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https://github.com/aljazceru/hummingbot-dashboard.git
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63 lines
2.7 KiB
Python
63 lines
2.7 KiB
Python
import pandas as pd
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import requests
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from glom import *
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class MinerUtils:
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MARKETS_ENDPOINT = "https://api.hummingbot.io/bounty/markets"
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@staticmethod
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def reward_splitter(base, reward_dict):
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tmp = {"rewards_HBOT": 0, "rewards_STABLE": 0, "rewards_base": 0, }
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if "HBOT" in reward_dict:
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tmp["rewards_HBOT"] += reward_dict["HBOT"]
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if "USDC" in reward_dict:
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tmp["rewards_STABLE"] += reward_dict["USDC"]
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if "USDT" in reward_dict:
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tmp["rewards_STABLE"] += reward_dict["USDT"]
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if base in reward_dict:
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tmp["rewards_base"] += reward_dict[base]
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return pd.Series(tmp, dtype=float)
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@staticmethod
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def exchange_coingecko_id(exchange: str):
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converter = {
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"kucoin": "kucoin",
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"binance": "binance",
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"gateio": "gate",
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"ascendex": "bitmax"
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}
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return converter.get(exchange, None)
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def get_miner_stats_df(self):
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miner_data = requests.get(self.MARKETS_ENDPOINT).json()
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spec = {
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'market_id': ('markets', ['market_id']),
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'trading_pair': ('markets', ['trading_pair']),
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'exchange': ('markets', ['exchange_name']),
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'base': ('markets', ['base_asset']),
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'quote': ('markets', ['quote_asset']),
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'start_timestamp': ('markets', [("active_bounty_periods", ['start_timestamp'])]),
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'end_timestamp': ('markets', [("active_bounty_periods", ['end_timestamp'])]),
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'budget': ('markets', [("active_bounty_periods", ['budget'])]),
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'spread_max': ('markets', [("active_bounty_periods", ['spread_max'])]),
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'payout_asset': ('markets', [("active_bounty_periods", ['payout_asset'])]),
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'return': ('markets', ['return']),
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'last_snapshot_ts': ('markets', ['last_snapshot_ts']),
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'hourly_payout_usd': ('markets', ['hourly_payout_usd']),
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'bots': ('markets', ['bots']),
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'last_hour_bots': ('markets', ['last_hour_bots']),
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'filled_24h_volume': ('markets', ['filled_24h_volume']),
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# 'weekly_reward_in_usd': ('markets', ['weekly_reward_in_usd']),
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# 'weekly_reward': ('markets', ['weekly_reward']),
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'market_24h_usd_volume': ('markets', ['market_24h_usd_volume'])
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}
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r = glom(miner_data, spec)
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df = pd.DataFrame(r)
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# df = pd.concat([df, df.apply(lambda x: self.reward_splitter(x.base, x.weekly_reward), axis=1)], axis=1)
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df["trading_pair"] = df.apply(lambda x: x.base + "-" + x.quote, axis=1)
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df["exchange_coingecko_id"] = df.apply(lambda x: self.exchange_coingecko_id(x.exchange), axis=1)
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return df
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