Requirements

  • Python 3.11 or later
  • pip

Standard Install

pip install goldencheck

This installs GoldenCheck with all core dependencies:

Package Version Purpose
polars >=1.0 Data operations
typer >=0.12 CLI framework
rich >=13.0 Console output
pyyaml >=6.0 Config file parsing
pydantic >=2.0 Config validation
openpyxl >=3.1 Excel file support
textual >=1.0 Interactive TUI

With LLM Boost

To use --llm-boost you need the optional llm extras:

pip install goldencheck[llm]

This adds:

Package Version Purpose
anthropic >=0.30 Anthropic Claude API
openai >=1.30 OpenAI GPT API

You only need one provider installed, but both are included in the extras group.

With MCP Server

To use goldencheck mcp-serve for Claude Desktop integration:

pip install goldencheck[mcp]

This adds:

Package Version Purpose
mcp >=1.0 Model Context Protocol server SDK

See MCP Server for setup instructions.

All Extras

Install everything:

pip install goldencheck[llm,mcp]

Verify Installation

goldencheck --version
# GoldenCheck 0.5.0

Development Setup

Clone the repository and install in editable mode with dev dependencies:

git clone https://github.com/benzsevern/goldencheck.git
cd goldencheck
pip install -e ".[dev,llm,mcp]"

Dev dependencies include:

Package Purpose
pytest >=8.0 Test runner
pytest-cov >=5.0 Coverage reporting
ruff >=0.4 Linter and formatter

Running Tests

pytest

With coverage:

pytest --cov=goldencheck --cov-report=term-missing

Linting

ruff check goldencheck/
ruff format goldencheck/

Project Structure

goldencheck/
├── goldencheck/
│   ├── cli/          # CLI entry points (Typer)
│   ├── config/       # YAML config loader, schema, writer
│   ├── engine/       # Scanner, validator, reader, sampler
│   ├── llm/          # LLM boost: providers, prompts, budget, merger
│   ├── mcp/          # MCP server (6 tools)
│   ├── models/       # Finding and DatasetProfile dataclasses
│   ├── notebook.py   # Jupyter/Colab display hooks
│   ├── profilers/    # 10 column profilers
│   ├── relations/    # 2 cross-column profilers
│   ├── semantic/     # Semantic type classification
│   ├── reporters/    # Rich console, JSON, CI reporters
│   └── tui/          # Textual TUI (4 tabs)
├── tests/            # pytest test suite (166 tests)
├── benchmarks/       # Speed and detection benchmarks
├── docs/wiki/        # This documentation
└── pyproject.toml