python5 v1.0 — OFFICIAL INSTRUCTION MANUAL THE FINAL SINGULARITY · NOVEMBER 2025 EDITION
Copyright © Daniel Harding — RomanAILabs Let’s save Python, everyone! Contact: romanailabs@gmail.com
📦 What is python5?
python5 v1.0 is a next-generation execution engine that supercharges plain Python scripts using advanced mathematics, compiler rewrites, tensor factorization, hybrid AI acceleration, and multi-paradigm optimization — without requiring a single change to your code.
Think of it as a transcendental runtime, blending:
⚡ TorchInductor + AOT-TS graphing
🧠 LLM-specific optimization (FlashAttention, 4-bit quant, device maps)
🔥 Tensor-Train & Low-Rank Sparse decomposition (TT/LRS)
♾ 4D Rotational Embeddings (SO(4) math)
🔷 Category Theory graph fusion
🧮 Geometric Algebra symbolic rewriting
🧬 E-Graph / Term Rewriting System optimizations
💾 Eternal deterministic cache (script hash → compiled wrapper)
All in one file. Zero boilerplate. Zero syntax changes.
🚀 Quick Start
First, download or clone python5.py.
Linux / macOS (bash/zsh) Add this to ~/.bashrc or ~/.zshrc: alias python5='python3 /full/path/to/python5.py' source ~/.bashrc
Windows Powershell function python5 { python "C:\path\to\python5.py" $args }
Windows CMD doskey python5=python C:\path\to\python5.py $*
RUN IN! python5 yourfile.py
That's it.
python5 will automatically:
Parse & rewrite your script using AST + math-fusion passes
Inject LLM acceleration (flash attention, 4-bit quant, hybrid hook)
Build a persistent compiled wrapper
Collapse the execution graph into a faster backend
Apply hybrid Tensor-Train + Low-Rank Sparse acceleration to any large model
Cache everything forever using its “ETERNAL” hashing engine
Your original script stays untouched.
🧬 Architecture Summary (“How python5 Works”)
- Pre-Execution Math Pipeline
Before execution, your script is rewritten using:
Geometric Algebra optimizer — replaces patterns like x*x with x.norm_sq().
Category Theory Fusion — functor-level call folding.
Term Rewriting / E-Graphs — high-level algebraic optimizations.
LLM Accelerator — injects:
load_in_4bit=True (bitsandbytes)
FlashAttention v2
Device map automation
Hybrid post-load hooks
- Hybrid Acceleration Engine (Level 3)
After the model loads:
Tensor-Train (TT) decomposition replaces huge linear layers
Low-Rank Sparse (LRS) factorization compresses projections
4D Rotational Embeddings wrap embeddings in SO(4) transforms
CPU FlashAttention avoids constructing QKᵀ matrices
Operator Fusion merges linear + activation into single fused ops
The model keeps all intelligence but uses far fewer FLOPS.
- Eternal Wrapper Cache
python5 fingerprints:
Your script
Python version
PyTorch version
Hardware/GPU name
Installed optional math libs
A unique wrapper is compiled and stored in: ~/.cache/python5_v3_0/
- Final Execution Collapse
The runtime decides dynamically:
TorchInductor (NVIDIA)
AOT-TS (CPU)
OpenVINO backend
AMP bf16 acceleration
Zero-GIL path (Python 3.14+)
python5 executes your script in a mathematically optimized singularity space for maximum speed, automatically.
🎯 Mission Statement
python5 exists for one purpose:
**To push Python beyond its limits through mathematics, compilers, and engineering —
without breaking backward compatibility or user experience.**
If you want to contribute, collaborate, or evolve this project into a full runtime:
Let’s build the future together.