crypto_fees_2021.py

crypto_fees_2021.py

import requests
import pandas as pd
from datetime import date, timedelta


def cryptofees(_query_str):
    fees_requests = requests.get("https://cryptofees.info/api/v1/feesByDay?" + _query_str)
    json_data = fees_requests.json()
    _df = pd.json_normalize(json_data['data'], record_path=['data'], meta=['id'], errors='ignore')

    # _df.id.replace(id_dict, inplace=True)

    return _df

id_dict = {
    # 'eth': 'Ethereum',
    # 'bsc': 'Binance Smart Chain',
    # 'uniswap-v3': 'Uniswap V3',
    # 'uniswap-v2': 'Uniswap V2',
    # 'compound': 'Compound',
    # 'aave-v2': 'Aave V2',

    # 'sushiswap-ethereum': 'Sushiswap - Ethereum',
    # 'trader-joe': 'Trade Joe',
    # 'terraswap': 'Terraswap',
    # 'aave-v2-polygon-proto': 'Aave - Polygon',

    'btc': 'Bitcoin',
    # 'maker': 'MakerDAO',
    # 'avalanche-c-chain': 'Avalanche C-chain',
    # 'aave-v2-avalanche-proto': 'Aave V2 - Avalanche',
    # 'solana': 'Solana',

    # 'quickswap': 'Quickswap',
    # 'ens': 'Ethereum Naming Service',
    # 'balancerv2': 'Balance V2',
    # 'bancor': 'Bancor',
    # 'polygon-pos': 'Polygon',
    # 'pangolin': 'Pangolin',

    # 'sushiswap-polygon': 'Sushiswap - Polygon',
    # 'arbitrum-one': 'Arbitrum',
    # 'fantom': 'Fantom',
    # 'uniswap-polygon': 'Uniswap - Polygon',

    # 'sushiswap-arbitrum-one': 'Sushiswap - Arbitrum',
    # 'ada': 'Cardano',
    # 'balancerv2-polygon': 'Balancer - Polygon',
    # 'uniswap-arbitrum': 'Uniswap - Arbitrum',

    # 'balancer-v1': 'Balancer V1',
    # 'liquity': 'Liquity',
    # 'terra': 'Terra',
    # 'dfyn': 'Dfyn',
    # 'aave-v1': 'Aave V1',
    # 'tornado-ethereum': 'Tornado',

    # 'hop-optimism': 'Hop - Optimism',
    # 'ren': 'Ren',
    # 'hop-polygon': 'Hop - Polygon',
    # 'hop-arbitrum': 'Hop - Arbitrum',
    # 'doge': 'Doge',
    # 'xdai': 'xDAI',
    # 'xtz': 'Tezos',

    # 'spookyswap': '',

    # 'abracadabra-ethereum': '',
    # 'abracadabra-bsc': '',
    # 'abracadabra-arbitrum-one': '',
    # 'abracadabra-fantom': '',
    # 'abracadabra-avalanche': '',

    # 'polkadot': 'Polkadot',
    # 'balancerv2-arbitrum': 'Balancer V2 - Arbitrum',
    # 'polymarket': 'Polymarket',
    # 'bsv': 'Bitcoin Satoshi Vision',
    # 'zilliqa': 'Zilliqa',
    # 'honeyswap': 'HoneySwap',

    # 'xlm': 'Stellar',
    # 'xrp': 'Ripple',
    # 'ltc': 'Litecoin',
    # 'sushiswap-fantom': 'Sushiswap - Fantom',
    # 'swapr-xdai': 'Swapr - xDAI',
    # 'hop-xdai': 'Hop - xDAI',

    # 'synthetix-mainnet': 'Synthetix',
    # 'mstable': 'mStable',
    # 'avalanche-x-chain': 'Avalanche X-chain',
    # 'swapr-arbitrum': 'Swapr - Arbitrum',
    # 'xmr': 'Monero',

    # 'bch': 'Bitcoin Cash',
    # 'aave-v2-amm': 'Aave V2',
    # 'swapr-ethereum': 'Swapr - Ethereum',
    # 'kusama': 'Kusama',
    # 'uniswap-v1': 'Uniswap V1',
    # 'avalanche-p-chain': 'Avalanche P-chain',
    # 'linkswap': 'Linkswap'
}
column_dict = {
    'id': '',
    'name': '',
    'fee': 'Fees',
}

date_obj = pd.date_range(start="2021-01-01", end='2021-12-31', freq='D').to_pydatetime().tolist()
# date_obj = pd.date_range(start="2021-01-01", end="2021-01-31", freq='D').to_pydatetime().tolist()
date_str = [i.strftime('%Y-%m-%d') for i in date_obj]
separator = ","
get_date = separator.join(date_str)
query_str=''
df_orig = pd.DataFrame()

# for i in ['polygon']:
for i in list(id_dict.keys()):
    print('started' + i)
    for j in date_obj:
        try:
            txt = i + '=' + j.strftime('%Y-%m-%d') + '&'
            cryptofees(txt)
        except:
            txt=''
            pass
        else:
            query_str += txt
            df_orig = pd.concat([df_orig, cryptofees(txt)], axis=0).reset_index(drop=True)
    print('finished' + i)
    df_orig.to_csv('cryptofees_yearly.csv')

print(df_orig)

# df_orig['year'] = pd.to_datetime(df_orig['date']).dt.year
# df_final = df_orig.groupby(['id', 'year']).sum()
# df_final.to_csv('cryptofees_yearly.csv')

# print(df_final)

# pd.DataFrame(missing_list).to_csv('missing_protocol_dates_1.csv')
# for each protocol and each day, see if data exists
# if data exists add it to a data frame as date, protocol, fees