Lark VS PurefunctionPipelineDataflow

Lark supports, and recommends, writing and storing the grammar in a .lark file. We have syntax highlighting support in all major IDEs, and even in github itself. For example, here is Lark's built-in grammar for Python: https://github.com/lark-parser/lark/blob/master/lark/grammar...

You can also test grammars "live" in our online IDE: https://www.lark-parser.org/ide/

The rationale is that it's more terse and has less visual clutter than a DSL over Python, which makes it easier to read and write.

First, let me introduce myself. My name is Erez. You may know some of the Python libraries I wrote in the past: Lark, Preql and Data-diff.

It's not super maintained but you might enjoy building something with ppci, Pure Python Compiler Infrastructure. It has some front-ends and some back-ends. There's also PeachPy for an assembler. People like using Lark for parsing, I hear.

lark, a parsing library where I am somewhat involved has a really nice solution to this: Rules starting with _ are inlined in a post processing step.

Lark is a good library to assist with this.

If I may ask, did you consider Lark, and if so, why wasn't it fit for your purposes?

A grammar provides the high level constructs you need to define the "shape" of your data, and it largely takes care of the rest. Grammar libraries exist in other language (eg. lark or Parsimonius in Python) and they weren't created just to make XML parsing easier.

I made a solid attempt at an Earley parser framework of my own, but apparently to get the most reliable performance from Earley parsing you need to implement Joop Leo's improvement for right-recursive grammars, which nobody has been able to adequately explain to me. I've read Kegler's open letter to Vaillant, I've tried to read other implementations, I've even tried to beat my head against the original academic paper, but I don't have the background knowledge to make sense of it all.

Implement relational data model and programming based on hash-map (NoSQL)

The Math-based Grand Unified Programming Theory: The Pure Function Pipeline Data Flow with Principle-based Warehouse/Workshop Model

I criticized "AMD Infinity Fabric Architecture" at the end of my article "Prediction: Intel will use "RISC-V plus x86 compatibility layer" or "RISC-V plus x86 heterogeneous computing architecture" to develop a new generation of "warehouse/workshop model" CPU".

What's more, you're being somewhat liberal with your "invention" dates here anyway. I'm sure you realize that anyone can review the commit history to see when content was added to the repo. As of Nov 2020, the day Apple announced a fully operational and tested, ready-to-ship silicon package the repo was a just series of bullet points listing out well-known concepts of functional programming sprinkled with some religious analogies and inspirational quotes. The farther you go back in the repo commit history, the less content is there.