DeFacto | Deep Fact Validation | Cryptocurrency library

When using a named v-model like this:

We use a special emit on the child component that looks like this:

But that got me thinking about how I name my other events not tied to a v-model.

Should they also have a keyword like update: or something similar preceeding them?

I know it's not required for it to work, but I'm trying to understand defacto naming conventions.

For example, should emit('my-custom-event') have any preceeding keyword in the name?

If I run this script, it returns an error NameError: name 'args' is not defined.

Below is the sample data. The task at hand is creating two new columns that would designate something by zip code. The first new column would be titled Las_Vegas and the second would be Laughlin. The first eight zip codes would have a value of 1 for Las Vegas and the second eight would have a value of 1 for Laughlin. The purpose of this is that I want to sum the employment for Las Vegas and Laughlin.

First question: Would it be best to use ifelse or case_when? Second question: Making the two new columns into defacto dummy variables... is this the best approach?

I want to create a docker image for wordpress, which creates a ready to use wp instance with already setup and completed installation, activated theme and plugins and other configurations. I was exploring WP CLI to do that as part of the Dockerfile build, however it turned out that this is a stateful process (it requires existing mysql database already in place), which is impossible during docker build.

I'm thinking about creating a bash script which brings up a docker WP CLI container and a pure ubuntu/php container. The wp cli container will then install and setup the wp instance on the ubuntu/php container which will become the defacto WP container, and at last the wp cli container will be shut down by the script.

I'm not sure if this is a good solution, do you have better advises for this use case?

I managed to find python code that defines a LinkedList class and all the defacto methods in it but quite can't figure out what each line of code does...Can someone comment on it explaining what each line does so i can grasp a better understanding of LinkedLists in python?

I'm trying to extend asyncs race function such that it could be applied to every IO function in a list but I'm having trouble in reasoning out the extension.

My first approach was to split the list in half and zip it together such that each entry is a distinct couple. Once that is done map race across the list and return a random entry as the defacto fastest. The issue with this approach was that I ran into the following error that I couldn't find a solution to mitigate :

The question is intended to build an understandable grasp on subtle differences between .dt and pd.to_datetime

I want understand which method is suited/preferred and if one can be used as a defacto and other differences that are there between the two

I am deploying Docker containers on VCHs (Virtual Container Hosts) in VMware VIC on vCenter. I would normally use Traefik as a proxy to control the ingress, but this is not possible in VIC, as VIC does not allow access to the docker.sock API. What is the defacto way to control ingress traffic for each container?