--- name: "daily-progress-report" description: "Generate automated daily progress reports from site data. Track work completed, labor hours, equipment usage, and weather conditions." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "📊", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}} --- # Daily Progress Report Generator

## Business Case

### Problem Statement Site managers spend hours creating daily reports: - Manual data collection - Inconsistent formats - Delayed submissions - Missing information

### Solution Automated daily progress report generation from structured site data inputs.

## Technical Implementation

```python import pandas as pd from datetime import datetime, date from typing import Dict, Any, List from dataclasses import dataclass from enum import Enum

class WeatherCondition(Enum): CLEAR = "clear" CLOUDY = "cloudy" RAIN = "rain" SNOW = "snow" WIND = "wind" EXTREME = "extreme"

class WorkStatus(Enum): COMPLETED = "completed" IN_PROGRESS = "in_progress" DELAYED = "delayed" NOT_STARTED = "not_started"

@dataclass class WorkActivity: activity_id: str description: str location: str planned_qty: float actual_qty: float unit: str status: WorkStatus crew_size: int hours_worked: float notes: str = ""

@dataclass class LaborEntry: trade: str company: str workers: int hours: float overtime_hours: float = 0

@dataclass class EquipmentEntry: equipment_type: str equipment_id: str hours_used: float status: str # active, idle, maintenance operator: str = ""

@dataclass class DailyReport: report_date: date project_name: str project_number: str weather: WeatherCondition temperature_high: float temperature_low: float work_activities: List[WorkActivity] labor: List[LaborEntry] equipment: List[EquipmentEntry] delays: List[str] safety_incidents: int visitors: List[str] deliveries: List[str] prepared_by: str

class DailyProgressReporter: """Generate daily progress reports."""

def __init__(self, project_name: str, project_number: str): self.project_name = project_name self.project_number = project_number

def create_report(self, report_date: date, weather: WeatherCondition, temp_high: float, temp_low: float, prepared_by: str) -> DailyReport: """Create new daily report."""

return DailyReport( report_date=report_date, project_name=self.project_name, project_number=self.project_number, weather=weather, temperature_high=temp_high, temperature_low=temp_low, work_activities=[], labor=[], equipment=[], delays=[], safety_incidents=0, visitors=[], deliveries=[], prepared_by=prepared_by )

def add_work_activity(self, report: DailyReport, activity_id: str, description: str, location: str, planned_qty: float, actual_qty: float, unit: str, crew_size: int, hours_worked: float, notes: str = ""): """Add work activity to report."""

# Determine status if actual_qty >= planned_qty: status = WorkStatus.COMPLETED elif actual_qty > 0: status = WorkStatus.IN_PROGRESS elif actual_qty == 0 and planned_qty > 0: status = WorkStatus.DELAYED else: status = WorkStatus.NOT_STARTED

activity = WorkActivity( activity_id=activity_id, description=description, location=location, planned_qty=planned_qty, actual_qty=actual_qty, unit=unit, status=status, crew_size=crew_size, hours_worked=hours_worked, notes=notes )

report.work_activities.append(activity)

def add_labor(self, report: DailyReport, trade: str, company: str, workers: int, hours: float, overtime_hours: float = 0): """Add labor entry."""

report.labor.append(LaborEntry( trade=trade, company=company, workers=workers, hours=hours, overtime_hours=overtime_hours ))

def add_equipment(self, report: DailyReport, equipment_type: str, equipment_id: str, hours_used: float, status: str, operator: str = ""): """Add equipment entry."""

report.equipment.append(EquipmentEntry( equipment_type=equipment_type, equipment_id=equipment_id, hours_used=hours_used, status=status, operator=operator ))

def calculate_summary(self, report: DailyReport) -> Dict[str, Any]: """Calculate report summary metrics."""

total_workers = sum(l.workers for l in report.labor) total_manhours = sum(l.workers * l.hours for l in report.labor) total_overtime = sum(l.workers * l.overtime_hours for l in report.labor) equipment_hours = sum(e.hours_used for e in report.equipment)

completed = sum(1 for a in report.work_activities if a.status == WorkStatus.COMPLETED) in_progress = sum(1 for a in report.work_activities if a.status == WorkStatus.IN_PROGRESS) delayed = sum(1 for a in report.work_activities if a.status == WorkStatus.DELAYED)

return { 'total_workers': total_workers, 'total_manhours': round(total_manhours, 1), 'total_overtime': round(total_overtime, 1), 'equipment_hours': round(equipment_hours, 1), 'activities_completed': completed, 'activities_in_progress': in_progress, 'activities_delayed': delayed, 'safety_incidents': report.safety_incidents, 'deliveries_count': len(report.deliveries) }

def export_to_excel(self, report: DailyReport, output_path: str) -> str: """Export report to Excel."""

with pd.ExcelWriter(output_path, engine='openpyxl') as writer: # Header header_df = pd.DataFrame([{ 'Project': report.project_name, 'Project #': report.project_number, 'Date': report.report_date, 'Weather': report.weather.value, 'High Temp': report.temperature_high, 'Low Temp': report.temperature_low, 'Prepared By': report.prepared_by }]) header_df.to_excel(writer, sheet_name='Summary', index=False)

# Work Activities if report.work_activities: activities_df = pd.DataFrame([ { 'Activity ID': a.activity_id, 'Description': a.description, 'Location': a.location, 'Planned': a.planned_qty, 'Actual': a.actual_qty, 'Unit': a.unit, 'Status': a.status.value, 'Crew': a.crew_size, 'Hours': a.hours_worked, 'Notes': a.notes } for a in report.work_activities ]) activities_df.to_excel(writer, sheet_name='Work Activities', index=False)

# Labor if report.labor: labor_df = pd.DataFrame([ { 'Trade': l.trade, 'Company': l.company, 'Workers': l.workers, 'Hours': l.hours, 'Overtime': l.overtime_hours, 'Total Hours': l.workers * (l.hours + l.overtime_hours) } for l in report.labor ]) labor_df.to_excel(writer, sheet_name='Labor', index=False)

# Equipment if report.equipment: equip_df = pd.DataFrame([ { 'Type': e.equipment_type, 'ID': e.equipment_id, 'Hours': e.hours_used, 'Status': e.status, 'Operator': e.operator } for e in report.equipment ]) equip_df.to_excel(writer, sheet_name='Equipment', index=False)

return output_path

def generate_text_report(self, report: DailyReport) -> str: """Generate text version of report."""

summary = self.calculate_summary(report)

lines = [ f"DAILY PROGRESS REPORT", f"=" * 50, f"Project: {report.project_name}", f"Project #: {report.project_number}", f"Date: {report.report_date}", f"Prepared by: {report.prepared_by}", f"", f"WEATHER CONDITIONS", f"-" * 30, f"Conditions: {report.weather.value}", f"Temperature: {report.temperature_low}°C - {report.temperature_high}°C", f"", f"SUMMARY", f"-" * 30, f"Total Workers: {summary['total_workers']}", f"Total Man-hours: {summary['total_manhours']}", f"Equipment Hours: {summary['equipment_hours']}", f"Activities Completed: {summary['activities_completed']}", f"Activities In Progress: {summary['activities_in_progress']}", f"Activities Delayed: {summary['activities_delayed']}", f"Safety Incidents: {summary['safety_incidents']}", ]

if report.delays: lines.extend([f"", f"DELAYS", f"-" * 30]) for delay in report.delays: lines.append(f"• {delay}")

return "\n".join(lines) ```

## Quick Start

```python from datetime import date

# Initialize reporter reporter = DailyProgressReporter("Office Tower A", "PRJ-2024-001")

# Create report report = reporter.create_report( report_date=date.today(), weather=WeatherCondition.CLEAR, temp_high=28, temp_low=18, prepared_by="John Smith" )

# Add activities reporter.add_work_activity( report, activity_id="A-101", description="Pour concrete slab Level 3", location="Level 3, Zone A", planned_qty=150, actual_qty=150, unit="m3", crew_size=8, hours_worked=10 )

# Add labor reporter.add_labor(report, "Concrete", "ABC Concrete Co", 8, 10, 2)

# Export reporter.export_to_excel(report, "daily_report.xlsx") ```

## Common Use Cases

### 1. Generate Text Summary ```python text = reporter.generate_text_report(report) print(text) ```

### 2. Track Delays ```python report.delays.append("Weather delay - rain from 14:00-16:00") report.delays.append("Material delivery late by 2 hours") ```

### 3. Calculate Metrics ```python summary = reporter.calculate_summary(report) print(f"Productivity: {summary['total_manhours']} man-hours") ```

## Resources - **DDC Book**: Chapter 4.1 - Site Data Collection