uzpreprocessor 1.0.1

Uzbek text preprocessing library for converting numbers, dates, times, and currency to words

UzPreprocessor

UzPreprocessor is a comprehensive Python library for converting numbers, dates, times, and currency amounts to Uzbek (Latin) words. Perfect for legal documents, invoices, receipts, and text preprocessing tasks.

🌟 NEW: Automatic Text Processing

from uzpreprocessor import UzPreprocessor

processor = UzPreprocessor()

text = """Shartnoma No.123
Sana: 2025-09-18, soat 14:35
Summa: 12500 so'm (15% chegirma)"""

# One method processes everything automatically!
result = processor.process(text)
print(result)

Output:

Shartnoma No. bir yuz yigirma uchinchi
Sana: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr, soat o'n to'rt soat o'ttiz besh daqiqa
Summa: o'n ikki ming besh yuz so'm (o'n besh foiz chegirma)

Features

✨ Number Conversion

• Integers (arbitrary size)
• Decimal numbers (up to 12 digits precision)
• Negative numbers
• Ordinal numbers

💰 Currency Conversion

• Uzbek so'm and tiyin
• Automatic handling of decimal places

📅 Date Conversion

• Multiple input formats (ISO, European, US, text)
• Supports English and Uzbek month names
• Legal date format support

⏰ Time Conversion

• 24-hour and 12-hour (AM/PM) formats
• Spoken Uzbek time periods (ertalab, tushlikdan keyin, kechqurun, etc.)
• Multiple time formats with flexible parsing

🔗 DateTime Conversion

• Combined date and time conversion
• ISO datetime format support

📝 Text Preprocessing

• Convert number markers (№1, #1, 1№, etc.) to words
• Legal document markers (п., ст., гл., разд., etc.)
• Process text files
• Flexible configuration options

Installation

pip install uzpreprocessor

Quick Start

Basic Usage

from uzpreprocessor import UzPreprocessor

# Initialize the processor
processor = UzPreprocessor()

# Convert numbers
print(processor.number.number(123))
# Output: bir yuz yigirma uch

print(processor.number.number(123.456))
# Output: bir yuz yigirma uch butun to'rt yuz ellik olti mingdan

# Convert currency
print(processor.number.money(12345.67))
# Output: o'n ikki ming uch yuz qirq besh so'm oltmish yetti tiyin

# Convert percentages
print(processor.number.percent(12.345))
# Output: o'n ikki butun uch yuz qirq besh mingdan foiz

# Convert dates
print(processor.date.date("2025-09-18"))
# Output: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr

# Convert time
print(processor.time.time("14:35:08"))
# Output: o'n to'rt soat o'ttiz besh daqiqa sakkiz soniya

# Convert datetime
print(processor.datetime.datetime("2025-09-18T14:35:08"))
# Output: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr o'n to'rt soat o'ttiz besh daqiqa sakkiz soniya

# Text preprocessing
print(processor.text.process("Bu №1 va #2 sonlar"))
# Output: Bu birinchi va ikkinchi sonlar

print(processor.text.process("Maqola №15, п.3 va ст.4"))
# Output: Maqola o'n beshinchi, punkt uchinchi va modda to'rtinchi

Advanced Usage

Direct Class Usage

from uzpreprocessor import UzNumberToWords, UzDateToWords, UzTimeToWords, UzDateAndTimeToWords, UzTextPreprocessor

# Create converters
number_converter = UzNumberToWords()
date_converter = UzDateToWords(number_converter)
time_converter = UzTimeToWords(number_converter)
datetime_converter = UzDateAndTimeToWords(date_converter, time_converter)

# Use individual converters
print(date_converter.date("18 September 2025"))
# Output: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr

print(time_converter.time("2 PM"))
# Output: tushlikdan keyin soat o'n to'rt

Detailed Examples

Number Conversion

from uzpreprocessor import UzNumberToWords

conv = UzNumberToWords()

# Integers
print(conv.number(0))          # nol
print(conv.number(5))          # besh
print(conv.number(42))         # qirq ikki
print(conv.number(123))        # bir yuz yigirma uch
print(conv.number(1000000))    # bir million

# Decimals
print(conv.number(123.456))    # bir yuz yigirma uch butun to'rt yuz ellik olti mingdan
print(conv.number(0.5))        # nol butun besh o'ndan

# Negative numbers
print(conv.number(-42))        # minus qirq ikki

# Ordinal numbers
print(conv.ordinal(5))         # beshinchi
print(conv.ordinal(123))       # bir yuz yigirma uchinchi

Currency Conversion

from uzpreprocessor import UzNumberToWords

conv = UzNumberToWords()

print(conv.money(1000))        # bir ming so'm
print(conv.money(12345.67))    # o'n ikki ming uch yuz qirq besh so'm oltmish yetti tiyin
print(conv.money(0.50))        # nol so'm ellik tiyin
print(conv.money(-100))        # minus bir yuz so'm

Date Conversion

The library supports multiple date formats:

from uzpreprocessor import UzPreprocessor

processor = UzPreprocessor()

# ISO format
print(processor.date.date("2025-09-18"))

# European format
print(processor.date.date("18.09.2025"))
print(processor.date.date("18/09/2025"))

# US format
print(processor.date.date("09/18/2025"))

# Text format (English)
print(processor.date.date("18 September 2025"))
print(processor.date.date("September 18, 2025"))

# Text format (Uzbek)
print(processor.date.date("18 sentabr 2025"))

# Legal format
print(processor.date.date("2025-yil 18-sentabr"))

# Python date objects
from datetime import date
print(processor.date.date(date(2025, 9, 18)))

Time Conversion

from uzpreprocessor import UzPreprocessor

processor = UzPreprocessor()

# 24-hour format (formal mode)
print(processor.time.time("14:35"))        # o'n to'rt soat o'ttiz besh daqiqa
print(processor.time.time("14:35:08"))     # o'n to'rt soat o'ttiz besh daqiqa sakkiz soniya
print(processor.time.time("00:00"))        # nol soat

# 12-hour format with AM/PM (spoken mode)
print(processor.time.time("2 PM"))         # tushlikdan keyin soat o'n to'rt
print(processor.time.time("2:35 PM"))      # tushlikdan keyin soat o'n to'rt o'ttiz besh daqiqa
print(processor.time.time("7 AM"))         # ertalab soat yetti

# Various formats
print(processor.time.time("14.35"))        # o'n to'rt soat o'ttiz besh daqiqa
print(processor.time.time("14 35"))        # o'n to'rt soat o'ttiz besh daqiqa
print(processor.time.time("14:35:08Z"))    # o'n to'rt soat o'ttiz besh daqiqa sakkiz soniya

# Python time objects
from datetime import time
print(processor.time.time(time(14, 35, 8)))

Time Periods (for AM/PM format):

• ertalab - 5:00-10:59
• tushlikdan oldin - 11:00-12:59
• tushlikdan keyin - 13:00-17:59
• kechqurun - 18:00-22:59
• tun - 23:00-4:59

DateTime Conversion

from uzpreprocessor import UzPreprocessor

processor = UzPreprocessor()

# ISO datetime format
print(processor.datetime.datetime("2025-09-18T14:35:08"))
# Output: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr o'n to'rt soat o'ttiz besh daqiqa sakkiz soniya

# Python datetime objects
from datetime import datetime
dt = datetime(2025, 9, 18, 14, 35, 8)
print(processor.datetime.datetime(dt))

Automatic Text Processing (Recommended)

The process() method automatically detects and converts ALL formats in text:

from uzpreprocessor import UzPreprocessor, ProcessingConfig

processor = UzPreprocessor()

# Process any text - automatically detects dates, times, money, percentages, markers
text = """Shartnoma No.123
Sana: 2025-09-18, soat 14:35
Summa: 12500 so'm (15% chegirma bilan)
Art.5, p.3 asosida, 1-bob, 2-modda

Jadval #45:
- 1-chi element: 100 dona
- 2-chi element: 250 dona

Jami: 15750 so'm"""

result = processor.process(text)
print(result)
# Output:
# Shartnoma No. bir yuz yigirma uchinchi
# Sana: ikki ming yigirma beshinchi yil o'n sakkizinchi sentabr, soat o'n to'rt soat o'ttiz besh daqiqa
# Summa: o'n ikki ming besh yuz so'm (o'n besh foiz chegirma bilan)
# art. beshinchi, p. uchinchi asosida, birinchi bob, ikkinchi modda
# ...

# Analyze text to see what was detected
analysis = processor.analyze(text)
print(f"Found {analysis['total_tokens']} tokens: {analysis['type_counts']}")
# Found 17 tokens: {'MARKER': 4, 'DATE': 1, 'TIME': 1, 'MONEY': 2, 'PERCENT': 1, 'SUFFIX': 5, 'NUMBER': 3}

# Selective processing
print(processor.numbers_only("12345 dona"))  # Process only numbers
print(processor.dates_only("2025-09-18"))    # Process only dates
print(processor.times_only("14:35"))         # Process only times
print(processor.money_only("12500 so'm"))    # Process only money

# Custom configuration
config = ProcessingConfig(
    process_numbers=True,
    process_dates=True,
    process_times=False,  # Skip time processing
    preserve_original=True  # Keep original in parentheses
)
custom_processor = UzPreprocessor(config)

Text Marker Preprocessing (Direct)

from uzpreprocessor import UzPreprocessor

processor = UzPreprocessor()

# Number markers (№, #)
print(processor.text.process("Bu №1 va #2 sonlar"))
# Output: Bu birinchi va ikkinchi sonlar

print(processor.text.process("1№, 2№, 10№"))
# Output: birinchi, ikkinchi, o'ninchi

# Latin markers
print(processor.text.process("No.1 No.2"))
# Output: No. birinchi No. ikkinchi

print(processor.text.process("art.1 sec.2 ch.3"))
# Output: art. birinchi sec. ikkinchi ch. uchinchi

print(processor.text.process("p.1 b.2 m.3 st.4"))
# Output: p. birinchi b. ikkinchi m. uchinchi st. to'rtinchi

# Uzbek suffixes
print(processor.text.process("1-chi, 2-chi, 3-chi"))
# Output: birinchi-chi, ikkinchi-chi, uchinchi-chi

print(processor.text.process("1-son, 2-bob, 3-modda"))
# Output: birinchi-son, ikkinchi-bob, uchinchi-modda

print(processor.text.process("1-qism, 2-bo'lim, 3-band"))
# Output: birinchi-qism, ikkinchi-bo'lim, uchinchi-band

# Process file
processor.text.process_file("document.txt", "document_processed.txt")

# Customize processing
processor.text.process("№1 art.2 3-chi", 
                       convert_numbers=True, 
                       convert_markers=True,
                       convert_suffixes=True)

Supported number signs:

• №1, № 1 - numero sign before
• 1№, 1 № - numero sign after
• #1, # 1 - hash before
• 1#, 1 # - hash after

Supported Latin markers:

• No., N. - number
• p. - punkt/point
• b., b- - band/bob
• m. - modda
• st. - statya
• ch. - chapter
• art. - article
• sec. - section
• pt. - point
• par. - paragraph
• item., fig., tab., eq., ex., app.

Supported Uzbek suffixes:

• -chi - ordinal suffix
• -son - number suffix
• -raqam - digit suffix
• -band - band suffix
• -modda - article suffix
• -bob - chapter suffix
• -qism - part suffix
• -bo'lim - section suffix
• -punkt - punkt suffix
• -jadval - table suffix
• -rasm - figure suffix
• -misol - example suffix
• -ilova - appendix suffix

API Reference

UzPreprocessor

Main convenience class that provides all conversion functionality.

Properties

• number - Access number converter (UzNumberToWords)
• date - Access date converter (UzDateToWords)
• time - Access time converter (UzTimeToWords)
• datetime - Access datetime converter (UzDateAndTimeToWords)
• text - Access text marker preprocessor (UzTextPreprocessor)
• processor - Access automatic text processor (UzTextProcessor)

Methods

• process(text, config=None) - Automatically process text (detects all formats)
• process_file(input_path, output_path=None, encoding='utf-8') - Process text file
• analyze(text) - Analyze text and return found tokens info
• numbers_only(text) - Process only numbers
• dates_only(text) - Process only dates
• times_only(text) - Process only times
• money_only(text) - Process only money amounts

UzTextProcessor

Unified text processor with automatic format detection.

Methods

• process(text, config=None) - Process text with all format detection
• process_file(input_path, output_path=None, encoding='utf-8') - Process file
• analyze(text) - Analyze text and return token information
• tokenize(text) - Split text into tokens

ProcessingConfig

Configuration for text processing.

Options

• process_numbers - Process plain numbers (default: True)
• process_ordinals - Process ordinal notations like "5-inchi" (default: True)
• process_money - Process currency amounts (default: True)
• process_percent - Process percentages (default: True)
• process_dates - Process dates (default: True)
• process_times - Process times (default: True)
• process_datetimes - Process ISO datetimes (default: True)
• process_markers - Process number markers №, #, No. (default: True)
• process_suffixes - Process Uzbek suffixes -chi, -bob, etc. (default: True)
• preserve_original - Keep original in parentheses (default: False)
• min_number - Minimum number to process (default: 0)
• max_number - Maximum number to process (default: 10^15)

UzNumberToWords

Converts numbers, currency, and percentages to Uzbek words.

Methods

• number(value) - Convert number to words
• money(amount) - Convert currency to words (so'm/tiyin)
• percent(value) - Convert percentage to words
• ordinal(value) - Convert number to ordinal form

UzDateToWords

Converts dates to Uzbek words.

Methods

• date(value) - Convert date to words

Supported input types:

• String (various formats)
• datetime.date object
• datetime.datetime object

UzTimeToWords

Converts time to Uzbek words.

Methods

• time(value) - Convert time to words

Supported input types:

• String (various formats)
• datetime.time object
• datetime.datetime object

Modes:

• Formal mode: Standard 24-hour format (e.g., "14:35")
• Spoken mode: 12-hour format with AM/PM (e.g., "2 PM")

UzDateAndTimeToWords

Combines date and time conversion.

Methods

• datetime(value) - Convert datetime to words

Supported input types:

• String (ISO format)
• datetime.datetime object

UzTextPreprocessor

Processes text to convert number markers to Uzbek words.

Methods

• process(text, convert_numbers=True, convert_markers=True, convert_suffixes=True) - Process text string
• process_file(input_path, output_path=None, convert_numbers=True, convert_markers=True, convert_suffixes=True, encoding='utf-8') - Process text file

Parameters:

• convert_numbers - If True, convert № and # markers
• convert_markers - If True, convert Latin markers (No., art., sec., etc.)
• convert_suffixes - If True, convert Uzbek suffixes (-chi, -son, -bob, etc.)

Performance

The library is optimized for performance:

• Compiled regex patterns for faster parsing
• Efficient string operations with minimal allocations
• Optimized data structures (tuples for immutable data, dicts for O(1) lookups)
• No external dependencies (uses only Python standard library)

Requirements

• Python 3.8 or higher
• No external dependencies (uses only standard library)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Inspired by the need for Uzbek text preprocessing in legal and financial documents
• Built with attention to accuracy and performance

Changelog

1.0.0 (2025-01-XX)

• Initial release
• Number to words conversion
• Date to words conversion
• Time to words conversion
• Currency conversion
• Percentage conversion
• Support for multiple input formats
• Optimized performance

Documentation

• Installation Guide - Detailed installation instructions
• Deployment Guide - Complete guide for publishing to PyPI
• Quick Deploy - Quick reference for deployment
• Project Structure - Project organization
• Optimizations - Performance optimizations

Support

For issues, questions, or contributions, please visit:

• GitHub Issues
• GitHub Repository

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