#%%
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')