wardbradt
peregrine
Python

Detects arbitrage opportunities across 131 cryptocurrency exchanges in 50 countries

Last updated Jul 8, 2026
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README

Peregrine

A Python library which provides several algorithms to detect arbitrage opportunities across over 120 cryptocurrency exchanges in 48 countries on over 38,000 trading pairs

I created this in 2017 as a proof-of-concept to familiarize myself with cryptocurrency arbitrage. I had fun building it, but do not presently have the bandwidth to maintain the repository. There are some known issues. See the Future Development section to see current issues and ideas for improvement.

Install · Usage · Future Development

Install

  • Ensure you have installed pip.
  • Run the following in your command line:
pip install git+https://github.com/wardbradt/peregrine

Usage

This section provides a brief overview of Peregrine's functionality. Examples demonstrating many more features are available in peregrine/examples.

Multiples Exchange/ One Currency

from peregrinearb import getopportunityfor_market
import asyncio
collections_dir = '/Users/wardbradt/cs/peregrine/'
opportunity = asyncio.geteventloop().rununtilcomplete(getopportunityformarket("BTC/USD", collectionsdir))
print(opportunity)

At the time of writing, this prints the following in less than one second.

{'highest_bid': {'exchange': <ccxt.async.lakebtc.lakebtc object at 0x10ea50518>, 'price': 11750.59},
'lowest_ask': {'exchange': <ccxt.async.gdax.gdax object at 0x10ea50400>, 'price': 8450.01}}

If you want to specify which exchanges to find opportunities on:

from peregrinearb import getopportunityfor_market
import asyncio

collections_dir = '/Users/wardbradt/cs/peregrine/' opportunity = asyncio.geteventloop().rununtilcomplete(getopportunityformarket("BTC/USD", collectionsdir, exchanges=["anxpro", "bitbay", "coinfloor", "gemini", "livecoin"])) print(opportunity)

If you want to find opportunities on the exchanges of only a certain country1, you can do it like so:

from peregrinearb import buildspecificcollections, getopportunityfor_market

usethbtcexchanges = buildspecific_collections(countries=['US']) collections_dir = '/Users/wardbradt/cs/peregrine/' opportunity = getopportunityformarket("ETH/BTC", collectionsdir, usethbtc_exchanges["ETH/BTC"]) print(opportunity)

1Accepted arguments in place of 'US' in this example are 'PA', 'AU', 'CA', 'JP', 'SG', 'HK', 'NZ', 'IE', 'CN', 'KR', 'IL', 'MT', 'EU', 'VG', 'GB', 'RU', 'PL', 'SC', 'MX', 'NL', 'BR', 'PH', 'UA', 'TR', 'IS', 'TH', 'DE', 'CY', 'CL', 'TW', 'ID', 'UK', 'IN', 'VN', 'BG', 'CZ', 'ES', 'SE', 'VC', 'ZA', 'CH', 'TZ', 'FR', 'AR', 'VE', 'PK', and 'AT'.

One Exchange/ Multiple Currencies

import asyncio
from peregrinearb import loadexchangegraph, printprofitopportunityforpath, bellman_ford
graph = asyncio.geteventloop().rununtilcomplete(loadexchangegraph('hitbtc'))

paths = bellman_ford(graph) for path in paths: printprofitopportunityforpath(graph, path)

This prints all of the arbitrage opportunities on the given exchange (in this case, HitBTC). At the time of writing, the first opportunity printed out is:

Starting with 100 in BTC
BTC to USDT at 7955.100000 = 795510.000000
USDT to NEO at 0.016173 = 12866.084425
NEO to ETH at 0.110995 = 1428.071041
ETH to XLM at 2709.292875 = 3869062.695088
XLM to BTC at 0.000026 = 100.208724
If you would like to account for transaction fees, set fees=True when calling loadexchangegraph.
import asyncio
from peregrinearb import loadexchangegraph, printprofitopportunityforpath, bellman_ford

graph = asyncio.geteventloop().rununtilcomplete(loadexchangegraph('gdax', fees=True))

paths = bellman_ford(graph) for path in paths: printprofitopportunityforpath(graph, path)

To find the maximum volume that can be used to execute the opportunity, set depth=True when calling bellman_ford. To my knowledge, the only exchange which offers the functionality of simultaneously fetching the volumes of the top price levels for all markets is Binance.

import asyncio from peregrinearb import loadexchangegraph, printprofitopportunityforpath, bellman_ford

graph = asyncio.geteventloop().rununtilcomplete(loadexchangegraph('binance'))

paths = bellman_ford(graph, depth=True) for path, starting_amount in paths: # Note that depth=True and starting_amount are set in this example printprofitopportunityforpath(graph, path, depth=True, startingamount=startingamount)

This would output:
Starting with 0.25 in BTC BTC to USDT at 7955.100000 = 1988.775 USDT to NEO at 0.016173 = 32.1652110625 NEO to ETH at 0.110995 = 3.5701776025 ETH to XLM at 2709.292875 = 9,672.65673772 XLM to BTC at 0.000026 = 0.25052181

Multiple Exchanges/ Multiple Currencies

from peregrinearb import createweightedmultiexchangedigraph, bellmanfordmulti, printprofitopportunityforpath_multi

graph = createweightedmultiexchangedigraph(['kraken', 'bittrex', 'gemini'], log=True) graph, paths = bellmanfordmulti(graph, 'ETH') for path in paths: printprofitopportunityforpath_multi(graph, path)

This prints all of the arbitrage opportunities on the given exchanges. At the time of writing, the first opportunity printed out is:

Starting with 100 in ETH
ETH to ANT at 204.26088199848851 = 20426.08819984885 on bittrex for ANT/ETH
ANT to BTC at 0.00034417000000000003 = 7.03004677574198 on bittrex for ANT/BTC
BTC to MLN at 136.57526594618665 = 960.1305080110928 on bittrex for MLN/BTC
MLN to BTC at 0.0073799999999999985 = 7.085763149121863 on kraken for MLN/BTC
BTC to GNO at 98.03921568627446 = 694.6826616786137 on bittrex for GNO/BTC
GNO to BTC at 0.010300000000000002 = 7.155231415289722 on kraken for GNO/BTC
BTC to GNO at 98.03921568627446 = 701.493276008796 on bittrex for GNO/BTC
GNO to BTC at 0.010300000000000002 = 7.2253807428906 on kraken for GNO/BTC
BTC to MLN at 136.57526594618665 = 986.8082965227394 on bittrex for MLN/BTC
MLN to BTC at 0.0073799999999999985 = 7.282645228337815 on kraken for MLN/BTC
BTC to USD at 7964.809999999999 = 58004.8855411173 on gemini for BTC/USD
USD to ETH at 0.0017965900720432618 = 104.21100149317708 on kraken for ETH/USD
Should you like to account for transaction fees. In the example above, simply set fees to True when calling createweightedmultiexchangedigraph. For example, the following code prints out all of the opportunities found on the given exchanges while accounting for fees:
from peregrinearb import createweightedmultiexchangedigraph, bellmanfordmulti, printprofitopportunityforpath_multi

graph = createweightedmultiexchangedigraph(['exmo', 'binance', 'bitmex', 'bittrex', 'gemini', 'kraken'], log=True)

graph, paths = bellmanfordmulti(graph, 'ETH', unique_paths=True) for path in paths: printprofitopportunityforpath_multi(graph, path)

The most profitable of the two printed out is:
Starting with 100 in ETH ETH to LTC at 3.2955444239388347 = 329.55444239388345 on binance for LTC/ETH LTC to USD at 173.00829999999996 = 57015.65383601369 on exmo for LTC/USD USD to XRP at 1.4110342881332016 = 80451.04252294863 on kraken for XRP/USD XRP to USD at 0.739201 = 59469.49108400615 on exmo for XRP/USD USD to BTC at 0.00011205737337516807 = 6.663994966831705 on bitmex for BTC/USD BTC to XRP at 12599.218848431392 = 83961.13099195795 on bittrex for XRP/BTC XRP to USD at 0.739201 = 62064.15199038631 on exmo for XRP/USD USD to BTC at 0.00011205737337516807 = 6.954745852799899 on bitmex for BTC/USD BTC to XRP at 12599.218848431392 = 87624.36503464654 on bittrex for XRP/BTC XRP to RUB at 39.120000000000005 = 3427865.160155373 on exmo for XRP/RUB RUB to USD at 0.018667164457718873 = 63988.522683505194 on exmo for USD/RUB USD to XRP at 1.4110342881332016 = 90289.99955341498 on kraken for XRP/USD XRP to RUB at 39.120000000000005 = 3532144.7825295944 on exmo for XRP/RUB RUB to USD at 0.018667164457718873 = 65935.1275439536 on exmo for USD/RUB USD to BCH at 0.000949667616334283 = 62.61645540736334 on kraken for BCH/USD BCH to ETH at 1.8874401 = 118.18480885571941 on bittrex for BCH/ETH

Future Development

I do not presently actively maintain this project but will respond to issues and pull requests.

Issues

See the repository's Issues tab for user-submitted issues. At the time of writing, issues I am aware of are:
  • async functionality may be broken
  • some issues with relative paths to generated json files

Enhancements

Improvements that would be appreciated:

  • Prune graph into connected components to improve runtimne
  • Split graph into cycles to find most profitable, instead of any, arbitrage opportunity
- A good algorithm to do this is Johnson's 1975 Cycle-Finding Algorithm
  • Update requirements and Python version
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