Comparison_Project/app/routes/generate_comparison_report.py

from flask import Blueprint, render_template, request, send_file, flash
from app.models.subcontractor_model import Subcontractor

from app.models.trench_excavation_model import TrenchExcavation
from app.models.tr_ex_client_model import TrenchExcavationClient
from app import db

import pandas as pd
import io

generate_report_bp = Blueprint("generate_report", __name__, url_prefix="/report")



@generate_report_bp.route("/comparison_report", methods=["GET", "POST"])
def comparison_report():
    subcontractors = Subcontractor.query.all()

    if request.method == "POST":
        subcontractor_id = request.form.get("subcontractor_id")

        if not subcontractor_id:
            flash("Please select a subcontractor.", "danger")
            return render_template("generate_comparison_report.html", subcontractors=subcontractors)

        subcontractor = Subcontractor.query.get_or_404(subcontractor_id)

        # Fetch data
        contractor_rows = TrenchExcavation.query.filter_by(subcontractor_id=subcontractor_id).all()
        client_rows = TrenchExcavationClient.query.filter_by(subcontractor_id=subcontractor_id).all()

       

        diff_rows = []

        for row1, row2 in zip(client_rows, contractor_rows):

            total1 = (
                (row1.Marshi_Muddy_Slushy_0_to_1_5_total or 0) +
                (row1.Marshi_Muddy_Slushy_1_5_to_3_0_total or 0) +
                (row1.Marshi_Muddy_Slushy_3_0_to_4_5_total or 0) +
                (row1.Soft_Murum_0_to_1_5_total or 0) +
                (row1.Soft_Murum_1_5_to_3_0_total or 0) +
                (row1.Soft_Murum_3_0_to_4_5_total or 0) +
                (row1.Hard_Murum_0_to_1_5_total or 0) +
                (row1.Hard_Murum_1_5_to_3_0_total or 0) +
                (row1.Hard_Murum_3_0_to_4_5_total or 0) +
                (row1.Soft_Rock_0_to_1_5_total or 0) +
                (row1.Soft_Rock_1_5_to_3_0_total or 0) +
                (row1.Soft_Rock_3_0_to_4_5_total or 0) +
                (row1.Hard_Rock_0_to_1_5_total or 0) +
                (row1.Hard_Rock_1_5_to_3_0_total or 0) +
                (row1.Hard_Rock_3_0_to_4_5_total or 0) +
                (row1.Hard_Rock_4_5_to_6_0_total or 0) +
                (row1.Hard_Rock_6_0_to_7_5_total or 0)
            )

            total2 = (
                (row2.Soft_Murum_0_to_1_5_total or 0) +
                (row2.Soft_Murum_1_5_to_3_0_total or 0) +
                (row2.Soft_Murum_3_0_to_4_5_total or 0) +
                (row2.Hard_Murum_0_to_1_5_total or 0) +
                (row2.Hard_Murum_1_5_and_above_total or 0) +
                (row2.Soft_Rock_0_to_1_5_total or 0) +
                (row2.Soft_Rock_1_5_and_above_total or 0) +
                (row2.Hard_Rock_0_to_1_5_total or 0) +
                (row2.Hard_Rock_1_5_and_above_total or 0) +
                (row2.Hard_Rock_4_5_to_6_0_total or 0) +
                (row2.Hard_Rock_6_0_to_7_5_total or 0)
            )

            diff = total1 - total2

            # ---- store for excel ----
            diff_rows.append({
                "Location": row1.Location,
                "Node No": row1.MH_NO,
                "Client Sum": round(total1, 2),
                "Subcontractor Sum": round(total2, 2),
                "Diff": round(diff, 2)
            })

            # optional console print
            print(
                f"Location : {row1.Location} | "
                f"MH_NO : {row1.MH_NO} | "
                f"Client : {total1} | "
                f"Sub : {total2} | "
                f"Diff : {diff}"
            )



        # Convert to DataFrame
        df_contractor = pd.DataFrame([r.__dict__ for r in contractor_rows])
        df_client = pd.DataFrame([r.__dict__ for r in client_rows])
        df_diff = pd.DataFrame(diff_rows, columns=["Location", "Node No", "Client Sum", "Subcontractor Sum", "Diff"])


        # Drop unwanted columns
        drop_cols = ["id", "subcontractor_id", "created_at", "_sa_instance_state", "Remarks"]
        df_contractor.drop(columns=drop_cols, errors="ignore", inplace=True)
        df_client.drop(columns=drop_cols, errors="ignore", inplace=True)

        # Convert to numeric
        df_contractor = df_contractor.apply(pd.to_numeric, errors="coerce").fillna(0)
        df_client = df_client.apply(pd.to_numeric, errors="coerce").fillna(0)

        
        # EXPORT EXCEL
        output = io.BytesIO()
        file_name = f"{subcontractor.subcontractor_name}_Comparison_Report.xlsx"

        with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
            df_contractor.to_excel(writer, index=False, sheet_name="Contractor_Data")
            df_client.to_excel(writer, index=False, sheet_name="Client_Data")
            df_diff.to_excel(writer, index=False, sheet_name="Diff")
            
           

        output.seek(0)

        return send_file(
            output,
            as_attachment=True,
            download_name=file_name,
            mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
        )

    return render_template("generate_comparison_report.html", subcontractors=subcontractors)