Comparison_Project/app/routes/file_report.py

import pandas as pd
import io
from flask import Blueprint, render_template, request, send_file, flash
from app.utils.helpers import login_required

from app.models.subcontractor_model import Subcontractor

from app.models.manhole_excavation_model import ManholeExcavation
from app.models.trench_excavation_model import TrenchExcavation
from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber
from app.models.laying_model import Laying

from app.models.mh_ex_client_model import ManholeExcavationClient
from app.models.tr_ex_client_model import TrenchExcavationClient
from app.models.mh_dc_client_model import ManholeDomesticChamberClient
from app.models.laying_client_model import LayingClient

 
# --- BLUEPRINT DEFINITION ---
file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
 
# --- Client class ---
class ClientBill:
    def __init__(self):
        self.df_tr = pd.DataFrame()
        self.df_mh = pd.DataFrame()
        self.df_dc = pd.DataFrame()
        self.df_laying = pd.DataFrame()
 
    def Fetch(self, RA_Bill_No):
        trench = TrenchExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
        mh = ManholeExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
        dc = ManholeDomesticChamberClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
        lay = LayingClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
 
        self.df_tr = pd.DataFrame([c.serialize() for c in trench])
        self.df_mh = pd.DataFrame([c.serialize() for c in mh])
        self.df_dc = pd.DataFrame([c.serialize() for c in dc])
        self.df_laying = pd.DataFrame([c.serialize() for c in lay])
  
        drop_cols = ["id", "created_at", "_sa_instance_state"]
        for df in [self.df_tr, self.df_mh, self.df_dc, self.df_laying]:
            if not df.empty:
                df.drop(columns=drop_cols, errors="ignore", inplace=True)
 
# --- Subcontractor class ---
class SubcontractorBill:
    def __init__(self):
        self.df_tr = pd.DataFrame()
        self.df_mh = pd.DataFrame()
        self.df_dc = pd.DataFrame()
        self.df_laying = pd.DataFrame()
 
    def Fetch(self, RA_Bill_No=None, subcontractor_id=None):
        filters = {}
        if subcontractor_id:
            filters["subcontractor_id"] = subcontractor_id
        if RA_Bill_No:
            filters["RA_Bill_No"] = RA_Bill_No
 
        trench = TrenchExcavation.query.filter_by(**filters).all()
        mh = ManholeExcavation.query.filter_by(**filters).all()
        dc = ManholeDomesticChamber.query.filter_by(**filters).all()
        lay = Laying.query.filter_by(**filters).all()
 
        self.df_tr = pd.DataFrame([c.serialize() for c in trench])
        self.df_mh = pd.DataFrame([c.serialize() for c in mh])
        self.df_dc = pd.DataFrame([c.serialize() for c in dc])
        self.df_laying = pd.DataFrame([c.serialize() for c in lay])
  
        drop_cols = ["id", "created_at", "_sa_instance_state"]
        for df in [self.df_tr, self.df_mh, self.df_dc, self.df_laying]:
            if not df.empty:
                df.drop(columns=drop_cols, errors="ignore", inplace=True)
 
# --- subcontractor report only  ---
@file_report_bp.route("/Subcontractor_report", methods=["GET", "POST"])
@login_required
def report_file():
    subcontractors = Subcontractor.query.all()
    tables = None 
    selected_sc_id = None
    ra_bill_no = None
    download_all = False
 
    if request.method == "POST":
        subcontractor_id = request.form.get("subcontractor_id")
        ra_bill_no = request.form.get("ra_bill_no")
        download_all = request.form.get("download_all") == "true"
        action = request.form.get("action")
 
        if not subcontractor_id:
            flash("Please select a subcontractor.", "danger")
            return render_template("report.html", subcontractors=subcontractors)
 
        subcontractor = Subcontractor.query.get(subcontractor_id)
        bill_gen = SubcontractorBill()
 
        if download_all:
            bill_gen.Fetch(subcontractor_id=subcontractor_id)
            file_name = f"{subcontractor.subcontractor_name}_ALL_BILLS.xlsx"
        else:
            if not ra_bill_no:
                flash("Please enter an RA Bill Number.", "danger")
                return render_template("report.html", subcontractors=subcontractors)
            bill_gen.Fetch(RA_Bill_No=ra_bill_no, subcontractor_id=subcontractor_id)
            file_name = f"{subcontractor.subcontractor_name}_RA_{ra_bill_no}_Report.xlsx"
 
        if bill_gen.df_tr.empty and bill_gen.df_mh.empty and bill_gen.df_dc.empty:
            flash("No data found for this selection.", "warning")
            return render_template("report.html", subcontractors=subcontractors)
 
        # If download is clicked, return file immediately
        if action == "download":
            output = io.BytesIO()
            with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
                bill_gen.df_tr.to_excel(writer, index=False, sheet_name="Tr.Ex.")
                bill_gen.df_mh.to_excel(writer, index=False, sheet_name="MH.Ex.")
                bill_gen.df_dc.to_excel(writer, index=False, sheet_name="MH & DC")
                bill_gen.df_laying.to_excel(writer, index=False, sheet_name="Laying")
            output.seek(0)
            return send_file(output, download_name=file_name, as_attachment=True)
 
        # We add bootstrap classes directly to the pandas output
        table_classes = "table table-bordered table-striped table-hover table-sm mb-0"
        tables = {
            "tr": bill_gen.df_tr.to_html(classes=table_classes, index=False),
            "mh": bill_gen.df_mh.to_html(classes=table_classes, index=False),
            "dc": bill_gen.df_dc.to_html(classes=table_classes, index=False),
            "laying": bill_gen.df_laying.to_html(classes=table_classes, index=False)
        }
        selected_sc_id = subcontractor_id
 
    return render_template(
        "subcontractor_report.html",
        subcontractors=subcontractors,
        tables=tables,
        selected_sc_id=selected_sc_id,
        ra_bill_no=ra_bill_no,
        download_all=download_all
    )
 
# --- client report only --- 
@file_report_bp.route("/client_report", methods=["GET", "POST"])
@login_required
def client_vs_all_subcontractor():
    # Initialize dictionary keys to match HTML variables
    tables = {"tr": None, "mh": None, "dc": None, "laying": None}
    ra_val = ""

    if request.method == "POST":
        RA_Bill_No = request.form.get("RA_Bill_No")
        action = request.form.get("action")  # Identify if 'download' or 'preview'
        ra_val = RA_Bill_No

        if not RA_Bill_No:
            flash("Please enter RA Bill No.", "danger")
            return render_template("client_report.html", tables=tables, ra_val=ra_val)

        clientBill = ClientBill()
        clientBill.Fetch(RA_Bill_No=RA_Bill_No)
        contractorBill = SubcontractorBill()
        contractorBill.Fetch(RA_Bill_No=RA_Bill_No)

        # Safety Check: Verify if data exists
        if clientBill.df_tr.empty and clientBill.df_mh.empty and clientBill.df_laying.empty:
            flash(f"No Client records found for RA Bill {RA_Bill_No}", "warning")
            return render_template("client_report.html", tables=tables, ra_val=ra_val)

        # Define columns based on your model field names
        qty_cols = [
            "pipe_150_mm", "pipe_200_mm", "pipe_250_mm", "pipe_300_mm", 
            "pipe_350_mm", "pipe_400_mm", "pipe_450_mm", "pipe_500_mm", 
            "pipe_600_mm", "pipe_700_mm", "pipe_900_mm", "pipe_1200_mm"
        ]
        mh_dc_qty_cols = ["qty", "total"]  # Update these based on your DC model fields
        mh_lay_qty_cols = qty_cols + ["Laying_Length", "CC_length"]

        def aggregate_df(df, group_cols, sum_cols):
            if df.empty:
                return pd.DataFrame(columns=group_cols + sum_cols)
            existing_cols = [c for c in sum_cols if c in df.columns]
            for col in group_cols:
                if col not in df.columns:
                    df[col] = "N/A"
            return df.groupby(group_cols, as_index=False)[existing_cols].sum()

        # Aggregate data from Subcontractor tables
        df_sub_tr_grp = aggregate_df(contractorBill.df_tr, ["Location", "MH_NO"], qty_cols)
        df_sub_mh_grp = aggregate_df(contractorBill.df_mh, ["Location", "MH_NO"], qty_cols)
        df_sub_dc_grp = aggregate_df(contractorBill.df_dc, ["Location", "MH_NO"], mh_dc_qty_cols)
        # FIXED: Aggregating from .df_laying
        df_sub_lay_grp = aggregate_df(contractorBill.df_laying, ["Location", "MH_NO"], mh_lay_qty_cols)

        # Standardize "Location" column to prevent merge keys being missing
        for df_client in [clientBill.df_tr, clientBill.df_mh, clientBill.df_dc, clientBill.df_laying]:
            if not df_client.empty and "Location" not in df_client.columns:
                df_client["Location"] = "Unknown"

        try:
            # Final Merge for Comparison
            df_tr_cmp = clientBill.df_tr.merge(df_sub_tr_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
            df_mh_cmp = clientBill.df_mh.merge(df_sub_mh_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
            df_dc_cmp = clientBill.df_dc.merge(df_sub_dc_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))
            df_lay_cmp = clientBill.df_laying.merge(df_sub_lay_grp, on=["Location", "MH_NO"], how="left", suffixes=("_Client", "_Sub"))

            # --- EXCEL DOWNLOAD LOGIC ---
            if action == "download":
                output = io.BytesIO()
                with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
                    df_tr_cmp.to_excel(writer, index=False, sheet_name="Tr.Ex ")
                    df_mh_cmp.to_excel(writer, index=False, sheet_name="Mh.Ex ")
                    df_dc_cmp.to_excel(writer, index=False, sheet_name="DC ")
                    df_lay_cmp.to_excel(writer, index=False, sheet_name="Laying and Bedding")
                output.seek(0)
                file_name = f"Client_Comparison_RA_{RA_Bill_No}.xlsx"
                return send_file(output, download_name=file_name, as_attachment=True)

            # --- PREVIEW HTML LOGIC ---
            table_classes = 'table table-striped table-hover table-sm border shadow-sm'
            tables["tr"] = df_tr_cmp.to_html(classes=table_classes, index=False)
            tables["mh"] = df_mh_cmp.to_html(classes=table_classes, index=False)
            tables["dc"] = df_dc_cmp.to_html(classes=table_classes, index=False)
            tables["laying"] = df_lay_cmp.to_html(classes=table_classes, index=False)

        except KeyError as e:
            flash(f"Merge Error: Missing column {str(e)}", "danger")
            return render_template("client_report.html", tables=tables, ra_val=ra_val)

    return render_template("client_report.html", tables=tables, ra_val=ra_val)