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'],
            'status': row['status'],
            'notes': row.get('notes', '')
        })

    return work_items

def get_work_planned(self, tasks: pd.DataFrame) -> List[dict]:
    """Get planned work for tomorrow"""
    tomorrow = self.report_date + pd.Timedelta(days=1)

    planned = tasks[
        tasks['date'] == tomorrow.strftime('%d.%m.%Y')
    ]

    work_items = []
    for _, row in planned.iterrows():
        work_items.append({
            'trade': row['trade'],
            'description': row['description'],
            'priority': row.get('priority', 'Medium')
        })

    return work_items

def get_issues(self, issues_log: pd.DataFrame) -> List[dict]:
    """Get active issues and delays"""
    active = issues_log[
        (issues_log['status'] == 'Open') |
        (issues_log['date_reported'] == self.report_date.strftime('%d.%m.%Y'))
    ]

    return active[['category', 'description', 'impact', 'resolution_date']].to_dict('records')

def get_safety_data(self, safety_log: pd.DataFrame) -> dict:
    """Get safety information for the day"""
    today_incidents = safety_log[
        safety_log['date'] == self.report_date.strftime('%d.%m.%Y')
    ]

    return {
        'incidents': len(today_incidents[today_incidents['type'] == 'Incident']),
        'near_misses': len(today_incidents[today_incidents['type'] == 'Near Miss']),
        'toolbox_talk': today_incidents[
            today_incidents['type'] == 'Toolbox Talk'
        ]['topic'].tolist(),
        'observations': today_incidents[
            today_incidents['type'] == 'Observation'
        ]['description'].tolist()
    }

def generate_report(self, data: dict, output_path: str) -> str:
    """Generate PDF report"""

    doc = SimpleDocTemplate(
        output_path,
        pagesize=A4,
        rightMargin=2*cm,
        leftMargin=2*cm,
        topMargin=2*cm,
        bottomMargin=2*cm
    )

    styles = getSampleStyleSheet()
    title_style = ParagraphStyle(
        'Title',
        parent=styles['Heading1'],
        fontSize=16,
        alignment=1,
        spaceAfter=12
    )
    heading_style = ParagraphStyle(
        'Heading',
        parent=styles['Heading2'],
        fontSize=12,
        spaceBefore=12,
        spaceAfter=6
    )

    elements = []

    # Title
    elements.append(Paragraph(
        f"DAILY CONSTRUCTION REPORT",
        title_style
    ))

    # Header info
    header_data = [
        ['Project:', self.project_name, 'Date:', self.report_date.strftime('%d.%m.%Y')],
        ['Report #:', data.get('report_number', 'DCR-001'), 'Weather:', f"{data['weather']['icon']} {data['weather']['temp']}°C"]
    ]
    header_table = Table(header_data, colWidths=[3*cm, 6*cm, 3*cm, 4*cm])
    header_table.setStyle(TableStyle([
        ('FONTNAME', (0, 0), (-1, -1), 'Helvetica'),
        ('FONTSIZE', (0, 0), (-1, -1), 10),
        ('FONTNAME', (0, 0), (0, -1), 'Helvetica-Bold'),
        ('FONTNAME', (2, 0), (2, -1), 'Helvetica-Bold'),
    ]))
    elements.append(header_table)
    elements.append(Spacer(1, 12))

    # Weather section
    elements.append(Paragraph("1. WEATHER CONDITIONS", heading_style))
    weather = data['weather']
    weather_text = f"""
    Temperature: {weather['temp']}°C | Humidity: {weather['humidity']}% |
    Wind: {weather['wind_speed']} m/s | Conditions: {weather['description']}
    """
    elements.append(Paragraph(weather_text, styles['Normal']))

    # Workforce section
    elements.append(Paragraph("2. WORKFORCE", heading_style))
    workforce = data['workforce']
    workforce_data = [['Trade', 'Planned', 'Actual', 'Hours']]
    for trade in workforce['trades']:
        workforce_data.append([
            trade['trade'],
            str(trade['planned_count']),
            str(trade['actual_count']),
            str(int(trade['actual_hours']))
        ])
    workforce_data.append([
        'TOTAL',
        str(workforce['total_planned']),
        str(workforce['total_workers']),
        str(int(workforce['total_hours']))
    ])

    workforce_table = Table(workforce_data, colWidths=[6*cm, 3*cm, 3*cm, 3*cm])
    workforce_table.setStyle(TableStyle([
        ('BACKGROUND', (0, 0), (-1, 0), colors.grey),
        ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
        ('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
        ('FONTNAME', (0, -1), (-1, -1), 'Helvetica-Bold'),
        ('GRID', (0, 0), (-1, -1), 1, colors.black),
        ('ALIGN', (1, 0), (-1, -1), 'CENTER'),
    ]))
    elements.append(workforce_table)

    # Work completed
    elements.append(Paragraph("3. WORK COMPLETED TODAY", heading_style))
    for item in data.get('work_completed', []):
        bullet = f"• {item['trade']}: {item['description']}"
        if item.get('notes'):
            bullet += f" ({item['notes']})"
        elements.append(Paragraph(bullet, styles['Normal']))

    # Work planned
    elements.append(Paragraph("4. WORK PLANNED FOR TOMORROW", heading_style))
    for item in data.get('work_planned', []):
        bullet = f"• {item['trade']}: {item['description']}"
        elements.append(Paragraph(bullet, styles['Normal']))

    # Issues
    elements.append(Paragraph("5. ISSUES / DELAYS", heading_style))
    issues = data.get('issues', [])
    if issues:
        for issue in issues:
            bullet = f"• {issue['category']}: {issue['description']}"
            if issue.get('resolution_date'):
                bullet += f" (ETA: {issue['resolution_date']})"
            elements.append(Paragraph(bullet, styles['Normal']))
    else:
        elements.append(Paragraph("No significant issues reported.", styles['Normal']))

    # Safety
    elements.append(Paragraph("6. SAFETY", heading_style))
    safety = data.get('safety', {})
    if safety.get('incidents', 0) == 0:
        elements.append(Paragraph("✅ No incidents reported", styles['Normal']))
    else:
        elements.append(Paragraph(f"⚠️ {safety['incidents']} incident(s) reported", styles['Normal']))

    if safety.get('toolbox_talk'):
        elements.append(Paragraph(f"✅ Toolbox talk: {', '.join(safety['toolbox_talk'])}", styles['Normal']))

    # Signature block
    elements.append(Spacer(1, 24))
    elements.append(Paragraph("─" * 60, styles['Normal']))
    elements.append(Paragraph(f"Prepared by: {data.get('prepared_by', '_________________')}", styles['Normal']))
    elements.append(Paragraph(f"Date: {datetime.now().strftime('%d.%m.%Y %H:%M')}", styles['Normal']))

    # Build PDF
    doc.build(elements)
    return output_path

Usage Example

def generate_daily_report( project_name: str, location: str, timesheet_path: str, tasks_path: str, output_dir: str ) -> str: """Generate daily report from source files"""

# Initialize generator
generator = DailyReportGenerator({
    'project_name': project_name,
    'weather_api_key': os.environ.get('WEATHER_API_KEY'),
    'report_date': date.today()
})

# Load data
timesheet = pd.read_excel(timesheet_path)
tasks = pd.read_excel(tasks_path)

# Compile report data
report_data = {
    'report_number': f"DCR-{date.today().strftime('%Y-%j')}",
    'weather': generator.get_weather_data(location),
    'workforce': generator.get_workforce_data(timesheet),
    'work_completed': generator.get_work_completed(tasks),
    'work_planned': generator.get_work_planned(tasks),
    'issues': [],  # Load from issues log if available
    'safety': {
        'incidents': 0,
        'toolbox_talk': ['Fall Protection'],
        'near_misses': 0
    },
    'prepared_by': 'Site Manager'
}

# Generate PDF
output_path = os.path.join(
    output_dir,
    f"Daily_Report_{date.today().strftime('%Y%m%d')}.pdf"
)

return generator.generate_report(report_data, output_path)

if name == "main": report_path = generate_daily_report( project_name="ЖК Солнечный, Корпус 2", location="Moscow,RU", timesheet_path="timesheet.xlsx", tasks_path="tasks.xlsx", output_dir="./reports" ) print(f"Report generated: {report_path}")

Data Sources Integration

From n8n Project Management System

Connect to Google Sheets used by n8n bot

def get_data_from_project_management(spreadsheet_id: str) -> dict: """Pull data from n8n project management system""" import gspread

gc = gspread.service_account()
sh = gc.open_by_key(spreadsheet_id)

# Get completed tasks
tasks_sheet = sh.worksheet('Tasks')
tasks = pd.DataFrame(tasks_sheet.get_all_records())

# Get workforce from worker responses
workers_sheet = sh.worksheet('Workers')
workers = pd.DataFrame(workers_sheet.get_all_records())

return {
    'tasks': tasks,
    'workers': workers
}

From Timesheet System

Integrate with common timesheet formats

def import_timesheet(source: str, format: str = 'excel') -> pd.DataFrame: """Import timesheet data from various sources"""

if format == 'excel':
    df = pd.read_excel(source)
elif format == 'csv':
    df = pd.read_csv(source)
elif format == 'procore':
    df = fetch_procore_timesheet(source)

# Standardize columns
df = df.rename(columns={
    'Trade': 'trade',
    'Worker': 'worker_name',
    'Hours': 'hours_worked',
    'Planned Hours': 'planned_hours'
})

return df

n8n Workflow for Automation

name: Daily Report Automation trigger: type: cron expression: "0 18 * * 1-6" # 6 PM daily

steps:

• collect_task_data: node: Google Sheets operation: readRows sheet: Tasks filter: Date = TODAY()

• collect_timesheet: node: Google Sheets operation: readRows sheet: Timesheet filter: Date = TODAY()

• get_weather: node: HTTP Request url: "https://api.openweathermap.org/data/2.5/weather" params: q: "Moscow,RU" appid: "{{$env.WEATHER_API_KEY}}"

• generate_report: node: Code (Python) code: | from daily_report import generate_report return generate_report(items)

• upload_to_drive: node: Google Drive operation: upload file: "={{$json.report_path}}" folder: "Daily Reports"

• send_notification: node: Telegram operation: sendDocument chatId: "MANAGERS_GROUP_ID" document: "={{$json.drive_url}}" caption: | 📋 Daily Report - {{$now.format('DD.MM.YYYY')}}

  Workforce: {{$json.total_workers}} workers
  Tasks completed: {{$json.completed_tasks}}
  Issues: {{$json.open_issues}}
  

Report Distribution

def distribute_report(report_path: str, recipients: dict): """Distribute report to stakeholders"""

# Email distribution
for email in recipients.get('email', []):
    send_email(
        to=email,
        subject=f"Daily Report - {date.today().strftime('%d.%m.%Y')}",
        body="Please find attached the daily construction report.",
        attachment=report_path
    )

# Telegram distribution
for chat_id in recipients.get('telegram', []):
    send_telegram_document(
        chat_id=chat_id,
        document_path=report_path,
        caption=f"📋 Daily Report - {date.today().strftime('%d.%m.%Y')}"
    )

# Upload to project portal
if portal_url := recipients.get('portal'):
    upload_to_portal(portal_url, report_path)

Best Practices

• Data Collection: Set up automated data collection to minimize manual input

• Review Time: Allow 5-10 minutes for manager review before distribution

• Photos: Include 3-5 key photos showing progress

• Issues: Be specific about impacts and resolution dates

• Distribution: Send by 6-7 PM to allow stakeholder review

"A good daily report tells the story of the day in 2 minutes or less."