213 lines
9.8 KiB
Python
213 lines
9.8 KiB
Python
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.utils.helpers import login_required
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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.laying_model import Laying
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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.models.laying_client_model import LayingClient
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# --- BLUEPRINT DEFINITION ---
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file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
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# --- Client class ---
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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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self.df_laying = 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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lay = LayingClient.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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self.df_laying = pd.DataFrame([c.serialize() for c in lay])
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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, self.df_laying]:
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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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# --- Subcontractor class ---
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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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self.df_laying = pd.DataFrame()
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def Fetch(self, RA_Bill_No=None, subcontractor_id=None):
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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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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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lay = Laying.query.filter_by(**filters).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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self.df_laying = pd.DataFrame([c.serialize() for c in lay])
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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, self.df_laying]:
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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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# --- subcontractor report only ---
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@file_report_bp.route("/Subcontractor_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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tables = None
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selected_sc_id = None
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ra_bill_no = None
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download_all = False
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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"
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action = request.form.get("action")
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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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bill_gen.Fetch(subcontractor_id=subcontractor_id)
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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.", "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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# If download is clicked, return file immediately
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if action == "download":
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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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bill_gen.df_laying.to_excel(writer, index=False, sheet_name="Laying")
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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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# We add bootstrap classes directly to the pandas output
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table_classes = "table table-bordered table-striped table-hover table-sm mb-0"
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tables = {
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"tr": bill_gen.df_tr.to_html(classes=table_classes, index=False),
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"mh": bill_gen.df_mh.to_html(classes=table_classes, index=False),
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"dc": bill_gen.df_dc.to_html(classes=table_classes, index=False),
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"laying": bill_gen.df_laying.to_html(classes=table_classes, index=False)
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}
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selected_sc_id = subcontractor_id
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return render_template(
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"subcontractor_report.html",
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subcontractors=subcontractors,
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tables=tables,
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selected_sc_id=selected_sc_id,
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ra_bill_no=ra_bill_no,
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download_all=download_all
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)
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# --- client report only ---
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@file_report_bp.route("/client_report", methods=["GET", "POST"])
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@login_required
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def client_vs_all_subcontractor():
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tables = {"tr": None, "mh": None, "dc": None}
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ra_val = ""
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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", tables=tables, ra_val=ra_val)
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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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# --- SAFETY CHECK: Verify data exists before merging ---
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if clientBill.df_tr.empty and clientBill.df_mh.empty:
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flash(f"No Client records found for RA Bill {RA_Bill_No}", "warning")
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return render_template("generate_comparison_client_vs_subcont.html", tables=tables, ra_val=ra_val)
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qty_cols = [...] # (Keep your existing list)
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mh_dc_qty_cols = [...] # (Keep your existing list)
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mh_lay_qty_cols =[...]
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def aggregate_df(df, group_cols, sum_cols):
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if df.empty:
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# Create an empty DF with the correct columns to avoid Merge/Key Errors
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return pd.DataFrame(columns=group_cols + sum_cols)
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existing_cols = [c for c in sum_cols if c in df.columns]
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# Ensure group_cols exist in the DF
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for col in group_cols:
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if col not in df.columns:
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df[col] = "N/A" # Fill missing join keys
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return df.groupby(group_cols, as_index=False)[existing_cols].sum()
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# Aggregate data
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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", "MH_NO"], mh_dc_qty_cols)
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df_sub_lay_grp = aggregate_df(contractorBill.df_dc, ["Location", "MH_NO"], mh_lay_qty_cols)
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# --- FINAL MERGE LOGIC ---
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# We check if "Location" exists in the client data. If not, we add it to prevent the KeyError.
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for df_client in [clientBill.df_tr, clientBill.df_mh, clientBill.df_dc, clientBill.df_laying ]:
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if not df_client.empty and "Location" not in df_client.columns:
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df_client["Location"] = "Unknown"
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try:
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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", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
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df_lay_cmp = clientBill.df_laying.merge(df_sub_lay_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
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except KeyError as e:
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flash(f"Merge Error: Missing column {str(e)}. Check if 'Location' is defined in your database models.", "danger")
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return render_template("generate_comparison_client_vs_subcont.html", tables=tables, ra_val=ra_val)
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# Convert to HTML for preview
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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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tables["laying"] = df_lay_cmp.to_html(classes='table table-striped table-hover table-sm', index=False)
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return render_template("client_report.html", tables=tables, ra_val=ra_val)
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