mirror of
https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
62 lines
1.4 KiB
Python
62 lines
1.4 KiB
Python
#%%
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import pandas as pd
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from tqdm import tqdm
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from utils.glassnode import GlassnodeClient, Indicators, Mining
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path = 'data/daily_glassnode/'
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client = GlassnodeClient(asset='BTC', since='2014-01-01', until='2021-12-17')
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print("Client initiated")
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indicator_client = Indicators(client)
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indicator_names = ['rhodl_ratio',
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'cvdd',
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'difficulty_ribbon_compression',
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'nvt_ratio',
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'nvt_signal',
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'velocity',
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'supply_adjusted_cdd',
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'binary_cdd',
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'supply_adjusted_dormancy',
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'puell_multiple',
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'asopr',
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'reserve_risk',
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'sopr',
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'cdd',
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'asol',
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'msol',
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'dormancy',
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'liveliness',
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'relative_unrealized_profit',
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'relative_unrealized_loss',
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'nupl',
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# 'sth_nupl',
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# 'lth_nupl',
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'ssr',
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'bvin',
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]
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def process_df(df: pd.DataFrame) -> pd.DataFrame:
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df.index.rename('time', inplace=True)
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if len(df.columns) != 1:
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df = df[['v']]
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df.rename(columns={df.columns[0]: 'close'}, inplace=True)
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df.sort_index(inplace=True)
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return df
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for name in tqdm(indicator_names):
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method_to_call = getattr(indicator_client, name)
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df = method_to_call()
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df = process_df(df)
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df.to_csv(path + name + '.csv')
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# Mining data
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mining_names = ['hash_rate']
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mining_client = Mining(client)
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for name in tqdm(mining_names):
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method_to_call = getattr(mining_client, name)
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df = method_to_call()
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df = process_df(df)
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df.to_csv(path + name + '.csv') |