{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/149883fee797ad95a91e535b7a74453587a3eb19ca87ab95f7d8585db160a8f4",
      "quote": "\"code_sha256\": \"5d1bd5272884f513b19f0e66a7c235f6c188a08e4f7787ac9346f1614dda3ed3\""
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/types.py",
      "quote": "class CancelOrder:\n    order_id: str"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
      "quote": "def sample_config(\n    base_config: ChallengeConfig,\n    variance: ParameterVariance,\n    *,\n    seed: int,\n) -> ChallengeConfig:"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/engine.py",
      "quote": "actions = strategy.on_step(state)\n                market.apply_actions(actions, step=step)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
      "quote": "n_steps: int = 2_000"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/market.py",
      "quote": "def cancel_order(self, order_id: str) -> None:"
    }
  ]
}