https://github.com/stephanakkerman/crypto-ohlcv

Gets historical OHLCV data from supported exchanges and converts it into dataframe readable by TensorTrade.
https://github.com/stephanakkerman/crypto-ohlcv

binance bitcoin crypto cryptocurrency data ethereum ftx ohlcv ohlcv-data

Last synced: about 2 months ago
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Gets historical OHLCV data from supported exchanges and converts it into dataframe readable by TensorTrade.

• Host: GitHub
• URL: https://github.com/stephanakkerman/crypto-ohlcv
• Owner: StephanAkkerman
• License: mit
• Created: 2021-07-14T11:11:01.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2023-08-09T14:32:40.000Z (over 1 year ago)
• Last Synced: 2024-05-02T00:56:54.909Z (9 months ago)
• Topics: binance, bitcoin, crypto, cryptocurrency, data, ethereum, ftx, ohlcv, ohlcv-data
• Language: Python
• Homepage:
• Size: 32.2 KB
• Stars: 15
• Watchers: 2
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Crypto OHLCV (Open High Low Close Volume)

[![Python 3.8](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![MIT License](https://img.shields.io/github/license/StephanAkkerman/Crypto_OHLCV.svg?color=brightgreen)](https://opensource.org/licenses/MIT)

---

crypto-ohlcv is a simple Python script that lets you fetch historical OHLCV data from ccxt supported exchanges.

I wrote this script, because my other script focussed solely on Binance, whereas this one supports many exchanges.

It consists of one simple function called `fetch_data()`, that returns a pandas Dataframe, readible by TensorTrade.

## How to use

- Add `ohlcv.py` located in src to same directory you're working in.

- Write: `from ohlcv import fetch_data`.

- To get the latest 500 daily data points of OHLCV on the BTC/USDT pair from Binance, write: `fetch_data(exchange='binance', symbol="BTC/USDT", timeframe='1d', limit=500)`.

- The result will be a pandas DataFrame consisting of the latest 500 daily candles of BTC/USDT on Binance.

## Supported exchanges

The `exchange` parameter should be one of the exchanges supported by ccxt, you can find the supported exchanges [here](https://github.com/ccxt/ccxt/wiki/Exchange-Markets).

## Symbols

`Symbol` can be any pair available on the specified exchange.

## Time frames

Supported time frames are: '1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h', '6h', '8h', '12h', '1d', '3d', '1w', '1M'.

## Limit

`Limit` is the number of rows you would like to have returned, leaving this unspecified will return most available.

Using `since` as parameter will change the starting point of gathering the data, this is an integer consisting of UTC timestamp in milliseconds. You can also specify it as a string or datetime object, it will automatically be converted to the right format.