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$ show Calysto/calysto_scheme

[account ↗] [repo ↗] APPLICATION ★ 297 26 ● active (last update 2 months ago)
reviewed by: nvidia/nemotron-3-super-120b-a12b

Calysto Scheme is a sophisticated Scheme interpreter implemented in Python that integrates with Jupyter notebooks. It features a multi-stage compilation pipeline (CPS → DS → RM → Python) with JIT compilation, continuation support (call/cc), and seamless Python interoperability. The system includes advanced optimizations like persistent vectors for O(1) lexical address lookup, epoch-based cache invalidation, and escape analysis for JIT inlining. It's used in educational contexts and provides debugging tools like a stepper-debugger, making it both a practical development tool and a platform for teaching programming language concepts.

RATING8.4/10
QUALITY8.2/10
MAINTENANCEactive
DRIFTlow
CONTRIBUTORS7
VELOCITY0.95
OPEN ISSUES0
CLOSED ISSUES38
LAST COMMIT2 months ago
calysto_scheme (pip)
metakernel (pip)
numpy (pip)
calysto (pip)
yasi (pip)
Files by Type (count)
Python
42
Other (.ss)
27
Jupyter Notebook
9
Markdown
7
Other (.png)
7
Other (.jpg)
5
Makefile
3
Text
2
LaTeX
2
Other (no ext)
2
YAML
1
Git Ignore
1
Files by Type (size)
Other (.pdf)
1MB
Other (.ss)
1MB
Python
918KB
Other (.jpg)
916KB
Jupyter Notebook
289KB
Other (.png)
236KB
Markdown
184KB
Other (.cls)
114KB
Other (.bst)
88KB
LaTeX
88KB
BibTeX
6KB
Makefile
1KB

The LLM identified 2 files worth highlighting for reuse:

Implements a 32-way trie persistent vector for O(1) lexical address lookup in environment frames. This general-purpose data structure provides efficient immutable access with good locality properties, featuring threshold gating to optimize for shallow recursion depths while eliminating O(depth) scaling for deeply nested environments. Demonstrates skill in persistent data structure design and practical performance trade-offs.

file: calysto_scheme/scheme.py ↗ | tags: #persistent-data-structure #functional-programming

Contains an _IdentityCache class that uses epoch-based invalidation to automatically detect when cached values become stale due to object mutations. Instead of tracking individual mutations, it maintains a global epoch that increments on mutations, with cache entries storing the epoch when created. This clever pattern solves a common caching problem with minimal overhead and could be extracted for use in other systems requiring identity-based caching with automatic invalidation.

file: calysto_scheme/scheme.py ↗ | tags: #caching #epoch-based-invalidation
Last analyzed: 2026-08-07 18:47:12.759030
Next check: 2026-08-14 18:47:12.752128
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