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Hacker News Show HN: The Oct Programming Language for scientific programming

Addresses frustrations with MATLAB and Python in scientific computing, specifically debugging large codebases, sharing code with less technical colleagues, and the 'Two-Language Problem' (prototyping in Python/MATLAB, rewriting in C++/Rust for performance). Positions itself as a statically typed, interpreted and compiled language that generates Go binaries, offering Go-level speed and ecosystem access, with built-in features for scientific computing (SI units, tensors, control systems) and an easy learning curve for those familiar with Rust/Go/C#/Swift.

4
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0
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Jun 17, 2026
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AI Executive Synthesis
Addresses frustrations with MATLAB and Python in scientific computing, specifically debugging large codebases, sharing code with less technical colleagues, and the 'Two-Language Problem' (prototyping in Python/MATLAB, rewriting in C++/Rust for performance). Positions itself as a statically typed, interpreted and compiled language that generates Go binaries, offering Go-level speed and ecosystem access, with built-in features for scientific computing (SI units, tensors, control systems) and an easy learning curve for those familiar with Rust/Go/C#/Swift.
This language targets a critical friction point in scientific and engineering workflows: the dichotomy between rapid prototyping and production-grade performance/deployment. The 'Two-Language Problem' represents a significant cost in development time and expertise. Oct's approach, combining static typing, Go-based compilation, and integrated scientific features like SI unit enforcement and tensor operations, directly addresses these pain points. Simplified deployment via Go binaries resolves the challenge of sharing code with non-technical users. While still in development, its focus on developer experience for scientific users, coupled with performance and ease of distribution, positions it to attract organizations seeking to streamline their computational science pipelines, reducing reliance on complex multi-language toolchains and mitigating common error sources in numerical analysis.
Apologies in advance if my writing is unclear.First, why make another programming language? This came out of my general frustration with working with MATLAB and Python during grad school as well as at work. I'm a mechanical engineer; I write Python scripts for my own use semi-regularly. My issue with Python is that while writing easy, debugging Python code I wrote is hard once the code gets big. Sharing my Python code to colleagues is very difficult as most of them are less technical on coding than I am, so asking them to setup a full Python env just to run a script is out of the question.Then, the Two-Language Problem for scientific computing: write the prototype code in Python/MATLAB and rewrite the performance sensitive code in C++/Rust when needed. The problem is that C++ and Rust are not very easy to learn and converting from a dynamically typed language like Python to a strict, statically typed language like Rust is not easy, especially for people who are not software engineers.The name Oct is a reference to GNU Octave and started as my concept of what Octave should have been, and the name stuck. About 75k lines of Oct code are in the repo across experiments, libraries, and examples. Pretty much all of it is written by Claude/Codex, my role is only to prevent drift/hallucinations.Features, in no particular order:- Function first, statically typed, both interpreted and compiled: Oct code compiles to a Go binary via MIR codegen, runs on anything that Go runs at Go speed, and inherits Go's absurd compile speed, which means that a JIT is mostly unnecessary.
- The entire Go ecosystem is available for Oct if you write a wrapper around it: Oct's `IO.Xlsx` library is `excelize`, Oct's builtin plot is `gonum/plot`, Oct's benchmark profiling is pprof, Oct's C interop is CGo.
- Boring syntax, easy to learn. If you know Rust/Go/C#/Swift, learning Oct would take a few hours at most. Vice versa, if you learn Oct, then you are halfway to knowing how to write Rust already;
- Octest, xUnit.NET style testing framework with `[Fact]/[Theory]` and various Asserts.
- Foundational SI unit built into the language and enforced by typechecker: you can't add Int and Int together. Units also propagate.
```oct
fn StiffnessForce(K: Matrix, u: Vector) -> Vector {
return K @ u
// Matrix @ Vector → Vector
}
```
- You can't ignore errors, Oct is exception free and `null`/`nil`-free, all errors must be handled explicitly: `?` for propagation, `!` for unwrap, or fallible `match`.
- Arrays and vector/matrix are separate but related concepts, with vectors/matrices explicitly defined as Rank 1 and 2 tensors, and Einstein notation for tensors is built into the language.
```oct
let c = a[i, k] * b[k, j]
```
- Octomata, Oct's own built in control system runtime, using explicit finite state machines and utility scoring as primitives for control systems.```oct
package Mainflow DoorControl(openCmd: Bool, closeCmd: Bool, blocked: Bool) -> String {
state Closed {
when {
case openCmd and blocked == false -> goto Opening
else -> return "closed"
}
} state Opening {
when {
case blocked -> goto Closed
case closeCmd -> goto Closing
else -> return "opening"
}
}

state Closing { return "closing" }
}
```
Oct is very much a work in progress, but enough jank/bugs has been fixed that hopefully it wouldn't be embarrassing to show it off now, although rough edges still expected. So, would love some feedback.
MATLAB Python C++ Rust dynamically typed statically typed Go binary MIR codegen

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What is The Oct Programming Language for scientific programming?
The Oct Programming Language for scientific programming is analyzed by our AI as: Addresses frustrations with MATLAB and Python in scientific computing, specifically debugging large codebases, sharing code with less technical colleagues, and the 'Two-Language Problem' (prototyping in Python/MATLAB, rewriting in C++/Rust for performance). Positions itself as a statically typed, interpreted and compiled language that generates Go binaries, offering Go-level speed and ecosystem access, with built-in features for scientific computing (SI units, tensors, control systems) and an easy learning curve for those familiar with Rust/Go/C#/Swift.. It focuses on This language targets a critical friction point in scientific and engineering workflows: the dichotomy between rapid prototyping and production-gra...
Where did The Oct Programming Language for scientific programming originate?
Data for The Oct Programming Language for scientific programming was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was The Oct Programming Language for scientific programming publicly launched?
The initial public indexing or launch date for The Oct Programming Language for scientific programming within our tracked developer communities was recorded on June 17, 2026.
How popular is The Oct Programming Language for scientific programming?
The Oct Programming Language for scientific programming has achieved measurable traction, logging over 4 traction score and facilitating 0 recorded discussions or engagements.
Which technical categories define The Oct Programming Language for scientific programming?
Based on metadata extraction, The Oct Programming Language for scientific programming is categorized under topics such as: MATLAB, Python, C++, Rust.
What are some commercial alternatives to The Oct Programming Language for scientific programming?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as YAGNI, which offers overlapping value propositions.
How does the creator describe The Oct Programming Language for scientific programming?
The original author or development team describes the product as follows: "Apologies in advance if my writing is unclear.First, why make another programming language? This came out of my general frustration with working with MATLAB and Python during grad school as well as..."

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