yaac 0.1.0

Yet Another AI Company - Python package for loading and using trained image classification models

yaac

Quick Start

1. Clone this repository:

git clone https://github.com/phil-yaac/yaac.git
cd yaac

2. Run the setup script:

./setup/build_env.sh

This will:

• Install uv if not present
• Create a virtual environment
• Install all dependencies
• Set up convenient aliases (ycd and yactivate)

Development

The project uses mypy for type checking, ruff for linting, and ruff format for code formatting. Here's how to use these tools:

Type Checking with mypy

# Check all Python files in the project
mypy yaac/

# Check a specific file
mypy yaac/specific_file.py

# Run with verbose output
mypy -v yaac/

# Faster options:
# Use incremental mode (caches results)
mypy --incremental yaac/

# Use mypy daemon for even faster checks
dmypy start
dmypy run -- yaac/
dmypy stop

Linting with ruff

# Check all Python files in the project
ruff check yaac/

# Check a specific file
ruff check yaac/specific_file.py

# Auto-fix issues where possible
ruff check --fix yaac/

# Show all available rules
ruff rule list

# Run with verbose output
ruff check -v yaac/

Code Formatting with ruff format

# Format all Python files in the project
ruff format yaac/

# Format a specific file
ruff format yaac/specific_file.py

# Check formatting without making changes
ruff format --check yaac/

# Show what would be changed without making changes
ruff format --diff yaac/

Running Tests

# Run all tests
pytest

# Run tests with verbose output
pytest -v

# Run tests for a specific module
pytest tests/models/sic/

# Run a specific test
pytest tests/models/sic/test_sic.py::test_make_model_shapetype

You can also integrate these tools with your editor:

• For VS Code: Install the "Python" and "Ruff" extensions
• For PyCharm: Install the "Mypy" and "Ruff" plugins