# #region DatasetsApi [C:3] [TYPE Module] [SEMANTICS fastapi, dataset, api, search, mapping, mapped-fields]
#
# @BRIEF API endpoints for the Dataset Hub - listing datasets with mapping progress
# @LAYER:     API
# @RELATION DEPENDS_ON -> [AppDependencies]
# @RELATION DEPENDS_ON -> [ResourceService]
# @RELATION DEPENDS_ON -> [SupersetClient]
#
# @INVARIANT: All dataset responses include last_task metadata


from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field

from ...core.logger import belief_scope, logger
from ...core.superset_client import SupersetClient
from ...dependencies import get_config_manager, get_resource_service, get_task_manager, has_permission

router = APIRouter(prefix="/api/datasets", tags=["Datasets"])

# #region MappedFields [C:1] [TYPE DataClass]
# @BRIEF DTO for dataset mapping progress statistics
class MappedFields(BaseModel):
    total: int
    mapped: int
# #endregion MappedFields

# #region LastTask [C:1] [TYPE DataClass]
# @BRIEF DTO for the most recent task associated with a dataset
class LastTask(BaseModel):
    task_id: str | None = None
    status: str | None = Field(None, pattern="^RUNNING|SUCCESS|ERROR|WAITING_INPUT$")
# #endregion LastTask

# #region DatasetItem [C:1] [TYPE DataClass]
# @BRIEF Summary DTO for a dataset in the hub listing
class DatasetItem(BaseModel):
    id: int
    table_name: str
    schema_name: str = Field(..., alias="schema")
    database: str
    mapped_fields: MappedFields | None = None
    last_task: LastTask | None = None

    class Config:
        allow_population_by_field_name = True
# #endregion DatasetItem

# #region LinkedDashboard [C:1] [TYPE DataClass]
# @BRIEF DTO for a dashboard linked to a dataset
class LinkedDashboard(BaseModel):
    id: int
    title: str
    slug: str | None = None
# #endregion LinkedDashboard

# #region DatasetColumn [C:1] [TYPE DataClass]
# @BRIEF DTO for a single dataset column's metadata
class DatasetColumn(BaseModel):
    id: int
    name: str
    type: str | None = None
    is_dttm: bool = False
    is_active: bool = True
    description: str | None = None
# #endregion DatasetColumn

# #region DatasetDetailResponse [C:1] [TYPE DataClass]
# @BRIEF Detailed DTO for a dataset including columns and links
class DatasetDetailResponse(BaseModel):
    id: int
    table_name: str | None = None
    schema_name: str | None = Field(None, alias="schema")
    database: str
    description: str | None = None
    columns: list[DatasetColumn]
    column_count: int
    sql: str | None = None
    linked_dashboards: list[LinkedDashboard]
    linked_dashboard_count: int
    is_sqllab_view: bool = False
    created_on: str | None = None
    changed_on: str | None = None

    class Config:
        allow_population_by_field_name = True
# #endregion DatasetDetailResponse

# #region DatasetsResponse [C:1] [TYPE DataClass]
# @BRIEF Paginated response DTO for dataset listings
class DatasetsResponse(BaseModel):
    datasets: list[DatasetItem]
    total: int
    page: int
    page_size: int
    total_pages: int
# #endregion DatasetsResponse

# #region TaskResponse [C:1] [TYPE DataClass]
# @BRIEF Response DTO containing a task ID for tracking
class TaskResponse(BaseModel):
    task_id: str
# #endregion TaskResponse

# #region get_dataset_ids [C:3] [TYPE Function]
# @BRIEF Fetch list of all dataset IDs from a specific environment (without pagination)
# @PRE: env_id must be a valid environment ID
# @POST: Returns a list of all dataset IDs
# @RELATION CALLS -> [get_datasets_with_status]
@router.get("/ids")
async def get_dataset_ids(
    env_id: str,
    search: str | None = None,
    config_manager=Depends(get_config_manager),
    task_manager=Depends(get_task_manager),
    resource_service=Depends(get_resource_service),
    _ = Depends(has_permission("plugin:migration", "READ"))
):
    with belief_scope("get_dataset_ids", f"env_id={env_id}, search={search}"):
        # Validate environment exists
        environments = config_manager.get_environments()
        env = next((e for e in environments if e.id == env_id), None)
        if not env:
            logger.error(f"[get_dataset_ids][Coherence:Failed] Environment not found: {env_id}")
            raise HTTPException(status_code=404, detail="Environment not found")

        try:
            # Get all tasks for status lookup
            all_tasks = task_manager.get_all_tasks()

            # Fetch datasets with status using ResourceService
            datasets = await resource_service.get_datasets_with_status(env, all_tasks)

            # Apply search filter if provided
            if search:
                search_lower = search.lower()
                datasets = [
                    d for d in datasets
                    if search_lower in d.get('table_name', '').lower()
                ]

            # Extract and return just the IDs
            dataset_ids = [d['id'] for d in datasets]
            logger.info(f"[get_dataset_ids][Coherence:OK] Returning {len(dataset_ids)} dataset IDs")

            return {"dataset_ids": dataset_ids}

        except Exception as e:
            logger.error(f"[get_dataset_ids][Coherence:Failed] Failed to fetch dataset IDs: {e}")
            raise HTTPException(status_code=503, detail=f"Failed to fetch dataset IDs: {e!s}")
# #endregion get_dataset_ids

# #region get_datasets [C:3] [TYPE Function]
# @BRIEF Fetch list of datasets from a specific environment with mapping progress
# @PRE: env_id must be a valid environment ID
# @PRE: page must be >= 1 if provided
# @PRE: page_size must be between 1 and 100 if provided
# @POST: Returns a list of datasets with enhanced metadata and pagination info
# @POST: Response includes pagination metadata (page, page_size, total, total_pages)
# @RELATION CALLS -> [get_datasets_with_status]
@router.get("", response_model=DatasetsResponse)
async def get_datasets(
    env_id: str,
    search: str | None = None,
    page: int = 1,
    page_size: int = 10,
    config_manager=Depends(get_config_manager),
    task_manager=Depends(get_task_manager),
    resource_service=Depends(get_resource_service),
    _ = Depends(has_permission("plugin:migration", "READ"))
):
    with belief_scope("get_datasets", f"env_id={env_id}, search={search}, page={page}, page_size={page_size}"):
        # Validate pagination parameters
        if page < 1:
            logger.error(f"[get_datasets][Coherence:Failed] Invalid page: {page}")
            raise HTTPException(status_code=400, detail="Page must be >= 1")
        if page_size < 1 or page_size > 100:
            logger.error(f"[get_datasets][Coherence:Failed] Invalid page_size: {page_size}")
            raise HTTPException(status_code=400, detail="Page size must be between 1 and 100")

        # Validate environment exists
        environments = config_manager.get_environments()
        env = next((e for e in environments if e.id == env_id), None)
        if not env:
            logger.error(f"[get_datasets][Coherence:Failed] Environment not found: {env_id}")
            raise HTTPException(status_code=404, detail="Environment not found")

        try:
            # Get all tasks for status lookup
            all_tasks = task_manager.get_all_tasks()

            # Fetch datasets with status using ResourceService
            datasets = await resource_service.get_datasets_with_status(env, all_tasks)

            # Apply search filter if provided
            if search:
                search_lower = search.lower()
                datasets = [
                    d for d in datasets
                    if search_lower in d.get('table_name', '').lower()
                ]

            # Calculate pagination
            total = len(datasets)
            total_pages = (total + page_size - 1) // page_size if total > 0 else 1
            start_idx = (page - 1) * page_size
            end_idx = start_idx + page_size

            # Slice datasets for current page
            paginated_datasets = datasets[start_idx:end_idx]

            logger.info(f"[get_datasets][Coherence:OK] Returning {len(paginated_datasets)} datasets (page {page}/{total_pages}, total: {total})")

            return DatasetsResponse(
                datasets=paginated_datasets,
                total=total,
                page=page,
                page_size=page_size,
                total_pages=total_pages
            )

        except Exception as e:
            logger.error(f"[get_datasets][Coherence:Failed] Failed to fetch datasets: {e}")
            raise HTTPException(status_code=503, detail=f"Failed to fetch datasets: {e!s}")
# #endregion get_datasets

# #region MapColumnsRequest [C:1] [TYPE DataClass]
# @BRIEF Request DTO for initiating column mapping
class MapColumnsRequest(BaseModel):
    env_id: str = Field(..., description="Environment ID")
    dataset_ids: list[int] = Field(..., description="List of dataset IDs to map")
    source_type: str = Field(..., description="Source type: 'postgresql' or 'xlsx'")
    connection_id: str | None = Field(None, description="Connection ID for PostgreSQL source")
    file_data: str | None = Field(None, description="File path or data for XLSX source")
# #endregion MapColumnsRequest

# #region map_columns [C:3] [TYPE Function]
# @BRIEF Trigger bulk column mapping for datasets
# @PRE: User has permission plugin:mapper:execute
# @PRE: env_id is a valid environment ID
# @PRE: dataset_ids is a non-empty list
# @POST: Returns task_id for tracking mapping progress
# @POST: Task is created and queued for execution
# @RELATION DISPATCHES -> [MapperPlugin]
# @RELATION CALLS -> [create_task]
@router.post("/map-columns", response_model=TaskResponse)
async def map_columns(
    request: MapColumnsRequest,
    config_manager=Depends(get_config_manager),
    task_manager=Depends(get_task_manager),
    _ = Depends(has_permission("plugin:mapper", "EXECUTE"))
):
    with belief_scope("map_columns", f"env={request.env_id}, count={len(request.dataset_ids)}, source={request.source_type}"):
        # Validate request
        if not request.dataset_ids:
            logger.error("[map_columns][Coherence:Failed] No dataset IDs provided")
            raise HTTPException(status_code=400, detail="At least one dataset ID must be provided")

        # Validate source type
        if request.source_type not in ['postgresql', 'xlsx']:
            logger.error(f"[map_columns][Coherence:Failed] Invalid source type: {request.source_type}")
            raise HTTPException(status_code=400, detail="Source type must be 'postgresql' or 'xlsx'")

        # Validate environment exists
        environments = config_manager.get_environments()
        env = next((e for e in environments if e.id == request.env_id), None)

        if not env:
            logger.error(f"[map_columns][Coherence:Failed] Environment not found: {request.env_id}")
            raise HTTPException(status_code=404, detail="Environment not found")

        try:
            # Create mapping task
            task_params = {
                'env': request.env_id,
                'dataset_id': request.dataset_ids[0] if request.dataset_ids else None,
                'source': request.source_type,
                'connection_id': request.connection_id,
                'file_data': request.file_data
            }

            task_obj = await task_manager.create_task(
                plugin_id='dataset-mapper',
                params=task_params
            )

            logger.info(f"[map_columns][Coherence:OK] Mapping task created: {task_obj.id} for {len(request.dataset_ids)} datasets")

            return TaskResponse(task_id=str(task_obj.id))

        except Exception as e:
            logger.error(f"[map_columns][Coherence:Failed] Failed to create mapping task: {e}")
            raise HTTPException(status_code=503, detail=f"Failed to create mapping task: {e!s}")
# #endregion map_columns

# #region GenerateDocsRequest [C:1] [TYPE DataClass]
# @BRIEF Request DTO for initiating documentation generation
class GenerateDocsRequest(BaseModel):
    env_id: str = Field(..., description="Environment ID")
    dataset_ids: list[int] = Field(..., description="List of dataset IDs to generate docs for")
    llm_provider: str = Field(..., description="LLM provider to use")
    options: dict | None = Field(None, description="Additional options for documentation generation")
# #endregion GenerateDocsRequest

# #region generate_docs [C:3] [TYPE Function]
# @BRIEF Trigger bulk documentation generation for datasets
# @PRE: User has permission plugin:llm_analysis:execute
# @PRE: env_id is a valid environment ID
# @PRE: dataset_ids is a non-empty list
# @POST: Returns task_id for tracking documentation generation progress
# @POST: Task is created and queued for execution
# @RELATION DISPATCHES -> [DocumentationPlugin]
# @RELATION CALLS -> [create_task]
@router.post("/generate-docs", response_model=TaskResponse)
async def generate_docs(
    request: GenerateDocsRequest,
    config_manager=Depends(get_config_manager),
    task_manager=Depends(get_task_manager),
    _ = Depends(has_permission("plugin:llm_analysis", "EXECUTE"))
):
    with belief_scope("generate_docs", f"env={request.env_id}, count={len(request.dataset_ids)}, provider={request.llm_provider}"):
        # Validate request
        if not request.dataset_ids:
            logger.error("[generate_docs][Coherence:Failed] No dataset IDs provided")
            raise HTTPException(status_code=400, detail="At least one dataset ID must be provided")

        # Validate environment exists
        environments = config_manager.get_environments()
        env = next((e for e in environments if e.id == request.env_id), None)

        if not env:
            logger.error(f"[generate_docs][Coherence:Failed] Environment not found: {request.env_id}")
            raise HTTPException(status_code=404, detail="Environment not found")

        try:
            # Create documentation generation task
            task_params = {
                'environment_id': request.env_id,
                'dataset_id': str(request.dataset_ids[0]) if request.dataset_ids else None,
                'provider_id': request.llm_provider,
                'options': request.options or {}
            }

            task_obj = await task_manager.create_task(
                plugin_id='llm_documentation',
                params=task_params
            )

            logger.info(f"[generate_docs][Coherence:OK] Documentation generation task created: {task_obj.id} for {len(request.dataset_ids)} datasets")

            return TaskResponse(task_id=str(task_obj.id))

        except Exception as e:
            logger.error(f"[generate_docs][Coherence:Failed] Failed to create documentation generation task: {e}")
            raise HTTPException(status_code=503, detail=f"Failed to create documentation generation task: {e!s}")
# #endregion generate_docs

# #region get_dataset_detail [C:3] [TYPE Function]
# @BRIEF Get detailed dataset information including columns and linked dashboards
# @PRE: env_id is a valid environment ID
# @PRE: dataset_id is a valid dataset ID
# @POST: Returns detailed dataset info with columns and linked dashboards
# @RELATION CALLS -> [SupersetClientGetDatasetDetail]
@router.get("/{dataset_id}", response_model=DatasetDetailResponse)
async def get_dataset_detail(
    env_id: str,
    dataset_id: int,
    config_manager=Depends(get_config_manager),
    _ = Depends(has_permission("plugin:migration", "READ"))
):
    with belief_scope("get_dataset_detail", f"env_id={env_id}, dataset_id={dataset_id}"):
        # Validate environment exists
        environments = config_manager.get_environments()
        env = next((e for e in environments if e.id == env_id), None)
        if not env:
            logger.error(f"[get_dataset_detail][Coherence:Failed] Environment not found: {env_id}")
            raise HTTPException(status_code=404, detail="Environment not found")

        try:
            # Fetch detailed dataset info using SupersetClient
            client = SupersetClient(env)
            dataset_detail = client.get_dataset_detail(dataset_id)

            logger.info(f"[get_dataset_detail][Coherence:OK] Retrieved dataset {dataset_id} with {dataset_detail['column_count']} columns and {dataset_detail['linked_dashboard_count']} linked dashboards")

            return DatasetDetailResponse(**dataset_detail)

        except Exception as e:
            logger.error(f"[get_dataset_detail][Coherence:Failed] Failed to fetch dataset detail: {e}")
            raise HTTPException(status_code=503, detail=f"Failed to fetch dataset detail: {e!s}")
# #endregion get_dataset_detail

# #endregion DatasetsApi