{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6",
      "quote": "bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae"
    },
    {
      "url": "https://api.imd.fun/artifacts/fbd2c0ef8a258d64f04248e339e5e400f6ded3cb13f287718f45540542689b76",
      "quote": "91ce2de42cda0eb65638767a546b272549638ee7cf7fb94ed45a9650e5959db7"
    },
    {
      "url": "https://api.imd.fun/artifacts/7d4477490a285f9c7f2eb0d2ac89b584550b5e094737e0fad1d7670280e76bf7",
      "quote": "b1edc389df0c35a2dc0d73096f6a5eed337ff4ef026000ef67621f34773fee8f"
    },
    {
      "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": "def run(self) -> SimulationResult:"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/config.py",
      "quote": "n_steps: int = 2_000"
    }
  ]
}