@alexeigor Hello. Version 0.0.501 of the qnt library works correctly in Colab. Python version support has been extended from 3.10 to 3.13. The basic functionality of the library should work without issues.

To install, use the following command:

!pip install git+https://github.com/quantiacs/toolbox.git 2>/dev/null

Note: Installing ta-lib in Colab is not working for me at the moment.

@vyacheslav_b Apologies for the late response. Thanks for the assistance, all is now well. Cheers

Thanks 🙏

@illustrious-felice Hi,

sorry for late answer, please check the correctness of dataset used for defining weights in strategy. Be sure that 'stocks_s&p500' dataset is used and not 'stocks_nasdaq100' for current competition. To ensure strategy trades only liquid assets in certain time period, multiply the output from your strategy function with 'is_liquid' field from correct dataset, or simply use clean() function from qnt.output:

import qnt.data as qndata import qnt.output as qnout def strategy(data): ..... # liquid = data.sel(field='is_liquid') # weights = weights * liquid return weights data = qndata.stocks_load_spx_data(min_date='2005-01-01') weights = strategy(data) weights = qnout.clean(weights, data, kind='stocks_s&p500') qnout.write(weights)

Also, keep in mind that submission will not be eligible for contest if stocks universe (in this case "top 7 magnificent") is hand picked (manually defined).

Best regards,

@magenta-grimer Hi, the Q22 basic template is a good starting point.

@alexeigor Hi,

sorry, it should work now.

Best regards