main.py

@@ -11,8 +11,7 @@ from core.config import UPLOAD_FOLDER, MAX_FILE_MB
 from services.reader_csv import read_csv
 from services.reader_shp import read_shp
 from services.reader_gdb import read_gdb
-# from services.reader_pdf import convert_df, read_pdf
+from services.reader_pdf import convert_df, read_pdf
-from testing.test_pdf_multi import convert_df, read_pdf
 from services.geometry_detector import detect_and_build_geometry
 from services.geometry_detector import attach_polygon_geometry_auto
 from database.connection import engine
@@ -148,8 +147,6 @@ async def upload_file(file: UploadFile = File(...)):
 
         if ext == ".csv":
             df = read_csv(str(tmp_path))
-        elif ext == ".xlsx":
-            df = read_csv(str(tmp_path))
         elif ext == ".pdf":
             tbl = read_pdf(tmp_path)
             if len(tbl) > 1:
@@ -421,7 +418,7 @@ class UploadRequest(BaseModel):
 @app.post("/upload_to_postgis")
 def upload_to_postgis(payload: UploadRequest):
     try:
-        table_name = payload.title.lower().replace(" ", "_").replace("-","_")
+        table_name = payload.title.lower().replace(" ", "_")
 
         df = pd.DataFrame(payload.rows)
         print(f"[INFO] Diterima {len(df)} baris data dari frontend.")

requirements.txt

@@ -20,8 +20,6 @@ starlette
 openpyxl
 requests
 pathlib
-pyarrow
-geoalchemy2
 
 # --- jika menggunakan ai ---
 groq

services/geometry_detector.py

@@ -159,15 +159,8 @@ def detect_and_build_geometry(df: pd.DataFrame, master_polygons: gpd.GeoDataFram
     if lat_col and lon_col:
         df[lat_col] = pd.to_numeric(df[lat_col], errors='coerce')
         df[lon_col] = pd.to_numeric(df[lon_col], errors='coerce')
-
-        lon_median = df[lon_col].abs().median()
-        lat_median = df[lat_col].abs().median()
-
-        if lon_median > 1000 or lat_median > 1000:
-            df[lon_col] = df[lon_col] / 1e7
-            df[lat_col] = df[lat_col] / 1e7
-
         gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df[lon_col], df[lat_col]), crs="EPSG:4326")
+        print("[INFO] Geometry dibangun dari kolom lat/lon.")
         return gdf
 
     coord_col = next(

services/reader_csv.py

@@ -1,9 +1,21 @@
+# import pandas as pd
+
+# def read_csv(path: str):
+#     df = pd.read_csv(path)
+#     df.columns = [c.strip() for c in df.columns]
+
+#     return df
+
+
+# services/reader_csv.py
 import pandas as pd
 import re
-import csv
-import os
 
 def detect_header_line(path, max_rows=10):
+    """
+    Mendeteksi baris header (nama kolom) di CSV.
+    Mengembalikan index baris header (0-based).
+    """
     with open(path, 'r', encoding='utf-8', errors='ignore') as f:
         lines = [next(f) for _ in range(max_rows)]
 
@@ -11,10 +23,12 @@ def detect_header_line(path, max_rows=10):
     best_score = -1
 
     for i, line in enumerate(lines):
+        # Pisahkan berdasarkan koma / titik koma / tab
         cells = re.split(r'[;,|\t]', line.strip())
+        # Heuristik: jika banyak huruf & sedikit angka → kemungkinan header
         alpha_ratio = sum(bool(re.search(r'[A-Za-z]', c)) for c in cells) / max(len(cells), 1)
         digit_ratio = sum(bool(re.search(r'\d', c)) for c in cells) / max(len(cells), 1)
-        score = alpha_ratio - digit_ratio 
+        score = alpha_ratio - digit_ratio  # makin tinggi makin mirip header
 
         if score > best_score:
             best_score = score
@@ -23,47 +37,23 @@ def detect_header_line(path, max_rows=10):
     return header_line_idx
 
 
-def detect_delimiter(path, sample_size=2048):
-    with open(path, 'r', encoding='utf-8', errors='ignore') as f:
-        sample = f.read(sample_size)
-    sniffer = csv.Sniffer()
-    try:
-        dialect = sniffer.sniff(sample)
-        return dialect.delimiter
-    except Exception:
-        for delim in [',', ';', '\t', '|']:
-            if delim in sample:
-                return delim
-        return ','
-
-
 def read_csv(path: str):
-    ext = os.path.splitext(path)[1].lower()  # ambil ekstensi file
+    """
-
+    Membaca CSV dengan deteksi otomatis baris header.
+    """
     try:
-        if ext in ['.csv', '.txt']:
-            # === Baca file CSV ===
         header_line = detect_header_line(path)
-            delimiter = detect_delimiter(path)
+        print(f"[INFO] Detected header line: {header_line + 1}")
-            print(f"[INFO] Detected header line: {header_line + 1}, delimiter: '{delimiter}'")
+        df = pd.read_csv(path, header=header_line, encoding='utf-8', low_memory=False)
-
-            df = pd.read_csv(path, header=header_line, sep=delimiter, encoding='utf-8', low_memory=False)
-
-        elif ext in ['.xlsx', '.xls']:
-            # === Baca file Excel ===
-            print(f"[INFO] Membaca file Excel: {os.path.basename(path)}")
-            df = pd.read_excel(path, header=0)  # default header baris pertama
-
-        else:
-            raise ValueError("Format file tidak dikenali (hanya .csv, .txt, .xlsx, .xls)")
-
     except Exception as e:
-        print(f"[WARN] Gagal membaca file ({e}), fallback ke default")
+        print(f"[WARN] Gagal deteksi header otomatis: {e}, fallback ke baris pertama")
         df = pd.read_csv(path, encoding='utf-8', low_memory=False)
 
-    # Bersihkan kolom dan baris kosong
+    # Bersihkan kolom kosong / unnamed
-    df = df.loc[:, ~df.columns.astype(str).str.contains('^Unnamed')]
+    df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
     df.columns = [str(c).strip() for c in df.columns]
+
+    # Hapus baris kosong total
     df = df.dropna(how='all')
 
     return df