{
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      "quote": "4f9167dddd457f394e988bf9c9e2576dd6120834bfb8d93573ce9451fd587598"
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    {
      "url": "https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6",
      "quote": "bf0d179f3e47d28819f6fa7e0d25548c2ced43374c216d36460b00a26a26ffae"
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    {
      "url": "https://api.imd.fun/artifacts/2d4b30bbc6bffbc500b37ce5e8a1ac821d6513c52a6a2377b4be3c11d97717fb",
      "quote": "3c07bdcd221ac25729c3ebc92b21ac9e2014510ecb85816c4391ed81e933291f"
    },
    {
      "url": "https://api.github.com/repos/danrobinson/prediction-market-challenge/commits/b244530ee2a6247b5f930830eeca9dd950da0e7e",
      "quote": "b244530ee2a6247b5f930830eeca9dd950da0e7e"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
      "quote": "        config = sample_config(base, var, seed=seed)\n        engine = SimulationEngine(config, strategy_factory, seed=seed)\n        results.append(engine.run())"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/loader.py",
      "quote": "    def factory():\n        instance = strategy_cls()"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/engine.py",
      "quote": "    def run(self) -> SimulationResult:\n        strategy = self._strategy_factory()"
    }
  ]
}