update reader csv

main.py

@@ -11,7 +11,8 @@ 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
@@ -147,6 +148,8 @@ 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:
@@ -418,7 +421,7 @@ class UploadRequest(BaseModel):
 @app.post("/upload_to_postgis")
 def upload_to_postgis(payload: UploadRequest):
     try:
-        table_name = payload.title.lower().replace(" ", "_")
+        table_name = payload.title.lower().replace(" ", "_").replace("-","_")
 
         df = pd.DataFrame(payload.rows)
         print(f"[INFO] Diterima {len(df)} baris data dari frontend.")

requirements.txt

@@ -21,6 +21,7 @@ openpyxl
 requests
 pathlib
 pyarrow
+geoalchemy2
 
 # --- jika menggunakan ai ---
 groq

services/geometry_detector.py

@@ -159,8 +159,15 @@ 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

@@ -1,21 +1,9 @@
-# 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)]
 
@@ -23,12 +11,10 @@ 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  # makin tinggi makin mirip header
+        score = alpha_ratio - digit_ratio 
 
         if score > best_score:
             best_score = score
@@ -37,23 +23,47 @@ def detect_header_line(path, max_rows=10):
     return header_line_idx
 
 
-def read_csv(path: str):
+def detect_delimiter(path, sample_size=2048):
-    """
+    with open(path, 'r', encoding='utf-8', errors='ignore') as f:
-    Membaca CSV dengan deteksi otomatis baris header.
+        sample = f.read(sample_size)
-    """
+    sniffer = csv.Sniffer()
     try:
-        header_line = detect_header_line(path)
+        dialect = sniffer.sniff(sample)
-        print(f"[INFO] Detected header line: {header_line + 1}")
+        return dialect.delimiter
-        df = pd.read_csv(path, header=header_line, encoding='utf-8', low_memory=False)
+    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
+
+    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}, delimiter: '{delimiter}'")
+
+            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 deteksi header otomatis: {e}, fallback ke baris pertama")
+        print(f"[WARN] Gagal membaca file ({e}), fallback ke default")
         df = pd.read_csv(path, encoding='utf-8', low_memory=False)
 
-    # Bersihkan kolom kosong / unnamed
+    # Bersihkan kolom dan baris kosong
-    df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
+    df = df.loc[:, ~df.columns.astype(str).str.contains('^Unnamed')]
     df.columns = [str(c).strip() for c in df.columns]
-
-    # Hapus baris kosong total
     df = df.dropna(how='all')
 
     return df