Getting Started

Prerequisites¶

• Python 3.11+

• uv — fast Python package manager

• GitHub CLI (gh) — for authentication and submitting work

Install uv if you don’t have it:

curl -LsSf https://astral.sh/uv/install.sh | sh

Setup¶

# 1. Authenticate with GitHub (one-time)
gh auth login

# 2. Clone and install
git clone https://github.com/QuantEcon/benchmark.translate-zh-cn.git
cd benchmark.translate-zh-cn
uv sync

# 3. Verify your setup
uv run qebench doctor

The doctor command checks that everything is configured correctly:

  ✓ GitHub CLI (gh) installed
  ✓ GitHub authenticated as your-username
  ✓ Git installed
  ✓ Inside a git repository
  ✓ Remote origin configured
  ✓ config.yaml found
  ✓ Dataset has entries
  ✓ uv package manager installed

Quick Start¶

# Pull latest code and data (run this each time you start a session)
uv run qebench update

# Check dataset status
uv run qebench stats

# Practice translating
uv run qebench translate

# Contribute new entries
uv run qebench add

# Submit your work to GitHub (updates the dashboard)
uv run qebench submit

Your GitHub username is detected automatically — no need to pass --user.

Daily Workflow¶

Every time you sit down to work, follow this pattern:

update → work → submit

1. qebench update — pulls the latest code, data, and dependencies from GitHub

2. Do your work — translate, add, or both

3. qebench submit — commits and pushes your changes

You never need to run git or uv commands directly — the CLI handles it.

How It Works¶

1. You run commands — translate or add save results to per-user files locally

2. You submit — qebench submit commits and pushes your work to GitHub

3. Dashboard updates — a GitHub Actions workflow exports data and rebuilds the dashboard

All data files are per-user (data/terms/your-username.json, results/xp/your-username.json), so there are no merge conflicts between contributors.

Next Steps¶

• Your First Translation Session — the main interactive mode

• CLI Reference — all available commands