Download Forex Prices from Yahoo

import os
import pytz
import requests
import pandas as pd
from datetime import datetime, timedelta
# need Stock and Price models ... are very simple
from stocks.models import Price, Stock


def get_working_dir():
    from django_test.settings import MEDIA_ROOT
    working_dir = os.path.join(MEDIA_ROOT, 'scripts')
    return working_dir


def download_file(download_path, local_filename):
    with requests.get(download_path, stream=True) as r:
        r.raise_for_status()
        with open(local_filename, 'wb') as f:
            for chunk in r.iter_content(chunk_size=8192):
                f.write(chunk)


def import_csv_main():

    symbol = 'EUR/USD'  # 'USD/JPY' ... etc ...
    # symbol = 'USD/JPY'
    symbol_replaced = symbol.replace('/', '')

    # create dataset folder if not exists
    working_dir = get_working_dir()
    dataset_folder = os.path.join(working_dir, 'dataset')
    if not os.path.isdir(dataset_folder):
        os.makedirs(dataset_folder)

    # calculate from / to
    today_0_00 = (datetime.now() + timedelta(days=1)).astimezone(pytz.utc).replace(hour=0, minute=0, second=0, microsecond=0)
    period1 = int(datetime.timestamp(today_0_00 - timedelta(days=365 * 5)))  # 5 years
    period2 = int(datetime.timestamp(today_0_00))
    print('from: {}'.format(datetime.fromtimestamp(period1)))
    print('to: {}'.format(datetime.fromtimestamp(period2)))

    # download csv ...
    download_path = 'https://query1.finance.yahoo.com/v7/finance/download/{}=X?period1={}&period2={}&interval=1d&events=history&includeAdjustedClose=true'.format(symbol_replaced, period1, period2)
    local_filename = os.path.join(dataset_folder, '{}.csv'.format(symbol_replaced))
    download_file(download_path, local_filename)

    stock, _ = Stock.objects.update_or_create(name=symbol, defaults={'comment': 'yahoo_csv'})
    # clean prices
    stock.prices.all().delete()
    df = pd.read_csv(local_filename, index_col=['Date'], parse_dates=['Date'])
    for index, row in df.iterrows():
        time = index.to_pydatetime().astimezone(pytz.utc)
        print(time)
        close = float(str(row['Close']).replace(',', ''))
        close_adj = float(str(row['Adj Close']).replace(',', ''))
        openp = float(str(row['Open']).replace(',', ''))
        high = float(str(row['High']).replace(',', ''))
        low = float(str(row['Low']).replace(',', ''))
        volume = float(str(row['Volume']).replace(',', ''))
        Price.objects.update_or_create(time=time, stock=stock,
                                       defaults={'close': close, 'close_adj': close_adj,
                                                 'open': openp,
                                                 'high': high, 'low': low,
                                                 'volume': volume})