Pyvorin — Native Python Acceleration
Compile. Accelerate. Scale.
Accelerate supported Python workloads — ETL pipelines, numerical transforms, loops, reductions, timestamps and feature engineering — with native compilation. Honest benchmarks, strict-mode safety and transparent fallback reporting.
Proven speed-ups from the Phase G canonical benchmark suite
Built for production Python
Pyvorin targets the workloads that matter most in data engineering and quantitative code — and tells you honestly when it cannot help.
Native Compilation
Your Python AST is analysed, typed and lowered to LLVM IR, then compiled to a native
.so / .dll and loaded back into the interpreter. No VM rewrite. No language change.
Honest Benchmarks
Every claim is backed by reproducible suites run on bare metal with thermal soak, statistical outlier rejection and fallback reporting. We publish what we cannot accelerate.
Strict Mode Safety
Strict mode fails loudly when a construct is unsupported, so you never silently fall back to CPython in performance-critical sections. Fallback is always reported and logged.
What Pyvorin does and does not do
We accelerate a supported subset of Python honestly. If your code is outside that subset, Pyvorin reports the limitation and falls back to CPython.
Best-fit workloads
- ETL pipelines — filter, map, reduce on lists, dicts and arrays
- Numerical transforms — group-by, rolling windows, reductions
- Feature engineering — timestamp arithmetic, vectorised expressions
- String processing — tokenisation, log parsing, pattern extraction
- Tight loops over numeric or string data with predictable types
Weak-fit or unsupported
- Dynamic class definitions and metaclass manipulation
-
Complex
eval/execat runtime - Unbounded recursion and arbitrary object graphs
- Heavy I/O-bound code (Pyvorin is CPU-focused; use async I/O instead)
- C extensions that rely on CPython internals not exposed to LLVM
Start accelerating today
Install the thin client, activate your licence and run your first compiled script in minutes.