astonai 0.2.0

Test Intelligence Engine

Aston AI

Aston is a code intelligence system for parsing, analyzing, and finding test coverage gaps in your code.

Installation

# Install from PyPI
pip install astonai

# For LLM-powered features (optional)
pip install "astonai[llm]"

Quick Start

# Initialize your repository
aston init --offline

# Generate knowledge graph relationships
aston graph build

# View knowledge graph statistics
aston graph stats

# Find critical paths and generate test suggestions
aston coverage --critical-path
aston test-suggest core/auth.py

Core Commands

Repository Initialization

# Initialize repository and create knowledge graph
aston init [--offline]

Options:

• --offline: Skip Neo4j integration and work with local files only (default)
• --online: Use Neo4j if available (broken right now)

Test Coverage

# Run tests with coverage
aston test

# Find testing gaps
aston coverage [--threshold 80] [--json results.json] [--exit-on-gap]

# Identify critical implementation nodes
aston coverage --critical-path [--n 50] [--weight loc]

Options:

• --threshold: Minimum coverage percentage (default: 0)
• --json: Output results in JSON format
• --exit-on-gap: Return code 1 if gaps found (useful for CI)
• --coverage-file: Specify custom coverage file location
• --critical-path: Identify critical code paths that need testing
• --n: Number of critical nodes to return (default: 50)
• --weight: Weight function for critical path (loc, calls, churn)

Knowledge Graph

# Build edge relationships between nodes
aston graph build

# View statistics about the knowledge graph
aston graph stats

# Export graph to DOT format
aston graph export [--output graph.dot] [--filter CALLS,IMPORTS] [--open]

# Open interactive graph viewer in browser
aston graph view [--filter CALLS,IMPORTS]

The graph command provides:

• build: Analyzes your codebase to extract CALLS and IMPORTS edges
• stats: Displays node and edge statistics
• export: Converts the graph to Graphviz DOT format
• view: Opens an interactive D3.js visualization in your browser

Test Suggestions

# Generate test suggestions for a file or function
aston test-suggest <file_or_node> [--k 5] [--llm] [--model gpt-4o]

# Generate rich context for developers or AI agents
aston test-suggest <file_or_node> --prompt [--llm]

# Debug path resolution issues
aston test-suggest <file_or_node> --debug

Options:

• --k: Number of suggestions to generate (default: 5)
• --llm: Use LLM fallback if heuristics fail
• --model: LLM model to use (default: gpt-4o)
• --budget: Maximum cost per suggestion (default: $0.03)
• --prompt, -p: Generate rich context for test development
• --debug: Enable detailed debugging output
• --json/--yaml: Output results in structured format

Environment Check

# Check if all required dependencies are installed
aston check

Options:

• --no-env-check: Skip environment dependency check (also works with any command)

Repository-Centric Design

Aston follows a repository-centric approach:

• All operations are relative to the repository root (current directory)
• Data is stored in .testindex directory at the repository root
• Path resolution is normalized for consistent matching
• Works with both offline and Neo4j storage

Environment Variables

DEBUG=1                      # Enable debug logging
NEO4J_URI=bolt://localhost:7687  # Optional Neo4j connection
NEO4J_USER=neo4j            # Optional Neo4j username
NEO4J_PASS=password         # Optional Neo4j password
ASTON_NO_ENV_CHECK=1        # Skip environment dependency check
OPENAI_API_KEY=sk-...       # Required for --llm features