Files
Comparison_Project/app/routes/file_report.py

130 lines
5.5 KiB
Python

from flask import Blueprint, render_template, request, send_file, flash
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 import db
import pandas as pd
import io
file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
@file_report_bp.route("/report", methods=["GET", "POST"])
def report_file():
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("report.html", subcontractors=subcontractors)
# Fetch subcontractor for file name
subcontractor = Subcontractor.query.get(subcontractor_id)
manhole_excavation = ManholeExcavation.query.filter_by(subcontractor_id=subcontractor_id).all()
trench_excavation = TrenchExcavation.query.filter_by(subcontractor_id=subcontractor_id).all()
domestic_chamber = ManholeDomesticChamber.query.filter_by(subcontractor_id=subcontractor_id).all()
# Convert to DataFrame
df_mh_exc = pd.DataFrame([m.__dict__ for m in manhole_excavation])
df_trench = pd.DataFrame([t.__dict__ for t in trench_excavation])
df_domestic = pd.DataFrame([d.__dict__ for d in domestic_chamber])
# Drop unnecessary SQLAlchemy fields
drop_cols = ["id", "subcontractor_id", "created_at", "_sa_instance_state","Remarks"]
df_mh_exc.drop(columns=drop_cols, errors="ignore", inplace=True)
df_trench.drop(columns=drop_cols, errors="ignore", inplace=True)
df_domestic.drop(columns=drop_cols, errors="ignore", inplace=True)
mh_exc_columns = [
"Location", "MH_NO", "Upto_IL_Depth", "Cutting_Depth", "ID_of_MH_m",
"Ex_Dia_of_Manhole", "Area_of_Manhole",
"Soft_Murum_0_to_1_5", "Soft_Murum_1_5_to_3_0", "Soft_Murum_3_0_to_4_5",
"Hard_Murum_0_to_1_5", "Hard_Murum_1_5_to_3_0",
"Soft_Rock_0_to_1_5", "Soft_Rock_1_5_to_3_0",
"Hard_Rock_0_to_1_5", "Hard_Rock_1_5_to_3_0",
"Hard_Rock_3_0_to_4_5", "Hard_Rock_4_5_to_6_0", "Hard_Rock_6_0_to_7_5",
"Soft_Murum_0_to_1_5_total", "Soft_Murum_1_5_to_3_0_total",
"Soft_Murum_3_0_to_4_5_total",
"Hard_Murum_0_to_1_5_total", "Hard_Murum_1_5_and_above_total",
"Soft_Rock_0_to_1_5_total", "Soft_Rock_1_5_and_above_total",
"Hard_Rock_0_to_1_5_total", "Hard_Rock_1_5_and_above_total",
"Hard_Rock_3_0_to_4_5_total", "Hard_Rock_4_5_to_6_0_total",
"Hard_Rock_6_0_to_7_5_total",
"Remarks", "Total"
]
trench_columns = [
"Location", "MH_NO", "CC_length", "Invert_Level", "MH_Top_Level",
"Ground_Level", "ID_of_MH_m", "Actual_Trench_Length", "Pipe_Dia_mm",
"Width_0_to_2_5", "Width_2_5_to_3_0", "Width_3_0_to_4_5", "Width_4_5_to_6_0",
"Upto_IL_Depth", "Cutting_Depth", "Avg_Depth",
"Soft_Murum_0_to_1_5", "Soft_Murum_1_5_to_3_0", "Soft_Murum_3_0_to_4_5",
"Hard_Murum_0_to_1_5", "Hard_Murum_1_5_to_3_0",
"Soft_Rock_0_to_1_5", "Soft_Rock_1_5_to_3_0",
"Hard_Rock_0_to_1_5", "Hard_Rock_1_5_to_3_0",
"Hard_Rock_3_0_to_4_5", "Hard_Rock_4_5_to_6_0", "Hard_Rock_6_0_to_7_5",
"Soft_Murum_0_to_1_5_total", "Soft_Murum_1_5_to_3_0_total",
"Soft_Murum_3_0_to_4_5_total",
"Hard_Murum_0_to_1_5_total", "Hard_Murum_1_5_and_above_total",
"Soft_Rock_0_to_1_5_total", "Soft_Rock_1_5_and_above_total",
"Hard_Rock_0_to_1_5_total", "Hard_Rock_1_5_and_above_total",
"Hard_Rock_3_0_to_4_5_total", "Hard_Rock_4_5_to_6_0_total",
"Hard_Rock_6_0_to_7_5_total",
"Remarks", "Total"
]
domestic_columns = [
"Location", "Node_No", "Depth_of_MH",
"d_0_to_0_75", "d_1_06_to_1_65", "d_1_66_to_2_15",
"d_2_16_to_2_65", "d_2_66_to_3_15", "d_3_16_to_3_65",
"d_3_66_to_4_15", "d_4_16_to_4_65", "d_4_66_to_5_15",
"d_5_16_to_5_65", "d_5_66_to_6_15", "d_6_16_to_6_65",
"d_6_66_to_7_15", "d_7_16_to_7_65", "d_7_66_to_8_15",
"d_8_16_to_8_65", "d_8_66_to_9_15", "d_9_16_to_9_65",
"Domestic_Chambers"
]
# Reorder columns serial wise
df_mh_exc = df_mh_exc.reindex(columns=mh_exc_columns, fill_value="")
df_trench = df_trench.reindex(columns=trench_columns, fill_value="")
df_domestic = df_domestic.reindex(columns=domestic_columns, fill_value="")
# WRITE EXCEL FILE
output = io.BytesIO()
file_name = f"{subcontractor.subcontractor_name}_Report.xlsx"
with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
df_trench.to_excel(writer, index=False, sheet_name="Tr.Ex.")
df_mh_exc.to_excel(writer, index=False, sheet_name="MH.Ex.")
df_domestic.to_excel(writer, index=False, sheet_name="MH & DC")
output.seek(0)
return send_file(
output,
download_name=file_name,
as_attachment=True,
mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
return render_template("report.html", subcontractors=subcontractors)