cwicr-report-generator

name	cwicr-report-generator
description	Generate professional cost estimation reports from CWICR calculations. HTML, PDF, Excel outputs with charts and breakdowns.
homepage	https://datadrivenconstruction.io
metadata	{"openclaw":{"emoji":"🗄️","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"]}}}

CWICR Report Generator

Overview

Generate professional cost reports from CWICR calculations - executive summaries, detailed breakdowns, charts, and export to multiple formats.

Python Implementation

import pandas as pd
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
import json


@dataclass
class ReportSection:
    
    title: 
    content: 
    chart_type: [] = 
    chart_data: [] = 



 :
    
    project_name: 
    generated_date: datetime
    total_cost: 
    currency: 
    sections: [ReportSection]
    line_items: []
    summary: [, ]


 :
    

     ():
        .project_name = project_name
        .currency = currency
        .sections: [ReportSection] = []
        .line_items: [] = []

     ():
        

        content = 

        .sections.append(ReportSection(
            title=,
            content=content,
            chart_type=,
            chart_data={
                : [, , , , ],
                : [
                    summary_data.get(, ),
                    summary_data.get(, ),
                    summary_data.get(, ),
                    summary_data.get(, ),
                    summary_data.get(, )
                ]
            }
        ))

     ():
        

        rows = 
         category, cost  (breakdown.items(), key= x: -x[]):
            rows += 

        content = 

        .sections.append(ReportSection(
            title=,
            content=content,
            chart_type=,
            chart_data={
                : (breakdown.keys()),
                : (breakdown.values())
            }
        ))

     ():
        
        .line_items = items

        rows = 
         item  items[:]:  
            rows += 

        content = 

        .sections.append(ReportSection(
            title=,
            content=content
        ))

     () -> :
        

        sections_html = 
         section  .sections:
            sections_html += 

        html = 

         html

     () -> :
        
        html = .generate_html()
         (output_path, , encoding=)  f:
            f.write(html)
         output_path

     () -> :
        

         pd.ExcelWriter(output_path, engine=)  writer:
            
             .sections:
                summary_data = []
                 section  .sections:
                     section.chart_data:
                         i, label  (section.chart_data.get(, [])):
                            summary_data.append({
                                : label,
                                : section.chart_data.get(, [])[i]
                            })
                 summary_data:
                    pd.DataFrame(summary_data).to_excel(
                        writer, sheet_name=, index=)

            
             .line_items:
                pd.DataFrame(.line_items).to_excel(
                    writer, sheet_name=, index=)

         output_path

     () -> :
        

        report = {
            : .project_name,
            : datetime.now().isoformat(),
            : .currency,
            : [
                {
                    : s.title,
                    : s.chart_data
                }  s  .sections
            ],
            : .line_items
        }

         json.dumps(report, indent=)


 :
    


     () -> CWICRReportGenerator:
        

        gen = CWICRReportGenerator(project_name)

        
        summary = {
            : df[].()    df.columns  ,
            : df[].()    df.columns  ,
            : df[].()    df.columns  ,
            : df[].()    df.columns  ,
            : df[].()    df.columns  ,
            : df[].()    df.columns  
        }
        gen.add_summary(summary)

        
           df.columns    df.columns:
            breakdown = df.groupby()[].().to_dict()
            gen.add_breakdown_by_category(breakdown)

        
        items = df.to_dict()
        gen.add_line_items(items)

         gen