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        "author": "Dema Ushchapovskyy, Suraj Tirupati",
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        "description": "## gym-crypto\n\nOpenAI Gym compatible environment for crypto-currency trading.\nThe environment allows to change the currency the bot trades, the granularity of trading \nand starting capital of the agent. More configurability to come in the future. \n\n### Observation Space\n\nThe observation space is a tuple structured as follows:\n\n```(OCHLV, Current Capital, Weight of the capital invested)```\n\nOCHLV represents Open, Close, High, Low prices and Volume respectively. So the total capital invested into\na coin at any time is:\n\n```(Current Capital)*(Weight of the capital invested)```\n\n### Action Space\n\nAction space is a single scalar between -1 and 1, which represents the percentage of the capital\nthat the agent has invested into the currency at the last time step.\n\n-1 representing a full short position and 1 representing a full long position.\n\n### Rewards\n\nThe reward is defined as the total amount of capital that has been gained/lost for that time-step.\nThis number includes the return on the investment as well as the transaction costs.\n\n#### Usage\n\nIn order to train the agent, the enviroment first has to be configured. This example shows how to handle the\ntraining and testing of the agents:\n\n```python\nimport gym\nfrom gym_crypto import configs\n\nenv = gym.make(\"gym-crypto-v0\")\nenv.configure_env(**configs.DEFAULT_CONFIG)\n\n### Train an agent on the environment\n\ntest_config = configs.DEFAULT_CONFIG.update({'start_date':'2019-01-01', 'end_date':'2019-06-01'})\nenv.configure_env(**test_config)\n\ndone = False\nobservation = env.reset()\n\nwhile not done:\n    action = agent.predict(observation)\n    observation, _, done, _ = env.step(action)\n\nreturns, weights = env.render()\n```\n\nTo get some results from the agent, a ```env.render()``` needs to be called, which will return\nthe capital returns as the first variable and weight allocation as the second variable. More detailed\nresults will be coming in the future.\n\n#### Data\n\nTo futher inspect the data two methods can be called from the ```data_utils``` module.\n\n```python\nfrom gym_crypto.data_utils.data_utils import *\n\ncurrencies = get_avaliable_currencies()\nfull_data = read_data('BTC')\n```\n\nAll data was obtained from the Bitfinex API.\n\n\n",
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