Alchemist_lib is an automatic trading library for cryptocurrencies that allow to personalize the portfolio based on a specific strategy.


  • Easy to use: The interface is similar to zipline, a popular backtesting software for stocks.
  • Portfolio personalization: You can choose the weight of every element on the portfolio.
  • Most common technical analysis indicators already integrated.
  • Execute orders on the most famous exchanges.
  • Possibility to visualize the asset allocation and the portfolio value charts for every strategy thanks to alchemist-view.
  • Fully documented and hosted on readthedocs.

Supported Exchanges

The following exchanges are available to trade on:


  • Python3
  • Mysql


See the installing documentation.

Code example

Strategy description: Hold a portfolio equally composed by Ethereum and BitcoinCash.

from alchemist_lib.portfolio import LongsOnlyPortfolio
from import PoloniexBroker
from alchemist_lib.tradingsystem import TradingSystem
import as exch
import pandas as pd

def set_weights(df):
    df["weight"] = 0.5 #Because there are just two assets.
    return df

def select_universe(session):
    poloniex_assets = exch.get_assets(session = session, exchange_name = "poloniex")

    my_universe = []
    for asset in poloniex_assets:
        if asset.ticker == "ETH" or asset.ticker == "BCH":
    return my_universe

def handle_data(session, universe):
    #The value of alpha is useless in this case.
    df = pd.DataFrame(data = {"asset" : universe, "alpha" : 0}, columns = ["asset", "alpha"]).set_index("asset")
    return df

algo = TradingSystem(name = "BuyAndHold",
                     portfolio = LongsOnlyPortfolio(capital = 0.02),
                     set_weights = set_weights,
                     select_universe = select_universe,
                     handle_data = handle_data,
                     broker = PoloniexBroker(api_key = "APIKEY",
                                             secret_key = "SECRETKEY"),
                     paper_trading = True) = "15M", frequency = 1)


BuyAndHold example

Basic concepts

Alchemist_lib works with three methods:

  • set_weights
  • select_universe
  • handle_data

set_weights is used to set the weight that an asset has respect the others within the portfolio. The sum of every weight must be close to 1. Must returns a pandas dataframe with two columns: “asset” and “alpha”, where “asset” is the index.

select_universe filters the assets saved on the database and returns just the ones the strategy will take into consideration.

handle_data is the most importat one because it manages the trading logic. Must returns a pandas dataframe with two columns: “asset” and “alpha”, where “asset” is the index.

You can find other examples in the examples directory.

Reporting bugs

A bug tracker is provided by Github.