Download history data from binance and save to dataframe or csv file

Overview

Binance history data downloader

Download history data from binance and save to dataframe or csv file

Requirements

python 3+
python-binance
pandas
tqdm

Install

git install git+https://github.com/zenoftrading/binance_downloader.git

Usage

Minimal interface:

from binance.client import Client
from binance_downloader import binance_downloader as bd

api_key = 'your binance api key'
api_secret = 'your binance api secret'

client = Client(api_key, api_secret)

candles = bd.get(client)
print(candles)

Output:

downloading BTCUSDT 1h from 2021-08-05 14:55:59 to 2021-08-06 14:55:59
                               open            high             low           close         volume
dateTime                                                                                          
2021-08-05 15:00:00  39005.30000000  39370.00000000  38545.59000000  38750.01000000  5612.00309000
2021-08-05 16:00:00  38750.00000000  39779.00000000  38737.31000000  39739.72000000  5641.43756100
...
2021-08-06 13:00:00  40762.87000000  41025.00000000  40700.68000000  40924.07000000  2340.43658100
2021-08-06 14:00:00  40924.08000000  40973.42000000  40649.89000000  40768.81000000  1563.73017300

Get custom data:

from binance.client import Client
from binance_downloader import binance_downloader as bd
from datetime import datetime

api_key = 'your binance api key'
api_secret = 'your binance api secret'

client = Client(api_key, api_secret)

coin = 'ETHUSDT'
interval = '1m' # support '1m', '1h' or '1d'
start = datetime(2018, 1, 1)
end = datetime(2018, 1, 2)
candles = bd.get(client, coin=coin, interval=interval, start=start, end=end, to_csv=True)
print(candles)

Output:

downloading ETHUSDT 1m from 2018-01-01 00:00:00 to 2018-01-02 00:00:00
1441it [00:01, 780.52its]           
saved to ETHUSDT_1m.csv
                             open          high           low         close        volume
dateTime                                                                                 
2018-01-01 00:00:00  733.01000000  733.97000000  732.75000000  732.75000000   19.77247000
2018-01-01 00:01:00  733.34000000  734.52000000  732.51000000  732.51000000   26.05199000
...                           ...           ...           ...           ...           ...
2018-01-01 23:59:00  755.00000000  755.01000000  754.34000000  754.99000000   40.92658000
2018-01-02 00:00:00  754.99000000  757.76000000  754.34000000  757.76000000  108.80959000

[1441 rows x 5 columns]
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