metagame 0.8.3

MetaGame Trading Bootcamp Python Client

MetaGame Trading Bootcamp Python Client

Write your trading bot with Python!

Dependencies

• python
• uv (which figures out all the python dependencies)

Installing uv

Install uv with the standalone installers:

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Or, from PyPI:

# With pip.
pip install uv

# Or pipx.
pipx install uv

Using bots

This following may not work on Windows without WSL.

0. git clone https://github.com/tradingbootcamp/arbiter && cd arbiter/python-client
1. Install the dependencies with uv sync
2. Copy example.env to .env
3. Go to the "Accounts" page on the exchange and copy your JWT into .env
4. Make sure you are acting as the account you are going to be trading from, then copy the ACT_AS into .env
5. Set API_URL to the base server URL (e.g. https://trading-bootcamp.fly.dev)
6. Optionally set COHORT to the cohort name you want to connect to. If omitted, the cohort is auto-detected from your memberships: if you belong to exactly one cohort it's picked automatically; otherwise (zero or multiple memberships) the client raises ValueError and you must set COHORT explicitly.

You can test if it is working by running

uv run examples/min_max_bot.py "<name of market>"

This command places orders at the min and max settlement prices, so you shouldn't be risking any capital.

You can look at other example bots in examples/, like the code for an (older?) version of mark (market_maker_bot.py) and bob (naive.py).

You can also use list_cohorts() to discover available cohorts programmatically:

from metagame import list_cohorts
info = list_cohorts("https://trading-bootcamp.fly.dev", jwt)
print(info["cohorts"])  # Available cohorts

You can figure out the Jupyter Notebook if you wish.