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daily-progress-report

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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

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

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

text = reporter.generate_text_report(report)
print(text)

2. Track Delays

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

3. Calculate Metrics

summary = reporter.calculate_summary(report)
print(f"Productivity: {summary['total_manhours']} man-hours")

Resources

  • DDC Book: Chapter 4.1 - Site Data Collection

Source

git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/blob/main/1_DDC_Toolkit/Analytics/daily-progress-report/SKILL.mdView on GitHub

Overview

This skill automates daily progress reporting by aggregating site data on work completed, labor hours, equipment usage, and weather. It standardizes the report format to save time for site managers and improve data accuracy and traceability.

How This Skill Works

Written in Python, it uses pandas and dataclasses to build a DailyReport from structured inputs. It determines work status (completed, in_progress, delayed, not_started) from planned versus actual quantities and aggregates labor, equipment, weather, delays, and safety info into a coherent daily summary that can be extended for export.

When to Use It

  • Daily field reporting for construction sites with a structured data feed
  • Projects requiring consistent, auditable daily summaries
  • Weather-influenced reporting and risk tracking
  • Data-driven dashboards fed by standardized site reports
  • New sites or multi-crew projects needing a unified reporting format

Quick Start

  1. Step 1: Install Python3 and pandas (and any needed dependencies)
  2. Step 2: Create a reporter with DailyProgressReporter('Project Name','Project-Number')
  3. Step 3: Call create_report with date, weather, high/low temps, and preparer; then add activities, labor, and equipment as needed

Best Practices

  • Define a single source of truth for input data (work, labor, equipment, weather)
  • Validate data types (float for quantities, int for crew sizes, enums for status)
  • Leverage the status logic to accurately reflect progress
  • Include weather, delays, and safety incidents for context
  • Test with representative data and edge cases (zero planned or actual)

Example Use Cases

  • High-rise residential project uses the daily-progress-report to generate end-of-day briefs for stakeholders
  • Bridge rehabilitation project tracks daily progress and weather impacts for schedule decisions
  • Offshore wind farm construction logs crew and equipment usage to optimize deployments
  • Commercial complex construction consolidates multiple subcontractor inputs into a single daily report
  • Urban development site logs visitors and deliveries to support site access planning

Frequently Asked Questions

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