302 lines
14 KiB
Python
302 lines
14 KiB
Python
from flask import Blueprint, render_template, request, send_file, flash
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from app.models.subcontractor_model import Subcontractor
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from app.models.manhole_excavation_model import ManholeExcavation
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from app.models.trench_excavation_model import TrenchExcavation
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from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber
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from app.models.mh_ex_client_model import ManholeExcavationClient
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from app.models.tr_ex_client_model import TrenchExcavationClient
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from app.models.mh_dc_client_model import ManholeDomesticChamberClient
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from app.utils.helpers import login_required
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import pandas as pd
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import io
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from enum import Enum
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# --- 1. DEFINE BLUEPRINT FIRST (Prevents NameError) ---
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file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
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class BillType(Enum):
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Client = 1
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Subcontractor = 2
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# --- 2. DEFINE CLASSES ---
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class SubcontractorBill:
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def __init__(self):
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self.df_tr = pd.DataFrame()
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self.df_mh = pd.DataFrame()
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self.df_dc = pd.DataFrame()
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def Fetch(self, RA_Bill_No=None, subcontractor_id=None):
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# Build dynamic filters based on what is provided
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filters = {}
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if subcontractor_id:
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filters["subcontractor_id"] = subcontractor_id
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if RA_Bill_No:
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filters["RA_Bill_No"] = RA_Bill_No
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# Query using the filters
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trench = TrenchExcavation.query.filter_by(**filters).all()
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mh = ManholeExcavation.query.filter_by(**filters).all()
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dc = ManholeDomesticChamber.query.filter_by(**filters).all()
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# Convert to DataFrames
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self.df_tr = pd.DataFrame([c.serialize() for c in trench])
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self.df_mh = pd.DataFrame([c.serialize() for c in mh])
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self.df_dc = pd.DataFrame([c.serialize() for c in dc])
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# Standardize columns and clean internal SQLAlchemy state
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if not self.df_dc.empty and "MH_NO" in self.df_dc.columns:
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self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True)
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drop_cols = ["id", "created_at", "_sa_instance_state"]
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for df in [self.df_tr, self.df_mh, self.df_dc]:
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if not df.empty:
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df.drop(columns=drop_cols, errors="ignore", inplace=True)
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# --- Updated Route with "Download All" Support ---
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@file_report_bp.route("/report", methods=["GET", "POST"])
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@login_required
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def report_file():
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subcontractors = Subcontractor.query.all()
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if request.method == "POST":
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subcontractor_id = request.form.get("subcontractor_id")
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ra_bill_no = request.form.get("ra_bill_no")
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download_all = request.form.get("download_all") == "true" # Check for toggle
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if not subcontractor_id:
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flash("Please select a subcontractor.", "danger")
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return render_template("report.html", subcontractors=subcontractors)
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subcontractor = Subcontractor.query.get(subcontractor_id)
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bill_gen = SubcontractorBill()
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if download_all:
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# Fetch EVERYTHING for this subcontractor
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bill_gen.Fetch(subcontractor_id=subcontractor_id, RA_Bill_No=None)
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file_name = f"{subcontractor.subcontractor_name}_ALL_BILLS.xlsx"
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else:
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if not ra_bill_no:
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flash("Please enter an RA Bill Number or select 'Download All'.", "danger")
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return render_template("report.html", subcontractors=subcontractors)
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bill_gen.Fetch(RA_Bill_No=ra_bill_no, subcontractor_id=subcontractor_id)
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file_name = f"{subcontractor.subcontractor_name}_RA_{ra_bill_no}_Report.xlsx"
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if bill_gen.df_tr.empty and bill_gen.df_mh.empty and bill_gen.df_dc.empty:
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flash("No data found for this selection.", "warning")
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return render_template("report.html", subcontractors=subcontractors)
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output = io.BytesIO()
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with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
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bill_gen.df_tr.to_excel(writer, index=False, sheet_name="Tr.Ex.")
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bill_gen.df_mh.to_excel(writer, index=False, sheet_name="MH.Ex.")
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bill_gen.df_dc.to_excel(writer, index=False, sheet_name="MH & DC")
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output.seek(0)
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return send_file(output, download_name=file_name, as_attachment=True,
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mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
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return render_template("report.html", subcontractors=subcontractors)
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class ClientBill:
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def __init__(self):
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self.df_tr = pd.DataFrame()
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self.df_mh = pd.DataFrame()
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self.df_dc = pd.DataFrame()
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def Fetch(self, RA_Bill_No):
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trench = TrenchExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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mh = ManholeExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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dc = ManholeDomesticChamberClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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self.df_tr = pd.DataFrame([c.serialize() for c in trench])
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self.df_mh = pd.DataFrame([c.serialize() for c in mh])
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self.df_dc = pd.DataFrame([c.serialize() for c in dc])
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# Standardize columns for merging
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if not self.df_dc.empty and "MH_NO" in self.df_dc.columns:
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self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True)
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drop_cols = ["id", "created_at", "_sa_instance_state"]
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for df in [self.df_tr, self.df_mh, self.df_dc]:
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if not df.empty:
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df.drop(columns=drop_cols, errors="ignore", inplace=True)
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import pandas as pd
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import io
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from flask import Blueprint, render_template, request, send_file, flash
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from app.models.subcontractor_model import Subcontractor
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from app.models.manhole_excavation_model import ManholeExcavation
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from app.models.trench_excavation_model import TrenchExcavation
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from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber
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from app.models.mh_ex_client_model import ManholeExcavationClient
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from app.models.tr_ex_client_model import TrenchExcavationClient
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from app.models.mh_dc_client_model import ManholeDomesticChamberClient
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from app.utils.helpers import login_required
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# --- BLUEPRINT DEFINITION ---
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# Ensure this is unique to avoid conflicts
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file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
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class ClientBill:
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def __init__(self):
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self.df_tr = pd.DataFrame()
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self.df_mh = pd.DataFrame()
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self.df_dc = pd.DataFrame()
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def Fetch(self, RA_Bill_No):
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trench = TrenchExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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mh = ManholeExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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dc = ManholeDomesticChamberClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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self.df_tr = pd.DataFrame([c.serialize() for c in trench])
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self.df_mh = pd.DataFrame([c.serialize() for c in mh])
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self.df_dc = pd.DataFrame([c.serialize() for c in dc])
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# Standardize columns for merging
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if not self.df_dc.empty and "MH_NO" in self.df_dc.columns:
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self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True)
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drop_cols = ["id", "created_at", "_sa_instance_state"]
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for df in [self.df_tr, self.df_mh, self.df_dc]:
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if not df.empty:
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df.drop(columns=drop_cols, errors="ignore", inplace=True)
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class SubcontractorBill:
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def __init__(self):
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self.df_tr = pd.DataFrame()
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self.df_mh = pd.DataFrame()
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self.df_dc = pd.DataFrame()
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def Fetch(self, RA_Bill_No):
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trench = TrenchExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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mh = ManholeExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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dc = ManholeDomesticChamber.query.filter_by(RA_Bill_No=RA_Bill_No).all()
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self.df_tr = pd.DataFrame([c.serialize() for c in trench])
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self.df_mh = pd.DataFrame([c.serialize() for c in mh])
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self.df_dc = pd.DataFrame([c.serialize() for c in dc])
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if not self.df_dc.empty and "MH_NO" in self.df_dc.columns:
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self.df_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True)
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drop_cols = ["id", "created_at", "_sa_instance_state"]
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for df in [self.df_tr, self.df_mh, self.df_dc]:
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if not df.empty:
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df.drop(columns=drop_cols, errors="ignore", inplace=True)
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@file_report_bp.route("/client_vs_subcont", methods=["GET", "POST"])
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@login_required
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def client_vs_all_subcontractor():
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<<<<<<< HEAD
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=======
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# Initialize empty variables for the template
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tables = {"tr": None, "mh": None, "dc": None}
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ra_val = ""
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>>>>>>> 2636f2e (added client RA bill wise download report)
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if request.method == "POST":
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RA_Bill_No = request.form.get("RA_Bill_No")
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ra_val = RA_Bill_No
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if not RA_Bill_No:
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flash("Please enter RA Bill No.", "danger")
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return render_template("generate_comparison_client_vs_subcont.html")
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# ... (Keep your existing data fetching and processing logic exactly as is) ...
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clientBill = ClientBill()
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clientBill.Fetch(RA_Bill_No=RA_Bill_No)
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contractorBill = SubcontractorBill()
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contractorBill.Fetch(RA_Bill_No=RA_Bill_No)
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<<<<<<< HEAD
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# Updated QTY lists to match model fields exactly
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qty_cols = [
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"Soft_Murum_0_to_1_5_total", "Soft_Murum_1_5_to_3_0_total", "Soft_Murum_3_0_to_4_5_total",
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"Hard_Murum_0_to_1_5_total", "Hard_Murum_1_5_to_3_0_total", "Hard_Murum_3_0_to_4_5_total",
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"Soft_Rock_0_to_1_5_total", "Soft_Rock_1_5_to_3_0_total", "Soft_Rock_3_0_to_4_5_total",
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"Hard_Rock_0_to_1_5_total", "Hard_Rock_1_5_to_3_0_total", "Hard_Rock_3_0_to_4_5_total",
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"Hard_Rock_4_5_to_6_0_total", "Hard_Rock_6_0_to_7_5_total"
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]
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mh_dc_qty_cols = [
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"d_0_to_1_5", "d_1_5_to_2_0", "d_2_0_to_2_5", "d_2_5_to_3_0",
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"d_3_0_to_3_5", "d_3_5_to_4_0", "d_4_0_to_4_5", "d_4_5_to_5_0",
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"d_5_0_to_5_5", "d_5_5_to_6_0", "d_6_0_to_6_5", "Domestic_Chambers"
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]
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# Aggregate Subcontractor Data safely
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=======
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# ... (Keep all your qty_cols, mh_dc_qty_cols, and aggregate_df function) ...
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qty_cols = [...] # (Your existing list)
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mh_dc_qty_cols = [...] # (Your existing list)
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>>>>>>> 2636f2e (added client RA bill wise download report)
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def aggregate_df(df, group_cols, sum_cols):
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if df.empty: return pd.DataFrame()
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existing_cols = [c for c in sum_cols if c in df.columns]
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return df.groupby(group_cols, as_index=False)[existing_cols].sum()
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df_sub_tr_grp = aggregate_df(contractorBill.df_tr, ["Location", "MH_NO"], qty_cols)
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df_sub_mh_grp = aggregate_df(contractorBill.df_mh, ["Location", "MH_NO"], qty_cols)
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df_sub_dc_grp = aggregate_df(contractorBill.df_dc, ["Location", "Node_No"], mh_dc_qty_cols)
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<<<<<<< HEAD
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# Merge and Calculate Difference
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=======
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>>>>>>> 2636f2e (added client RA bill wise download report)
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df_tr_cmp = clientBill.df_tr.merge(df_sub_tr_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
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df_mh_cmp = clientBill.df_mh.merge(df_sub_mh_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
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df_dc_cmp = clientBill.df_dc.merge(df_sub_dc_grp, on=["Location", "Node_No"], how="left", suffixes=("_Client", "_Sub"))
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<<<<<<< HEAD
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# Calculate Diffs
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=======
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>>>>>>> 2636f2e (added client RA bill wise download report)
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for df in [df_tr_cmp, df_mh_cmp]:
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for col in qty_cols:
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if f"{col}_Client" in df.columns:
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df[f"{col}_Diff"] = df[f"{col}_Client"].fillna(0) - df[f"{col}_Sub"].fillna(0)
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for col in mh_dc_qty_cols:
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if f"{col}_Client" in df_dc_cmp.columns:
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df_dc_cmp[f"{col}_Diff"] = df_dc_cmp[f"{col}_Client"].fillna(0) - df_dc_cmp[f"{col}_Sub"].fillna(0)
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<<<<<<< HEAD
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output = io.BytesIO()
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file_name = f"Comparison_RA_Bill_{RA_Bill_No}.xlsx"
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with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
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df_tr_cmp.to_excel(writer, sheet_name="Tr.Ex Comparison", index=False)
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df_mh_cmp.to_excel(writer, sheet_name="Mh.Ex Comparison", index=False)
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df_dc_cmp.to_excel(writer, sheet_name="MH & DC Comparison", index=False)
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output.seek(0)
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return send_file(output, download_name=file_name, as_attachment=True, mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
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return render_template("generate_comparison_client_vs_subcont.html")
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=======
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# ACTION LOGIC: Check if user clicked "Download" or just "Preview/Generate"
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if request.form.get("action") == "download":
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output = io.BytesIO()
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file_name = f"Comparison_RA_Bill_{RA_Bill_No}.xlsx"
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with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
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df_tr_cmp.to_excel(writer, sheet_name="Tr.Ex Comparison", index=False)
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df_mh_cmp.to_excel(writer, sheet_name="Mh.Ex Comparison", index=False)
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df_dc_cmp.to_excel(writer, sheet_name="MH & DC Comparison", index=False)
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output.seek(0)
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return send_file(output, download_name=file_name, as_attachment=True, mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
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# If not downloading, convert DFs to HTML for the UI
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tables["tr"] = df_tr_cmp.to_html(classes='table table-striped table-hover table-sm', index=False)
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tables["mh"] = df_mh_cmp.to_html(classes='table table-striped table-hover table-sm', index=False)
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tables["dc"] = df_dc_cmp.to_html(classes='table table-striped table-hover table-sm', index=False)
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return render_template("generate_comparison_client_vs_subcont.html", tables=tables, ra_val=ra_val)
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>>>>>>> 2636f2e (added client RA bill wise download report)
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