htmx/backend/routes/admin.py

from fastapi import APIRouter, HTTPException
from fastapi.responses import JSONResponse
from config import EPT_DIR, UPLOADS_DIR, ENTWINE_PATH, DATA_DIR
from services.manifest import read_manifest
from services.converter import ENTWINE_AVAILABLE, ENTWINE_PATH, run_entwine
import shutil
import subprocess
import os

router = APIRouter()

@router.get("/backend-config")
def backend_config():
    """Retourne la configuration du backend"""
    import os
    try:
        stat = shutil.disk_usage(DATA_DIR)
        disk_free_gb = round(stat.free / (1024**3), 2)
    except:
        disk_free_gb = "?"
    
    return {
        "entwine_available": ENTWINE_AVAILABLE,
        "entwine_path": ENTWINE_PATH,
        "pdal_available": shutil.which("pdal") is not None,
        "disk_free_gb": disk_free_gb,
    }


@router.get("/debug/{pc_id}")
def debug(pc_id: str):
    out_dir = EPT_DIR / pc_id
    if not out_dir.exists():
        raise HTTPException(status_code=404, detail=f"ID {pc_id} non trouvé")

    manifest = read_manifest(out_dir)

    files = []
    total_size = 0
    for p in out_dir.rglob("*"):
        if p.is_file():
            size = p.stat().st_size
            total_size += size
            files.append({
                "path": str(p.relative_to(out_dir)),
                "size_mb": round(size / (1024 * 1024), 2),
            })

    entry_file = manifest.get("entry_file")
    entry_exists = False
    if entry_file:
        entry_exists = (EPT_DIR / entry_file).exists()

    return {
        "pc_id": pc_id,
        "exists": True,
        "manifest": manifest,
        "entry_exists": entry_exists,
        "stats": {
            "total_files": len(files),
            "total_size_mb": round(total_size / (1024 * 1024), 2),
        },
        "files": sorted(files, key=lambda x: x["size_mb"], reverse=True)[:20],
        "entwine_available": ENTWINE_AVAILABLE,
        "entwine_path": ENTWINE_PATH,
    }


@router.delete("/delete/{pc_id}")
def delete_pointcloud(pc_id: str):
    out_dir = EPT_DIR / pc_id
    if not out_dir.exists():
        raise HTTPException(status_code=404, detail=f"ID {pc_id} non trouvé")

    try:
        for ext in [".las", ".laz", ".ply", ".xyz", ".pts"]:
            original = UPLOADS_DIR / f"{pc_id}{ext}"
            if original.exists():
                original.unlink()

        shutil.rmtree(out_dir)
        return {"ok": True, "message": f"Nuage {pc_id} supprimé"}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Erreur suppression : {str(e)}")


@router.post("/crop/{pc_id}")
def crop_pointcloud(pc_id: str, box: dict):
    """
    Crop le nuage de points avec PDAL.
    
    Args:
        pc_id: ID du nuage de points à cropper
        box: dict avec les coordonnées de la box 3D
              {"minX", "minY", "minZ", "maxX", "maxY", "maxZ"}
    """
    out_dir = EPT_DIR / pc_id
    if not out_dir.exists():
        raise HTTPException(status_code=404, detail=f"ID {pc_id} non trouvé")

    manifest = read_manifest(out_dir)
    if not manifest or not manifest.get("ept_dir"):
        raise HTTPException(status_code=400, detail="Manifeste invalide")

    ept_dir = EPT_DIR / manifest["ept_dir"]

    # Vérifier que PDAL est disponible
    try:
        pdal_path = subprocess.run(
            ["which", "pdal"],
            capture_output=True, text=True, check=False
        ).stdout.strip()
        if not pdal_path:
            raise HTTPException(500, "PDAL non disponible")
    except Exception:
        raise HTTPException(500, "PDAL non disponible")

    # Construire le pipeline PDAL pour le crop
    pipeline = {
        "pipeline": [
            {
                "type": "readers.las",
                "filename": str(ept_dir / "ept.json"),
                "skip_z": False,
                "force_z": True
            },
            {
                "type": "filters.crop",
                "crop_box": [
                    box.get("minX", 0),
                    box.get("minY", 0),
                    box.get("minZ", 0),
                    box.get("maxX", 0),
                    box.get("maxY", 0),
                    box.get("maxZ", 0)
                ]
            },
            {
                "type": "writers.ept",
                "filename": str(out_dir / "cropped.las"),
                "force_z": True
            }
        ]
    }

    try:
        result = subprocess.run(
            [pdal_path, "--pipeline=JSON", "--stdin"],
            input=pipeline,
            capture_output=True,
            text=True,
            timeout=7200,
            env=os.environ.copy()
        )

        if result.returncode != 0:
            raise HTTPException(
                500,
                f"PDAL crop failed (code {result.returncode}):\n{result.stderr}"
            )

        # Convertir le fichier LAS croppé en EPT
        cropped_las = out_dir / "cropped.las"
        if not cropped_las.exists():
            raise HTTPException(500, "Fichier LAS croppé non généré")

        # Supprimer le fichier original
        for ext in [".las", ".laz", ".ply", ".xyz", ".pts"]:
            original = UPLOADS_DIR / f"{pc_id}{ext}"
            if original.exists():
                original.unlink()

        # Convertir en EPT
        run_entwine(cropped_las, out_dir)

        return {
            "ok": True,
            "id": pc_id,  # Même ID, le nuage a été mis à jour
            "size_mb": round(cropped_las.stat().st_size / (1024 * 1024), 2),
            "conversion_time_seconds": 0,
        }

    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Erreur crop : {str(e)}")