btc_historical_csv.py

import csv
import json
import os

import pandas as pd
from binance.client import Client

# init
api_key = os.environ.get('binance_api')
api_secret = os.environ.get('binance_secret')

client = Client(api_key, api_secret)

## main

# valid intervals - 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1M
# get timestamp of earliest date data is available
timestamp = client._get_earliest_valid_timestamp('BTCUSDT', '1d')
print(timestamp)

# request historical candle (or klines) data
bars = client.get_historical_klines('BTCUSDT', '1d', timestamp, limit=1000)
# print(bars)

# option 1 - save to file using json method - this will retain Python format (list of lists)
with open('btc_bars.json', 'w') as e:
	json.dump(bars, e)

# option 2 - save as CSV file using the csv writer library
with open('btc_bars.csv', 'w', newline='') as f:
	wr = csv.writer(f)
	for line in bars:
		wr.writerow(line)

# option 3 - save as CSV file without using a library. Shorten to just date, open, high, low, close
with open('btc_bars2.csv', 'w') as d:
	for line in bars:
		d.write(f'{line[0]}, {line[1]}, {line[2]}, {line[3]}, {line[4]}\n')

# delete unwanted data - just keep date, open, high, low, close
for line in bars:
	del line[5:]

# option 4 - create a Pandas DataFrame and export to CSV
btc_df = pd.DataFrame(bars, columns=['date', 'open', 'high', 'low', 'close'])
btc_df.set_index('date', inplace=True)
print(btc_df.head())
# export DataFrame to csv
btc_df.to_csv('btc_bars3.csv')