skka3134

1. Use WSL
2. Install python pip venv, pip is used to install packages, venv is used to create virtual environments

sudo apt update
sudo apt upgrade
sudo apt install python3
sudo apt install python3-pip
sudo apt install python3-venv

3. Create a virtual environment

sudo python3 -m venv bot

4. Activate the environment

source bot/bin/activate 

5. Configure vscode

which python

/home/skka3134/folder/bot/bin/python
6. Select the interpreter, ctrl+shift+p, select the environment "bot" created earlier

7. Install python extension

8. Install ccxt, ccxt encapsulates the APIs of most exchanges worldwide, which we can use to download data and initiate trades

sudo /home/skka3134/folder/bot/bin/python -m pip install ccxt

9. Instantiate the exchange and cache market data

exchange = ccxt.binance({
    'apiKey': '',
    'secret': '',
    'enableRateLimit': True,
})
exchange.load_markets()

11. Use exchange.fetch_ohlcv to get candlestick data, where ohlcv represents o (open), h (high), l (low), c (close), v (volume). Set symbol to the cryptocurrency pair you want to query, time_interval to 1 day, and start to the start time

symbol = 'BTC/USDT' 
time_interval = '1d' 
start = exchange.parse8601('2020-01-01T00:00:00') 
data = exchange.fetch_ohlcv(symbol=symbol, timeframe=time_interval,since=start)

12. Convert the data format for easy viewing, install pandas

sudo /home/skka3134/folder/bot/bin/python -m pip install pandas

13. Convert the data using DataFrame, which is a tabular data structure

import pandas as pd
data = pd.DataFrame(data, dtype=float) 
data.columns = ['Time','Open','High','Low','Close','Volume']
data['Time'] = pd.to_datetime(data['Time'], unit='ms') 

14. Save the new data

data.to_csv('data.csv')