feat(Data): added daily_glassnode DataCollection (#99)

run_fetch_data_glassnode.py

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