"""Schemas for the data processor service."""

from typing import Any, Dict, List
from pydantic import BaseModel, Field


class UpdateDbResponse(BaseModel):
    success: bool = Field(
        ..., description="Indicates if the database update was successful."
    )


class TableConfigSchema(BaseModel):
    """Schema for a single table configuration.

    Defines how a table should be read from Power BI and preprocessed.

    Attributes:
        name: The name to use for the table in the local SQLite database
        powerbi_table_name: The name of the source table in Power BI dataset
        steps: List of preprocessing steps to apply to the table data
    """

    name: str = Field(
        ..., description="Name for the table in the local database", example="Data"
    )
    powerbi_table_name: str = Field(
        ...,
        description="Name of the table in the Power BI dataset",
        example="data_full",
    )
    steps: List[Dict[str, Any]] = Field(
        default_factory=list,
        description="List of preprocessing steps to apply",
        example=[
            {"keep": {"columns": ["col1", "col2"]}},
            {"fillna": {"column": "col1", "value": "Unknown"}},
        ],
    )


class PreprocessingConfigSchema(BaseModel):
    """Schema for the complete preprocessing configuration.

    This schema defines the structure for JSON-based preprocessing configuration,
    replacing the need for a YAML configuration file. It allows dynamic
    configuration of table preprocessing operations per API request.

    The configuration supports multiple tables, each with its own set of
    preprocessing steps. Available preprocessing steps include:

    - **keep**: Keep only specified columns
        - Parameters: columns (List[str])
        - Example: {"keep": {"columns": ["Name", "Price", "Quantity"]}}

    - **fillna**: Fill missing values in a column
        - Parameters: column (str), value (Any)
        - Example: {"fillna": {"column": "Supplier", "value": "Unknown"}}

    - **to_numeric**: Convert a column to numeric type
        - Parameters: column (str), errors (str, optional)
        - Example: {"to_numeric": {"column": "Price", "errors": "coerce"}}

    - **dropna**: Drop rows with missing values in specified columns
        - Parameters: subset (List[str])
        - Example: {"dropna": {"subset": ["Name", "Price"]}}

    Attributes:
        tables: List of table configurations to process

    Example Request Body:
        {
            "tables": [
                {
                    "name": "ProductData",
                    "powerbi_table_name": "products_raw",
                    "steps": [
                        {
                            "keep": {
                                "columns": [
                                    "ProductID",
                                    "ProductName",
                                    "Supplier",
                                    "Stock",
                                    "Unit",
                                    "Price"
                                ]
                            }
                        },
                        {
                            "fillna": {
                                "column": "Supplier",
                                "value": "Unknown"
                            }
                        },
                        {
                            "to_numeric": {
                                "column": "Price",
                                "errors": "coerce"
                            }
                        },
                        {
                            "dropna": {
                                "subset": [
                                    "ProductID",
                                    "ProductName",
                                    "Stock",
                                    "Unit",
                                    "Price"
                                ]
                            }
                        }
                    ]
                }
            ]
        }
    """

    tables: List[TableConfigSchema] = Field(
        ..., description="List of table configurations to process", min_items=1
    )


class UpdateDbWithConfigResponse(BaseModel):
    """Response schema for the JSON-based database update endpoint.

    Attributes:
        success: Indicates if the database update was successful
        tables_processed: Number of tables that were processed
        warnings: List of any warnings encountered during preprocessing
    """

    success: bool = Field(
        ..., description="Indicates if the database update was successful"
    )
    tables_processed: int = Field(
        ..., description="Number of tables that were successfully processed"
    )
    warnings: List[str] = Field(
        default_factory=list,
        description="List of warnings encountered during preprocessing",
    )