{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/db22aff7167a4798251ed3d20432509f30e511e4958799aba5b17b41bb39b4b6",
      "quote": "Started from 151e0b1b16f90a1384b823bc528d6d1407f7b4bbfcc7966c12119fe483bfd326 and merged syntax-tree fragments from c1-pairs (spread 1), c2-queue (spread 2), a3-ledger (spread 3), and c4-all (spread 4"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/types.py",
      "quote": "    `buy_filled_quantity` and `sell_filled_quantity` are the participant's\n    aggregate filled quantities from the previous step."
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/orderbook_pm_challenge/runner.py",
      "quote": "    rng = random.Random(seed)"
    },
    {
      "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": "        quantity = quantize_down(float(action.quantity), self._config.share_quantum)"
    },
    {
      "url": "https://raw.githubusercontent.com/danrobinson/prediction-market-challenge/b244530ee2a6247b5f930830eeca9dd950da0e7e/pyproject.toml",
      "quote": "dependencies = []"
    }
  ]
}