mirror of
https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
66 lines
1.4 KiB
Python
66 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 = [
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"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")
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