production, this would use snowflake.connector.connect()
        await asyncio.sleep(0.1)  # Simulate network latency
        self._connection = {
            "status": "connected",
            "account": self.config.get("account"),
            "user": self.config.get("user"),
            "database": self.config.get("database"),
            "schema": self.config.get("schema"),
        }
        logger.info("snowflake_adapter_mock_connection_established")

    async def _do_disconnect(self) -> None:
        '''
        Closes the connection to the Snowflake database.

        This is a mock implementation. A real implementation would call the
        `close()` method on the connection object.
        '''
        if self._connection:
            logger.info("snowflake_adapter_disconnecting")
            # MOCK: In production, this would call self._connection.close()
            await asyncio.sleep(0.05)
            self._connection = None
            logger.info("snowflake_adapter_mock_connection_closed")

    async def _do_validate_credentials(self) -> dict[str, Any]:
        '''
        Validates the configured credentials by attempting a test connection.

        Returns a dictionary with validation details. This mock implementation
        always succeeds.
        '''
        # MOCK: In production, this would attempt a real connection and
        # report success or failure.
        logger.info("snowflake_adapter_validating_credentials")
        await asyncio.sleep(0.2)
        return {
            "status": "ok",
            "message": "Credentials appear to be valid (mock check).",
            "account": self.config.get("account"),
        }

    async def _do_execute(self, operation: str, params: dict[str, Any]) -> AdapterResponse:
        '''
        Dispatches and executes the requested operation.

        This method routes the operation to the appropriate handler function.
        '''
        if operation == "query":
            return await self._op_query(params)
        elif operation == "list_schemas":
            return await self._op_list_schemas()
        elif operation == "list_tables":
            return await self._op_list_tables(params)
        elif operation == "describe_table":
            return await self._op_describe_table(params)
        elif operation == "execute_sql":
            return await self._op_execute_sql(params)
        else:
            # This path should ideally not be reached due to the check in BaseAdapter
            return AdapterResponse(success=False, error=f"Unsupported operation: {operation}")

    # --- Operation-Specific Implementations ---

    async def _op_query(self, params: dict[str, Any]) -> AdapterResponse:
        '''MOCK: Executes a read-only SQL query.'''
        sql = params.get("sql")
        if not sql:
            return AdapterResponse(success=False, error="'sql' parameter is required for query.")

        logger.info("snowflake_adapter_executing_query", sql=sql)
        await asyncio.sleep(0.3)  # Simulate query execution time

        # MOCK: Return a realistic-looking dataset
        mock_data = [
            {"ID": 1, "NAME": "First Customer", "EMAIL": "customer1@example.com"},
            {"ID": 2, "NAME": "Second Customer", "EMAIL": "customer2@example.com"},
            {"ID": 3, "NAME": "Third Customer", "EMAIL": "customer3@example.com"},
        ]
        return AdapterResponse(success=True, data=mock_data)

    async def _op_list_schemas(self) -> AdapterResponse:
        '''MOCK: Lists all schemas in the current database.'''
        logger.info("snowflake_adapter_listing_schemas")
        await asyncio.sleep(0.1)
        mock_schemas = [
            {"name": "PUBLIC", "created_on": "2023-01-01T10:00:00Z"},
            {"name": "INFORMATION_SCHEMA", "created_on": "2023-01-01T10:00:00Z"},
            {"name": "CUSTOM_SCHEMA_1", "created_on": "2023-05-15T14:30:00Z"},
        ]
        return AdapterResponse(success=True, data=mock_schemas)

    async def _op_list_tables(self, params: dict[str, Any]) -> AdapterResponse:
        '''MOCK: Lists tables in a given schema.'''
        schema = params.get("schema", self.config.get("schema", "PUBLIC"))
        logger.info("snowflake_adapter_listing_tables", schema=schema)
        await asyncio.sleep(0.1)
        mock_tables = [
            {"name": "CUSTOMERS", "schema": schema, "rows": 1500},
            {"name": "ORDERS", "schema": schema, "rows": 12500},
            {"name": "PRODUCTS", "schema": schema, "rows": 200},
        ]
        return AdapterResponse(success=True, data=mock_tables)

    async def _op_describe_table(self, params: dict[str, Any]) -> AdapterResponse:
        '''MOCK: Describes the columns of a table.'''
        table_name = params.get("table_name")
        if not table_name:
            return AdapterResponse(success=False, error="'table_name' parameter is required.")

        logger.info("snowflake_adapter_describing_table", table=table_name)
        await asyncio.sleep(0.1)
        mock_description = [
            {"column_name": "ID", "data_type": "NUMBER(38,0)", "is_nullable": "N"},
            {"column_name": "NAME", "data_type": "VARCHAR(255)", "is_nullable": "N"},
            {"column_name": "EMAIL", "data_type": "VARCHAR(255)", "is_nullable": "Y"},
            {"column_name": "CREATED_AT", "data_type": "TIMESTAMP_NTZ", "is_nullable": "N"},
        ]
        return AdapterResponse(success=True, data=mock_description)

    async def _op_execute_sql(self, params: dict[str, Any]) -> AdapterResponse:
        '''MOCK: Executes a DML or DDL statement.'''
        sql = params.get("sql")
        if not sql:
            return AdapterResponse(success=False, error="'sql' parameter is required.")

        logger.info("snowflake_adapter_executing_sql", sql=sql)
        await asyncio.sleep(0.2)

        # MOCK: Determine affected rows based on statement type
        if "INSERT" in sql.upper():
            affected_rows = 1
        elif "UPDATE" in sql.upper():
            affected_rows = 5
        elif "DELETE" in sql.upper():
            affected_rows = 2
        else:
            affected_rows = 0  # For DDL like CREATE, ALTER

        return AdapterResponse(
            success=True,
            data={"status": "success", "rows_affected": affected_rows},
            metadata={"sql": sql},
        )

