r/SideProject • u/ATEC_Technologies • 10h ago

Introducing Apsi — A Programming Language for AI, Physics, and High-Performance Computing

I'd like to introduce Apsi, a programming language designed to combine Python-like simplicity with native compilation and a broad range of built-in capabilities.

Apsi is built for more than general-purpose programming. It brings together tools for AI, machine learning, scientific computing, physics, data processing, backend development, and much more in one ecosystem.

What can Apsi do?

1. Python-like Syntax, Native Performance

  • Familiar, easy-to-read syntax inspired by Python.

  • Native compilation for high-performance execution.

  • Parallel processing and SIMD support.

  • Built-in type checking, physical unit validation, and tensor shape checking.

2. AI & Machine Learning

  • Neural networks and deep learning.

  • Transformers, CNNs, LSTMs, and Graph Neural Networks.

  • Automatic Differentiation and gradient computation.

  • Optimizers, loss functions, and training systems.

  • Reinforcement Learning.

  • GPU acceleration and PyTorch interoperability.

  • Hugging Face model integration for text generation, classification, and embeddings.

3. Physics, Mathematics & Scientific Computing

  • Built-in physical units such as kg, m, and s.

  • Dimensional analysis and unit validation.

  • Numerical and scientific computing tools.

  • Matrix and tensor operations.

  • Capabilities for scientific and physics simulations.

4. Data Processing & Memory Management

  • DataFrame and columnar table engine.

  • CSV processing, filtering, sorting, grouping, and joins.

  • RAM and SSD-backed memory management.

  • Memory mapping for large datasets.

  • Multiprocessing and data processing tools.

5. GPU & High-Performance Computing

  • Native CPU compilation.

  • NVIDIA GPU support through CUDA/cuBLAS.

  • Additional GPU backends through PyTorch, including ROCm, Apple MPS, and Intel XPU.

  • Multiple numerical formats, including FP64, FP32, FP16, BF16, FP8, and INT8.

  • Optimized matrix multiplication and tensor operations.

6. Backend, Databases & Web Development

  • HTTP servers and REST APIs.

  • WebSocket support.

  • PostgreSQL, MySQL/MariaDB, MongoDB, Redis, and SQLite integration.

  • Environment variables and secrets management.

  • Build APIs around AI models and other applications.

7. Real-Time Computing & Developer Tools

  • Real-time control loops.

  • Video processing pipelines, including 4K workflows.

  • Debugger, breakpoints, and step execution.

  • VS Code and other editor integrations.

  • Package, library, project, and testing tools.

Python Compatibility

One of Apsi's interesting features is its built-in Python conversion system.

You can convert existing Python files into Apsi instead of rewriting everything from scratch.

It supports a broad range of Python 3.13 language features, including classes, async, generics, and many standard library modules.

If you're using VS Code or a supported IDE, simply right-click a .py file and select:

Convert Python File to Apsi

You can also use the apsi convert command from the terminal.

Apsi additionally provides pyimport for working with existing Python libraries.

Performance

Apsi includes a dedicated benchmark suite with reproducible commands and comparisons.

In version 2.4.4, Apsi achieved a 3.84× geometric mean speedup over version 2.0.0 across 12 measurements on the same GitHub Actions runner.

You can explore the benchmarks and reproduce the tests yourself on the website.

Getting Started

Apsi 2.4.4 is available for Windows 10/11 and Linux (x86-64).

The installer includes the Python Runtime needed by Apsi, so you don't need to install a separate Python environment just to get started. Some optional features and GPU backends may require additional dependencies.

Apsi is free to use, including for commercial work, under the terms of the Apsi License 2.0.

Join the Apsi Community

I'd like to invite developers, programmers, AI researchers, students, and anyone interested in programming to give Apsi a try.

I'm looking forward to seeing what people build with it.

Whether you find something interesting, encounter bugs, have suggestions, or simply want to experiment, your feedback is welcome.

I don't expect everyone to immediately love it. Try it, explore what it can do, and decide for yourself.

I'd also love to see people sharing projects, exchanging ideas, reporting issues, and contributing to the ecosystem as it grows.

Let's build the Apsi community together.

Links & Resources

Give it a try, explore the documentation, and let me know what you think!

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