word-number-converter 0.1.0

A multi-language library to convert numbers to words and words to numbers.

Word Number Converter

A lightweight, multi-language Python library for converting numbers to words and words back to numbers.
It supports multiple human languages, Chinese numeral systems, and Roman numerals, all through a simple API.

---

✨ Features

• Convert integers to words in multiple languages
• Convert words back to integers (where supported)
• Chinese number systems:
  • Simplified
  • Traditional
  • Financial
• Roman numeral conversion
• Handles negative numbers
• No external dependencies

---

🌍 Supported Languages

Number → Words

• English (en)
• Chinese (zh)
• Spanish (es)
• French (fr)
• German (de)
• Swahili (sw)
• Japanese (ja)
• Arabic (ar)
• Roman numerals

Words → Number

• English (en)
• Chinese (zh)
• Roman numerals (roman)

⚠️ Reverse conversion is not yet implemented for all languages.

---

📦 Installation

pip install word-number-converter

---

🚀 Quick Start

from word_number_converter import WordNumberConverter

converter = WordNumberConverter()

Number to Words

converter.number_to_words(123)
# "one hundred twenty-three"

converter.number_to_words(456, lang="es")
# "cuatrocientos cincuenta y seis"

converter.number_to_words(789, lang="fr")
# "sept cent quatre-vingt-neuf"

converter.number_to_words(2024, lang="zh", system="simplified")
# "二千零二十四"

converter.number_to_words(-15, lang="de")
# "minus fünfzehn"

Words to Number

converter.words_to_number("one hundred twenty three")
# 123

converter.words_to_number("一百二十三", lang="zh")
# 123

converter.words_to_number("MCMXCIV", lang="roman")
# 1994

Roman Numerals

converter.number_to_roman(1994)
# "MCMXCIV"

converter.roman_to_number("XLII")
# 42

---

🀄 Chinese Number Systems

converter.number_to_words(1024, lang="zh", system="simplified")
# 一千零二十四

converter.number_to_words(1024, lang="zh", system="traditional")
# 一千零二十四

converter.number_to_words(1024, lang="zh", system="financial")
# 壹仟零贰拾肆

Supported systems:

• simplified
• traditional
• financial

---

🧠 Design Notes

• Focused on correctness and readability over linguistic edge cases
• Designed for NLP preprocessing, localization, and educational use
• No third-party dependencies
• Python ≥ 3.7

---

📄 License

MIT License

---

👤 Author

Ricardo 📧 [e-mail]

---

🔗 Links

• Homepage: https://github.com/mricardo888/WordNumberConverter
• Issues: https://github.com/mricardo888/WordNumberConverter/issues