A learning-augmented text compression engine in C++20
Project description
moezip
A learning-augmented, high-efficiency text compression engine written in C++20. moezip combines a Mixture of Experts (MoE) predictive state router, 32-bit Asymmetric Numeral Systems (rANS) arithmetic coding, and LZ back-referencing.
Standard dictionary-less compressors (like raw Zstandard or Gzip) incur frame-header inflation on short inputs, often expanding small text strings. moezip embeds pre-trained vocabulary tables and transition matrices directly into the compiled library or executable, enabling instant pattern prediction with zero metadata overhead.
Installation
Install directly from PyPI:
pip install moezip
Documentation
Full technical documentation, build guides, and API specifications are hosted on the moezip GitHub Wiki:
- Architecture & Design: Internal pipeline, tokenization, 32x32 MoE router, and
make.pystring-literal generator. - Building & Compilation: CMake and PyPI build guides for Windows (MSVC) and Linux (GCC/Clang).
- CLI Usage & Training: Command reference, stream piping, and training domain-specific matrices.
- API Reference: Documentation for Python (
import moezip), C-API dynamic libraries, and native C++ headers. - Performance & Benchmarks: Detailed space savings and speed metrics across micro-strings (< 500 B) and medium documents.
Key Highlights
- Zero Warm-Up Penalty: Compresses small text payloads and chat messages (< 500 bytes) without header bloat.
- Self-Contained Portability: Default vocabulary (
words_final.txt) and router matrix (router_stateless_v4.json) compile directly into the binary. No external asset files are required at runtime. - Multi-Target Compilation: Single CMake build produces standalone CLI executables, C-API dynamic libraries (
.dll/.so), or native PyBind11 Python extension modules (.pyd/.so). - Domain Trainable: Built-in training mode (
moezip train) optimizes state transition weights for specialized corpora (code, medical, legal).
Quick Start
Python Extension (import moezip)
import moezip
# Compress string in memory using embedded assets
compressed = moezip.compress("Hello world, compress this text!")
restored = moezip.decompress(compressed)
assert restored == "Hello world, compress this text!"
Command Line Interface
# Compress text file
moezip compress input.txt -o archive.moe
# Decompress back to original text
moezip decompress archive.moe -o restored.txt
Performance Snapshot
Across 532 cumulative bytes of micro-string test samples:
moezip: Reduced size to 247 bytes (53.6% space savings).- Raw Zstandard (L3): Reduced size to 456 bytes (14.3% space savings).
For detailed test data and medium-clip benchmarks, see the Performance & Benchmarks Wiki page.
Compiled Artifacts
| Platform | Executable | Shared Library (C-API) | Python Module |
|---|---|---|---|
| Windows (MSVC) | moezip.exe |
moezip.dll / moezip.lib |
moezip.pyd |
| Linux (GCC / Clang) | moezip |
libmoezip.so |
moezip.so |
License
This project is licensed under the MIT License.
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