cwicr-cost-calculator

name	cwicr-cost-calculator
description	Calculate construction costs using DDC CWICR resource-based methodology. Break down costs into labor, materials, equipment with transparent pricing.
homepage	https://datadrivenconstruction.io
metadata	{"openclaw":{"emoji":"💰","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"]}}}

CWICR Cost Calculator

Business Case

Problem Statement

Traditional cost estimation often produces "black box" estimates with hidden markups. Stakeholders need:

• Transparent cost breakdowns
• Traceable pricing logic
• Auditable calculations
• Resource-level detail

Solution

Resource-based cost calculation using CWICR methodology that separates physical norms (labor hours, material quantities) from volatile prices, enabling transparent and auditable estimates.

Business Value

• Full transparency - Every cost component visible
• Auditable - Traceable calculation logic
• Flexible - Update prices without changing norms
• Accurate - Based on 55,000+ validated work items

Technical Implementation

Prerequisites

pip install pandas numpy

Python Implementation

import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
from datetime import datetime


class CostComponent(Enum):
    """Cost breakdown components."""
    LABOR = "labor"
    MATERIAL = "material"
    EQUIPMENT = "equipment"
    OVERHEAD = "overhead"
    PROFIT = "profit"
    TOTAL = "total"


class CostStatus(Enum):
    """Cost calculation status."""
    CALCULATED = "calculated"
    ESTIMATED = "estimated"
    MISSING_DATA = "missing_data"
    ERROR = "error"


@dataclass
class CostBreakdown:
    """Detailed cost breakdown for a work item."""
    work_item_code: str
    description: str
    unit: str
    quantity: float

    labor_cost: float = 0.0
    material_cost: float = 0.0
    equipment_cost: float = 0.0
    overhead_cost:  = 
    profit_cost:  = 

    unit_price:  = 
    total_cost:  = 

    labor_hours:  = 
    labor_rate:  = 

    resources: [[, ]] = field(default_factory=)
    status: CostStatus = CostStatus.CALCULATED

     () -> [, ]:
         {
            : .work_item_code,
            : .description,
            : .unit,
            : .quantity,
            : .labor_cost,
            : .material_cost,
            : .equipment_cost,
            : .overhead_cost,
            : .profit_cost,
            : .total_cost,
            : .status.value
        }



 :
    
    total_cost: 
    labor_total: 
    material_total: 
    equipment_total: 
    overhead_total: 
    profit_total: 

    item_count: 
    currency: 
    calculated_at: datetime

    breakdown_by_category: [, ] = field(default_factory=)


 :
    

    DEFAULT_OVERHEAD_RATE =   
    DEFAULT_PROFIT_RATE =    

     ():
        
        .data = cwicr_data
        .overhead_rate = overhead_rate  .DEFAULT_OVERHEAD_RATE
        .profit_rate = profit_rate  .DEFAULT_PROFIT_RATE
        .currency = currency

        
        ._index_data()

     ():
        
           .data.columns:
            ._code_index = .data.set_index()
        :
            ._code_index = 

     () -> CostBreakdown:
        

        
         ._code_index     work_item_code  ._code_index.index:
            item = ._code_index.loc[work_item_code]
        :
            
            matches = .data[
                .data[]..contains(work_item_code, =, na=)
            ]
             matches.empty:
                 CostBreakdown(
                    work_item_code=work_item_code,
                    description=,
                    unit=,
                    quantity=quantity,
                    status=CostStatus.MISSING_DATA
                )
            item = matches.iloc[]

        
        labor_unit = (item.get(, )  )
        material_unit = (item.get(, )  )
        equipment_unit = (item.get(, )  )

        
         price_overrides:
               price_overrides:
                labor_norm = (item.get(, )  )
                labor_unit = labor_norm * price_overrides[]
               price_overrides:
                material_unit *= price_overrides[]
               price_overrides:
                equipment_unit *= price_overrides[]

        
        labor_cost = labor_unit * quantity
        material_cost = material_unit * quantity
        equipment_cost = equipment_unit * quantity

        
        direct_cost = labor_cost + material_cost + equipment_cost

        
        overhead_cost = direct_cost * .overhead_rate
        profit_cost = (direct_cost + overhead_cost) * .profit_rate

        
        total_cost = direct_cost + overhead_cost + profit_cost

        
        unit_price = total_cost / quantity  quantity >   

         CostBreakdown(
            work_item_code=work_item_code,
            description=(item.get(, )),
            unit=(item.get(, )),
            quantity=quantity,
            labor_cost=labor_cost,
            material_cost=material_cost,
            equipment_cost=equipment_cost,
            overhead_cost=overhead_cost,
            profit_cost=profit_cost,
            unit_price=unit_price,
            total_cost=total_cost,
            labor_hours=(item.get(, )  ) * quantity,
            labor_rate=(item.get(, )  ),
            status=CostStatus.CALCULATED
        )

     () -> CostSummary:
        

        breakdowns = []
         item  items:
            code = item.get()  item.get()
            qty = item.get(, )
            overrides = item.get()

            breakdown = .calculate_item_cost(code, qty, overrides)
            breakdowns.append(breakdown)

        
        labor_total = (b.labor_cost  b  breakdowns)
        material_total = (b.material_cost  b  breakdowns)
        equipment_total = (b.equipment_cost  b  breakdowns)
        overhead_total = (b.overhead_cost  b  breakdowns)
        profit_total = (b.profit_cost  b  breakdowns)
        total_cost = (b.total_cost  b  breakdowns)

        
        breakdown_by_category = {}
         group_by_category:
             b  breakdowns:
                
                category = b.work_item_code.split()[]    b.work_item_code  
                 category   breakdown_by_category:
                    breakdown_by_category[category] = 
                breakdown_by_category[category] += b.total_cost

         CostSummary(
            total_cost=total_cost,
            labor_total=labor_total,
            material_total=material_total,
            equipment_total=equipment_total,
            overhead_total=overhead_total,
            profit_total=profit_total,
            item_count=(breakdowns),
            currency=.currency,
            calculated_at=datetime.now(),
            breakdown_by_category=breakdown_by_category
        )

     () -> pd.DataFrame:
        

        results = []
         _, row  qto_df.iterrows():
            code = row[code_column]
            qty = row[quantity_column]

            breakdown = .calculate_item_cost(code, qty)
            result = breakdown.to_dict()

            
             col  qto_df.columns:
                 col   result:
                    result[] = row[col]

            results.append(result)

         pd.DataFrame(results)

     () -> pd.DataFrame:
        
        adjusted = base_costs.copy()

           adjusted.columns    region_factors:
            adjusted[] *= region_factors[]

           adjusted.columns    region_factors:
            adjusted[] *= region_factors[]

           adjusted.columns    region_factors:
            adjusted[] *= region_factors[]

        
        adjusted[] = (
            adjusted.get(, ) +
            adjusted.get(, ) +
            adjusted.get(, )
        )
        adjusted[] = adjusted[] * ( + .overhead_rate) * ( + .profit_rate)

         adjusted

     () -> [, ]:
        
         {
            : estimate2.total_cost - estimate1.total_cost,
            : (
                (estimate2.total_cost - estimate1.total_cost) /
                estimate1.total_cost *   estimate1.total_cost >   
            ),
            : estimate2.labor_total - estimate1.labor_total,
            : estimate2.material_total - estimate1.material_total,
            : estimate2.equipment_total - estimate1.equipment_total,
            : estimate2.item_count - estimate1.item_count
        }


 :
    

     ():
        .calculator = calculator

     () -> [, ]:
        
        summary = .calculator.calculate_estimate(items)

         {
            : datetime.now().isoformat(),
            : summary.currency,
            : (summary.total_cost, ),
            : {
                : (summary.labor_total, ),
                : (summary.material_total, ),
                : (summary.equipment_total, ),
                : (summary.overhead_total, ),
                : (summary.profit_total, )
            },
            : {
                : (summary.labor_total / summary.total_cost * , )  summary.total_cost >   ,
                : (summary.material_total / summary.total_cost * , )  summary.total_cost >   ,
                : (summary.equipment_total / summary.total_cost * , )  summary.total_cost >   ,
            },
            : summary.item_count,
            : summary.breakdown_by_category
        }

     () -> pd.DataFrame:
        
        results = []

         item  items:
            code = item.get()  item.get()
            qty = item.get(, )

            breakdown = .calculator.calculate_item_cost(code, qty)
            results.append(breakdown.to_dict())

        df = pd.DataFrame(results)

        
        totals = df[[, , ,
                     , , ]].()
        totals[] = 
        totals[] = 

        df = pd.concat([df, pd.DataFrame([totals])], ignore_index=)

         df



 () -> :
    
    calc = CWICRCostCalculator(cwicr_data)
    breakdown = calc.calculate_item_cost(work_item_code, quantity)
     breakdown.total_cost


 () -> [, ]:
    
    calc = CWICRCostCalculator(cwicr_data)
    report = CostReportGenerator(calc)
     report.generate_summary_report(items)

Quick Start

import pandas as pd
from cwicr_data_loader import CWICRDataLoader

# Load CWICR data
loader = CWICRDataLoader()
cwicr = loader.load("TR_workitems_costs_resources_DDC_CWICR.parquet")

# Initialize calculator
calc = CWICRCostCalculator(cwicr)

# Calculate single item
breakdown = calc.calculate_item_cost("CONC-001", quantity=150)
print(f"Total: ${breakdown.total_cost:,.2f}")
print(f"  Labor: ${breakdown.labor_cost:,.2f}")
print(f"  Material: ${breakdown.material_cost:,.2f}")
print(f"  Equipment: ${breakdown.equipment_cost:,.2f}")

Common Use Cases

1. Project Estimate

items = [
    {'work_item_code': 'CONC-001', 'quantity': 150},
    {'work_item_code': 'EXCV-002', 'quantity': 200},
    {'work_item_code': 'REBAR-003', 'quantity': 15000}  # kg
]

summary = calc.calculate_estimate(items)
print(f"Project Total: ${summary.total_cost:,.2f}")

2. QTO Integration

# Load BIM quantities
qto = pd.read_excel("quantities.xlsx")

# Calculate costs
costs = calc.calculate_from_qto(qto,
    code_column='work_item',
    quantity_column='quantity'
)
print(costs[['description', 'quantity', 'total_cost']])

3. Regional Adjustment

# Apply Berlin pricing
berlin_factors = {
    'labor': 1.15,      # 15% higher labor
    'material': 0.95,   # 5% lower materials
    'equipment': 1.0
}

adjusted = calc.apply_regional_factors(costs, berlin_factors)

Resources

• GitHub: OpenConstructionEstimate-DDC-CWICR
• DDC Book: Chapter 3.1 - Construction Cost Estimation