correction of comparison data show

This commit is contained in:
2026-07-31 12:44:09 +05:30
parent 46d11ec01f
commit 604e948986
2 changed files with 264 additions and 50 deletions

View File

@@ -1,3 +1,4 @@
import matplotlib import matplotlib
matplotlib.use("Agg") matplotlib.use("Agg")
@@ -10,6 +11,7 @@ from app.utils.helpers import login_required
from app.services.dashboard_service import DashboardService from app.services.dashboard_service import DashboardService
from sqlalchemy import func from sqlalchemy import func
from app import db from app import db
from sqlalchemy import tuple_
# Subcontractor models import # Subcontractor models import
from app.models.subcontractor_model import Subcontractor from app.models.subcontractor_model import Subcontractor
@@ -127,9 +129,7 @@ def get_ra_bills():
Laying.subcontractor_id == subcontractor_id Laying.subcontractor_id == subcontractor_id
).distinct().order_by(Laying.RA_Bill_No).all() ).distinct().order_by(Laying.RA_Bill_No).all()
ra_bills = [r[0] for r in results if r[0]] ra_bills = [r[0] for r in results if r[0]]
print(results)
return {"ra_bills": ra_bills} return {"ra_bills": ra_bills}
@@ -150,7 +150,6 @@ def trench_analysis():
# Subcontractor Query # Subcontractor Query
sub_query = TrenchExcavation.query sub_query = TrenchExcavation.query
if subcontractor_id: if subcontractor_id:
sub_query = sub_query.filter( sub_query = sub_query.filter(
TrenchExcavation.subcontractor_id == int(subcontractor_id) TrenchExcavation.subcontractor_id == int(subcontractor_id)
@@ -161,99 +160,111 @@ def trench_analysis():
TrenchExcavation.RA_Bill_No.in_(ra_bill_list) TrenchExcavation.RA_Bill_No.in_(ra_bill_list)
) )
tr_sub = [r.serialize() for r in sub_query.all()] sub_records = sub_query.all()
sub_keys = [
(
(r.MH_NO or "").strip().upper(),
(r.Location or "").strip().upper()
)
for r in sub_records
]
# Client Query
client_query = TrenchExcavationClient.query client_query = TrenchExcavationClient.query
if ra_bill_list: if sub_keys:
client_query = client_query.filter( client_query = client_query.filter(
TrenchExcavationClient.RA_Bill_No.in_(ra_bill_list)
tuple_(
func.upper(func.trim(TrenchExcavationClient.MH_NO)),
func.upper(func.trim(TrenchExcavationClient.Location))
).in_(sub_keys)
) )
tr_client = [r.serialize() for r in client_query.all()] client_records = client_query.all()
chart_data = [ chart_data = [
{ {
"label": "Marshi 0 to 1.5", "label": "Marshi 0 to 1.5",
"client": total(client_query.all(), "Marshi_Muddy_Slushy_0_to_1_5_total"), "client": total(client_records, "Marshi_Muddy_Slushy_0_to_1_5_total"),
"sub": 0 "sub": 0
}, },
{ {
"label": "Marshi 1.5 to 3.0", "label": "Marshi 1.5 to 3.0",
"client": total(client_query.all(), "Marshi_Muddy_Slushy_1_5_to_3_0_total"), "client": total(client_records, "Marshi_Muddy_Slushy_1_5_to_3_0_total"),
"sub": 0 "sub": 0
}, },
{ {
"label": "Marshi 3.0-4.5", "label": "Marshi 3.0 to 4.5",
"client": total(client_query.all(), "Marshi_Muddy_Slushy_3_0_to_4_5_total"), "client": total(client_records, "Marshi_Muddy_Slushy_3_0_to_4_5_total"),
"sub": 0 "sub": 0
}, },
{ {
"label": "Soft Murum 0-1.5", "label": "Soft Murum 0 to 1.5",
"client": total(client_query.all(), "Soft_Murum_0_to_1_5_total"), "client": total(client_records, "Soft_Murum_0_to_1_5_total"),
"sub": total(sub_query.all(), "Soft_Murum_0_to_1_5_total") "sub": total(sub_records, "Soft_Murum_0_to_1_5_total")
}, },
{ {
"label": "Soft Murum 1.5-3.0", "label": "Soft Murum 1.5 to 3.0",
"client": total(client_query.all(), "Soft_Murum_1_5_to_3_0_total"), "client": total(client_records, "Soft_Murum_1_5_to_3_0_total"),
"sub": total(sub_query.all(), "Soft_Murum_1_5_to_3_0_total") "sub": total(sub_records, "Soft_Murum_1_5_to_3_0_total")
}, },
{ {
"label": "Soft Murum 3.0-4.5", "label": "Soft Murum 3.0 to 4.5",
"client": total(client_query.all(), "Soft_Murum_3_0_to_4_5_total"), "client": total(client_records, "Soft_Murum_3_0_to_4_5_total"),
"sub": total(sub_query.all(), "Soft_Murum_3_0_to_4_5_total") "sub": total(sub_records, "Soft_Murum_3_0_to_4_5_total")
}, },
{ {
"label": "Hard Murum 0-1.5", "label": "Hard Murum 0 to 1.5",
"client": total(client_query.all(), "Hard_Murum_0_to_1_5_total"), "client": total(client_records, "Hard_Murum_0_to_1_5_total"),
"sub": total(sub_query.all(), "Hard_Murum_0_to_1_5_total") "sub": total(sub_records, "Hard_Murum_0_to_1_5_total")
}, },
{ {
"label": "Hard Murum 1.5+", "label": "Hard Murum 1.5 to 3.0",
"client": total(client_query.all(), "Hard_Murum_1_5_to_3_0_total"), "client": total(client_records, "Hard_Murum_1_5_to_3_0_total"),
"sub": total(sub_query.all(), "Hard_Murum_1_5_and_above_total") "sub": total(sub_records, "Hard_Murum_1_5_and_above_total")
}, },
{ {
"label": "Soft Rock 0-1.5", "label": "Soft Rock 0 to 1.5",
"client": total(client_query.all(), "Soft_Rock_0_to_1_5_total"), "client": total(client_records, "Soft_Rock_0_to_1_5_total"),
"sub": total(sub_query.all(), "Soft_Rock_0_to_1_5_total") "sub": total(sub_records, "Soft_Rock_0_to_1_5_total")
}, },
{ {
"label": "Soft Rock 1.5+", "label": "Soft Rock 1.5 to 3.0",
"client": total(client_query.all(), "Soft_Rock_1_5_to_3_0_total"), "client": total(client_records, "Soft_Rock_1_5_to_3_0_total"),
"sub": total(sub_query.all(), "Soft_Rock_1_5_and_above_total") "sub": total(sub_records, "Soft_Rock_1_5_and_above_total")
}, },
{ {
"label": "Hard Rock 0-1.5", "label": "Hard Rock 0 to 1.5",
"client": total(client_query.all(), "Hard_Rock_0_to_1_5_total"), "client": total(client_records, "Hard_Rock_0_to_1_5_total"),
"sub": total(sub_query.all(), "Hard_Rock_0_to_1_5_total") "sub": total(sub_records, "Hard_Rock_0_to_1_5_total")
}, },
{ {
"label": "Hard Rock 1.5-3.0", "label": "Hard Rock 1.5 to 3.0",
"client": total(client_query.all(), "Hard_Rock_1_5_to_3_0_total"), "client": total(client_records, "Hard_Rock_1_5_to_3_0_total"),
"sub": total(sub_query.all(), "Hard_Rock_1_5_to_3_0_total") "sub": total(sub_records, "Hard_Rock_1_5_to_3_0_total")
}, },
{ {
"label": "Hard Rock 3.0-4.5", "label": "Hard Rock 3.0 to 4.5",
"client": total(client_query.all(), "Hard_Rock_3_0_to_4_5_total"), "client": total(client_records, "Hard_Rock_3_0_to_4_5_total"),
"sub": total(sub_query.all(), "Hard_Rock_3_0_to_4_5_total") "sub": total(sub_records, "Hard_Rock_3_0_to_4_5_total")
}, },
{ {
"label": "Hard Rock 4.5-6.0", "label": "Hard Rock 4.5 to 6.0",
"client": total(client_query.all(), "Hard_Rock_4_5_to_6_0_total"), "client": total(client_records, "Hard_Rock_4_5_to_6_0_total"),
"sub": total(sub_query.all(), "Hard_Rock_4_5_to_6_0_total") "sub": total(sub_records, "Hard_Rock_4_5_to_6_0_total")
}, },
{ {
"label": "Hard Rock 6.0-7.5", "label": "Hard Rock 6.0 to 7.5",
"client": total(client_query.all(), "Hard_Rock_6_0_to_7_5_total"), "client": total(client_records, "Hard_Rock_6_0_to_7_5_total"),
"sub": total(sub_query.all(), "Hard_Rock_6_0_to_7_5_total") "sub": total(sub_records, "Hard_Rock_6_0_to_7_5_total")
} }
] ]
@@ -263,4 +274,3 @@ def trench_analysis():
"sub_qty": [x["sub"] for x in chart_data] "sub_qty": [x["sub"] for x in chart_data]
}) })

View File

@@ -0,0 +1,204 @@
from collections import defaultdict
import pandas as pd
from app.utils.regex_utils import RegularExpression
class ComparisonService:
TRENCH_MAPPING = [
{
"label": "Marshi 0 to 1.5",
"client": "Client_Marshi_Muddy_Slushy_0_to_1_5_total",
"sub": None
},
{
"label": "Marshi 1.5 to 3.0",
"client": "Client_Marshi_Muddy_Slushy_1_5_to_3_0_total",
"sub": None
},
{
"label": "Marshi 3.0 to 4.5",
"client": "Client_Marshi_Muddy_Slushy_3_0_to_4_5_total",
"sub": None
},
{
"label": "Soft Murum 0 to 1.5",
"client": "Client_Soft_Murum_0_to_1_5_total",
"sub": "Sub_Soft_Murum_0_to_1_5_total"
},
{
"label": "Soft Murum 1.5 to 3.0",
"client": "Client_Soft_Murum_1_5_to_3_0_total",
"sub": "Sub_Soft_Murum_1_5_to_3_0_total"
},
{
"label": "Soft Murum 3.0 to 4.5",
"client": "Client_Soft_Murum_3_0_to_4_5_total",
"sub": "Sub_Soft_Murum_3_0_to_4_5_total"
},
{
"label": "Hard Murum 0 to 1.5",
"client": "Client_Hard_Murum_0_to_1_5_total",
"sub": "Sub_Hard_Murum_0_to_1_5_total"
},
{
"label": "Hard Murum 1.5+",
"client": "Client_Hard_Murum_1_5_to_3_0_total",
"sub": "Sub_Hard_Murum_1_5_and_above_total"
},
{
"label": "Soft Rock 0 to 1.5",
"client": "Client_Soft_Rock_0_to_1_5_total",
"sub": "Sub_Soft_Rock_0_to_1_5_total"
},
{
"label": "Soft Rock 1.5+",
"client": "Client_Soft_Rock_1_5_to_3_0_total",
"sub": "Sub_Soft_Rock_1_5_and_above_total"
},
{
"label": "Hard Rock 0 to 1.5",
"client": "Client_Hard_Rock_0_to_1_5_total",
"sub": "Sub_Hard_Rock_0_to_1_5_total"
},
{
"label": "Hard Rock 1.5 to 3.0",
"client": "Client_Hard_Rock_1_5_to_3_0_total",
"sub": "Sub_Hard_Rock_1_5_to_3_0_total"
},
{
"label": "Hard Rock 3.0 to 4.5",
"client": "Client_Hard_Rock_3_0_to_4_5_total",
"sub": "Sub_Hard_Rock_3_0_to_4_5_total"
},
{
"label": "Hard Rock 4.5 to 6.0",
"client": "Client_Hard_Rock_4_5_to_6_0_total",
"sub": "Sub_Hard_Rock_4_5_to_6_0_total"
},
{
"label": "Hard Rock 6.0 to 7.5",
"client": "Client_Hard_Rock_6_0_to_7_5_total",
"sub": "Sub_Hard_Rock_6_0_to_7_5_total"
}
]
@staticmethod
def normalize_key(value):
if value is None:
return ""
return str(value).strip().upper()
@classmethod
def make_lookup(cls, rows, key_field):
"""
Create lookup dictionary using:
(Location, MH_NO)
"""
lookup = defaultdict(list)
for row in rows:
location = cls.normalize_key(row.get("Location"))
key = cls.normalize_key(row.get(key_field))
if location and key:
lookup[(location, key)].append(row)
return lookup
@classmethod
def build_comparison(cls, client_rows, subcontractor_rows, key_field="MH_NO"):
subcontractor_lookup = cls.make_lookup(
subcontractor_rows,
key_field
)
used = defaultdict(int)
output = []
for client in client_rows:
location = cls.normalize_key(client.get("Location"))
key = cls.normalize_key(client.get(key_field))
if not location or not key:
continue
rows = subcontractor_lookup.get((location, key))
if not rows:
continue
index = used[(location, key)]
if index >= len(rows):
continue
subcontractor = rows[index]
used[(location, key)] += 1
client_total = sum(
float(v or 0)
for k, v in client.items()
if k.endswith("_total")
or RegularExpression.D_RANGE_PATTERN.match(k)
or RegularExpression.PIPE_MM_PATTERN.match(k)
)
subcontractor_total = sum(
float(v or 0)
for k, v in subcontractor.items()
if k.endswith("_total")
or RegularExpression.D_RANGE_PATTERN.match(k)
or RegularExpression.PIPE_MM_PATTERN.match(k)
)
row = {
"Location": location,
key_field: key,
"Client_Total": round(client_total, 2),
"Subcontractor_Total": round(subcontractor_total, 2),
"Difference": round(
client_total - subcontractor_total,
2
)
}
# Client Columns
for column, value in client.items():
if column in [
"id",
"created_at"
]:
continue
row[f"Client_{column}"] = value
# Subcontractor Columns
for column, value in subcontractor.items():
if column in [
"id",
"created_at",
"subcontractor_id"
]:
continue
row[f"Sub_{column}"] = value
output.append(row)
return pd.DataFrame(output)