from flask import Blueprint, render_template, request, send_file, flash from app.models.subcontractor_model import Subcontractor from app.models.manhole_excavation_model import ManholeExcavation from app.models.trench_excavation_model import TrenchExcavation from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber from app.models.mh_ex_client_model import ManholeExcavationClient from app.models.tr_ex_client_model import TrenchExcavationClient from app.models.mh_dc_client_model import ManholeDomesticChamberClient from app.utils.helpers import login_required import pandas as pd import io from enum import Enum # --- 1. DEFINE BLUEPRINT FIRST (Prevents NameError) --- file_report_bp = Blueprint("file_report", __name__, url_prefix="/file") class BillType(Enum): Client = 1 Subcontractor = 2 # --- 2. DEFINE CLASSES --- class SubcontractorBill: def __init__(self): # Initialize as empty DataFrames so .to_excel() always exists self.df_tr = pd.DataFrame() self.df_mh = pd.DataFrame() self.df_dc = pd.DataFrame() def Fetch(self, RA_Bill_No, subcontractor_id): # Query data filtered by both Bill No and Subcontractor ID trench = TrenchExcavation.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all() mh = ManholeExcavation.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all() dc = ManholeDomesticChamber.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all() # Convert SQL objects to DataFrames self.df_tr = pd.DataFrame([c.__dict__ for c in trench]) self.df_mh = pd.DataFrame([c.__dict__ for c in mh]) self.df_dc = pd.DataFrame([c.__dict__ for c in dc]) # Clean Columns (remove SQLAlchemy internal state) drop_cols = ["id", "created_at", "_sa_instance_state"] for df in [self.df_tr, self.df_mh, self.df_dc]: if not df.empty: df.drop(columns=drop_cols, errors="ignore", inplace=True) # --- 3. DEFINE ROUTES --- @file_report_bp.route("/report", methods=["GET", "POST"]) @login_required def report_file(): subcontractors = Subcontractor.query.all() if request.method == "POST": subcontractor_id = request.form.get("subcontractor_id") ra_bill_no = request.form.get("ra_bill_no") # Collected from the updated HTML if not subcontractor_id or not ra_bill_no: flash("Please select a subcontractor and enter an RA Bill Number.", "danger") return render_template("report.html", subcontractors=subcontractors) subcontractor = Subcontractor.query.get(subcontractor_id) # Instantiate and Fetch Data bill_gen = SubcontractorBill() bill_gen.Fetch(RA_Bill_No=ra_bill_no, subcontractor_id=subcontractor_id) # Check if any data was found if bill_gen.df_tr.empty and bill_gen.df_mh.empty and bill_gen.df_dc.empty: flash(f"No data found for {subcontractor.subcontractor_name} in RA Bill {ra_bill_no}", "warning") return render_template("report.html", subcontractors=subcontractors) # WRITE EXCEL FILE output = io.BytesIO() file_name = f"{subcontractor.subcontractor_name}_RA_{ra_bill_no}_Report.xlsx" with pd.ExcelWriter(output, engine="xlsxwriter") as writer: bill_gen.df_tr.to_excel(writer, index=False, sheet_name="Tr.Ex.") bill_gen.df_mh.to_excel(writer, index=False, sheet_name="MH.Ex.") bill_gen.df_dc.to_excel(writer, index=False, sheet_name="MH & DC") output.seek(0) return send_file( output, download_name=file_name, as_attachment=True, mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" ) return render_template("report.html", subcontractors=subcontractors) # (ClientBill class and client_vs_all_subcontractor route would follow here...) import pandas as pd import io from flask import Blueprint, render_template, request, send_file, flash from app.models.subcontractor_model import Subcontractor from app.models.manhole_excavation_model import ManholeExcavation from app.models.trench_excavation_model import TrenchExcavation from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber from app.models.mh_ex_client_model import ManholeExcavationClient from app.models.tr_ex_client_model import TrenchExcavationClient from app.models.mh_dc_client_model import ManholeDomesticChamberClient from app.utils.helpers import login_required # --- BLUEPRINT DEFINITION --- # Ensure this is unique to avoid conflicts file_report_bp = Blueprint("file_report", __name__, url_prefix="/file") class ClientBill: def __init__(self): self.df_tr = pd.DataFrame() self.df_mh = pd.DataFrame() self.df_dc = pd.DataFrame() def Fetch(self, RA_Bill_No): trench = TrenchExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all() mh = ManholeExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all() dc = ManholeDomesticChamberClient.query.filter_by(RA_Bill_No=RA_Bill_No).all() self.df_tr = pd.DataFrame([c.serialize() for c in trench]) self.df_mh = pd.DataFrame([c.serialize() for c in mh]) self.df_dc = pd.DataFrame([c.serialize() for c in dc]) # Standardize columns for merging if not self.df_dc.empty and "MH_NO" in self.df_dc.columns: self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True) drop_cols = ["id", "created_at", "_sa_instance_state"] for df in [self.df_tr, self.df_mh, self.df_dc]: if not df.empty: df.drop(columns=drop_cols, errors="ignore", inplace=True) class SubcontractorBill: def __init__(self): self.df_tr = pd.DataFrame() self.df_mh = pd.DataFrame() self.df_dc = pd.DataFrame() def Fetch(self, RA_Bill_No): trench = TrenchExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all() mh = ManholeExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all() dc = ManholeDomesticChamber.query.filter_by(RA_Bill_No=RA_Bill_No).all() self.df_tr = pd.DataFrame([c.serialize() for c in trench]) self.df_mh = pd.DataFrame([c.serialize() for c in mh]) self.df_dc = pd.DataFrame([c.serialize() for c in dc]) if not self.df_dc.empty and "MH_NO" in self.df_dc.columns: self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True) drop_cols = ["id", "created_at", "_sa_instance_state"] for df in [self.df_tr, self.df_mh, self.df_dc]: if not df.empty: df.drop(columns=drop_cols, errors="ignore", inplace=True) @file_report_bp.route("/client_vs_subcont", methods=["GET", "POST"]) @login_required def client_vs_all_subcontractor(): if request.method == "POST": RA_Bill_No = request.form.get("RA_Bill_No") if not RA_Bill_No: flash("Please enter RA Bill No.", "danger") return render_template("generate_comparison_client_vs_subcont.html") clientBill = ClientBill() clientBill.Fetch(RA_Bill_No=RA_Bill_No) contractorBill = SubcontractorBill() contractorBill.Fetch(RA_Bill_No=RA_Bill_No) # Updated QTY lists to match model fields exactly qty_cols = [ "Soft_Murum_0_to_1_5_total", "Soft_Murum_1_5_to_3_0_total", "Soft_Murum_3_0_to_4_5_total", "Hard_Murum_0_to_1_5_total", "Hard_Murum_1_5_to_3_0_total", "Hard_Murum_3_0_to_4_5_total", "Soft_Rock_0_to_1_5_total", "Soft_Rock_1_5_to_3_0_total", "Soft_Rock_3_0_to_4_5_total", "Hard_Rock_0_to_1_5_total", "Hard_Rock_1_5_to_3_0_total", "Hard_Rock_3_0_to_4_5_total", "Hard_Rock_4_5_to_6_0_total", "Hard_Rock_6_0_to_7_5_total" ] mh_dc_qty_cols = [ "d_0_to_1_5", "d_1_5_to_2_0", "d_2_0_to_2_5", "d_2_5_to_3_0", "d_3_0_to_3_5", "d_3_5_to_4_0", "d_4_0_to_4_5", "d_4_5_to_5_0", "d_5_0_to_5_5", "d_5_5_to_6_0", "d_6_0_to_6_5", "Domestic_Chambers" ] # Aggregate Subcontractor Data safely def aggregate_df(df, group_cols, sum_cols): if df.empty: return pd.DataFrame() existing_cols = [c for c in sum_cols if c in df.columns] return df.groupby(group_cols, as_index=False)[existing_cols].sum() df_sub_tr_grp = aggregate_df(contractorBill.df_tr, ["Location", "MH_NO"], qty_cols) df_sub_mh_grp = aggregate_df(contractorBill.df_mh, ["Location", "MH_NO"], qty_cols) df_sub_dc_grp = aggregate_df(contractorBill.df_dc, ["Location", "Node_No"], mh_dc_qty_cols) # Merge and Calculate Difference df_tr_cmp = clientBill.df_tr.merge(df_sub_tr_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub")) df_mh_cmp = clientBill.df_mh.merge(df_sub_mh_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub")) df_dc_cmp = clientBill.df_dc.merge(df_sub_dc_grp, on=["Location", "Node_No"], how="left", suffixes=("_Client", "_Sub")) # Calculate Diffs for df in [df_tr_cmp, df_mh_cmp]: for col in qty_cols: if f"{col}_Client" in df.columns: df[f"{col}_Diff"] = df[f"{col}_Client"].fillna(0) - df[f"{col}_Sub"].fillna(0) for col in mh_dc_qty_cols: if f"{col}_Client" in df_dc_cmp.columns: df_dc_cmp[f"{col}_Diff"] = df_dc_cmp[f"{col}_Client"].fillna(0) - df_dc_cmp[f"{col}_Sub"].fillna(0) output = io.BytesIO() file_name = f"Comparison_RA_Bill_{RA_Bill_No}.xlsx" with pd.ExcelWriter(output, engine="xlsxwriter") as writer: df_tr_cmp.to_excel(writer, sheet_name="Tr.Ex Comparison", index=False) df_mh_cmp.to_excel(writer, sheet_name="Mh.Ex Comparison", index=False) df_dc_cmp.to_excel(writer, sheet_name="MH & DC Comparison", index=False) output.seek(0) return send_file(output, download_name=file_name, as_attachment=True, mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet") return render_template("generate_comparison_client_vs_subcont.html")