bandit | tool designed to find common security issues | Security library

I played around with it and here is how you can make it into a data frame. Assuming that you wanted to use pandas in the first place:

Based on this github issue try deleting everything in the cache directory of matplotlib

It could be a problem with your Python version: k-armed-bandits library was made 4 years ago, when Python 3.9 didn't exist. Besides this, the configuration files in the repo indicates that the Python version is 2.7 (not 3.9).

If you create an environment with Python 2.7 and follow the setup instructions it works correctly on Windows:

You're only moving to the next runner when the current runner is inside the button. So when your while loop gets to a runner that isn't in the button, it gets stuck on that element and loops infinitely.

Take the runner = runner.next; line out of the if.

You may interested in looking into VW's wiki page which has some information on CCB:

https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Conditional-Contextual-Bandit

You can think of CCB as a layer above CB, which runs a separate CB example with all actions for each slot, however actions are excluded as a slot selects it. The example above likely uses more functionality than is necessary for your purposes. If you only want to rank actions, this would be a better format:

ccb shared | s_1 s_2
ccb action | a:1 b:1 c:1
ccb action | a:0.5 b:2 c:1
ccb action | a:0.5
ccb action | c:1
ccb slot 1:0.8:0.8 |
ccb slot 0:0.8:0.8 |
ccb slot 3:0.8:0.8 |
ccb slot 2:0.8:0.8 |

This example could be used for learning and prediction, however if you just wanted to do prediction you could use unlabeled slots like this:

ccb shared | s_1 s_2
ccb action | a:1 b:1 c:1
ccb action | a:0.5 b:2 c:1
ccb action | a:0.5
ccb action | c:1
ccb slot |
ccb slot |
ccb slot |
ccb slot |

I'll answer each of your questions separately:

I also do not understand why it needs features for the slot part?
Slots do not need features. They are allowed to use features if you want each slot to learn differently, however this is not a requirement. If you are trying rank actions you probably don't want slot-specific features.

Furthermore i do not fully understand why we have to tell it the action ids to include?
You don't need to do this. By default all actions which have not yet been selected will be included in each slot. As an example, if there are actions 0,1,2,3 and slot 0 select action 1, then slot 1 will have actions 1,2,3 available. In this sense, each later action will not include actions select from prior slots, thus the action that each slot selects will rank the actions in order.

What is the purpose of it?
If you wanted a more complicated system with specialized slots you may want to explicitly exclude certain actions from a slot, but for simply ranking actions you will not want to do this.

Also which format does it need for the prediction?
Predictions can be done on any CCB example (labeled or unlabeled). You don't need to do anything special with the example, you only have to specify the -p pred_file.txt flag to output predictions to that file.

Why does it need the slot part if I do not have any action costs yet?
If you have no costs (so you are only doing prediction), the number of slots will represent the number of predictions you want to make. If you only want to find the top n actions you could use only n slots. Let me know if you have any other questions.

Using Stream :

immer does not work on class instances by default. You can mark them as immerable though.

But generally, you should not put class instances in your Redux store in the first place, see the Redux Style Guide

If you're using the pre-built SAST images, this isn't possible, even if you run the docker command manually like so:

Check your ssh-config in case you are stuck like me.
I had these lines among it