Code Weaver

A proactive code healer that predicts and fixes Python issues before they cause problems, with ML-based learning from user feedback.

Features

• AST-based Analysis: Deep code analysis using Python's Abstract Syntax Tree
• Issue Detection: Finds undefined variables, unused imports, type errors, and syntax issues
• Auto-fix Suggestions: Intelligent fix suggestions with confidence scores
• ML Learning: Learns from your feedback to improve fix suggestions over time
• File Watching: Continuous monitoring with automatic issue detection
• Safe Healing: Rollback support and atomic file operations

Installation

pip install weave-master

Quick Start

Command Line

# Analyze a file or directory
weave check src/
weave check myfile.py

# Watch mode (continuous monitoring)
weave watch src/

# Interactive fix mode
weave heal src/myfile.py

# Rollback last fix
weave rollback src/myfile.py

# View/manage ML model
weave model status        # Show model stats
weave model retrain       # Force retrain
weave model reset         # Reset to baseline

# Configure
weave config set auto_heal true
weave config set confidence_threshold 0.85

Python API

from code_weaver import Weaver, analyze_file, analyze_code

# Quick analysis
issues = analyze_file("mycode.py")
issues = analyze_code("x = undefined_var")

# Full control
weaver = Weaver(
    auto_heal=False,
    confidence_threshold=0.8,
    learn=True,  # Enable ML feedback
)

# Analyze
issues = weaver.analyze("src/")

# Apply fixes interactively
for issue in issues:
    if issue.suggested_fix:
        weaver.apply_fix(issue)  # Prompts for confirmation

# Watch mode
weaver.watch("src/", callback=my_handler)

Issue Types Detected

Undefined Variables

• Detects use before assignment
• Suggests imports, typo fixes, or initialization

Unused Imports

• Tracks all imports and their usage
• Safe removal suggestions

Type Errors

• Detects obvious type mismatches (str + int, etc.)
• Uses type hints when available

Syntax Issues

• Missing colons, unmatched brackets
• f-string errors
• Indentation problems

Configuration

Code Weaver stores its configuration in ~/.config/code_weaver/config.json:

{
    "auto_heal": false,
    "confidence_threshold": 0.8,
    "watch_debounce_ms": 300,
    "max_history_per_file": 50,
    "ignore_patterns": [".git", "__pycache__", "venv", ".venv", "node_modules"]
}

ML Feedback System

Code Weaver learns from your decisions:

1. When you accept or reject a fix, the feedback is recorded
2. Features are extracted from each issue (type, severity, context, etc.)
3. A RandomForest classifier learns your preferences
4. Future suggestions are ranked by predicted acceptance probability

Force retrain the model:

weave model retrain

Reset to baseline:

weave model reset

Support

License

MIT License - see LICENSE file for details.