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coinglass-api

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    coinglass-api

Unofficial Python client for Coinglass API


Maintainers
1

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Coinglass API

PyPi version Downloads Python 3.10 codecov API unittest

Unofficial Python client for Coinglass API

Wrapper around the Coinglass API to fetch data about crypto derivatives. All data is output in pandas DataFrames (single or multi-index) and all time-series data uses a DateTimeIndex. Supports all Coinglass API endpoints.

Example Plot

Installation

pip install coinglass-api

Usage

from coinglass_api import CoinglassAPI

cg = CoinglassAPI(coinglass_secret="abcd1234")

# Get perpetual markets for BTC
perp_markets_btc = cg.perpetual_market(symbol="BTC")

# Get OI history
oi_history_btc = cg.open_interest_history(symbol="BTC", time_type="h1", currency="USD")

# Funding rate of ETH on dYdX
fr_btc_dydx = cg.funding(ex="dYdX", pair="ETH-USD", interval="h8")

# Get average funding for BTC
fr_avg_btc = cg.funding_average(symbol="BTC", interval="h4")

# Get funding OHLC for ETH-USDT on Binance
fr_ohlc_eth_binance = cg.funding_ohlc(ex="Binance", pair="ETHUSDT", interval="h4")

# Get aggregated OI OHLC data for BTC
oi_agg_eth = cg.open_interest_aggregated_ohlc(symbol="ETH", interval="h4")

# Get OHLC liquidations data for ETH-USD on dYdX
liq_ohlc_eth_dydx = cg.liquidation_pair(ex="dYdX", pair="ETH-USD", interval="h4")

# Get liquidation data for BTC
liq_btc = cg.liquidation_symbol(symbol="BTC", interval="h4")

# Get long/short ratios for BTC
lsr_btc = cg.long_short_symbol(symbol="BTC", interval="h4")

# Get GBTC market history
gbtc_history = cg.grayscale_market_history()

# and more...

Examples

>>> cg.funding(ex="dYdX", pair="ETH-USD", interval="h8").head()

time
exchangeName
symbol
quoteCurrency
fundingRate
2022-08-22 08:00:00dYdXETHUSD-0.001151
2022-08-22 16:00:00dYdXETHUSD0.001678
2022-08-23 00:00:00dYdXETHUSD0.003743
2022-08-23 08:00:00dYdXETHUSD0.003561
2022-08-23 16:00:00dYdXETHUSD0.000658
>>> cg.funding(ex="dYdX", pair="ETH-USD", interval="h8").info()
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 500 entries, 2022-08-22 08:00:00 to 2023-02-04 16:00:00
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype  
---  ------         --------------  -----  
 0   exchangeName   500 non-null    object 
 1   symbol         500 non-null    object 
 2   quoteCurrency  500 non-null    object 
 3   fundingRate    500 non-null    float64
dtypes: float64(1), object(3)
memory usage: 19.5+ KB
>>> cg.funding(ex="dYdX", pair="ETH-USD", interval="h8").plot(y="fundingRate")

funding_rate

Disclaimer

This project is for educational purposes only. You should not construe any such information or other material as legal, tax, investment, financial, or other advice. Nothing contained here constitutes a solicitation, recommendation, endorsement, or offer by me or any third party service provider to buy or sell any securities or other financial instruments in this or in any other jurisdiction in which such solicitation or offer would be unlawful under the securities laws of such jurisdiction.

Under no circumstances will I be held responsible or liable in any way for any claims, damages, losses, expenses, costs, or liabilities whatsoever, including, without limitation, any direct or indirect damages for loss of profits.

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