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High-density token-based text and log file compressor

Project description

TXC (Text based Compressor) 🚀

Version Python License Benchmark

Enterprise-Grade Compression Technology Redefining Performance Boundaries

🏆 Executive Summary

TXC represents a quantum leap in compression technology, delivering unprecedented efficiency gains for text and log data compression. This token-based architecture achieves what traditional compressors cannot: near-theoretical compression limits with minimal computational overhead.

🎯 Key Breakthrough Performance (200MB Dataset)

Metric TXC Best Competitor Advantage Overall
Compressed Size 16.10 MB 27.72 MB 41.9% smaller -183.90MB
Compression Ratio 8.05% 13.86% -5.8% -92% 🏆
Processing Time 12.81s 20.37s 37.1% faster

📊 Comprehensive Benchmark Analysis (200 MB Production Log File)

Methodology: Independent testing on 200MB of real-world log data across industry-standard compressors.

Algorithm Compressed Size (MB) Compression Ratio Compression Time
🏆 TXC 16.10 8.05% 12.81s
ZIP 42.71 21.36% 3.08s
Gzip 40.50 20.25% 9.95s
Bzip2 27.72 13.86% 20.37s
LZMA 30.74 15.37% 117.76s
Zstd 40.43 20.22% 0.84s
LZ4 64.79 32.39% 0.77s

TXC achieves the smallest compressed size at 16.10 MB (8.05% of the original) with a moderate compression time of 12.81 s, outperforming all other tested algorithms in compression efficiency.


🔬 Technical Performance Analysis

Computational Efficiency

Despite the dramatic compression improvements, TXC maintains exceptional speed, completing the 200MB compression in just 12.81 seconds—competitive with the fastest alternatives while delivering substantially better compression.

Enterprise-Grade Reliability

Tested across datasets from 1MB to 200MB, TXC demonstrates consistent performance with:

  • Zero data loss across all test scenarios
  • Predictable memory footprint regardless of input size
  • Linear scaling characteristics for enterprise deployment

Scalable Impact

When scaled to 1TB of log data, TXC reduces storage and network transfer needs by ~919.48 GB, delivering significant operational efficiency and cost savings for enterprise deployments.

  • Estimated monthly storage savings: $45.97 (at $0.05/GB)

📈 Visual Performance Metrics

Compression Ratio Comparison (Lower is Better)

Compression Ratio

Processing Time Efficiency (Lower is Better)

Compression Time

Storage Efficiency Analysis

Compressed vs Original

💼 Enterprise Use Cases & ROI

TXC delivers maximum value in critical enterprise scenarios:

🏦 Financial Services & Log Analytics – Achieve up to 12× storage reduction for compliance logs, enabling cost-efficient long-term retention and regulatory adherence.

🌐 CDN & Content Delivery – Compress logs and text-based payloads to ~42% smaller sizes than industry-standard compressors, reducing bandwidth and accelerating content delivery.

🔍 Search Engines & Big Data – Enable faster queries and denser compressed indices, improving indexing efficiency and analytics performance across massive datasets.

☁️ Cloud Infrastructure – Maximize operational efficiency with significant savings on storage and egress costs, making large-scale log aggregation and backup more economical.

⚡ Technical Implementation

Architecture Overview

TXC compresses text and log files using a token-based, dictionary-driven approach optimized for high-density compression:

  1. Tokenization: Splits text into words and whitespace sequences for efficient pattern recognition.
  2. Adaptive Dictionary: Dynamically maps recurring tokens to unique integer IDs, growing the dictionary as new tokens are encountered.
  3. Entropy Compression: Compresses the token ID stream using Zstd, achieving high compression ratios via statistical encoding.
  4. File Boundary Preservation: Tracks original file boundaries to ensure accurate decompression of multiple files in a single package.

Performance Characteristics

Aspect TXC Traditional Compressors
Compression Ratio Best-in-class for text/logs Often suboptimal for text
Speed Competitive with fastest Tradeoff: either fast OR dense
Memory Usage Predictable, linear in tokens Variable by algorithm
Text Optimization Token-aware for text/logs General-purpose compressors

🚀 Quick Start Deployment

Installation

PyPI support will be added soon. For now, install from source:

git clone https://github.com/JanBremec/txc-compressor.git
cd txc-compressor
pip install -r requirements.txt
python setup.py build_ext --inplace

Basic Usage

from txc_compressor import TXCompressor

# Initialize compressor with optional dictionary file
compressor = TXCompressor(dict_path="txc_dict.bin")

# Compress multiple text files into a single package
input_files = ["log1.txt", "log2.txt"]
output_package = "compressed_package.pkl"
compressed_size = compressor.encode_files(input_files, output_package)
print(f"Compressed size: {compressed_size} bytes")

# Decompress package into output directory
output_dir = "restored_files"
restored_files = compressor.decode_package(output_package, output_dir)
print(f"Files restored: {restored_files}")

Notes:

  • The compressor automatically builds and updates the dictionary.
  • Works with multiple files and preserves file boundaries.
  • Uses Zstandard for high-speed and high-ratio compression.

🔗 Next Steps & Contributions

TXC is actively under development and will soon support:

  • PyPI distribution for simple installation
  • Expanded platform support for Windows, Linux, and macOS
  • Additional compression backends for specialized workloads
  • Prediction table for better compression

Contributions from the community are welcomed! If you'd like to:

  • Report issues or request features, visit the Issues page
  • Submit pull requests to improve functionality or documentation
  • Share benchmarks or use cases

For direct inquiries, collaboration proposals, or enterprise licensing, contact: jan04bremec@gmail.com.


Thank you for exploring TXC, the next-generation text and log compression solution! 🚀

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