OANDA JapanのAPIから1分足で大量のデータをダウンロードする方法

from oandapyV20 import API
import oandapyV20.endpoints.instruments as instruments

import json
import datetime
import pandas as pd
from dateutil.relativedelta import relativedelta


def getCandleDataFromOanda(instrument, api, date_from, date_to, granularity):
    params = {
        "from": date_from.isoformat(),
        "to": date_to.isoformat(),
        "granularity": granularity,
    }
    r = instruments.InstrumentsCandles(instrument=instrument, params=params)
    return api.request(r)


def oandaJsonToPythonList(JSONRes):
    data = []
    for res in JSONRes['candles']:
        data.append([
            datetime.datetime.fromisoformat(res['time'][:19]),
            res['volume'],
            res['mid']['o'],
            res['mid']['h'],
            res['mid']['l'],
            res['mid']['c'],
        ])
    return data


if __name__ == "__main__":
    access_info = json.load(open('./config/access_info.json', 'r'))
    accountID = access_info["access_id"]
    access_token = access_info["access_token"]

    api = API(access_token=access_token, environment="live")

    all_data = []
    # 通貨ペアと取得するデータの開始日を指定する
    # 例えば、2020年2月１日からのデータを取得したいとすると
    # startdate = datetime.datetime(2020, 2, 1)
    # とする。
    currency_pair = "USD_JPY"
    startdate = datetime.datetime(2020, 2, 1)

    date_from = None
    date_to = None
    while(1):
        if date_to == None:
            date_from = startdate
        else:
            date_from = date_to + relativedelta(minutes=1)

        date_to = date_from + relativedelta(minutes=4000)
        if date_to > datetime.datetime.now():
            date_to = datetime.datetime.now().replace(second=0, microsecond=0)

            print("From: ", date_from, ",", "To: ", date_to)
            break
        print("From: ", date_from, ",", "To: ", date_to)

        ret = getCandleDataFromOanda("USD_JPY", api, date_from, date_to, "M1")
        data = oandaJsonToPythonList(ret)

        all_data.extend(data)
    # pandas DataFrameへ変換
    df = pd.DataFrame(all_data)
    df.columns = ['Datetime', 'Volume', 'Open', 'High', 'Low', 'Close']
    df = df.set_index('Datetime')
    start = "{}{:0>2}{:0>2}".format(df.index[0].year,
                                    df.index[0].month, df.index[0].day)
    end = "{}{:0>2}{:0>2}".format(df.index[-1].year,
                                  df.index[-1].month, df.index[-1].day)
    # # CSVファイルへの出力
    df.to_csv('./{}_{}-{}_M1.csv'.format(currency_pair, start, end))