SMARTS | Scalable Multi-Agent RL Training School | Reinforcement Learning library

I'm trying to query a database using Python/Pandas. This will be a recurring request where I'd like to look back into a window of time that changes over time, so I'd like to use some smarts in how I do this.

In my SQLite query, if I say

The only ways I can find in python that redirects the console output to string in a variable also seem to turn off the functionality of displaying the output to the console in a live manner similar to how python would output the code normally.

I currently am changing the sys.stdout but again, this is either one or the other it seems.

If I redefine it, I get the perfect performance for distant error checking, as I am able to save the output variable to a cloud based spreadsheet in the event of exception handling, which sends me notifications anywhere that I am.

However, redefining it means I don't get to come and locally check on the output of the program while it is "running smoothly"

EDIT: some of your answers have helped me refine my question. Here is a fresh re wording:

What is the best way to concisely store and record outputs with a single variable as the elements are printed to the console without overwriting sys.stdout?

I try without success to display the options of smart select. I recover the options with axios and I make a v-for to display the options but without success. I first put the function that allows me to retrieve the data in the computed hook without success then I put it in the mounted hook and I used the setvalue property of smart select without success too. Any help is welcome and I thank you in advance.

Note: I have found a partial solution to my problem, please refer to the UPDATE section below.

I am currently trying to take data from 3 separate columns and merge them together into another specified column. For clarity please refer to the image below, where code 1, code 2, and code 3 are all concatenated together in the Merged Code column. Example of desired outcome. I have written a for loop that can update the values of every cell in a specified column, please refer to the code below.

I am currently trying to import an excel sheet into Smartsheet, then take the rows of the imported sheet, and move them to the bottom of an existing sheet. To do this I am using the Sheets.move_row function. Below is a snippet of that code.

Using Typescipt 4.x.x

I wrote some code to implement the Maybe/Option type commonly used in other languages Elm/Rust/Haskell.

I wanted to write a generic function that could take a mapped type

I have many APIs that run on-premises and a cloud application that talks to them.

We are worried about the amount of effort that its going to take for companies to open their firewall to allow the API exposure to the outside.

I've heard of people using Web Sockets to making an outgoing connection to a server. Has anyone done this and can give me a high level in how your approaching it? I tried to do some research but don't see a lot of documentation.

I'm familiar with web sockets but a couple questions I would have before implementing them is:

• Is it scalable? I assume there would be one connection coming out of the server, and then you would have that socket to communicate, or could you have multiple web sockets connect and build some smarts on different sockets to communicate from the calling server?
• What would be the approach to have a Stateless protocol as the initial requests from the consumer and then integrating that with the web sockets? It seems like I would have to develop a lot of pluming here to manage the requests then integrating it into one or many sockets that are connected as a bridge of sorts. HTTPRequest -> Server -> Socket Communication To On-Premises Server -> Server -> HTTPResponse

Any feedback on approaches using web sockets to integrate into on-premise service would be appreciated.

I'm a relative Postgres newbie, though have some basic experience with MSSQL.

I have a table on PostgreSQL (PostGIS, it's spatial) that contains about 10,000,000 polygons. The machine it's sitting on has 64gb RAM, 16 cores and a 1TB spinning HDD. This is only of the only tables in the database at the moment. Because access to the table is infrequent (perhaps once every few hours) I'm noticing that the table will not stay located in RAM, as I would expect with MSSQL. Instead, the table seems to be released from memory and sit on disc in an active state. This is leading to 100% HDD utilization for 15+ minutes when I want to query / join / interrogate / etc. When the table seemingly appears to be in memory subsequent operations are notably faster (seconds rather than minutes).

Is there a way to ask Postgres to keep a certain table in memory, or have the scheduler / whatever bits of postgres that perform the smarts keep the table in ram, rather than letting it go to disk then having to recall it into memory when required?

I have spatial indexes (and a couple of other columns that often require filtering / sorting indexed), so when being called from memory it's quite fast.

This same issue also seems to massively affect JOINS, because they too require the table to be read first. This is a separate issue for me, but seemingly affected by the same root problem. Disk IO bound.

My DB settings are as such - so generally I'm not inhibited by available memory / ram, so far as I can tell.

Edit: Table is 26gb

There are lot of answers related to custom fields on stackoverflow but when trying with them, I am getting different error, so posting a separate question.

I wanted to return a JSON Response for the following url

urls.py