"""
api/routes/datasets.py — Dataset Discovery REST API (Cloud Registry Version).
"""
from __future__ import annotations

from typing import Optional
from datetime import datetime

from fastapi import APIRouter, HTTPException, Query

from adapters.roboflow_adapter import RoboflowAdapter
from datasets import registry as ds_reg
from models.dataset import (
    Dataset, DatasetSummary, RoboflowSearchRequest,
)
from models.analytics import DatasetAnalytics, SplitAnalytics, QualityIssues, ClassDistributionItem
from observability.logger import audit, get_logger

log = get_logger("datasets_route")

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


# ── Analytics ─────────────────────────────────────────────────────────────────

@router.get("/{dataset_id}/analytics", response_model=DatasetAnalytics)
async def get_dataset_analytics(dataset_id: str):
    """
    Fetch comprehensive analytics for a dataset.
    """
    ds = await ds_reg.get_dataset(dataset_id)
    if not ds:
        raise HTTPException(404, f"Dataset {dataset_id!r} not found")
    
    stats = ds.stats
    
    analytics = DatasetAnalytics(
        dataset_id=dataset_id,
        healthScore=stats.health_score,
        split=SplitAnalytics(
            train=stats.split.train if stats.split.total > 0 else 70,
            val=stats.split.val if stats.split.total > 0 else 20,
            test=stats.split.test if stats.split.total > 0 else 10
        ),
        qualityIssues=QualityIssues(
            missingLabels=stats.missing_labels,
            emptyImages=stats.empty_images,
            duplicates=stats.duplicate_count,
            outliers=int(ds.images * 0.005) # placeholder
        ),
        classDistribution=[
            ClassDistributionItem(name=name, count=int(ds.images / ds.classes) if ds.classes > 0 else 0)
            for name in ds.class_names[:20]
        ]
    )
    
    return analytics


# ── List / Search datasets ────────────────────────────────────────────────────

@router.get("", response_model=list[DatasetSummary])
async def list_datasets(
    task:    Optional[str]  = Query(None),
    format:  Optional[str]  = Query(None),
    source:  Optional[str]  = Query(None),
    status:  Optional[str]  = Query(None),
    search:  Optional[str]  = Query(None),
    starred: Optional[bool] = Query(None),
    limit:   int            = Query(100, ge=1, le=1000),
    offset:  int            = Query(0,   ge=0),
):
    try:
        datasets = await ds_reg.get_all_datasets(
            task=task, format=format, source=source,
            status=status, search=search, starred=starred,
            limit=limit, offset=offset,
        )
        return [_to_summary(d) for d in datasets]
    except Exception as exc:
        log.exception("list_datasets_error")
        raise HTTPException(status_code=500, detail=str(exc))


# ── Roboflow Search & Sync ────────────────────────────────────────────────────

@router.post("/search/roboflow", response_model=list[DatasetSummary])
async def search_roboflow(req: RoboflowSearchRequest):
    """
    Live search Roboflow Universe. Results are cached for 1 hour.
    """
    try:
        datasets = await RoboflowAdapter.search_datasets(
            api_key   = req.api_key,
            query     = req.query,
            workspace = req.workspace,
            page      = req.page,
            page_size = req.page_size,
        )
    except Exception as exc:
        log.error("roboflow_search_error", error=str(exc))
        raise HTTPException(502, f"Roboflow API error: {exc}")

    # Upsert to registry DB
    await ds_reg.bulk_upsert_datasets(datasets)
    await audit("roboflow_search", {"query": req.query, "count": len(datasets)})
    return [_to_summary(d) for d in datasets]


@router.post("/sync/roboflow", response_model=dict)
async def sync_roboflow_workspace(
    api_key: str = Query(..., description="Roboflow API key"),
    workspace: str = Query(..., description="Workspace slug"),
):
    """Sync all datasets from a Roboflow workspace into the global registry."""
    try:
        datasets = await RoboflowAdapter.list_workspace_datasets(api_key, workspace)
    except Exception as exc:
        raise HTTPException(502, f"Roboflow API error: {exc}")
    count = await ds_reg.bulk_upsert_datasets(datasets)
    return {"synced": count, "workspace": workspace}


# ── Dataset detail ────────────────────────────────────────────────────────────

@router.get("/{dataset_id}", response_model=Dataset)
async def get_dataset(dataset_id: str):
    ds = await ds_reg.get_dataset(dataset_id)
    if not ds:
        raise HTTPException(404, f"Dataset {dataset_id!r} not found")
    return ds


# ── Star ─────────────────────────────────────────────────────────────

@router.post("/{dataset_id}/star", response_model=dict)
async def toggle_star(dataset_id: str):
    new_val = await ds_reg.toggle_starred(dataset_id)
    return {"dataset_id": dataset_id, "starred": new_val}


# ── Helper ────────────────────────────────────────────────────────────────────

def _to_summary(d: Dataset) -> DatasetSummary:
    health_score = 0.0
    try:
        if hasattr(d, 'stats') and d.stats:
            health_score = getattr(d.stats, 'health_score', 0.0)
    except Exception:
        pass

    return DatasetSummary(
        id              = d.id,
        name            = d.name,
        task            = str(d.task),
        format          = str(d.format),
        source          = str(d.source),
        status          = str(d.status),
        images          = d.images,
        classes         = d.classes,
        size_label      = d.size_label,
        tags            = d.tags,
        starred         = d.starred,
        import_progress = d.import_progress,
        health_score    = health_score,
        created_at      = d.created_at,
        updated_at      = d.updated_at,
    )