GAIN | Generative Adversarial Imputation Networks - ICML | Machine Learning library

I'm trying to understand best practices for Golang concurrency. I read O'Reilly's book on Go's concurrency and then came back to the Golang Codewalks, specifically this example:

https://golang.org/doc/codewalk/sharemem/

This is the code I was hoping to review with you in order to learn a little bit more about Go. My first impression is that this code is breaking some best practices. This is of course my (very) unexperienced opinion and I wanted to discuss and gain some insight on the process. This isn't about who's right or wrong, please be nice, I just want to share my views and get some feedback on them. Maybe this discussion will help other people see why I'm wrong and teach them something.

I'm fully aware that the purpose of this code is to teach beginners, not to be perfect code.

Issue 1 - No Goroutine cleanup logic

I am trying to install all needed modules for an existing Django project. When I run pip install -r requirements.txt I get the following errors:

Hey, I am working on putting up a rocket rest api with a mongodb database.

I have been able to create a successful connection to the MongoDB Atlas and put the resulting client into the state management of rocket via the manage builder function like this:

I'm creating an int (32 bit) vector with 1024 * 1024 * 1024 elements like so:

I have a Google Sheet (Excel formulas apply) containing 2000 transactions that are structured like below:

Link to Google Sheet with example calcs here.

I need to calculate the Profit (ie. FIFO Capital Gains) for every sell order and place this amount in the 5th column (as pictured). This can be achieved with either traditional formulas or with a Google App Script. Preferably in Google Sheets.

I'm finding it difficult via formulas to match the sell order with the buy as you proceed down the table as some sell orders are split across multiple buy lines. If anyone could help with a formula or solution to tackle this problem it would be much appreciated. This is an updated question to the original here.

MDN says:

The yield keyword causes the call to the generator's next() method to return an IteratorResult object with two properties: value and done. The value property is the result of evaluating the yield expression, and done is false, indicating that the generator function has not fully completed.

I ran a test in Chrome 91.0.4472.77 and it appears to be a fresh object every single time. Which seems very wasteful if the processing is fine grained (high numbers of iterations, each with low computation). To avoid unpredictable throughput and GC jank, this is undesirable.

To avoid this, I can define an iterator function, where I can control (ensure) the reuse of the {value, done} object by each next() causing the property values to be modified in place, ie. there's no memory allocation for a new {value, done} object.

Am I missing something, or do generators have this inherent garbage producing nature? Which browsers are smart enough to not allocate a new {value, done} object if all I do is const {value, done} = generatorObject.next(); ie. I can't possibly gain a handle on the object, ie. no reason for the engine to allocate a fresh object?

I'm trying to connect to a server and earn the banner, but I'm not succeeding.

My script runs in theory as follows:

1. Get port and IP but I can use port e IP static on variables.

2. Execute the socket, with timeout 7

3. If connected

4. Wait the response e use the handle <> to get banner

5. Execute print to show banner.

QUESTION: What, if anything, could cause an SQLite trigger to only run some of the time?

SUMMARY: I'm getting seemingly inconsistent results from a new trigger I've written in SQLite and I'd like to understand if this is happening because I've made a mistake in my SQL/Java code or if I've possibly encountered a rare scenario where SQL triggers may not work as expected.

DETAILS: While working on an Android project I have encountered what I originally perceived to be a problem with an SQLite trigger. However, since my new trigger exactly matches several other working triggers in the same project (except for the table names) I am beginning to wonder if my Java code is the issue instead.

The purpose of the trigger I am having trouble with is to monitor changes to TableA, such as the addition of a value in the DismissDateUTC column for example. When an update is made to any data in TableA, the trigger is supposed to put the ID of that updated TableA record into TableAChanges which is later used to determine which records were updated and should be sent back to a web server.

When using the database inspector (in Android Studio v4.2.1) or the program “DB Browser for SQLite” and running an update query on TableA manually, the trigger works exactly as expected and records appear in TableAChanges. When I make updates to TableA programmatically, the trigger does not appear to run. I believe it is not running because no records are written to TableAChanges after updates have been written to TableA.

Things I have tried so far:

• Running the app on an Android 7.1.1 device (trigger is NOT working)
• Running the app on an Android 8.1.0 device (trigger is NOT working)
• Running the app on an Android 11 device (trigger is NOT working)
• Running manual update query on TableA from Android Studio DB Inspector (trigger IS working)
• Running manual update query on TableA from DB Browser for SQLite (trigger IS working)
• Running manual update query on TableA from Android Debug Database by “amitshekhar” (trigger IS working)

The Tables and Trigger SQL:

I'm trying to write a function I'm frequently in my dissertation but having a hard time getting it to run.

The code works but then fails once I run the function, I think, because of how R reads in the designated variable via the embracing function options. Here is the successful code for one variable, prburden and a link to sample data: