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I've continued working on developing my C interpreter: https://github.com/foonathan/clauf
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Start moving with the new interpretation engine for my TablaM.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Restarting work on https://github.com/lorentzj/serious. I have a clearer objective now: an array-oriented DSL to embed in python to build transformations/models like tensorflow with automatic array shape and access checks. For example, multiplying two matrices, automatically verifying that the first's second dimension size is equal to the second's first dimension size.
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After somewhat completing my previous programming language [CSpydr]https://github.com/spydr06/cspydr, I've started again from scratch with a new language called [Astatine]https://github.com/spydr06/astatine.
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astatine
Astatine is a is a mid-level, statically typed, procedural programming language with some functional components.
After somewhat completing my previous programming language [CSpydr]https://github.com/spydr06/cspydr, I've started again from scratch with a new language called [Astatine]https://github.com/spydr06/astatine.
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candy
🍭 A sweet, functional programming language that is robust, minimalistic, and expressive. (by candy-lang)
Continued working on Candy (https://github.com/candy-lang/Candy).
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I’ve started on my new language, SynthML! The project’s goal is to make program synthesis user-friendly and approachable. I’m also keeping a devlog for the project.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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I wrote a specification a while back for an Expression Language for data validation (mostly for input in loosely typed languages) called Mighty. It’s a pretty simple, expressive, and powerful language that makes validating structured data a breeze. I already implemented it in PHP and currently working on implementing it in other languages (JavaScript makes sense the most right now). The goal is to make an embeddable language to unify how data is validated across multiple languages.
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September was another productive month for Boba, which is starting to get more 'quality of life' improvements rather than broad new features. That doesn't make the work less important: one of the bug fixes to the type inference engine last month caught a previously unseen bug in the core Boba libraries!
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With all of this, the Boba core library has been moved out of the compiler repository to be separately maintained, although they're still very closely linked.
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I've already put together a download page to see what those possibilities might look like when presented, although the product itself is not ready.
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FWIW - here is the stage manager code that I referred to.
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Current work is focused on finding the right feature set. After spending way too much time on thinking about a concrete syntax I decided to instead work on the AST and use S-Expr to serialize it. I plan on sticking with the S-Expr as the "file format" and offer tooling to go back and forth to the yet to be defined concrete syntax.
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I've been doing some work on my Iversonian array language caesura, which just receved a primitive type system with monomorphised functions for arithmetic.
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I'm working on my toy language: https://github.com/differenzkern/hindley-milner So far I've got hindley milner inference with let polymorphism and algebraic data types.
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Two years ago, I was writing a project named KCL in Python: https://github.com/KusionStack/KCLVM/ 。 Fortunately, two years later, I was still working in this project, but I changed from Python to Rust. Using Python did bring some benefits. It was easy to get started and the code was easy to understand, but it finally brought fatal problems to our project, with poor performance. So we used Rust to rewrite the entire compiler implementation, which has brought about a great performance improvement. Some modules have a 20-40 times significant improvement. So we directly chose Rust as the next compiler in blockchain smart contract language, but it is not open source. In the whole process, it is found that Rust's comprehensive quality is really excellent (the performance of the first echelon, and the degree of abstraction is sufficient). Although there is some cost in some language features, such as lifetime, it is not rich in ecology.
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SaaSHub
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