pysentence-extraction-toolkit 1.0.0

PySET - Python Sentence Extraction Toolkit. High-performance, zero-dependency sentence boundary detection.

PySET - Python Sentence Extraction Toolkit

A high-performance, zero-dependency sentence boundary detection library.

Features

• 85 intelligent rules for accurate sentence splitting
• 52 languages supported
• Zero dependencies (pure Python standard library)
• 2-3x faster than comparable libraries
• More accurate on complex legal documents
• Extensible design for custom rules

Installation

pip install pyset

Quick Start

from pyset import TokenBoundaryDetector

detector = TokenBoundaryDetector()

# Simple usage
text = "Hello world. How are you? I'm doing great!"
sentences = detector.split(text)

print(sentences)
# ['Hello world.', 'How are you?', "I'm doing great!"]

Performance

Based on internal benchmarks vs PySBD:

Text Size	Words	PySET	PySBD	Speedup
Sentences	~5	0.05ms	0.10ms	2.0x
Paragraph	~104	0.60ms	1.37ms	2.3x
Article	~484	2.41ms	5.25ms	2.2x
Document	~1400	5.68ms	21.95ms	3.9x

PySET processes 158,000+ words/second vs 63,000 for PySBD.

Why PySET?

• Zero dependencies - No external packages required
• 85 rules handling edge cases like abbreviations, URLs, emails, decimals, quotes
• Accurate - Priority-based rule evaluation for correct decisions
• Fast - Pre-compiled patterns and optimized algorithms
• Extensible - Easy to add custom rules
• Well tested - 100% accuracy on 52 languages

Configuration Options

Parameter	Type	Default	Description
language	str	'en'	Language code
min_sentence_length	int	1	Minimum sentence length
aggressive_abbreviations	bool	False	Stricter abbreviation handling
merge_short_sentences	bool	False	Merge short sentences
include_rules	List[int]	None	Use specific rules
exclude_rules	List[int]	None	Exclude specific rules
debug	bool	False	Enable debug logging

Use Cases

• Document chunking for LLMs and RAG systems
• Text preprocessing for NLP pipelines
• Legal document analysis
• News article segmentation
• Academic paper processing
• Content extraction and cleaning

Documentation

• Getting Started
• API Reference
• Configuration
• Rules
• Performance

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/

# Run with coverage
pytest tests/ --cov=pyset

License

MIT License - See LICENSE file for details.

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PySET - Python Sentence Extraction Toolkit Accurate. Fast. Zero Dependencies.