Skip to content
Back to skills

Cwicr Multilingual

ASecurity

Work with CWICR database across 9 languages. Cross-language matching, translation, and regional pricing.

  • 299 stars
  • 0 votes
  • 0 copies
  • 2 views
  • Added February 7, 2026
datapythondatabase

Security analysis

A100/100

Scanned February 12, 2026

npx -y skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill cwicr-multilingual --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Cwicr Multilingual?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Cwicr Multilingual
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/datadrivenconstruction-cwicr-multilingual/badge)](https://www.skillsdirectory.com/skills/datadrivenconstruction-cwicr-multilingual)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
slug: "cwicr-multilingual"
display_name: "CWICR Multilingual"
description: "Work with CWICR database across 9 languages. Cross-language matching, translation, and regional pricing."
---

# CWICR Multilingual Support

## Overview
CWICR database supports 9 languages with consistent work item codes. This skill enables cross-language work item matching, translation, and regional price comparison.

## Supported Languages

| Code | Language | Region | Currency |
|------|----------|--------|----------|
| AR | Arabic | Dubai | AED |
| DE | German | Berlin | EUR |
| EN | English | Toronto | CAD |
| ES | Spanish | Barcelona | EUR |
| FR | French | Paris | EUR |
| HI | Hindi | Mumbai | INR |
| PT | Portuguese | São Paulo | BRL |
| RU | Russian | St. Petersburg | RUB |
| ZH | Chinese | Shanghai | CNY |

## Python Implementation

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


class CWICRLanguage(Enum):
    """Supported CWICR languages."""
    ARABIC = ("ar", "Arabic", "AED", "Dubai")
    GERMAN = ("de", "German", "EUR", "Berlin")
    ENGLISH = ("en", "English", "CAD", "Toronto")
    SPANISH = ("es", "Spanish", "EUR", "Barcelona")
    FRENCH = ("fr", "French", "EUR", "Paris")
    HINDI = ("hi", "Hindi", "INR", "Mumbai")
    PORTUGUESE = ("pt", "Portuguese", "BRL", "São Paulo")
    RUSSIAN = ("ru", "Russian", "RUB", "St. Petersburg")
    CHINESE = ("zh", "Chinese", "CNY", "Shanghai")

    @property
    def code(self) -> str:
        return self.value[0]

    @property
    def name(self) -> str:
        return self.value[1]

    @property
    def currency(self) -> str:
        return self.value[2]

    @property
    def region(self) -> str:
        return self.value[3]


@dataclass
class MultilingualWorkItem:
    """Work item with translations."""
    work_item_code: str
    translations: Dict[str, str]  # language_code -> description
    prices: Dict[str, float]      # language_code -> unit_price
    unit: str


class CWICRMultilingual:
    """Work with CWICR across languages."""

    # Exchange rates to USD (approximate)
    EXCHANGE_RATES = {
        'AED': 0.27,
        'EUR': 1.08,
        'CAD': 0.74,
        'INR': 0.012,
        'BRL': 0.20,
        'RUB': 0.011,
        'CNY': 0.14,
        'USD': 1.0
    }

    def __init__(self, databases: Dict[str, pd.DataFrame] = None):
        """Initialize with language databases."""
        self.databases = databases or {}
        self._index_databases()

    def _index_databases(self):
        """Create code-based index for each database."""
        self.indexes = {}
        for lang, df in self.databases.items():
            if 'work_item_code' in df.columns:
                self.indexes[lang] = df.set_index('work_item_code')

    def load_database(self, language: CWICRLanguage,
                      file_path: str):
        """Load database for specific language."""
        # Detect format and load
        if file_path.endswith('.parquet'):
            df = pd.read_parquet(file_path)
        elif file_path.endswith('.xlsx'):
            df = pd.read_excel(file_path)
        elif file_path.endswith('.csv'):
            df = pd.read_csv(file_path)
        else:
            raise ValueError(f"Unsupported format: {file_path}")

        self.databases[language.code] = df
        if 'work_item_code' in df.columns:
            self.indexes[language.code] = df.set_index('work_item_code')

    def get_item_translations(self, work_item_code: str) -> MultilingualWorkItem:
        """Get all translations for a work item."""

        translations = {}
        prices = {}
        unit = ""

        for lang, index in self.indexes.items():
            if work_item_code in index.index:
                row = index.loc[work_item_code]
                translations[lang] = str(row.get('description', ''))
                prices[lang] = float(row.get('unit_price', 0))
                if not unit:
                    unit = str(row.get('unit', ''))

        return MultilingualWorkItem(
            work_item_code=work_item_code,
            translations=translations,
            prices=prices,
            unit=unit
        )

    def translate(self, work_item_code: str,
                  from_lang: str,
                  to_lang: str) -> Optional[str]:
        """Translate work item description."""

        if to_lang not in self.indexes:
            return None

        if work_item_code in self.indexes[to_lang].index:
            return str(self.indexes[to_lang].loc[work_item_code].get('description', ''))

        return None

    def compare_prices(self, work_item_code: str,
                       normalize_to_usd: bool = True) -> Dict[str, float]:
        """Compare prices across regions."""

        prices = {}

        for lang, index in self.indexes.items():
            if work_item_code in index.index:
                price = float(index.loc[work_item_code].get('unit_price', 0))

                if normalize_to_usd:
                    # Get currency for this language
                    currency = self._get_currency(lang)
                    rate = self.EXCHANGE_RATES.get(currency, 1.0)
                    price = price * rate

                prices[lang] = round(price, 2)

        return prices

    def _get_currency(self, lang_code: str) -> str:
        """Get currency for language code."""
        for lang in CWICRLanguage:
            if lang.code == lang_code:
                return lang.currency
        return 'USD'

    def find_cheapest_region(self, work_item_code: str) -> Tuple[str, float]:
        """Find region with lowest price (USD normalized)."""

        prices = self.compare_prices(work_item_code, normalize_to_usd=True)

        if not prices:
            return ('', 0)

        cheapest = min(prices.items(), key=lambda x: x[1])
        return cheapest

    def find_most_expensive_region(self, work_item_code: str) -> Tuple[str, float]:
        """Find region with highest price (USD normalized)."""

        prices = self.compare_prices(work_item_code, normalize_to_usd=True)

        if not prices:
            return ('', 0)

        expensive = max(prices.items(), key=lambda x: x[1])
        return expensive

    def cross_language_search(self, query: str,
                              source_lang: str) -> Dict[str, List[str]]:
        """Search in one language, get results in all languages."""

        if source_lang not in self.databases:
            return {}

        source_df = self.databases[source_lang]

        # Find matching codes
        matches = source_df[
            source_df['description'].str.contains(query, case=False, na=False)
        ]['work_item_code'].tolist()

        # Get translations for matches
        results = {}
        for code in matches[:10]:  # Limit to 10
            item = self.get_item_translations(code)
            results[code] = item.translations

        return results

    def price_comparison_report(self, work_item_codes: List[str]) -> pd.DataFrame:
        """Generate price comparison report across regions."""

        rows = []
        for code in work_item_codes:
            item = self.get_item_translations(code)
            prices_usd = self.compare_prices(code, normalize_to_usd=True)

            row = {
                'code': code,
                'description': item.translations.get('en', list(item.translations.values())[0] if item.translations else ''),
                'unit': item.unit
            }

            for lang, price in prices_usd.items():
                row[f'price_{lang}_usd'] = price

            if prices_usd:
                row['min_price'] = min(prices_usd.values())
                row['max_price'] = max(prices_usd.values())
                row['price_variance'] = row['max_price'] - row['min_price']

            rows.append(row)

        return pd.DataFrame(rows)


class LanguageDetector:
    """Detect language of construction text."""

    # Common construction terms by language
    KEYWORDS = {
        'en': ['concrete', 'wall', 'floor', 'door', 'window', 'steel', 'brick'],
        'de': ['beton', 'wand', 'boden', 'tür', 'fenster', 'stahl', 'ziegel'],
        'es': ['hormigón', 'pared', 'piso', 'puerta', 'ventana', 'acero', 'ladrillo'],
        'fr': ['béton', 'mur', 'plancher', 'porte', 'fenêtre', 'acier', 'brique'],
        'ru': ['бетон', 'стена', 'пол', 'дверь', 'окно', 'сталь', 'кирпич'],
        'zh': ['混凝土', '墙', '地板', '门', '窗', '钢', '砖'],
        'pt': ['concreto', 'parede', 'piso', 'porta', 'janela', 'aço', 'tijolo'],
        'ar': ['خرسانة', 'جدار', 'أرضية', 'باب', 'نافذة', 'فولاذ', 'طوب'],
        'hi': ['कंक्रीट', 'दीवार', 'फर्श', 'दरवाजा', 'खिड़की', 'इस्पात', 'ईंट']
    }

    @staticmethod
    def detect(text: str) -> str:
        """Detect language of text."""
        text_lower = text.lower()

        scores = {}
        for lang, keywords in LanguageDetector.KEYWORDS.items():
            score = sum(1 for kw in keywords if kw in text_lower)
            if score > 0:
                scores[lang] = score

        if scores:
            return max(scores.items(), key=lambda x: x[1])[0]

        return 'en'  # Default to English
```

## Quick Start

```python
# Initialize multilingual support
multi = CWICRMultilingual()

# Load databases
multi.load_database(CWICRLanguage.ENGLISH, "cwicr_en.parquet")
multi.load_database(CWICRLanguage.GERMAN, "cwicr_de.parquet")
multi.load_database(CWICRLanguage.SPANISH, "cwicr_es.parquet")

# Get translations
item = multi.get_item_translations("CONC-001")
print(f"EN: {item.translations.get('en')}")
print(f"DE: {item.translations.get('de')}")
```

## Price Comparison

```python
# Compare concrete prices across regions
prices = multi.compare_prices("CONC-001", normalize_to_usd=True)
print(prices)

# Find cheapest region
region, price = multi.find_cheapest_region("CONC-001")
print(f"Cheapest: {region} at ${price}")
```

## Resources
- **DDC Book**: Chapter 2.2 - Open Data Integration
- **CWICR Database**: 9 languages, 55,000+ items

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.