305 lines
12 KiB
Python
305 lines
12 KiB
Python
import os
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import pandas as pd
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from werkzeug.utils import secure_filename
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from app.config import Config
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from app import db
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from app.models.trench_excavation_model import TrenchExcavation
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from app.models.manhole_excavation_model import ManholeExcavation
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from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber
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from app.models.tr_ex_client_model import TrenchExcavationClient
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from app.models.mh_ex_client_model import ManholeExcavationClient
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from app.utils.file_utils import ensure_upload_folder
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class FileService:
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def allowed_file(self, filename):
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return "." in filename and filename.rsplit(".", 1)[1].lower() in Config.ALLOWED_EXTENSIONS
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def handle_file_upload(self, file, subcontractor_id, file_type):
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if not subcontractor_id:
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return False, "Please select subcontractor."
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if not file_type:
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return False, "Please select file type."
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if not file or file.filename == "":
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return False, "No file selected."
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if not self.allowed_file(file.filename):
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return False, "Invalid file type! Allowed: CSV, XLSX, XLS"
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ensure_upload_folder()
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folder = os.path.join(Config.UPLOAD_FOLDER, f"sub_{subcontractor_id}")
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os.makedirs(folder, exist_ok=True)
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filename = secure_filename(file.filename)
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filepath = os.path.join(folder, filename)
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file.save(filepath)
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try:
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df = pd.read_csv(filepath) if filename.endswith(".csv") else pd.read_excel(filepath)
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print("\n=== Uploaded File Preview ===")
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print(df.head())
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print("=============================\n")
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# Trench Excavation save (subcontractor)
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if file_type == "trench_excavation":
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return self.process_trench_excavation(df, subcontractor_id)
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# Manhole Excavation save (subcontractor)
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if file_type == "manhole_excavation":
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return self.process_manhole_excavation(df, subcontractor_id)
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# Manhole and Domestic Chamber Construction save (subcontractor)
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if file_type == "manhole_domestic_chamber":
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return self.process_manhole_domestic_chamber(df, subcontractor_id)
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# Trench Excavation save (client)
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if file_type =="tr_ex_client":
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return self.client_trench_excavation(df, subcontractor_id)
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# Manhole Excavation save (client)
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# if file_type =="mh_ex_client":
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# return self.client_manhole_excavation(df, subcontractor_id)
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return True, "File uploaded successfully."
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except Exception as e:
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return False, f"Processing failed: {e}"
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# ---------------------- Sub contractor --------------------------
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# Trench Excavation save method (TrenchExcavation model)
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def process_trench_excavation(self, df, subcontractor_id):
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df.columns = [str(c).strip() for c in df.columns]
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# If the sheet has merged cells -> forward fill Location
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if "Location" in df.columns:
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df["Location"] = df["Location"].ffill()
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df = df.dropna(how="all") # REMOVE empty rows
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# Identify missing location rows before insert
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missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
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if not missing_loc.empty:
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return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
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saved_count = 0
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try:
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for index, row in df.iterrows():
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record_data = {}
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# Insert only fields that exist in model
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for col in df.columns:
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if hasattr(TrenchExcavation, col):
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value = row[col]
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# Normalize empty values
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if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
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value = None
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record_data[col] = value
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record = TrenchExcavation(
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subcontractor_id=subcontractor_id,
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**record_data
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)
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db.session.add(record)
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saved_count += 1
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db.session.commit()
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return True, f"Trench Excavation data saved successfully. Total rows: {saved_count}"
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except Exception as e:
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db.session.rollback()
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return False, f"Trench Excavation Save Failed: {e}"
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# Manhole Excavation save method (ManholeExcavation model)
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def process_manhole_excavation(self, df, subcontractor_id):
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# Clean column names (strip whitespace)
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df.columns = [str(c).strip() for c in df.columns]
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# If the sheet has merged cells -> forward fill Location
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if "Location" in df.columns:
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df["Location"] = df["Location"].ffill()
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# REMOVE empty rows
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df = df.dropna(how="all")
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# Identify missing location rows before insert
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missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
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if not missing_loc.empty:
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return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
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saved_count = 0
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try:
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for index, row in df.iterrows():
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record_data = {}
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# Insert only fields that exist in model
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for col in df.columns:
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if hasattr(ManholeExcavation, col):
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value = row[col]
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# Normalize empty values
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if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
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value = None
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record_data[col] = value
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record = ManholeExcavation(
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subcontractor_id=subcontractor_id,
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**record_data
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)
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db.session.add(record)
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saved_count += 1
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db.session.commit()
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return True, f"Manhole Excavation data saved successfully. Total rows: {saved_count}"
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except Exception as e:
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db.session.rollback()
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return False, f"Manhole Excavation Save Failed: {e}"
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# Manhole and Domestic Chamber Construction save method (ManholeDomesticChamber model)
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def process_manhole_domestic_chamber(self, df, subcontractor_id):
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# Clean column names (strip whitespace)
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df.columns = [str(c).strip() for c in df.columns]
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# If the sheet has merged cells -> forward fill Location
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if "Location" in df.columns:
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df["Location"] = df["Location"].ffill()
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# REMOVE empty rows
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df = df.dropna(how="all")
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# Identify missing location rows before insert
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missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
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if not missing_loc.empty:
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return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
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saved_count = 0
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try:
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for index, row in df.iterrows():
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record_data = {}
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# Insert only fields that exist in model
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for col in df.columns:
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if hasattr(ManholeDomesticChamber, col):
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value = row[col]
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# Normalize empty values
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if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
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value = None
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record_data[col] = value
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record = ManholeDomesticChamber(
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subcontractor_id=subcontractor_id,
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**record_data
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)
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db.session.add(record)
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saved_count += 1
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db.session.commit()
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return True, f"Manhole Domestic Chamber Construction data saved successfully. Total rows: {saved_count}"
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except Exception as e:
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db.session.rollback()
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return False, f"Manhole Domestic Chamber Construction Save Failed: {e}"
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# ---------------------- client ----------------------------------
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# Trench Excavation save method (TrenchExcavationClient model)
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def client_trench_excavation(self, df, subcontractor_id):
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df.columns = [str(c).strip() for c in df.columns]
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# If the sheet has merged cells -> forward fill Location
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if "Location" in df.columns:
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df["Location"] = df["Location"].ffill()
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df = df.dropna(how="all") # REMOVE empty rows
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# Identify missing location rows before insert
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missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
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if not missing_loc.empty:
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return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
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saved_count = 0
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try:
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for index, row in df.iterrows():
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record_data = {}
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# Insert only fields that exist in model
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for col in df.columns:
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if hasattr(TrenchExcavationClient, col):
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value = row[col]
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# Normalize empty values
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if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
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value = None
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record_data[col] = value
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record = TrenchExcavationClient(
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subcontractor_id=subcontractor_id,
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**record_data
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)
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db.session.add(record)
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saved_count += 1
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db.session.commit()
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return True, f"Clinnt Tr Ex data saved successfully. Total rows: {saved_count}"
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except Exception as e:
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db.session.rollback()
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return False, f"Clinnt Tr Ex Save Failed: {e}"
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# Manhole Excavation save method (ManholeExcavationClient model)
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# def client_manhole_excavation(self, df, subcontractor_id):
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# # Clean column names (strip whitespace)
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# df.columns = [str(c).strip() for c in df.columns]
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# # If the sheet has merged cells -> forward fill Location
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# if "Location" in df.columns:
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# df["Location"] = df["Location"].ffill()
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# # REMOVE empty rows
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# df = df.dropna(how="all")
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# # Identify missing location rows before insert
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# missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
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# if not missing_loc.empty:
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# return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
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# saved_count = 0
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# try:
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# for index, row in df.iterrows():
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# record_data = {}
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# # Insert only fields that exist in model
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# for col in df.columns:
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# if hasattr(ManholeExcavationClient, col):
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# value = row[col]
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# # Normalize empty values
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# if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
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# value = None
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# record_data[col] = value
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# record = ManholeExcavationClient(
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# subcontractor_id=subcontractor_id,
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# **record_data
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# )
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# db.session.add(record)
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# saved_count += 1
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# db.session.commit()
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# return True, f" Client Mh Ex. data saved successfully. Total rows: {saved_count}"
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# except Exception as e:
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# db.session.rollback()
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# return False, f"Client Mh Ex. Save Failed: {e}"
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