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pjpatil12
2025-12-23 19:40:41 +05:30
parent 54c3b8f160
commit 7cb01bd9fb
3 changed files with 206 additions and 3 deletions
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161
app/routes/file_report.py
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@@ -3,6 +3,10 @@ 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.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 import db
import pandas as pd
@@ -10,7 +14,7 @@ import io
file_report_bp = Blueprint("file_report", __name__, url_prefix="/file")
# get report by contractor id and dowanload
@file_report_bp.route("/report", methods=["GET", "POST"])
def report_file():
subcontractors = Subcontractor.query.all()
@@ -127,3 +131,158 @@ def report_file():
return render_template("report.html", subcontractors=subcontractors)
@file_report_bp.route("/client_vs_subcont", methods=["GET", "POST"])
def client_vs_all_subcontractor():
if request.method == "POST":
RA_Bill_No = request.form.get("RA_Bill_No")
if not RA_Bill_No:
flash("Please select RA Bill No.", "danger")
return render_template("generate_comparison_client_vs_subcont.html")
# CLIENT DATA (RA BILL WISE)
client_trench = TrenchExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
client_mh = ManholeExcavationClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
client_dc = ManholeDomesticChamberClient.query.filter_by(RA_Bill_No=RA_Bill_No).all()
df_client_tr = pd.DataFrame([c.__dict__ for c in client_trench])
df_client_mh = pd.DataFrame([c.__dict__ for c in client_mh])
df_client_dc = pd.DataFrame([c.__dict__ for c in client_dc])
# ALL SUBCONTRACTOR DATA
sub_trench = TrenchExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all()
sub_mh = ManholeExcavation.query.filter_by(RA_Bill_No=RA_Bill_No).all()
sub_dc = ManholeDomesticChamber.query.filter_by(RA_Bill_No=RA_Bill_No).all()
df_sub_tr = pd.DataFrame([s.__dict__ for s in sub_trench])
df_sub_mh = pd.DataFrame([s.__dict__ for s in sub_mh])
df_sub_dc = pd.DataFrame([s.__dict__ for s in sub_dc])
# CLEAN COLUMNS
drop_cols = ["id","created_at","Remarks","_sa_instance_state"]
for df in [df_client_tr, df_client_mh, df_client_dc,df_sub_tr, df_sub_mh, df_sub_dc]:
if not df.empty:
df.drop(columns=drop_cols, errors="ignore", inplace=True)
# GROUP SUBCONTRACTOR DATA
qty_cols = [
"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_to_3_0_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"
]
mh_dc_qty_cols = [
"d_0_to_0_75",
"d_0_76_to_1_05",
"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"
]
df_sub_tr_grp = (df_sub_tr.groupby(["Location", "MH_NO"], as_index=False)[qty_cols].sum())
df_sub_mh_grp = (df_sub_mh.groupby(["Location", "MH_NO"], as_index=False)[qty_cols].sum())
df_sub_dc_grp = (df_sub_dc.groupby(["Location", "Node_No"], as_index=False)[mh_dc_qty_cols].sum())
# MERGE CLIENT VS SUBCONTRACTOR
df_tr_cmp = df_client_tr.merge(
df_sub_tr_grp,
on=["Location", "MH_NO"],
how="left",
suffixes=("_Client", "_Sub")
)
df_mh_cmp = df_client_mh.merge(
df_sub_mh_grp,
on=["Location", "MH_NO"],
how="left",
suffixes=("_Client", "_Sub")
)
if "MH_NO" in df_client_dc.columns:
df_client_dc.rename(columns={"MH_NO": "Node_No"}, inplace=True)
df_dc_cmp = df_client_dc.merge(
df_sub_dc_grp,
on=["Location", "Node_No"],
how="left",
suffixes=("_Client", "_Sub")
)
# CALCULATE DIFFERENCE
for col in qty_cols:
if f"{col}_Client" in df_tr_cmp.columns:
df_tr_cmp[f"{col}_Diff"] = (
df_tr_cmp[f"{col}_Client"].fillna(0)
- df_tr_cmp[f"{col}_Sub"].fillna(0)
)
print("Sum of df_tr_cmp::",df_tr_cmp)
df_mh_cmp[f"{col}_Diff"] = (
df_mh_cmp[f"{col}_Client"].fillna(0)
- df_mh_cmp[f"{col}_Sub"].fillna(0)
)
print("Sum of df_mh_cmp::",df_mh_cmp)
df_dc_cmp["Domestic_Chambers_Diff"] = (
df_dc_cmp["Domestic_Chambers_Client"].fillna(0)
- df_dc_cmp["Domestic_Chambers_Sub"].fillna(0)
)
# EXPORT EXCEL
output = io.BytesIO()
file_name = f"Client_vs_All_Subcontractor_RA_{RA_Bill_No}.xlsx"
with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
df_tr_cmp.to_excel(writer, sheet_name="Tr.Ex", index=False)
df_mh_cmp.to_excel(writer, sheet_name="Mh.Ex", index=False)
df_dc_cmp.to_excel(writer, sheet_name="MH & DC", index=False)
output.seek(0)
return send_file(
output,
download_name=file_name,
as_attachment=True,
mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
return render_template("generate_comparison_client_vs_subcont.html")