unit-price-database-manager

# Unit Price Database Manager for Construction

## Overview

Manage and maintain construction unit price databases. Update prices from vendors, apply location and time adjustments, track price history, and ensure estimating accuracy.

## Business Case

Accurate unit prices are critical for:
- **Competitive Bids**: Win work with accurate pricing
- **Cost Control**: Avoid budget surprises
- **Vendor Management**: Track supplier pricing
- **Historical Analysis**: Understand price trends

## Technical Implementation

```python
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional
from datetime import datetime, date
from decimal import Decimal
import pandas as pd
import json

@dataclass
class UnitPrice:
    code: str
    description: str
    unit: str
    base_price: Decimal
    labor_cost: Decimal
    material_cost: Decimal
    equipment_cost: Decimal
    effective_date: date
    expiration_date: Optional[date] = None
    source: str = ""
    vendor: str = ""
    location: str = "National Average"
    notes: str = ""
    tags: List[str] = field(default_factory=list)

@dataclass
class PriceUpdate:
    code: str
    old_price: Decimal
    new_price: Decimal
    change_pct: float
    updated_at: datetime
    updated_by: str
    reason: str

@dataclass
class VendorQuote:
    vendor_name: str
    item_code: str
    quoted_price: Decimal
    quote_date: date
    valid_until: date
    quantity_break: Optional[int] = None
    notes: str = ""

class UnitPriceDatabaseManager:
    """Manage construction unit price databases."""

    # Location adjustment factors
    LOCATION_FACTORS = {
        'New York': 1.32, 'San Francisco': 1.28, 'Los Angeles': 1.15,
        'Chicago': 1.12, 'Boston': 1.18, 'Seattle': 1.08,
        'Denver': 1.02, 'National Average': 1.00,
        'Houston': 0.92, 'Dallas': 0.89, 'Phoenix': 0.93,
        'Atlanta': 0.91, 'Miami': 0.95
    }

    def __init...