simuradar 0.1.0

Code duplication detection using AST analysis

Simuradar

AST-based Python code duplication detection.

Why AST?

Simuradar uses Python's built-in ast module—no external parser dependencies. This means:

• Zero parser dependencies — Only standard library + output formatters
• Native Python version alignment — The AST parser IS your Python interpreter. No parser/ runtime version mismatches
• Automatic updates — When Python adds new syntax match (like in 3.10 or improved f-strings in 3.12), Simuradar gets it for free
• No third-party parser edge cases — External parsers may diverge from CPython's behavior. We use the real thing

Installation

pip install .
# or with uv
uv pip install .

Usage

simuradar /path/to/project

Options:

• --engine {apted,jaccard,jaccard-norm} — Similarity algorithm (default: jaccard)
• --threshold 0.8 — Similarity threshold 0.0-1.0 (default: 0.8)
• --output {rich,json} — Output format (default: rich)

How It Works

1. Parse — Walk the target directory, extract code fragments (functions, classes, modules) using Python's ast module
2. Normalize — Optional: strip comments, normalize whitespace (not yet implemented)
3. Compare — Run selected similarity algorithm against all fragment pairs
4. Report — Group similar fragments and display results

Engines

Engine	Description	Complexity
apted	Tree edit distance (APTED)	O(n³) — Slow but accurate
jaccard	Node type Jaccard similarity	O(n²) — Fast
jaccard-norm	Jaccard + subtree patterns	O(n²) — Balanced

Requirements

• Python 3.12+
• cyclopts (CLI)
• rich (terminal output)
• apted (optional, for apted engine)