import os import pandas as pd from werkzeug.utils import secure_filename from app.config import Config from app import db from app.models.trench_excavation_model import TrenchExcavation from app.models.manhole_excavation_model import ManholeExcavation from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber from app.models.tr_ex_client_model import TrenchExcavationClient from app.models.mh_ex_client_model import ManholeExcavationClient from app.models.mh_dc_client_model import ManholeDomesticChamberClient from app.utils.file_utils import ensure_upload_folder class FileService: def allowed_file(self, filename): return "." in filename and filename.rsplit(".", 1)[1].lower() in Config.ALLOWED_EXTENSIONS # def handle_file_upload(self, file, subcontractor_id, file_type): def handle_file_upload(self, file, subcontractor_id, RA_Bill_No): if not subcontractor_id: return False, "Please select subcontractor." if not RA_Bill_No: return False, "Please Enter RA Bill No)." if not file or file.filename == "": return False, "No file selected." if not self.allowed_file(file.filename): return False, "Invalid file type! Allowed: CSV, XLSX, XLS" ensure_upload_folder() folder = os.path.join(Config.UPLOAD_FOLDER, f"sub_{subcontractor_id}") os.makedirs(folder, exist_ok=True) filename = secure_filename(file.filename) filepath = os.path.join(folder, filename) file.save(filepath) try: df_tr_ex = pd.read_excel(filepath, sheet_name ="Tr.Ex.", header=12) df_mh_ex = pd.read_excel(filepath, sheet_name="MH Ex.", header=12) df_mh_dc = pd.read_excel(filepath, sheet_name="MH & DC", header=11) self.process_trench_excavation(df_tr_ex, subcontractor_id, RA_Bill_No) self.process_manhole_excavation(df_mh_ex, subcontractor_id, RA_Bill_No) self.process_manhole_domestic_chamber(df_mh_dc, subcontractor_id, RA_Bill_No) return True, "File uploaded successfully." except Exception as e: return False, f"Processing failed: {e}" # Trench Excavation save method (TrenchExcavation model) def process_trench_excavation(self, df, subcontractor_id,RA_Bill_No): print("trench_excavation RA_Bill_No :",RA_Bill_No) print("=== trench_excavation ===") print(df.columns.tolist()) print("===================") # Clean column names df.columns = ( df.columns.astype(str) .str.strip() .str.replace(r"[^\w]", "_", regex=True) .str.replace("__+", "_", regex=True) .str.strip("_") ) # Remove completely empty rows df = df.dropna(how="all") # Forward fill merged Location if "Location" in df.columns: df["Location"] = df["Location"].ffill() saved_count = 0 skipped_count = 0 try: for index, row in df.iterrows(): record_data = {} location = row.get("Location") mh_no = row.get("MH_NO") if (pd.isna(location) or str(location).strip() == "" or pd.isna(mh_no) or str(mh_no).strip() == ""): skipped_count += 1 continue # Map only model columns for col in df.columns: if hasattr(TrenchExcavation, col): value = row[col] # Normalize empty values if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan"]: value = None record_data[col] = value # If all mapped fields are None → skip if all(v is None for v in record_data.values()): skipped_count += 1 continue record = TrenchExcavation( subcontractor_id=subcontractor_id, RA_Bill_No=RA_Bill_No, **record_data ) print("trench_excavation Saving Row → Location:", record.Location, " MH_NO:", record.MH_NO) db.session.add(record) saved_count += 1 db.session.commit() return True, ( f"Trench Excavation saved successfully. " f"Inserted: {saved_count}, Skipped: {skipped_count}" ) except Exception as e: db.session.rollback() return False, f"Trench Excavation save failed: {e}" # Manhole Excavation save method (ManholeExcavation model) def process_manhole_excavation(self, df, subcontractor_id, RA_Bill_No): print("manhole_excavation RA_Bill_No:",RA_Bill_No) print("=== manhole_excavation ===") print(df.columns.tolist()) print("===================") # Clean column names df.columns = ( df.columns.astype(str) .str.strip() .str.replace(r"[^\w]", "_", regex=True) .str.replace("__+", "_", regex=True) .str.strip("_") ) # Remove completely empty rows df = df.dropna(how="all") # Forward fill merged Location if "Location" in df.columns: df["Location"] = df["Location"].ffill() saved_count = 0 skipped_count = 0 try: for index, row in df.iterrows(): record_data = {} location = row.get("Location") mh_no = row.get("MH_NO") if (pd.isna(location) or str(location).strip() == "" or pd.isna(mh_no) or str(mh_no).strip() == ""): skipped_count += 1 continue # Map only model columns for col in df.columns: if hasattr(ManholeExcavation, col): value = row[col] # Normalize empty values if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan"]: value = None record_data[col] = value # If all mapped fields are None → skip if all(v is None for v in record_data.values()): skipped_count += 1 continue record = ManholeExcavation( subcontractor_id=subcontractor_id, RA_Bill_No=RA_Bill_No, **record_data ) print("manhole_excavation Saving Row → Location:", record.Location, " MH_NO:", record.MH_NO) db.session.add(record) saved_count += 1 db.session.commit() return True, ( f"Manhole Excavation saved successfully. " f"Inserted: {saved_count}, Skipped: {skipped_count}" ) except Exception as e: db.session.rollback() return False, f"Manhole Excavation save failed: {e}" # Manhole and Domestic Chamber Construction save method (ManholeDomesticChamber model) def process_manhole_domestic_chamber(self, df, subcontractor_id, RA_Bill_No): print("manhole_domestic_chamber RA_Bill_No :",RA_Bill_No) print("=== manhole_domestic_chamber ===") print(df.columns.tolist()) print("===================") # Clean column names df.columns = ( df.columns.astype(str) .str.strip() .str.replace(r"[^\w]", "_", regex=True) .str.replace("__+", "_", regex=True) .str.strip("_") ) # Remove completely empty rows df = df.dropna(how="all") # Forward fill merged Location if "Location" in df.columns: df["Location"] = df["Location"].ffill() saved_count = 0 skipped_count = 0 try: for index, row in df.iterrows(): record_data = {} location = row.get("Location") Node_No = row.get("Node_No") if (pd.isna(location) or str(location).strip() == "" or pd.isna(Node_No) or str(Node_No).strip() == ""): skipped_count += 1 continue # Map only model columns for col in df.columns: if hasattr(ManholeDomesticChamber, col): value = row[col] # Normalize empty values if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan"]: value = None record_data[col] = value # If all mapped fields are None → skip if all(v is None for v in record_data.values()): skipped_count += 1 continue record = ManholeDomesticChamber( subcontractor_id=subcontractor_id, RA_Bill_No=RA_Bill_No, **record_data ) print("manhole_domestic_chamber Saving Row → Location:", record.Location, " Node_No:", record.Node_No) db.session.add(record) saved_count += 1 db.session.commit() return True, ( f"Manhole Domestic Chamber saved successfully. " f"Inserted: {saved_count}, Skipped: {skipped_count}" ) except Exception as e: db.session.rollback() return False, f"Manhole Domestic Chamber save failed: {e}" # ---------------------- client ---------------------------------- # def handle_client_file_upload(self, file, RA_Bill_No): # if not RA_Bill_No: # return False, "Please Enter RA Bill No ." # if not file or file.filename == "": # return False, "No file selected." # if not self.allowed_file(file.filename): # return False, "Invalid file type! Allowed: CSV, XLSX, XLS" # ensure_upload_folder() # folder = os.path.join(Config.UPLOAD_FOLDER, f"Client_Bill_{RA_Bill_No}") # os.makedirs(folder, exist_ok=True) # filename = secure_filename(file.filename) # filepath = os.path.join(folder, filename) # file.save(filepath) # try: # df_tr_ex = pd.read_excel(filepath, sheet_name ="Tr.Ex.", header=12) # df_mh_ex = pd.read_excel(filepath, sheet_name="MH Ex.", header=12) # df_mh_dc = pd.read_excel(filepath, sheet_name="MH & DC", header=11) # print("\n=== Uploaded File tr ex ===") # print(df_tr_ex.head()) # print("=============================\n") # print("\n=== Uploaded File mh ex ===") # print(df_mh_ex.head()) # print("========================================\n") # print("\n=== Uploaded File MH DC ===") # print(df_mh_dc.head()) # print("========================================\n") # self.client_trench_excavation(df_tr_ex, RA_Bill_No) # self.client_manhole_excavation(df_mh_ex, RA_Bill_No) # self.client_manhole_domestic_chamber(df_mh_dc, RA_Bill_No) # return True, "File uploaded successfully." # except Exception as e: # return False, f"Processing failed: {e}" # # Tr Ex save method (TrenchExcavationClient model) # def client_trench_excavation(self, df, RA_Bill_No): # df.columns = [str(c).strip() for c in df.columns] # # If the sheet has merged cells -> forward fill Location # if "Location" in df.columns: # df["Location"] = df["Location"].ffill() # df = df.dropna(how="all") # REMOVE empty rows # # Identify missing location rows before insert # missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")] # if not missing_loc.empty: # return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}" # saved_count = 0 # try: # for index, row in df.iterrows(): # record_data = {} # # Insert only fields that exist in model # for col in df.columns: # if hasattr(TrenchExcavationClient, col): # value = row[col] # # Normalize empty values # if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]: # value = None # record_data[col] = value # record = TrenchExcavationClient( # RA_Bill_No=RA_Bill_No, # **record_data # ) # db.session.add(record) # saved_count += 1 # db.session.commit() # return True, f"Clinnt Tr Ex data saved successfully. Total rows: {saved_count}" # except Exception as e: # db.session.rollback() # return False, f"Clinnt Tr Ex Save Failed: {e}" # # Mh Ex save method (ManholeExcavationClient model) # def client_manhole_excavation(self, df, RA_Bill_No): # # Clean column names (strip whitespace) # df.columns = [str(c).strip() for c in df.columns] # # If the sheet has merged cells -> forward fill Location # if "Location" in df.columns: # df["Location"] = df["Location"].ffill() # # REMOVE empty rows # df = df.dropna(how="all") # # Identify missing location rows before insert # missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")] # if not missing_loc.empty: # return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}" # saved_count = 0 # try: # for index, row in df.iterrows(): # record_data = {} # # Insert only fields that exist in model # for col in df.columns: # if hasattr(ManholeExcavationClient, col): # value = row[col] # # Normalize empty values # if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]: # value = None # record_data[col] = value # record = ManholeExcavationClient( # RA_Bill_No=RA_Bill_No, # **record_data # ) # db.session.add(record) # saved_count += 1 # db.session.commit() # return True, f" Client Mh Ex. data saved successfully. Total rows: {saved_count}" # except Exception as e: # db.session.rollback() # return False, f"Client Mh Ex. Save Failed: {e}" # # Mh and Dc save method (ManholeDomesticChamberClient model) # def client_manhole_domestic_chamber(self, df, RA_Bill_No): # Clean column names (strip whitespace) # df.columns = [str(c).strip() for c in df.columns] # # If the sheet has merged cells -> forward fill Location # if "Location" in df.columns: # df["Location"] = df["Location"].ffill() # # REMOVE empty rows # df = df.dropna(how="all") # # Identify missing location rows before insert # missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")] # if not missing_loc.empty: # return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}" # saved_count = 0 # try: # for index, row in df.iterrows(): # record_data = {} # # Insert only fields that exist in model # for col in df.columns: # if hasattr(ManholeDomesticChamberClient, col): # value = row[col] # # Normalize empty values # if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]: # value = None # record_data[col] = value # record = ManholeDomesticChamberClient( # RA_Bill_No=RA_Bill_No, # **record_data # ) # db.session.add(record) # saved_count += 1 # db.session.commit() # return True, f"Mh and Dc data saved successfully. Total rows: {saved_count}" # except Exception as e: # db.session.rollback() # return False, f"Mh and Dc data Save Failed: {e}" def handle_client_file_upload(self, file, RA_Bill_No): if not RA_Bill_No: return False, "Please Enter RA Bill No." if not file or file.filename == "": return False, "No file selected." if not self.allowed_file(file.filename): return False, "Invalid file type! Allowed: CSV, XLSX, XLS" ensure_upload_folder() folder = os.path.join(Config.UPLOAD_FOLDER, f"Client_Bill_{RA_Bill_No}") os.makedirs(folder, exist_ok=True) filename = secure_filename(file.filename) filepath = os.path.join(folder, filename) file.save(filepath) try: df_tr_ex = pd.read_excel(filepath, sheet_name="Tr.Ex.", header=12) df_mh_ex = pd.read_excel(filepath, sheet_name="MH Ex.", header=12) df_mh_dc = pd.read_excel(filepath, sheet_name="MH & DC", header=11) # Single transaction self._save_client_data(df_tr_ex, TrenchExcavationClient, "Trench Excavation", RA_Bill_No) self._save_client_data(df_mh_ex, ManholeExcavationClient, "Manhole Excavation", RA_Bill_No) self._save_client_data(df_mh_dc, ManholeDomesticChamberClient, "MH & DC", RA_Bill_No) db.session.commit() return True, "Client file uploaded and all data saved successfully." except ClientDataSaveError as e: db.session.rollback() return False, str(e) except Exception as e: db.session.rollback() return False, f"Unexpected system error: {e}" def _save_client_data(self, df, model, RA_Bill_No): # Clean column names df.columns = [str(c).strip() for c in df.columns] # Forward fill Location (merged cells issue) if "Location" in df.columns: df["Location"] = df["Location"].ffill() # Remove fully empty rows df = df.dropna(how="all") # Validate Location if "Location" in df.columns: missing_loc = df[ df["Location"].isna() | (df["Location"].astype(str).str.strip() == "") ] if not missing_loc.empty: raise Exception( f"{model.__name__}: Empty Location at rows {missing_loc.index.tolist()}" ) # Insert rows for _, row in df.iterrows(): record_data = {} for col in df.columns: if hasattr(model, col): value = row[col] if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]: value = None record_data[col] = value record = model( RA_Bill_No=RA_Bill_No, **record_data ) db.session.add(record)