5 Commits

Author SHA1 Message Date
de8e68aff2 Update app/templates/base.html 2026-02-02 06:47:42 +00:00
2ef8a9aff9 new dashboard 1 2026-01-24 16:46:33 +05:30
20a5d01f88 dashboarded added 2026-01-24 13:41:52 +05:30
1dceb640bd Merge pull request 'Dowload report of client report fix' (#10) from dev-anish into main
Reviewed-on: #10
2026-01-19 06:54:02 +00:00
359847958d Dowload report of client report fix 2026-01-17 18:06:58 +05:30
5 changed files with 307 additions and 351 deletions

2
.env
View File

@@ -20,7 +20,7 @@ DB_HOST=127.0.0.1
DB_PORT=3306
DB_NAME=comparisondb
DB_USER=root
DB_PASSWORD=root
DB_PASSWORD=admin
# DATABASE_URL=mysql+pymysql://root:root@localhost/comparisondb

View File

@@ -1,87 +1,136 @@
import matplotlib
matplotlib.use("Agg")
# import matplotlib
# matplotlib.use("Agg")
from flask import Blueprint, render_template, session, redirect, url_for
import matplotlib.pyplot as plt
import io
import base64
from app.utils.plot_utils import plot_to_base64
from app.services.dashboard_service import DashboardService
# from flask import Blueprint, render_template, session, redirect, url_for
# import matplotlib.pyplot as plt
# import io
# import base64
# from app.utils.plot_utils import plot_to_base64
# from app.services.dashboard_service import DashboardService
# dashboard_bp = Blueprint("dashboard", __name__, url_prefix="/dashboard")
# # dashboard_bp = Blueprint("dashboard", __name__)
# # charts
# # def plot_to_base64():
# # img = io.BytesIO()
# # plt.savefig(img, format="png", bbox_inches="tight")
# # plt.close()
# # img.seek(0)
# # return base64.b64encode(img.getvalue()).decode()
# # bar chart
# def bar_chart():
# categories = ["Trench", "Manhole", "Pipe Laying", "Restoration"]
# values = [120, 80, 150, 60]
# plt.figure()
# plt.bar(categories, values)
# plt.title("Work Category Report")
# plt.xlabel("test Category")
# plt.ylabel("test Quantity")
# return plot_to_base64(plt)
# # Pie chart
# def pie_chart():
# labels = ["Completed", "In Progress", "Pending"]
# sizes = [55, 20, 25]
# plt.figure()
# plt.pie(sizes, labels=labels, autopct="%1.1f%%", startangle=140)
# plt.title("Project Status")
# return plot_to_base64(plt)
# # Histogram chart
# def histogram_chart():
# daily_work = [5, 10, 15, 20, 20, 25, 30, 35, 40, 45, 50]
# plt.figure()
# plt.hist(daily_work, bins=5)
# plt.title("Daily Work Distribution")
# plt.xlabel("Work Units")
# plt.ylabel("Frequency")
# return plot_to_base64(plt)
# # Dashboaed page
# @dashboard_bp.route("/")
# def dashboard():
# if not session.get("user_id"):
# return redirect(url_for("auth.login"))
# return render_template(
# "dashboard.html",
# title="Dashboard",
# bar_chart=bar_chart(),
# pie_chart=pie_chart(),
# histogram=histogram_chart()
# )
# # subcontractor dashboard
# @dashboard_bp.route("/subcontractor_dashboard", methods=["GET", "POST"])
# def subcontractor_dashboard():
# if not session.get("user_id"):
# return redirect(url_for("auth.login"))
# tr_dash = DashboardService().bar_chart_of_tr_ex
# return render_template(
# "subcontractor_dashboard.html",
# title="Dashboard",
# bar_chart=tr_dash
# )
from flask import Blueprint, render_template, session, redirect, url_for, jsonify
from sqlalchemy import func
from app import db
from app.models.trench_excavation_model import TrenchExcavation
from app.models.manhole_excavation_model import ManholeExcavation
from app.models.laying_model import Laying
dashboard_bp = Blueprint("dashboard", __name__, url_prefix="/dashboard")
# dashboard_bp = Blueprint("dashboard", __name__)
@dashboard_bp.route("/api/live-stats")
def live_stats():
try:
# 1. Overall Volume
t_count = TrenchExcavation.query.count()
m_count = ManholeExcavation.query.count()
l_count = Laying.query.count()
# charts
# def plot_to_base64():
# img = io.BytesIO()
# plt.savefig(img, format="png", bbox_inches="tight")
# plt.close()
# img.seek(0)
# return base64.b64encode(img.getvalue()).decode()
# 2. Location Distribution (Business reach)
loc_results = db.session.query(
TrenchExcavation.Location,
func.count(TrenchExcavation.id)
).group_by(TrenchExcavation.Location).all()
# bar chart
def bar_chart():
categories = ["Trench", "Manhole", "Pipe Laying", "Restoration"]
values = [120, 80, 150, 60]
# 3. Work Timeline (Business productivity trend)
# Assuming your models have a 'created_at' field
timeline_results = db.session.query(
func.date(TrenchExcavation.created_at),
func.count(TrenchExcavation.id)
).group_by(func.date(TrenchExcavation.created_at)).order_by(func.date(TrenchExcavation.created_at)).all()
plt.figure()
plt.bar(categories, values)
plt.title("Work Category Report")
plt.xlabel("test Category")
plt.ylabel("test Quantity")
return jsonify({
"summary": {
"trench": t_count,
"manhole": m_count,
"laying": l_count,
"total": t_count + m_count + l_count
},
"locations": {row[0]: row[1] for row in loc_results if row[0]},
"timeline": {str(row[0]): row[1] for row in timeline_results}
})
except Exception as e:
return jsonify({"error": str(e)}), 500
return plot_to_base64(plt)
# Pie chart
def pie_chart():
labels = ["Completed", "In Progress", "Pending"]
sizes = [55, 20, 25]
plt.figure()
plt.pie(sizes, labels=labels, autopct="%1.1f%%", startangle=140)
plt.title("Project Status")
return plot_to_base64(plt)
# Histogram chart
def histogram_chart():
daily_work = [5, 10, 15, 20, 20, 25, 30, 35, 40, 45, 50]
plt.figure()
plt.hist(daily_work, bins=5)
plt.title("Daily Work Distribution")
plt.xlabel("Work Units")
plt.ylabel("Frequency")
return plot_to_base64(plt)
# Dashboaed page
@dashboard_bp.route("/")
def dashboard():
if not session.get("user_id"):
return redirect(url_for("auth.login"))
return render_template(
"dashboard.html",
title="Dashboard",
bar_chart=bar_chart(),
pie_chart=pie_chart(),
histogram=histogram_chart()
)
# subcontractor dashboard
@dashboard_bp.route("/subcontractor_dashboard", methods=["GET", "POST"])
def subcontractor_dashboard():
if not session.get("user_id"):
return redirect(url_for("auth.login"))
tr_dash = DashboardService().bar_chart_of_tr_ex
return render_template(
"subcontractor_dashboard.html",
title="Dashboard",
bar_chart=tr_dash
)
return render_template("dashboard.html", title="Business Intelligence Dashboard")

View File

@@ -1,6 +1,8 @@
from flask import Blueprint, render_template, request, send_file, flash
import pandas as pd
import io
import re
from collections import defaultdict
from app.models.subcontractor_model import Subcontractor
from app.models.trench_excavation_model import TrenchExcavation
@@ -14,26 +16,20 @@ from app.models.mh_dc_client_model import ManholeDomesticChamberClient
from app.models.laying_client_model import LayingClient
from app.utils.helpers import login_required
import re
generate_report_bp = Blueprint("generate_report", __name__, url_prefix="/report")
# sum field of pipe laying (pipe_150_mm)
# --- REGEX PATTERNS FOR TOTALING ---
PIPE_MM_PATTERN = re.compile(r"^pipe_\d+_mm$")
# sum fields of MH dc (d_0_to_0_75)
D_RANGE_PATTERN = re.compile( r"^d_\d+(?:_\d+)?_to_\d+(?:_\d+)?$")
D_RANGE_PATTERN = re.compile(r"^d_\d+(?:_\d+)?_to_\d+(?:_\d+)?$")
# --- UTILITIES ---
# NORMALIZER
def normalize_key(value):
if value is None:
return None
return ""
return str(value).strip().upper()
# HEADER FORMATTER
def format_header(header):
if "-" in header:
prefix, rest = header.split("-", 1)
@@ -44,7 +40,6 @@ def format_header(header):
parts = rest.split("_")
result = []
i = 0
while i < len(parts):
if i + 1 < len(parts) and parts[i].isdigit() and parts[i + 1].isdigit():
result.append(f"{parts[i]}.{parts[i + 1]}")
@@ -56,122 +51,125 @@ def format_header(header):
final_text = " ".join(result)
return f"{prefix}-{final_text}" if prefix else final_text
# LOOKUP CREATOR
def make_lookup(rows, key_field):
lookup = {}
"""Creates a mapping of (Location, Key) to a list of records."""
lookup = defaultdict(list)
for r in rows:
location = normalize_key(r.get("Location"))
key_val = normalize_key(r.get(key_field))
if location and key_val:
lookup[(location, key_val)] = r
# Check both capitalized and lowercase keys for robustness
loc = normalize_key(r.get("Location") or r.get("location"))
key = normalize_key(r.get(key_field) or r.get(key_field.lower()))
if loc and key:
lookup[(loc, key)].append(r)
return lookup
def calculate_row_total(row_dict):
"""Calculates total based on _total suffix or regex patterns."""
return sum(
float(v or 0) for k, v in row_dict.items()
if k.endswith("_total") or D_RANGE_PATTERN.match(k) or PIPE_MM_PATTERN.match(k)
)
# --- CORE COMPARISON LOGIC ---
# COMPARISON BUILDER
def build_comparison(client_rows, contractor_rows, key_field):
contractor_lookup = make_lookup(contractor_rows, key_field)
# 1. Create Lookup for Subcontractors
contractor_lookup = {}
for r in contractor_rows:
loc = normalize_key(r.get("Location") or r.get("location"))
key = normalize_key(r.get(key_field) or r.get(key_field.lower()))
if loc and key:
contractor_lookup[(loc, key)] = r
output = []
# 2. Iterate through Client rows
for c in client_rows:
client_location = normalize_key(c.get("Location"))
client_key = normalize_key(c.get(key_field))
loc_raw = c.get("Location") or c.get("location")
key_raw = c.get(key_field) or c.get(key_field.lower())
loc_norm = normalize_key(loc_raw)
key_norm = normalize_key(key_raw)
if not client_location or not client_key:
continue
# Match check
s = contractor_lookup.get((loc_norm, key_norm))
# We only include the row if there is a match (Inner Join)
if s:
client_total = calculate_row_total(c)
sub_total = calculate_row_total(s)
s = contractor_lookup.get((client_location, client_key))
if not s:
continue
row = {
"Location": loc_raw,
key_field.replace("_", " "): key_raw
}
client_total = sum(
float(v or 0)
for k, v in c.items()
if k.endswith("_total") or D_RANGE_PATTERN.match(k) or PIPE_MM_PATTERN.match(k)
)
# Add Client Data
for k, v in c.items():
if k in ["id", "created_at"]: continue
row[f"Client-{k}"] = v
row["Client-Total"] = round(client_total, 2)
sub_total = sum(
float(v or 0)
for k, v in s.items()
if k.endswith("_total") or D_RANGE_PATTERN.match(k) or PIPE_MM_PATTERN.match(k)
)
row[" "] = "" # Spacer
diff = client_total - sub_total
# Add Subcontractor Data (Aligned on same row)
for k, v in s.items():
if k in ["id", "created_at", "subcontractor_id"]: continue
row[f"Subcontractor-{k}"] = v
row["Subcontractor-Total"] = round(sub_total, 2)
row["Diff"] = round(client_total - sub_total, 2)
output.append(row)
row = {
"Location": client_location,
key_field.replace("_", " "): client_key
}
# CLIENT DATA
for k, v in c.items():
if k in ["id", "created_at"]:
continue
row[f"Client-{k}"] = v
row["Client-Total"] = round(client_total, 2)
row[" "] = ""
# SUBCONTRACTOR DATA
for k, v in s.items():
if k in ["id", "created_at", "subcontractor_id"]:
continue
row[f"Subcontractor-{k}"] = v
row["Subcontractor-Total"] = round(sub_total, 2)
row["Diff"] = round(diff, 2)
output.append(row)
# 3. Handle the "Empty/Blank" scenario using pd.concat
if not output:
# Create a basic dataframe with a message so the Excel file isn't empty/corrupt
return pd.DataFrame([{"Location": "N/A", "Message": "No matching data found"}])
df = pd.DataFrame(output)
df.columns = [format_header(col) for col in df.columns]
return df
# --- EXCEL WRITER ---
# EXCEL SHEET WRITER
def write_sheet(writer, df, sheet_name, subcontractor_name):
if df.empty:
return
workbook = writer.book
df.to_excel(writer, sheet_name=sheet_name, index=False, startrow=3)
ws = writer.sheets[sheet_name]
# Formats
title_fmt = workbook.add_format({"bold": True, "font_size": 14})
client_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#B6DAED"})
sub_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#F3A081"})
total_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#F7D261"})
diff_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#82DD49"})
default_header_fmt = workbook.add_format({"bold": True,"border": 1,"bg_color": "#E7E6E6","align": "center","valign": "vcenter"})
ws.merge_range(
0, 0, 0, len(df.columns) - 1,
"CLIENT vs SUBCONTRACTOR",
title_fmt
)
ws.merge_range(
1, 0, 1, len(df.columns) - 1,
f"Subcontractor Name - {subcontractor_name}",
title_fmt
)
client_header_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#B6DAED", "align": "center"})
sub_header_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#F3A081", "align": "center"})
total_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#F7D261", "align": "center"})
diff_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#82DD49", "align": "center"})
default_header_fmt = workbook.add_format({"bold": True, "border": 1, "bg_color": "#E7E6E6", "align": "center"})
# Header Titles
ws.merge_range(0, 0, 0, len(df.columns) - 1, "CLIENT vs SUBCONTRACTOR COMPARISON", title_fmt)
ws.merge_range(1, 0, 1, len(df.columns) - 1, f"Subcontractor: {subcontractor_name}", title_fmt)
for col_num, col_name in enumerate(df.columns):
if col_name.startswith("Client-"):
ws.write(3, col_num, col_name, client_fmt)
fmt = client_header_fmt
elif col_name.startswith("Subcontractor-"):
ws.write(3, col_num, col_name, sub_fmt)
elif col_name.endswith("_total") or col_name.endswith("_total") :
ws.write(3, col_num, col_name, total_fmt)
fmt = sub_header_fmt
elif "Total" in col_name:
fmt = total_fmt
elif col_name == "Diff":
ws.write(3, col_num, col_name, diff_fmt)
fmt = diff_fmt
else:
ws.write(3, col_num, col_name, default_header_fmt)
fmt = default_header_fmt
ws.write(3, col_num, col_name, fmt)
ws.set_column(col_num, col_num, 18)
ws.set_column(col_num, col_num, 20)
# --- ROUTES ---
# REPORT ROUTE
@generate_report_bp.route("/comparison_report", methods=["GET", "POST"])
@login_required
def comparison_report():
@@ -180,48 +178,29 @@ def comparison_report():
if request.method == "POST":
subcontractor_id = request.form.get("subcontractor_id")
if not subcontractor_id:
flash("Please select subcontractor", "danger")
return render_template("generate_comparison_report.html",subcontractors=subcontractors)
flash("Please select a subcontractor", "danger")
return render_template("generate_comparison_report.html", subcontractors=subcontractors)
subcontractor = Subcontractor.query.get_or_404(subcontractor_id)
# -------- DATA --------
tr_client = [r.serialize() for r in TrenchExcavationClient.query.all()]
tr_sub = [r.serialize() for r in TrenchExcavation.query.filter_by(
subcontractor_id=subcontractor_id
).all()]
df_tr = build_comparison(tr_client, tr_sub, "MH_NO")
# Build Dataframes for each section
sections = [
(TrenchExcavationClient, TrenchExcavation, "Tr.Ex"),
(ManholeExcavationClient, ManholeExcavation, "Mh.Ex"),
(ManholeDomesticChamberClient, ManholeDomesticChamber, "MH & DC"),
(LayingClient, Laying, "Laying")
]
mh_client = [r.serialize() for r in ManholeExcavationClient.query.all()]
mh_sub = [r.serialize() for r in ManholeExcavation.query.filter_by(
subcontractor_id=subcontractor_id
).all()]
df_mh = build_comparison(mh_client, mh_sub, "MH_NO")
dc_client = [r.serialize() for r in ManholeDomesticChamberClient.query.all()]
dc_sub = [r.serialize() for r in ManholeDomesticChamber.query.filter_by(
subcontractor_id=subcontractor_id
).all()]
df_dc = build_comparison(dc_client, dc_sub, "MH_NO")
# df_dc = build_comparison_mh_dc(dc_client, dc_sub, "MH_NO")
lay_client = [r.serialize() for r in LayingClient.query.all()]
lay_sub = [r.serialize() for r in Laying.query.filter_by(
subcontractor_id=subcontractor_id
).all()]
df_lay = build_comparison(lay_client, lay_sub, "MH_NO")
# df_lay = build_comparison_laying(lay_client, lay_sub, "MH_NO")
# -------- EXCEL --------
output = io.BytesIO()
filename = f"{subcontractor.subcontractor_name}_Comparison_Report.xlsx"
with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
write_sheet(writer, df_tr, "Tr.Ex", subcontractor.subcontractor_name)
write_sheet(writer, df_mh, "Mh.Ex", subcontractor.subcontractor_name)
write_sheet(writer, df_dc, "MH & DC", subcontractor.subcontractor_name)
write_sheet(writer, df_lay, "Laying", subcontractor.subcontractor_name)
for client_model, sub_model, sheet_name in sections:
c_data = [r.serialize() for r in client_model.query.all()]
s_data = [r.serialize() for r in sub_model.query.filter_by(subcontractor_id=subcontractor_id).all()]
df = build_comparison(c_data, s_data, "MH_NO")
write_sheet(writer, df, sheet_name, subcontractor.subcontractor_name)
output.seek(0)
return send_file(
@@ -231,107 +210,4 @@ def comparison_report():
mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
)
return render_template("generate_comparison_report.html",subcontractors=subcontractors)
# def build_comparison_mh_dc(client_rows, contractor_rows, key_field):
# contractor_lookup = make_lookup(contractor_rows, key_field)
# mh_dc_fields = ManholeDomesticChamberClient.sum_mh_dc_fields()
# output = []
# for c in client_rows:
# loc = normalize_key(c.get("Location"))
# key = normalize_key(c.get(key_field))
# if not loc or not key:
# continue
# s = contractor_lookup.get((loc, key))
# if not s:
# continue
# client_total = sum(float(c.get(f, 0) or 0) for f in mh_dc_fields)
# sub_total = sum(float(s.get(f, 0) or 0) for f in mh_dc_fields)
# row = {
# "Location": loc,
# key_field.replace("_", " "): key
# }
# # CLIENT ALL FIELDS
# for k, v in c.items():
# if k in ["id", "created_at"]:
# continue
# row[f"Client-{k}"] = v
# row["Client-Total"] = round(client_total, 2)
# row[" "] = ""
# # SUBCONTRACTOR ALL FIELDS
# for k, v in s.items():
# if k in ["id", "created_at", "subcontractor_id"]:
# continue
# row[f"Subcontractor-{k}"] = v
# row["Subcontractor-Total"] = round(sub_total, 2)
# row["Diff"] = round(client_total - sub_total, 2)
# output.append(row)
# df = pd.DataFrame(output)
# df.columns = [format_header(col) for col in df.columns]
# return df
# def build_comparison_laying(client_rows, contractor_rows, key_field):
# contractor_lookup = make_lookup(contractor_rows, key_field)
# laying_fields = Laying.sum_laying_fields()
# output = []
# for c in client_rows:
# loc = normalize_key(c.get("Location"))
# key = normalize_key(c.get(key_field))
# if not loc or not key:
# continue
# s = contractor_lookup.get((loc, key))
# if not s:
# continue
# client_total = sum(float(c.get(f, 0) or 0) for f in laying_fields)
# sub_total = sum(float(s.get(f, 0) or 0) for f in laying_fields)
# print("--------------",key,"----------")
# print("sum -client_total ",client_total)
# print("sum -sub_total ",sub_total)
# print("Diff ---- ",client_total - sub_total)
# print("------------------------")
# row = {
# "Location": loc,
# key_field.replace("_", " "): key
# }
# # CLIENT ALL FIELDS
# for k, v in c.items():
# if k in ["id", "created_at"]:
# continue
# row[f"Client-{k}"] = v
# row["Client-Total"] = round(client_total, 2)
# row[" "] = ""
# # SUBCONTRACTOR ALL FIELDS
# for k, v in s.items():
# if k in ["id", "created_at", "subcontractor_id"]:
# continue
# row[f"Subcontractor-{k}"] = v
# row["Subcontractor-Total"] = round(sub_total, 2)
# row["Diff"] = round(client_total - sub_total, 2)
# output.append(row)
# df = pd.DataFrame(output)
# df.columns = [format_header(col) for col in df.columns]
# return df
return render_template("generate_comparison_report.html", subcontractors=subcontractors)

View File

@@ -38,7 +38,7 @@
<!-- Dashboard -->
<li class="nav-item">
<a class="nav-link" href="/dashboard">
<i class="bi bi-speedometer2 me-1"></i> Dashboard
<i class="bi bi-speedometer2 me-1"></i> Dashboard - Anish
</a>
</li>

View File

@@ -1,87 +1,118 @@
{% extends "base.html" %}
{% block content %}
<div class="container-fluid px-2 px-md-4">
<h4 class="mb-3 text-center text-md-start">Comparison Software Solapur (UGD) - Live Dashboard</h4>
<h4 class="mb-3 text-center text-md-start">Comparison Software Solapur(UGD) </h4>
<!-- Summary Cards -->
<div class="row g-3 mb-4">
<!-- Total Work -->
<div class="col-12 col-md-4">
<div class="card text-white bg-primary shadow h-100">
<div class="card-body text-center text-md-start">
<h6>Test Total Work</h6>
<h3 class="fw-bold">30%</h3>
<h6>Trenching Units</h6>
<h3 class="fw-bold" id="card-trench">0</h3>
</div>
</div>
</div>
<!-- Completed -->
<div class="col-12 col-md-4">
<div class="card text-white bg-success shadow h-100">
<div class="card-body text-center text-md-start">
<h6>test Completed</h6>
<h3 class="fw-bold">35%</h3>
<h6>Manhole Units</h6>
<h3 class="fw-bold" id="card-manhole">0</h3>
</div>
</div>
</div>
<!-- Pending -->
<div class="col-12 col-md-4">
<div class="card text-dark bg-warning shadow h-100">
<div class="card-body text-center text-md-start">
<h6>Pending</h6>
<h3 class="fw-bold">35%</h3>
<h6>Laying Units</h6>
<h3 class="fw-bold" id="card-laying">0</h3>
</div>
</div>
</div>
</div>
<!-- Charts -->
<div class="row g-3">
<!-- Bar Chart -->
<div class="col-12 col-md-6">
<div class="card shadow-sm h-100">
<div class="card-header bg-dark text-white text-center text-md-start">
Work Category Bar Chart
</div>
<div class="card-body text-center">
<img src="data:image/png;base64,{{ bar_chart }}" class="img-fluid" style="max-height:300px;">
<div class="card-header bg-dark text-white">Live Category Bar Chart</div>
<div class="card-body">
<canvas id="liveBarChart" style="max-height:300px;"></canvas>
</div>
</div>
</div>
<!-- Pie Chart -->
<div class="col-12 col-md-6">
<div class="card shadow-sm h-100">
<div class="card-header bg-dark text-white text-center text-md-start">
Project Status Pie Chart
</div>
<div class="card-body text-center">
<img src="data:image/png;base64,{{ pie_chart }}" class="img-fluid" style="max-height:300px;">
<div class="card-header bg-dark text-white">Location Distribution Pie Chart</div>
<div class="card-body">
<canvas id="livePieChart" style="max-height:300px;"></canvas>
</div>
</div>
</div>
<!-- Histogram -->
<div class="col-12">
<div class="card shadow-sm">
<div class="card-header bg-dark text-white text-center text-md-start">
Daily Work Histogram
</div>
<div class="card-body text-center">
<img src="data:image/png;base64,{{ histogram }}" class="img-fluid" style="max-height:350px;">
</div>
</div>
</div>
</div>
</div>
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
<script>
// 2. Initialize the Bar Chart
const barCtx = document.getElementById('liveBarChart').getContext('2d');
let liveBarChart = new Chart(barCtx, {
type: 'bar',
data: {
labels: ['Trenching', 'Manholes', 'Laying'],
datasets: [{
label: 'Units Completed',
data: [0, 0, 0],
backgroundColor: ['#0d6efd', '#198754', '#ffc107']
}]
},
options: { responsive: true, maintainAspectRatio: false }
});
// 3. Initialize the Pie Chart
const pieCtx = document.getElementById('livePieChart').getContext('2d');
let livePieChart = new Chart(pieCtx, {
type: 'pie',
data: {
labels: [], // Will be filled from SQL
datasets: [{
data: [],
backgroundColor: ['#0d6efd', '#198754', '#ffc107', '#6f42c1', '#fd7e14']
}]
},
options: { responsive: true, maintainAspectRatio: false }
});
// 4. Function to Fetch Live Data from your Python API
function fetchLiveData() {
fetch('/dashboard/api/live-stats') // This matches the route we created in the "Kitchen"
.then(response => response.json())
.then(data => {
// Update the Summary Cards
document.getElementById('card-trench').innerText = data.summary.trench;
document.getElementById('card-manhole').innerText = data.summary.manhole;
document.getElementById('card-laying').innerText = data.summary.laying;
// Update Bar Chart
liveBarChart.data.datasets[0].data = [
data.summary.trench,
data.summary.manhole,
data.summary.laying
];
liveBarChart.update();
// Update Pie Chart (Location stats)
livePieChart.data.labels = Object.keys(data.locations);
livePieChart.data.datasets[0].data = Object.values(data.locations);
livePieChart.update();
})
.catch(err => console.error("Error fetching live data:", err));
}
// 5. Check for updates every 10 seconds (Real-time effect)
setInterval(fetchLiveData, 10000);
fetchLiveData(); // Load immediately on page open
</script>
{% endblock %}