Daily Report Generator for Construction Sites
Automate the creation of comprehensive daily construction reports by aggregating data from multiple sources into professional documentation.
Business Case
Problem: Site managers spend 45-60 minutes daily on:
- Collecting information from foremen
- Checking weather conditions
- Compiling worker counts and hours
- Writing narrative summaries
- Formatting and distributing reports
Solution: Automated system that:
- Pulls data from Google Sheets/project database
- Integrates weather API data
- Aggregates worker timesheets
- Generates professional PDF reports
- Distributes to stakeholders automatically
ROI: 80% reduction in daily reporting time (45 min → 9 min for review)
Report Structure
┌──────────────────────────────────────────────────────────────────────┐
│ DAILY CONSTRUCTION REPORT │
│ │
│ Project: ЖК Солнечный, Корпус 2 Date: 24.01.2026 │
│ Report #: DCR-2026-024 Weather: ☁️ -5°C │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ 1. WEATHER CONDITIONS │
│ ┌────────────┬────────────┬────────────┬────────────┐ │
│ │ Morning │ Afternoon │ Evening │ Impact │ │
│ │ -8°C ☀️ │ -5°C ☁️ │ -7°C 🌙 │ Normal │ │
│ └────────────┴────────────┴────────────┴────────────┘ │
│ │
│ 2. WORKFORCE │
│ ┌────────────────────────────────────────────────────┐ │
│ │ Category │ Planned │ Actual │ Hours │ │
│ ├────────────────────────────────────────────────────┤ │
│ │ GC Supervision │ 3 │ 3 │ 27 │ │
│ │ Electrical │ 12 │ 11 │ 88 │ │
│ │ Plumbing │ 8 │ 8 │ 64 │ │
│ │ HVAC │ 6 │ 6 │ 48 │ │
│ │ TOTAL │ 29 │ 28 │ 227 │ │
│ └────────────────────────────────────────────────────┘ │
│ │
│ 3. WORK COMPLETED TODAY │
│ • Electrical: Completed rough-in floors 5-6 │
│ • Plumbing: Installed risers section A │
│ • HVAC: Ductwork installation 60% complete │
│ │
│ 4. WORK PLANNED FOR TOMORROW │
│ • Electrical: Begin rough-in floor 7 │
│ • Plumbing: Continue risers section B │
│ • HVAC: Complete ductwork, begin testing │
│ │
│ 5. ISSUES / DELAYS │
│ • Material delay: Electrical panels (ETA: 26.01) │
│ • Weather: Expected snow may delay exterior work │
│ │
│ 6. SAFETY │
│ ✅ No incidents │
│ ✅ Toolbox talk completed: Fall protection │
│ │
│ 7. PHOTOS │
│ [Photo 1: Floor 5 electrical] [Photo 2: Riser installation] │
│ │
│ ───────────────────────────────────────────────────────────────── │
│ Prepared by: Иван Петров, Site Manager │
│ Approved by: ___________________ │
│ Distribution: Owner, Architect, PM │
└──────────────────────────────────────────────────────────────────────┘Python Implementation
import pandas as pd
from datetime import datetime, date
from typing import Optional, List, Dict
import requests
from reportlab.lib import colors
from reportlab.lib.pagesizes import A4
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, Image
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
import os
class DailyReportGenerator:
"""Generate professional daily construction reports"""
def __init__(self, config: dict):
self.config = config
self.weather_api_key = config.get('weather_api_key')
self.project_name = config.get('project_name')
self.report_date = config.get('report_date', date.today())
def get_weather_data(self, location: str) -> dict:
"""Fetch weather data from API"""
if not self.weather_api_key:
return self._mock_weather()
url = f"https://api.openweathermap.org/data/2.5/weather"
params = {
'q': location,
'appid': self.weather_api_key,
'units': 'metric',
'lang': 'ru'
}
response = requests.get(url, params=params)
if response.status_code == 200:
data = response.json()
return {
'temp': round(data['main']['temp']),
'description': data['weather'][0]['description'],
'humidity': data['main']['humidity'],
'wind_speed': round(data['wind']['speed']),
'icon': self._get_weather_icon(data['weather'][0]['main'])
}
return self._mock_weather()
def _get_weather_icon(self, condition: str) -> str:
icons = {
'Clear': '☀️',
'Clouds': '☁️',
'Rain': '🌧️',
'Snow': '❄️',
'Thunderstorm': '⛈️',
'Mist': '🌫️'
}
return icons.get(condition, '🌤️')
def _mock_weather(self) -> dict:
return {
'temp': -5,
'description': 'облачно',
'humidity': 65,
'wind_speed': 3,
'icon': '☁️'
}
def get_workforce_data(self, source: pd.DataFrame) -> dict:
"""Aggregate workforce data from timesheet"""
# Expected columns: trade, worker_name, hours_worked, planned_hours
summary = source.groupby('trade').agg({
'worker_name': 'count',
'hours_worked': 'sum',
'planned_hours': 'sum'
}).reset_index()
summary.columns = ['trade', 'actual_count', 'actual_hours', 'planned_hours']
# Calculate planned count (assuming 8-hour shifts)
summary['planned_count'] = (summary['planned_hours'] / 8).astype(int)
return {
'trades': summary.to_dict('records'),
'total_workers': summary['actual_count'].sum(),
'total_hours': summary['actual_hours'].sum(),
'total_planned': summary['planned_count'].sum()
}
def get_work_completed(self, tasks: pd.DataFrame) -> List[dict]:
"""Extract completed work from task system"""
# Filter completed tasks for today
completed = tasks[
(tasks['date'] == self.report_date.strftime('%d.%m.%Y')) &
(tasks['status'].isin(['Completed', 'Partial']))
]
work_items = []
for _, row in completed.iterrows():
work_items.append({
'trade': row['trade'],
'description': row['description'],