keyan/schemeling — explained in plain English
Analysis updated 2026-07-03 · repo last pushed 2015-02-04
Build a code editor that highlights Scheme syntax.
Create an automated tool that refactors or evaluates Scheme code.
Develop a custom interpreter for Scheme or Lisp-like languages.
| keyan/schemeling | 0xhassaan/nn-from-scratch | a-little-hoof/dsr | |
|---|---|---|---|
| Stars | — | 0 | 0 |
| Language | Python | Python | Python |
| Last pushed | 2015-02-04 | — | — |
| Maintenance | Dormant | — | — |
| Setup difficulty | easy | moderate | hard |
| Complexity | 2/5 | 4/5 | 5/5 |
| Audience | developer | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Schemeling is a Python tool that reads Scheme code and breaks it down into structured pieces your programs can work with. In simple terms, if you have text written in the Scheme programming language, this library takes that raw text and converts it into a format Python can understand and manipulate. Scheme is a dialect of Lisp, known for its minimalist syntax and heavy use of parentheses. A parser like this takes that text, figures out the underlying structure, and represents it as a tree of nested elements. This allows developers to programmatically inspect, analyze, or transform Scheme expressions without having to write their own parsing logic from scratch. This would be useful for anyone building tools that interact with Scheme or Lisp-like languages. For example, if you are creating a code editor that highlights Scheme syntax, an automated tool that refactors or evaluates Scheme code, or even a custom interpreter, this library handles the foundational step of translating raw text into a workable data structure. The project is written in Python, making it accessible to developers already working in that ecosystem. Beyond that, the README doesn't go into detail about specific design decisions, performance tradeoffs, or advanced features.
Schemeling is a Python library that parses Scheme code text and converts it into structured data your programs can easily work with and manipulate.
Mainly Python. The stack also includes Python.
Dormant — no commits in 2+ years (last push 2015-02-04).
The explanation does not mention a license, so it is unclear what permissions you have for using this code.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.