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@@ -144,70 +144,87 @@ def report_file():
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@file_report_bp.route("/client_report", methods=["GET", "POST"])
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@file_report_bp.route("/client_report", methods=["GET", "POST"])
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@login_required
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@login_required
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def client_vs_all_subcontractor():
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def client_vs_all_subcontractor():
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tables = {"tr": None, "mh": None, "dc": None}
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# Initialize dictionary keys to match HTML variables
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tables = {"tr": None, "mh": None, "dc": None, "laying": None}
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ra_val = ""
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ra_val = ""
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if request.method == "POST":
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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_Bill_No = request.form.get("RA_Bill_No")
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action = request.form.get("action") # Identify if 'download' or 'preview'
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ra_val = 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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if not RA_Bill_No:
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flash("Please enter RA Bill No.", "danger")
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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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return render_template("client_report.html", tables=tables, ra_val=ra_val)
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clientBill = ClientBill()
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clientBill = ClientBill()
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clientBill.Fetch(RA_Bill_No=RA_Bill_No)
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clientBill.Fetch(RA_Bill_No=RA_Bill_No)
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contractorBill = SubcontractorBill()
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contractorBill = SubcontractorBill()
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contractorBill.Fetch(RA_Bill_No=RA_Bill_No)
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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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# Safety Check: Verify if data exists
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if clientBill.df_tr.empty and clientBill.df_mh.empty:
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if clientBill.df_tr.empty and clientBill.df_mh.empty and clientBill.df_laying.empty:
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flash(f"No Client records found for RA Bill {RA_Bill_No}", "warning")
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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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return render_template("client_report.html", tables=tables, ra_val=ra_val)
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qty_cols = [...] # (Keep your existing list)
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# Define columns based on your model field names
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mh_dc_qty_cols = [...] # (Keep your existing list)
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qty_cols = [
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mh_lay_qty_cols =[...]
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"pipe_150_mm", "pipe_200_mm", "pipe_250_mm", "pipe_300_mm",
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"pipe_350_mm", "pipe_400_mm", "pipe_450_mm", "pipe_500_mm",
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"pipe_600_mm", "pipe_700_mm", "pipe_900_mm", "pipe_1200_mm"
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]
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mh_dc_qty_cols = ["qty", "total"] # Update these based on your DC model fields
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mh_lay_qty_cols = qty_cols + ["Laying_Length", "CC_length"]
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def aggregate_df(df, group_cols, sum_cols):
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def aggregate_df(df, group_cols, sum_cols):
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if df.empty:
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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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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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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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for col in group_cols:
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if col not in df.columns:
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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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df[col] = "N/A"
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return df.groupby(group_cols, as_index=False)[existing_cols].sum()
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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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# Aggregate data from Subcontractor tables
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df_sub_tr_grp = aggregate_df(contractorBill.df_tr, ["Location", "MH_NO"], qty_cols)
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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_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_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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# FIXED: Aggregating from .df_laying
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df_sub_lay_grp = aggregate_df(contractorBill.df_laying, ["Location", "MH_NO"], mh_lay_qty_cols)
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# --- FINAL MERGE LOGIC ---
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# Standardize "Location" column to prevent merge keys being missing
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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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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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if not df_client.empty and "Location" not in df_client.columns:
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df_client["Location"] = "Unknown"
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df_client["Location"] = "Unknown"
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try:
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try:
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# Final Merge for Comparison
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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_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_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_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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df_lay_cmp = clientBill.df_laying.merge(df_sub_lay_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
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# --- EXCEL DOWNLOAD LOGIC ---
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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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df_tr_cmp.to_excel(writer, index=False, sheet_name="Tr.Ex ")
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df_mh_cmp.to_excel(writer, index=False, sheet_name="Mh.Ex ")
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df_dc_cmp.to_excel(writer, index=False, sheet_name="DC ")
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df_lay_cmp.to_excel(writer, index=False, sheet_name="Laying and Bedding")
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output.seek(0)
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file_name = f"Client_Comparison_RA_{RA_Bill_No}.xlsx"
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return send_file(output, download_name=file_name, as_attachment=True)
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# --- PREVIEW HTML LOGIC ---
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table_classes = 'table table-striped table-hover table-sm border shadow-sm'
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tables["tr"] = df_tr_cmp.to_html(classes=table_classes, index=False)
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tables["mh"] = df_mh_cmp.to_html(classes=table_classes, index=False)
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tables["dc"] = df_dc_cmp.to_html(classes=table_classes, index=False)
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tables["laying"] = df_lay_cmp.to_html(classes=table_classes, index=False)
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except KeyError as e:
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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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flash(f"Merge Error: Missing column {str(e)}", "danger")
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return render_template("client_report.html", tables=tables, ra_val=ra_val)
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return render_template("client_report.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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return render_template("client_report.html", tables=tables, ra_val=ra_val)
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