Overview
The Statistics API provides aggregated data for dashboard displays, including counts of PTEs, OTEs, production records, and total production volumes.
Get Statistics
Retrieve dashboard statistics.
Endpoint: GET /operaciones/api/estadisticas/
curl -X GET "https://api.sascop-bme-subtec.com/operaciones/api/estadisticas/" \
-H "Cookie: sessionid=your_session_id"
Response Fields
Total count of all PTEs in the system
Total count of all OTEs (work orders) in the system
Total count of production records
Aggregated sum of all production volumes across all records
Response Example
{
"total_ptes": 45,
"total_otes": 128,
"total_produccion": 1543,
"volumen_total": 25678.50
}
Source Code
URL Configuration (operaciones/urls.py:177)
path('api/estadisticas/', api.api_estadisticas, name='api_estadisticas'),
operaciones/views/api.py:7-24)
@login_required(login_url='/accounts/login/')
def api_estadisticas(request):
"""API para estadísticas del dashboard"""
total_ptes = PTEHeader.objects.count()
total_otes = OTE.objects.count()
total_produccion = Produccion.objects.count()
from django.db.models import Sum
volumen_total = Produccion.objects.aggregate(
total=Sum('volumen_produccion')
)['total'] or 0
return JsonResponse({
'total_ptes': total_ptes,
'total_otes': total_otes,
'total_produccion': total_produccion,
'volumen_total': float(volumen_total)
})
Implementation Details
Database Queries
The endpoint executes the following queries:
- Count PTEs:
PTEHeader.objects.count()
- Count OTEs:
OTE.objects.count()
- Count Production:
Produccion.objects.count()
- Sum Volumes:
Produccion.objects.aggregate(total=Sum('volumen_produccion'))
This endpoint performs 4 database queries each time it’s called. Consider caching the results for frequently accessed dashboards.
Recommended Caching Strategy:from django.core.cache import cache
def api_estadisticas(request):
cache_key = 'dashboard_stats'
stats = cache.get(cache_key)
if stats is None:
# Compute statistics
stats = {
'total_ptes': PTEHeader.objects.count(),
'total_otes': OTE.objects.count(),
'total_produccion': Produccion.objects.count(),
'volumen_total': float(Produccion.objects.aggregate(
total=Sum('volumen_produccion')
)['total'] or 0)
}
# Cache for 5 minutes
cache.set(cache_key, stats, 300)
return JsonResponse(stats)
Use Cases
Dashboard Display
import { useEffect, useState } from 'react';
import axios from 'axios';
function DashboardStats() {
const [stats, setStats] = useState(null);
const [loading, setLoading] = useState(true);
useEffect(() => {
const fetchStats = async () => {
try {
const response = await axios.get('/operaciones/api/estadisticas/', {
withCredentials: true
});
setStats(response.data);
} catch (error) {
console.error('Failed to fetch statistics:', error);
} finally {
setLoading(false);
}
};
fetchStats();
// Refresh every 5 minutes
const interval = setInterval(fetchStats, 300000);
return () => clearInterval(interval);
}, []);
if (loading) return <div>Loading...</div>;
return (
<div className="stats-grid">
<StatCard title="PTEs" value={stats.total_ptes} />
<StatCard title="OTEs" value={stats.total_otes} />
<StatCard title="Production Records" value={stats.total_produccion} />
<StatCard
title="Total Volume"
value={stats.volumen_total.toFixed(2)}
/>
</div>
);
}
import requests
import argparse
from tabulate import tabulate
def get_statistics(session_id):
cookies = {'sessionid': session_id}
response = requests.get(
'https://api.sascop-bme-subtec.com/operaciones/api/estadisticas/',
cookies=cookies
)
if response.status_code == 200:
return response.json()
else:
raise Exception(f"Failed to fetch statistics: {response.status_code}")
def main():
parser = argparse.ArgumentParser(description='Get SASCOP statistics')
parser.add_argument('--session-id', required=True, help='Session ID')
args = parser.parse_args()
stats = get_statistics(args.session_id)
table = [
['Metric', 'Value'],
['Total PTEs', stats['total_ptes']],
['Total OTEs', stats['total_otes']],
['Production Records', stats['total_produccion']],
['Total Volume', f"{stats['volumen_total']:.2f}"]
]
print(tabulate(table, headers='firstrow', tablefmt='grid'))
if __name__ == '__main__':
main()
Excel Report Generator
import requests
import openpyxl
from datetime import datetime
def generate_stats_report(session):
# Fetch statistics
response = session.get(
'https://api.sascop-bme-subtec.com/operaciones/api/estadisticas/'
)
stats = response.json()
# Create Excel workbook
wb = openpyxl.Workbook()
ws = wb.active
ws.title = 'Statistics'
# Headers
ws['A1'] = 'SASCOP BME SubTec - Statistics Report'
ws['A2'] = f'Generated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}'
# Data
ws['A4'] = 'Metric'
ws['B4'] = 'Value'
ws['A5'] = 'Total PTEs'
ws['B5'] = stats['total_ptes']
ws['A6'] = 'Total OTEs'
ws['B6'] = stats['total_otes']
ws['A7'] = 'Production Records'
ws['B7'] = stats['total_produccion']
ws['A8'] = 'Total Volume'
ws['B8'] = stats['volumen_total']
# Save
filename = f'stats_report_{datetime.now().strftime("%Y%m%d_%H%M%S")}.xlsx'
wb.save(filename)
print(f'Report saved: {filename}')
# Usage
session = requests.Session()
# ... login ...
generate_stats_report(session)
PTEHeader
Technical execution projects
Produccion
Production records
