222 lines
10 KiB
Python
222 lines
10 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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# Initialize as empty DataFrames so .to_excel() always exists
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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, subcontractor_id):
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# Query data filtered by both Bill No and Subcontractor ID
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trench = TrenchExcavation.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all()
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mh = ManholeExcavation.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all()
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dc = ManholeDomesticChamber.query.filter_by(RA_Bill_No=RA_Bill_No, subcontractor_id=subcontractor_id).all()
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# Convert SQL objects to DataFrames
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self.df_tr = pd.DataFrame([c.__dict__ for c in trench])
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self.df_mh = pd.DataFrame([c.__dict__ for c in mh])
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self.df_dc = pd.DataFrame([c.__dict__ for c in dc])
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# Clean Columns (remove SQLAlchemy internal state)
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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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# --- 3. DEFINE ROUTES ---
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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") # Collected from the updated HTML
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if not subcontractor_id or not ra_bill_no:
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flash("Please select a subcontractor and enter an RA Bill Number.", "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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# Instantiate and Fetch Data
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bill_gen = SubcontractorBill()
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bill_gen.Fetch(RA_Bill_No=ra_bill_no, subcontractor_id=subcontractor_id)
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# Check if any data was found
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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(f"No data found for {subcontractor.subcontractor_name} in RA Bill {ra_bill_no}", "warning")
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return render_template("report.html", subcontractors=subcontractors)
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# WRITE EXCEL FILE
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output = io.BytesIO()
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file_name = f"{subcontractor.subcontractor_name}_RA_{ra_bill_no}_Report.xlsx"
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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(
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output,
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download_name=file_name,
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as_attachment=True,
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mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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)
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return render_template("report.html", subcontractors=subcontractors)
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# (ClientBill class and client_vs_all_subcontractor route would follow here...)
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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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if request.method == "POST":
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RA_Bill_No = request.form.get("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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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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# 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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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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# Merge and Calculate Difference
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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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# Calculate Diffs
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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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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") |