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ENIGMA CATALYST - WARNING: Loader: Refusing to download new treasury data because a download succeeded

I'm playing around with Enigma Catalyst. Unfortunately, the documentation is rather limited.

So I'm trying to run their example "hello world" type algo which looks as follows:

from catalyst import run_algorithm
from catalyst.api import order, record, symbol
import pandas as pd

def initialize(context):
    context.asset = symbol('btc_usd')


def handle_data(context, data):
    order(context.asset, 1)
    record(btc=data.current(context.asset, 'price'))


if __name__ == '__main__':
    run_algorithm(
        capital_base=10000,
        data_frequency='daily',
        initialize=initialize,
        handle_data=handle_data,
        exchange_name='Bitfinex',
        algo_namespace='buy_and_hodl',
        base_currency='usd',
        start=pd.to_datetime('2018-01-02', utc=True),
        end=pd.to_datetime('2018-01-03', utc=True),
    )

I realize according to the documentation it says you first need to "ingest" download the historical data which I believe I did. However this leads to the following error:

[2018-02-25 02:54:10.696049] WARNING: Loader: Refusing to download new
treasury data because a download succeeded at 2018-02-25
02:08:26.001177+00:00.

Which results in no data

[2018-02-25 02:54:10.830665] INFO: Performance: first open: 2018-01-02
00:00:00+00:00 [2018-02-25 02:54:10.830665] INFO: Performance: last
close: 2018-01-03 23:59:00+00:00

Question:

How do I access the downloaded data? Or, how do I delete and re-download the historical data, which is not covered in the docs?

Many Thanks.

like image 845
Timothy Coetzee Avatar asked Feb 25 '18 03:02

Timothy Coetzee


1 Answers

Figured it out with help from core Catalyst developer on Discord. Pricing data gets downloaded from the Catalyst server as data bundles on your local machine. You have to start the catalyst environment every time you plan to use it. When in the Enigma Catalyst environment you can clear data bundles (previously downloaded pricing data) using the catalyst clean command.

like image 180
Timothy Coetzee Avatar answered Nov 14 '22 03:11

Timothy Coetzee