Getting Started

Installation

Cointables can be installed using pip:

pip install cointables

It is recommended you run Cointables using a virtualenv virtual environment. To do so, follow the below simple protocol to create the virtual environment, run it, and install the package there:

virtualenv venv
source venv/bin/activate
pip install cointables

To exit the virtual environment, simply type deactivate. To access it at any other time again, enter with the above source venv... command.

Easy GET

Once you have installed Cointables, you can start using it to extract historical Open-High-Low-Close (OHLC) data for various cryptocurrencies from Binance.

You can use Cointables to extract OHLC data for Bitcoin (BTC) in USDT using 30-minute candles:

from cointables import Chart
from binance.client import Client

client = Client(api_key='my_api_key', api_secret='my_api_secret')
btc_chart = Chart(client, coin='BTC', market='USDT', candles='30m')
btc_chart.coinGET()
print(btc_chart.dataframe)

>>> [/O]
                             open_time  ...           low
2023-04-06 02:59:59.999  1680766200000  ...  7.789329e+08
2023-04-06 03:29:59.999  1680768000000  ...  7.773495e+08
2023-04-06 03:59:59.999  1680769800000  ...  7.802205e+08
2023-04-06 04:29:59.999  1680771600000  ...  7.826171e+08
2023-04-06 04:59:59.999  1680773400000  ...  7.785227e+08
...                                ...  ...           ...
2023-04-16 10:29:59.999  1681657200000  ...  9.191869e+08
2023-04-16 10:59:59.999  1681659000000  ...  9.199183e+08
2023-04-16 11:29:59.999  1681660800000  ...  9.169926e+08
2023-04-16 11:59:59.999  1681662600000  ...  9.179277e+08
2023-04-16 12:29:59.999  1681664400000  ...  9.195774e+08

[500 rows x 16 columns]

This creates a Chart object with the specified parameters, calling the internal get_data() method to extract the OHLC data. The resulting data is returned as a Pandas DataFrame object, which can be used for further analysis and visualization.

For more detailed usage instructions, see the cointables package documentation.