thousands | micro js library for formatting numbers

I have a list [A,B,C,D,E] and a list of indexes [3,2,0,4,1] but the indexes actually points to itself, giving the order to follow.

So starting at 0, next index is 3, then at index 3, the next index is 4,1,2,0 etc.

I can achieve this by looping and updating the index, but my list may have thousands of points, Is there a way to avoid loops and vectorize this?

my code:

I have a column that gives the date (its type is str) and another column that gives a first name, I would like all the names that are in 2020 have "_2020" at the end of their first name, and same thing for 2021, and its pandas DataFrame.

As I have thousands of rows, I need a loop that automates the task.

it would be like going from this:

To That:

I have about a half million records that look somewhat like this:

I'm getting some very weird behavior from mixing tidyverse and data.table syntax. For context, I often find myself using tidyverse syntax, and then adding a pipe back to data.table when I need speed vs. when I need code readability. I know Hadley's working on a new package that uses tidyverse syntax with data.table speed, but from what I see, it's still in it's nascent phases, so I haven't been using it.

Anyone care to explain what's going on here? This is very scary for me, as I've probably done these thousands of times without thinking.

I have thousands of JSON files, and I want to merge them into a single one. I'm using the command below to do this.

I have a requirement where I need to make a HTTP request to a Flask server where the payload is a question(string) and a paragraph(string). The server uses machine learning to find the answer to the question within the paragraph and return it.

Now, the paragraph can be huge, as in thousands of words. So will a GET request with a JSON payload be appropriate? or should I be using POST?

Assume we have a redis set with hundreds thousands elements in it. As smember command does eager-loading, it fetches all of the elements just by this one command and consequently it consumes too much time. I want to know is there a way to read redis data as bulks or maybe as a stream?

Lets say i have a social media app where users can post and for each post i'm inserting a row to the posts table, and updating the user_affiliates table.

Now lets say that the user wants to see all of his/her posts what's the most efficient way to select posts that the user has posted?

This is a simplified version of my database:

How can I ensure fairness in the Pub/Sub Pattern in e.g. kafka when one publisher produces thousands of messages, while all other producers are in a low digit of messages? It's not predictable which producer will have high activity.

It would be great if other messages from other producers don't have to wait hours just because one producer is very very active.

What are the patterns for that? Is it possible with Kafka or another technology like Google PubSub? If yes, how?

Multiple partitions also doesn't work very well in that case, or I can see how.