For your first question, you can certainly choose stocks based on the filters you have defined while simultaneously sorting them based on performance. I attached a backtest where the pipeline uses factors, instead of the filters used in your version.
Keep in mind to differentiate these two for the future. In proper pipeline construction, it’s best practice to use your factors as columns and filters as derivatives of your factors. For example, your ‘returns_filter’, which filters your factor ‘returns’ relative to a threshold value of 0.1.
Before diving into your second question, I recommend always writing your pipeline logic in another function such as in make_pipeline() in your first example - that way modifying your pipeline and debugging becomes much easier as you add logic. The pipeline is returning the same set of securities because on line 23, if you switch the inequality to ‘returns > 0.1’ the pipeline output will match expectations. The way you have it now will prevent you from trading securities of higher returns.
For future direction, I would also suggest placing orders using the Optimize API as you continue to work on the algo.
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