998 lines
36 KiB
Python
Executable File
998 lines
36 KiB
Python
Executable File
import json
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import os
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import pandas as pd
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import geopandas as gpd
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import numpy as np
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import re
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import zipfile
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import tempfile
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import asyncio
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from pyproj import CRS
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from shapely.geometry.base import BaseGeometry
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from shapely.geometry import base as shapely_base
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from fastapi import Depends, File, Form, UploadFile, HTTPException
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from api.routers.datasets_router import cleansing_data, publish_layer, query_cleansing_data, upload_to_main
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from core.config import UPLOAD_FOLDER, MAX_FILE_MB, VALID_WKT_PREFIXES, GEONETWORK_URL
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from services.upload_file.ai_generate import send_metadata
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from services.upload_file.readers.reader_csv import read_csv
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from services.upload_file.readers.reader_shp import read_shp
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from services.upload_file.readers.reader_gdb import read_gdb
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from services.upload_file.readers.reader_mpk import read_mpk
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from services.upload_file.readers.reader_pdf import convert_df, read_pdf
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from services.upload_file.utils.geometry_detector import detect_and_build_geometry, attach_polygon_geometry_auto
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from services.upload_file.upload_ws import report_progress
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from database.connection import engine, sync_engine
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from database.models import Base
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from pydantic import BaseModel
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from typing import Any, Dict, List, Optional
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from shapely import MultiLineString, MultiPolygon, wkt
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from sqlalchemy import text
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from datetime import datetime
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from response import successRes, errorRes
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from utils.logger_config import log_activity
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# Base.metadata.create_all(bind=engine)
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def is_geom_empty(g):
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if g is None:
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return True
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if isinstance(g, float) and pd.isna(g):
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return True
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if isinstance(g, BaseGeometry):
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return g.is_empty
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return False
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def safe_json(value):
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"""Konversi aman untuk semua tipe numpy/pandas/shapely ke tipe JSON-serializable"""
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if isinstance(value, (np.int64, np.int32)):
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return int(value)
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if isinstance(value, (np.float64, np.float32)):
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return float(value)
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if isinstance(value, pd.Timestamp):
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return value.isoformat()
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if isinstance(value, shapely_base.BaseGeometry):
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return str(value) # convert to WKT string
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if pd.isna(value):
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return None
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return value
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def detect_zip_type(zip_path: str) -> str:
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with zipfile.ZipFile(zip_path, "r") as zip_ref:
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files = zip_ref.namelist()
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if any(f.lower().endswith(".gdb/") or ".gdb/" in f.lower() for f in files):
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return "gdb"
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if any(f.lower().endswith(ext) for ext in [".gdbtable", ".gdbtablx", ".gdbindexes", ".spx"] for f in files):
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return "gdb"
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if any(f.lower().endswith(".shp") for f in files):
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return "shp"
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return "unknown"
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# def detect_zip_type(zip_path: str) -> str:
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# files = zip_ref.namelist()
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# # -------------------------------------------------------------
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# # 1) DETECT FileGDB
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# # -------------------------------------------------------------
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# is_gdb = (
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# any(".gdb/" in f.lower() for f in files)
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# or any(f.lower().endswith(ext) for ext in
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# [".gdbtable", ".gdbtablx", ".gdbindexes", ".spx"] for f in files)
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# )
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# if is_gdb:
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# print("\n[INFO] ZIP terdeteksi berisi FileGDB.")
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# with tempfile.TemporaryDirectory() as temp_dir:
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# # extract ZIP
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# zip_ref.extractall(temp_dir)
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# # find folder *.gdb
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# gdb_path = None
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# for root, dirs, _ in os.walk(temp_dir):
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# for d in dirs:
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# if d.lower().endswith(".gdb"):
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# gdb_path = os.path.join(root, d)
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# break
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# if not gdb_path:
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# print("[ERROR] Folder .gdb tidak ditemukan.")
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# return "gdb"
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# print(f"[INFO] GDB Path: {gdb_path}")
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# # Cari seluruh file .gdbtable
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# table_files = [
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# os.path.join(gdb_path, f)
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# for f in os.listdir(gdb_path)
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# if f.lower().endswith(".gdbtable")
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# ]
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# if not table_files:
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# print("[ERROR] Tidak ada file .gdbtable ditemukan.")
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# return "gdb"
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# # Scan semua table file untuk mencari SpatialReference
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# found_crs = False
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# for table_file in table_files:
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# try:
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# with open(table_file, "rb") as f:
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# raw = f.read(15000) # baca awal file, cukup untuk header JSON
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# text = raw.decode("utf-8", errors="ignore")
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# start = text.find("{")
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# end = text.rfind("}") + 1
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# if start == -1 or end == -1:
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# continue
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# json_str = text[start:end]
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# meta = json.loads(json_str)
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# spatial_ref = meta.get("SpatialReference")
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# if not spatial_ref:
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# continue
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# wkt = spatial_ref.get("WKT")
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# if not wkt:
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# continue
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# print(f"[FOUND] CRS metadata pada: {os.path.basename(table_file)}")
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# print(f"[CRS WKT] {wkt[:200]}...")
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# # Convert to EPSG
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# try:
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# epsg = CRS.from_wkt(wkt).to_epsg()
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# print(f"[EPSG] {epsg}")
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# except:
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# print("[EPSG] Tidak ditemukan EPSG.")
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# found_crs = True
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# break
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# except Exception:
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# continue
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# if not found_crs:
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# print("[WARNING] Tidak ditemukan CRS di file .gdbtable manapun.")
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# return "gdb"
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# # -----------------------------------------------------
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# # 2. DETEKSI SHP
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# # -----------------------------------------------------
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# if any(f.lower().endswith(".shp") for f in files):
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# print("\n[INFO] ZIP terdeteksi berisi SHP.")
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# # cari file .prj
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# prj_files = [f for f in files if f.lower().endswith(".prj")]
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# if not prj_files:
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# print("[WARNING] Tidak ada file .prj → CRS tidak diketahui.")
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# return "shp"
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# with zipfile.ZipFile(zip_path, "r") as zip_ref:
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# with tempfile.TemporaryDirectory() as temp_dir:
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# prj_path = os.path.join(temp_dir, os.path.basename(prj_files[0]))
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# zip_ref.extract(prj_files[0], temp_dir)
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# # baca isi prj
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# with open(prj_path, "r") as f:
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# prj_text = f.read()
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# try:
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# crs = CRS.from_wkt(prj_text)
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# print(f"[CRS WKT] {crs.to_wkt()[:200]}...")
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# epsg = crs.to_epsg()
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# if epsg:
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# print(f"[EPSG] {epsg}")
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# else:
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# print("[EPSG] Tidak ditemukan dalam database EPSG.")
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# except Exception as e:
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# print("[ERROR] Gagal membaca CRS dari file PRJ:", e)
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# return "shp"
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# # -----------------------------------------------------
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# # 3. UNKNOWN
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# # -----------------------------------------------------
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# return "unknown"
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def process_data(df: pd.DataFrame, ext: str, filename: str, fileDesc: str):
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result = detect_and_build_geometry(df, master_polygons=None)
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if not hasattr(result, "geometry") or result.geometry.isna().all():
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result = attach_polygon_geometry_auto(result)
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# if isinstance(result, gpd.GeoDataFrame) and "geometry" in result.columns:
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# geom_type = ", ".join([g for g in result.geometry.geom_type.unique() if g]) \
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# if not result.empty else "None"
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# null_geom = result.geometry.isna().sum()
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def normalize_geom_type(geom_type):
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if geom_type.startswith("Multi"):
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return geom_type.replace("Multi", "")
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return geom_type
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if isinstance(result, gpd.GeoDataFrame) and "geometry" in result.columns:
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geom_types = (
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result.geometry
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.dropna()
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.geom_type
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.apply(normalize_geom_type)
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.unique()
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)
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geom_type = geom_types[0] if len(geom_types) > 0 else "None"
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null_geom = result.geometry.isna().sum()
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print(f"[INFO] Tipe Geometry: {geom_type}")
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print(f"[INFO] Jumlah geometry kosong: {null_geom}")
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else:
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res = {
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"message": "Tidak menemukan tabel yang relevan.",
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"file_type": ext,
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"rows": 0,
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"columns": 0,
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"geometry_valid": 0,
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"geometry_empty": 0,
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"geometry_valid_percent": 0,
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"warnings": [],
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"warning_examples": [],
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"preview": []
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}
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return errorRes(message="Tidak berhasil mencocokan geometry pada tabel." ,details=res, status_code=422)
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result = result.replace([pd.NA, float('inf'), float('-inf')], None)
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if isinstance(result, gpd.GeoDataFrame) and 'geometry' in result.columns:
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result['geometry'] = result['geometry'].apply(
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lambda g: g.wkt if g is not None else None
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)
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empty_count = result['geometry'].apply(is_geom_empty).sum()
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valid_count = len(result) - empty_count
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match_percentage = (valid_count / len(result)) * 100
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warnings = []
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if empty_count > 0:
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warnings.append(
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f"{empty_count} dari {len(result)} baris tidak memiliki geometry yang valid "
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f"({100 - match_percentage:.2f}% data gagal cocok)."
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)
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if empty_count > 0:
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examples = result[result['geometry'].apply(is_geom_empty)].head(500)
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warning_examples = examples.to_dict(orient="records")
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else:
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warning_examples = []
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# preview_data = result.head(15).to_dict(orient="records")
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preview_data = result.to_dict(orient="records")
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preview_safe = [
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{k: safe_json(v) for k, v in row.items()} for row in preview_data
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]
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warning_safe = [
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{k: safe_json(v) for k, v in row.items()} for row in warning_examples
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]
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ai_context = {
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"nama_file_peta": filename,
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"nama_opd": "Badan Penanggulangan Bencana Daerah (BPBD) Provinsi Jatim",
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"tipe_data_spasial": geom_type,
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"deskripsi_singkat": fileDesc,
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"struktur_atribut_data": {},
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# "metadata": {
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# "judul": "",
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# "abstrak": "",
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# "tujuan": "",
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# "keyword": [],
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# "kategori": [],
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# "kategori_mapset": ""
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# }
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}
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ai_suggest = send_metadata(ai_context)
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# ai_suggest = {'judul': 'Peta Risiko Letusan Gunung Arjuna di Provinsi Jawa Timur', 'abstrak': 'Peta ini menggambarkan wilayah berisiko letusan Gunung Arjuna yang berada di Provinsi Jawa Timur. Data disajikan dalam bentuk poligon yang menunjukkan zona risiko berdasarkan analisis potensi aktivitas vulkanik.', 'tujuan': 'Data dapat digunakan untuk perencanaan mitigasi bencana dan pengambilan keputusan di wilayah Jawa Timur.', 'keyword': ['Risiko letusan', 'Gunung Arjuna', 'Bencana alam', 'Provinsi Jawa Timur', 'Geologi'], 'kategori': ['Geoscientific information', 'Environment'], 'kategori_mapset': 'Lingkungan Hidup'}
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# print(ai_suggest)
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response = {
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"message": "File berhasil dibaca dan dianalisis.",
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"file_name": filename,
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"file_type": ext,
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"rows": int(len(result)),
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"columns": list(map(str, result.columns)),
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"geometry_valid": int(valid_count),
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"geometry_empty": int(empty_count),
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"geometry_valid_percent": float(round(match_percentage, 2)),
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"geometry_type": geom_type,
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"warnings": warnings,
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"warning_rows": warning_safe,
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"preview": preview_safe,
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"metadata_suggest": ai_suggest
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}
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# return successRes(content=response)
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return response
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async def handle_upload_file(file: UploadFile = File(...), page: Optional[str] = Form(""), sheet: Optional[str] = Form(""), fileDesc: Optional[str] = Form("")):
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fname = file.filename
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ext = os.path.splitext(fname)[1].lower()
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contents = await file.read()
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size_mb = len(contents) / (1024*1024)
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if size_mb > MAX_FILE_MB:
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raise errorRes(status_code=413, message="Ukuran File Terlalu Besar")
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tmp_path = UPLOAD_FOLDER / fname
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with open(tmp_path, "wb") as f:
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f.write(contents)
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try:
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df = None
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print('ext', ext)
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if ext == ".csv":
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df = read_csv(str(tmp_path))
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elif ext == ".xlsx":
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df = read_csv(str(tmp_path), sheet)
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elif ext == ".mpk":
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df = read_mpk(str(tmp_path))
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elif ext == ".pdf":
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tbl = read_pdf(tmp_path, page)
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if len(tbl) == 0:
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res = {
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"message": "Tidak ditemukan tabel valid pada halaman yang dipilih",
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"tables": {},
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"file_type": ext
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}
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return successRes(message="Tidak ditemukan tabel valid pada halaman yang dipilih", data=res)
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elif len(tbl) > 1:
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res = {
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"message": "File berhasil dibaca dan dianalisis.",
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"tables": tbl,
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"file_type": ext
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}
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return successRes(data=res, message="File berhasil dibaca dan dianalisis.")
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else:
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df = convert_df(tbl[0])
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elif ext == ".zip":
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zip_type = detect_zip_type(str(tmp_path))
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if zip_type == "shp":
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print("[INFO] ZIP terdeteksi sebagai Shapefile.")
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df = read_shp(str(tmp_path))
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elif zip_type == "gdb":
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print("[INFO] ZIP terdeteksi sebagai Geodatabase (GDB).")
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df = read_gdb(str(tmp_path))
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else:
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return successRes(message="ZIP file tidak mengandung SHP / GDB valid.")
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else:
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raise errorRes(status_code=400, message="Unsupported file type")
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if df is None or (hasattr(df, "empty") and df.empty):
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return successRes(message="File berhasil dibaca, Tetapi tidak ditemukan tabel valid")
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res = process_data(df, ext, fname, fileDesc)
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tmp_path.unlink(missing_ok=True)
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return successRes(data=res)
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except Exception as e:
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print(f"[ERROR] {e}")
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return errorRes(
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message="Internal Server Error",
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details=str(e),
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status_code=500
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)
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# finally:
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# db_session.close()
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class PdfRequest(BaseModel):
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title: str
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columns: List[str]
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rows: List[List]
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fileName: str
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fileDesc: str
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async def handle_process_pdf(payload: PdfRequest):
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try:
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df = convert_df(payload.model_dump())
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if df is None or (hasattr(df, "empty") and df.empty):
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return errorRes(message="Tidak ada tabel")
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res = process_data(df, '.pdf', payload.fileName, payload.fileDesc)
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return successRes(data=res)
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except Exception as e:
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print(f"[ERROR] {e}")
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return errorRes(message="Internal Server Error", details= str(e), status_code=500)
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# finally:
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# db_session.close()
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class UploadRequest(BaseModel):
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title: str
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rows: List[dict]
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columns: List[str]
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author: Dict[str, Any]
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style: str
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# generate _2 if exist
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async def generate_unique_table_name(base_name: str):
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base_name = base_name.lower().replace(" ", "_").replace("-", "_")
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table_name = base_name
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counter = 2
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async with engine.connect() as conn:
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while True:
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result = await conn.execute(
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text("SELECT to_regclass(:tname)"),
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{"tname": table_name}
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)
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exists = result.scalar()
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if not exists:
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return table_name
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table_name = f"{base_name}_{counter}"
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counter += 1
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def str_to_date(raw_date: str):
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if raw_date:
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try:
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return datetime.strptime(raw_date, "%Y-%m-%d").date()
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except Exception as e:
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print("[WARNING] Tidak bisa parse dateCreated:", e)
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return None
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def generate_job_id(user_id: str) -> str:
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timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
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return f"{user_id}_{timestamp}"
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def save_xml_to_sld(xml_string, filename):
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folder_path = 'style_temp'
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os.makedirs(folder_path, exist_ok=True)
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file_path = os.path.join(folder_path, f"{filename}.sld")
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with open(file_path, "w", encoding="utf-8") as f:
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||
f.write(xml_string)
|
||
|
||
return file_path
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
||
try:
|
||
table_name = await generate_unique_table_name(payload.title)
|
||
# DataFrame
|
||
df = pd.DataFrame(payload.rows)
|
||
df.columns = [col.upper() for col in df.columns]
|
||
if "GEOMETRY" not in df.columns:
|
||
raise HTTPException(400, "Kolom GEOMETRY tidak ditemukan")
|
||
|
||
# =====================================================================
|
||
# 1. LOAD WKT → SHAPELY
|
||
# =====================================================================
|
||
def safe_load_wkt(g):
|
||
if not isinstance(g, str):
|
||
return None
|
||
try:
|
||
geom = wkt.loads(g)
|
||
return geom
|
||
except:
|
||
return None
|
||
|
||
df["GEOMETRY"] = df["GEOMETRY"].apply(safe_load_wkt)
|
||
df = df.rename(columns={"GEOMETRY": "geom"})
|
||
|
||
# =====================================================================
|
||
# 2. DROP ROW geometry NULL
|
||
# =====================================================================
|
||
df = df[df["geom"].notnull()]
|
||
if df.empty:
|
||
raise HTTPException(400, "Semua geometry invalid atau NULL")
|
||
|
||
# =====================================================================
|
||
# 3. VALIDATE geometry (very important)
|
||
# =====================================================================
|
||
df["geom"] = df["geom"].apply(lambda g: g if g.is_valid else g.buffer(0))
|
||
|
||
# =====================================================================
|
||
# 4. SERAGAMKAN TIPE GEOMETRY (Polygon→MultiPolygon, Line→MultiLine)
|
||
# =====================================================================
|
||
def unify_geometry_type(g):
|
||
gtype = g.geom_type.upper()
|
||
if gtype == "POLYGON":
|
||
return MultiPolygon([g])
|
||
if gtype == "LINESTRING":
|
||
return MultiLineString([g])
|
||
return g # sudah MULTI atau POINT
|
||
df["geom"] = df["geom"].apply(unify_geometry_type)
|
||
|
||
# =====================================================================
|
||
# 5. DETEKSI CRS DARI METADATA / INPUT / DEFAULT
|
||
# =====================================================================
|
||
detected_crs = payload.author.get("crs")
|
||
|
||
detected = payload.author.get("crs")
|
||
print('crs', detected)
|
||
|
||
if not detected_crs:
|
||
detected_crs = "EPSG:4326"
|
||
|
||
detected_crs = 'EPSG:4326'
|
||
# Buat GeoDataFrame
|
||
gdf = gpd.GeoDataFrame(df, geometry="geom", crs=detected_crs)
|
||
row_count = len(gdf)
|
||
|
||
# =====================================================================
|
||
# 6. VERIFY CRS (SRID) VALID di PROJ / PostGIS
|
||
# =====================================================================
|
||
try:
|
||
_ = gdf.to_crs(gdf.crs) # test CRS valid
|
||
except:
|
||
raise HTTPException(400, f"CRS {detected_crs} tidak valid")
|
||
|
||
# =====================================================================
|
||
# 7. SIMPAN KE POSTGIS (synchronous)
|
||
# =====================================================================
|
||
loop = asyncio.get_running_loop()
|
||
await loop.run_in_executor(
|
||
None,
|
||
lambda: gdf.to_postgis(
|
||
table_name,
|
||
sync_engine,
|
||
if_exists="replace",
|
||
index=False
|
||
)
|
||
)
|
||
|
||
# =====================================================================
|
||
# 8. ADD PRIMARY KEY (wajib untuk QGIS API)
|
||
# =====================================================================
|
||
async with engine.begin() as conn:
|
||
await conn.execute(text(
|
||
f'ALTER TABLE "{table_name}" ADD COLUMN _ID SERIAL PRIMARY KEY;'
|
||
))
|
||
|
||
# =====================================================================
|
||
# 9. SIMPAN METADATA (geom_type, author metadata)
|
||
# =====================================================================
|
||
unified_geom_type = list(gdf.geom_type.unique())
|
||
author = payload.author
|
||
async with engine.begin() as conn:
|
||
await conn.execute(text("""
|
||
INSERT INTO backend.author_metadata (
|
||
table_title,
|
||
dataset_title,
|
||
dataset_abstract,
|
||
keywords,
|
||
topic_category,
|
||
date_created,
|
||
dataset_status,
|
||
organization_name,
|
||
contact_person_name,
|
||
contact_email,
|
||
contact_phone,
|
||
geom_type,
|
||
user_id,
|
||
process,
|
||
geometry_count
|
||
) VALUES (
|
||
:table_title,
|
||
:dataset_title,
|
||
:dataset_abstract,
|
||
:keywords,
|
||
:topic_category,
|
||
:date_created,
|
||
:dataset_status,
|
||
:organization_name,
|
||
:contact_person_name,
|
||
:contact_email,
|
||
:contact_phone,
|
||
:geom_type,
|
||
:user_id,
|
||
:process,
|
||
:geometry_count
|
||
)
|
||
"""), {
|
||
"table_title": table_name,
|
||
"dataset_title": payload.title,
|
||
"dataset_abstract": author.get("abstract"),
|
||
"keywords": author.get("keywords"),
|
||
# "topic_category": author.get("topicCategory"),
|
||
"topic_category": ", ".join(author.get("topicCategory")),
|
||
"date_created": str_to_date(author.get("dateCreated")),
|
||
"dataset_status": author.get("status"),
|
||
"organization_name": author.get("organization"),
|
||
"contact_person_name": author.get("contactName"),
|
||
"contact_email": author.get("contactEmail"),
|
||
"contact_phone": author.get("contactPhone"),
|
||
"geom_type": json.dumps(unified_geom_type),
|
||
"user_id": user_id,
|
||
"process": 'CLEANSING',
|
||
"geometry_count": row_count
|
||
})
|
||
|
||
|
||
# =====================================================================
|
||
# 10. LOGGING
|
||
# =====================================================================
|
||
await log_activity(
|
||
user_id=user_id,
|
||
action_type="UPLOAD",
|
||
action_title=f"Upload dataset {table_name}",
|
||
details={"table_name": table_name, "rows": len(gdf)}
|
||
)
|
||
|
||
job_id = generate_job_id(str(user_id))
|
||
result = {
|
||
"job_id": job_id,
|
||
"job_status": "wait",
|
||
"table_name": table_name,
|
||
"status": "success",
|
||
"message": f"Tabel '{table_name}' berhasil dibuat.",
|
||
"total_rows": len(gdf),
|
||
"geometry_type": unified_geom_type,
|
||
"crs": detected_crs,
|
||
"metadata_uuid": ""
|
||
}
|
||
save_xml_to_sld(payload.style, job_id)
|
||
|
||
await report_progress(job_id, "upload", 20, "Upload selesai")
|
||
# cleansing_data(table_name, job_id)
|
||
|
||
cleansing = await query_cleansing_data(table_name)
|
||
result['job_status'] = cleansing
|
||
|
||
publish = await publish_layer(table_name, job_id)
|
||
result['metadata_uuid'] = publish['uuid']
|
||
|
||
mapset = {
|
||
"name": payload.title,
|
||
"description": author.get("abstract"),
|
||
"scale": "1:25000",
|
||
"projection_system_id": "0196c746-d1ba-7f1c-9706-5df738679cc7",
|
||
"category_id": author.get("mapsetCategory"),
|
||
"data_status": "sementara",
|
||
"classification_id": "01968b4b-d3f9-76c9-888c-ee887ac31ce4",
|
||
"producer_id": "019bd4ea-eb33-704e-83c3-8253d457b187",
|
||
"layer_type": unified_geom_type[0],
|
||
"source_id": ["019bd4e7-3df8-75c8-9b89-3f310967649c"],
|
||
"layer_url": publish['geos_link'],
|
||
"metadata_url": f"{GEONETWORK_URL}/srv/eng/catalog.search#/metadata/{publish['uuid']}",
|
||
"coverage_level": "provinsi",
|
||
"coverage_area": "kabupaten",
|
||
"data_update_period": "Tahunan",
|
||
"data_version": "2026",
|
||
"is_popular": False,
|
||
"is_active": True,
|
||
"regional_id": "01968b53-a910-7a67-bd10-975b8923b92e",
|
||
"notes": "Mapset baru dibuat",
|
||
"status_validation": "on_verification",
|
||
}
|
||
|
||
print("mapset data",mapset)
|
||
await upload_to_main(mapset)
|
||
|
||
return successRes(data=result)
|
||
|
||
except Exception as e:
|
||
await log_activity(
|
||
user_id=user_id,
|
||
action_type="ERROR",
|
||
action_title="Upload gagal",
|
||
details={"error": str(e)}
|
||
)
|
||
raise HTTPException(status_code=500, detail=str(e))
|
||
|
||
|
||
|
||
|
||
# async def handle_to_postgis(payload: UploadRequest, user_id: int = 2):
|
||
# try:
|
||
# job_id = generate_job_id(str(user_id))
|
||
# result = {
|
||
# "job_id": job_id,
|
||
# "job_status": "done",
|
||
# "table_name": "just for test",
|
||
# "status": "success",
|
||
# "message": f"Tabel test berhasil dibuat.",
|
||
# "total_rows": 10,
|
||
# "geometry_type": "Polygon",
|
||
# "crs": "EPSG 4326",
|
||
# "metadata_uuid": "-"
|
||
# }
|
||
|
||
# mapset = {
|
||
# "name": "Resiko Letusan Gunung Arjuno",
|
||
# "description": "Testing Automation Upload",
|
||
# "scale": "1:25000",
|
||
# "projection_system_id": "0196c746-d1ba-7f1c-9706-5df738679cc7",
|
||
# "category_id": "0196c80c-855f-77f9-abd0-0c8a30b8c2f5",
|
||
# "data_status": "sementara",
|
||
# "classification_id": "01968b4b-d3f9-76c9-888c-ee887ac31ce4",
|
||
# "producer_id": "019bd4ea-eb33-704e-83c3-8253d457b187",
|
||
# "layer_type": "polygon",
|
||
# "source_id": ["019bd4e7-3df8-75c8-9b89-3f310967649c"],
|
||
# "layer_url": "http://192.168.60.24:8888/geoserver/wms?service=WMS&version=1.1.0&request=GetMap&layers=labai:risiko_letusan_gunung_arjuno_bromo&bbox=110.89528623700005,-8.780412043999945,116.26994997700001,-5.042971664999925&width=768&height=534&srs=EPSG:4326&styles=&format=application/openlayers",
|
||
# "metadata_url": "http://192.168.60.24:7777/geonetwork/srv/eng/catalog.search#/metadata/9e5e2f09-13ef-49b5-bb49-1cb12136f63b",
|
||
# "coverage_level": "provinsi",
|
||
# "coverage_area": "kabupaten",
|
||
# "data_update_period": "Tahunan",
|
||
# "data_version": "2026",
|
||
# "is_popular": False,
|
||
# "is_active": True,
|
||
# "regional_id": "01968b53-a910-7a67-bd10-975b8923b92e",
|
||
# "notes": "Mapset baru dibuat",
|
||
# "status_validation": "on_verification",
|
||
# }
|
||
|
||
# await upload_to_main(mapset)
|
||
|
||
# return successRes(data=result)
|
||
|
||
# except Exception as e:
|
||
# print("errot", e)
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
# ===================================
|
||
# partition +VIEW
|
||
# ===================================
|
||
|
||
|
||
# Daftar prefix WKT yang valid
|
||
# VALID_WKT_PREFIXES = ("POINT", "LINESTRING", "POLYGON", "MULTIPOLYGON", "MULTILINESTRING")
|
||
|
||
|
||
def slugify(value: str) -> str:
|
||
"""Mengubah judul dataset jadi nama aman untuk VIEW"""
|
||
return re.sub(r'[^a-zA-Z0-9]+', '_', value.lower()).strip('_')
|
||
|
||
|
||
|
||
# Partition + VIEW
|
||
# async def create_dataset_view_from_metadata(conn, metadata_id: int, user_id: int, title: str):
|
||
# norm_title = slugify(title)
|
||
# view_name = f"v_user_{user_id}_{norm_title}"
|
||
# base_table = f"test_partition_user_{user_id}"
|
||
|
||
# # Ambil daftar field
|
||
# result = await conn.execute(text("SELECT fields FROM dataset_metadata WHERE id=:mid"), {"mid": metadata_id})
|
||
# fields_json = result.scalar_one_or_none()
|
||
|
||
# base_columns = {"id", "user_id", "metadata_id", "geom"}
|
||
# columns_sql = ""
|
||
# field_list = []
|
||
|
||
# if fields_json:
|
||
# fields = json.loads(fields_json) if isinstance(fields_json, str) else fields_json
|
||
# field_list = fields
|
||
|
||
# for f in field_list:
|
||
# safe_col = slugify(f)
|
||
# alias_name = safe_col if safe_col not in base_columns else f"attr_{safe_col}"
|
||
|
||
# # CAST otomatis
|
||
# if safe_col in ["longitude", "latitude", "lon", "lat"]:
|
||
# columns_sql += f", (p.attributes->>'{f}')::float AS {alias_name}"
|
||
# else:
|
||
# columns_sql += f", p.attributes->>'{f}' AS {alias_name}"
|
||
|
||
# # Drop view lama
|
||
# await conn.execute(text(f"DROP VIEW IF EXISTS {view_name} CASCADE;"))
|
||
|
||
# # 🔥 Buat VIEW baru yang punya FID unik
|
||
# create_view_query = f"""
|
||
# CREATE OR REPLACE VIEW {view_name} AS
|
||
# SELECT
|
||
# row_number() OVER() AS fid, -- FID unik untuk QGIS
|
||
# p.id,
|
||
# p.user_id,
|
||
# p.metadata_id,
|
||
# p.geom
|
||
# {columns_sql},
|
||
# m.title,
|
||
# m.year,
|
||
# m.description
|
||
# FROM {base_table} p
|
||
# JOIN dataset_metadata m ON m.id = p.metadata_id
|
||
# WHERE p.metadata_id = {metadata_id};
|
||
# """
|
||
# await conn.execute(text(create_view_query))
|
||
|
||
# # Register geometry untuk QGIS
|
||
# await conn.execute(text(f"DELETE FROM geometry_columns WHERE f_table_name = '{view_name}';"))
|
||
# await conn.execute(text(f"""
|
||
# INSERT INTO geometry_columns
|
||
# (f_table_schema, f_table_name, f_geometry_column, coord_dimension, srid, type)
|
||
# VALUES ('public', '{view_name}', 'geom', 2, 4326, 'GEOMETRY');
|
||
# """))
|
||
|
||
# print(f"[INFO] VIEW {view_name} dibuat dengan FID unik dan kompatibel dengan QGIS.")
|
||
|
||
|
||
# async def handle_to_postgis(payload, engine, user_id: int = 3):
|
||
# """
|
||
# Menangani upload data spasial ke PostGIS (dengan partition per user).
|
||
# - Jika partisi belum ada, akan dibuat otomatis
|
||
# - Metadata dataset disimpan di tabel dataset_metadata
|
||
# - Data spasial dimasukkan ke tabel partisi (test_partition_user_{id})
|
||
# - VIEW otomatis dibuat untuk QGIS
|
||
# """
|
||
|
||
# try:
|
||
# df = pd.DataFrame(payload.rows)
|
||
# print(f"[INFO] Diterima {len(df)} baris data dari frontend.")
|
||
|
||
# # --- Validasi kolom geometry ---
|
||
# if "geometry" not in df.columns:
|
||
# raise errorRes(status_code=400, message="Kolom 'geometry' tidak ditemukan dalam data.")
|
||
|
||
# # --- Parsing geometry ke objek shapely ---
|
||
# df["geometry"] = df["geometry"].apply(
|
||
# lambda g: wkt.loads(g)
|
||
# if isinstance(g, str) and g.strip().upper().startswith(VALID_WKT_PREFIXES)
|
||
# else None
|
||
# )
|
||
|
||
# # --- Buat GeoDataFrame ---
|
||
# gdf = gpd.GeoDataFrame(df, geometry="geometry", crs="EPSG:4326")
|
||
|
||
# # --- Metadata info dari payload ---
|
||
# # dataset_title = getattr(payload, "dataset_title", None)
|
||
# # dataset_year = getattr(payload, "dataset_year", None)
|
||
# # dataset_desc = getattr(payload, "dataset_description", None)
|
||
# dataset_title = "hujan 2045"
|
||
# dataset_year = 2045
|
||
# dataset_desc = "test metadata"
|
||
|
||
# if not dataset_title:
|
||
# raise errorRes(status_code=400, detail="Field 'dataset_title' wajib ada untuk metadata.")
|
||
|
||
# async with engine.begin() as conn:
|
||
# fields = [col for col in df.columns if col != "geometry"]
|
||
# # 💾 1️⃣ Simpan Metadata Dataset
|
||
# print("[INFO] Menyimpan metadata dataset...")
|
||
# result = await conn.execute(
|
||
# text("""
|
||
# INSERT INTO dataset_metadata (user_id, title, year, description, fields, created_at)
|
||
# VALUES (:user_id, :title, :year, :desc, :fields, :created_at)
|
||
# RETURNING id;
|
||
# """),
|
||
# {
|
||
# "user_id": user_id,
|
||
# "title": dataset_title,
|
||
# "year": dataset_year,
|
||
# "desc": dataset_desc,
|
||
# "fields": json.dumps(fields),
|
||
# "created_at": datetime.utcnow(),
|
||
# },
|
||
# )
|
||
# metadata_id = result.scalar_one()
|
||
# print(f"[INFO] Metadata disimpan dengan ID {metadata_id}")
|
||
|
||
# # ⚙️ 2️⃣ Auto-create Partisi Jika Belum Ada
|
||
# print(f"[INFO] Memastikan partisi test_partition_user_{user_id} tersedia...")
|
||
# await conn.execute(
|
||
# text(f"""
|
||
# DO $$
|
||
# BEGIN
|
||
# IF NOT EXISTS (
|
||
# SELECT 1 FROM pg_tables WHERE tablename = 'test_partition_user_{user_id}'
|
||
# ) THEN
|
||
# EXECUTE format('
|
||
# CREATE TABLE test_partition_user_%s
|
||
# PARTITION OF test_partition
|
||
# FOR VALUES IN (%s);
|
||
# ', {user_id}, {user_id});
|
||
# EXECUTE format('CREATE INDEX IF NOT EXISTS idx_partition_user_%s_geom ON test_partition_user_%s USING GIST (geom);', {user_id}, {user_id});
|
||
# EXECUTE format('CREATE INDEX IF NOT EXISTS idx_partition_user_%s_metadata ON test_partition_user_%s (metadata_id);', {user_id}, {user_id});
|
||
# END IF;
|
||
# END
|
||
# $$;
|
||
# """)
|
||
# )
|
||
|
||
# # 🧩 3️⃣ Insert Data Spasial ke Partisi
|
||
# print(f"[INFO] Memasukkan data ke test_partition_user_{user_id} ...")
|
||
# insert_count = 0
|
||
# for _, row in gdf.iterrows():
|
||
# geom_wkt = row["geometry"].wkt if row["geometry"] is not None else None
|
||
# attributes = row.drop(labels=["geometry"]).to_dict()
|
||
|
||
# await conn.execute(
|
||
# text("""
|
||
# INSERT INTO test_partition (user_id, metadata_id, geom, attributes, created_at)
|
||
# VALUES (:user_id, :metadata_id, ST_Force2D(ST_GeomFromText(:geom, 4326)),
|
||
# CAST(:attr AS jsonb), :created_at);
|
||
# """),
|
||
# {
|
||
# "user_id": user_id,
|
||
# "metadata_id": metadata_id,
|
||
# "geom": geom_wkt,
|
||
# "attr": json.dumps(attributes),
|
||
# "created_at": datetime.utcnow(),
|
||
# },
|
||
# )
|
||
# insert_count += 1
|
||
|
||
# # 🧩 4️⃣ Membuat VIEW untuk dataset baru di QGIS
|
||
# await create_dataset_view_from_metadata(conn, metadata_id, user_id, dataset_title)
|
||
|
||
# print(f"[INFO] ✅ Berhasil memasukkan {insert_count} baris ke partisi user_id={user_id} (metadata_id={metadata_id}).")
|
||
|
||
# return {
|
||
# "status": "success",
|
||
# "user_id": user_id,
|
||
# "metadata_id": metadata_id,
|
||
# "dataset_title": dataset_title,
|
||
# "inserted_rows": insert_count,
|
||
# "geometry_type": list(gdf.geom_type.unique()),
|
||
# }
|
||
|
||
# except Exception as e:
|
||
# print(f"[ERROR] Gagal upload ke PostGIS partition: {e}")
|
||
# raise errorRes(status_code=500, message="Gagal upload ke PostGIS partition", details=str(e))
|
||
|