steady | Java applications for open-source dependencies | Code Analyzer library

I am trying to use Torch for Label Propagation. I have a dataframe that looks like

I'm writing an Chrome Extension for Google Calendar, which adds an div under the header section of Google Calendar.

For simplicity, this is what essentially happens in Chrome Extension content script, you can just paste this code in the console of calendar.google.com to check what happens:

I need to subscribe to the app-db for a value that I want to check only once when the parent component is rendered. For example, when I click a button "Click me", and there's a certain on-click event being processed, whose status I have saved on the app-db with the list of processes that are being done, I just want to check against that value once, and display two different components based on that value.

If the value is empty, I want to proceed with the normal event. If not, I'd like to show something else to the user, a popup for example.

Now the thing is that, because it's actively listening to the app-db, and the value is changing almost every second (or in a matter of milliseconds), the said popup appears, disappears, reappears, and disappears again super fast with each change to the app-db, which isn't helpful at all.

I would like to just subscribe once, get the value, and do the checks based on the value when the parent was first rendered. And then I'll do something to make that go away.

If I click the "Click me" button once again, that's only when I'd like for it to re-render.

I haven't quite been able to achieve this. I tried numerous methods such as introducing a delay during the dispatch of popup as well as after introducing processing states to the app-db in the first place hoping that since the data will already be in a steady state, it might not change as much, but now that I realize it's actively listening to it, it's expected that the values would change.

I did try using the subscription without the deref, but that only introduced an error to my frontend, so I'm not sure which way to go now.

I'm using pubsub to trigger a cloud function that I have defined to have maximum of 10 instances.

When a bulk of around 300 messages or more arrive to the topic and start triggering the function, suddenly the number of unacked messages stops going, it just doesn't change, although I know that my cloud functions that are triggered are automatically acking those messages...

I'm wondering what I'm missing here...

Adding the following chart to show what I'm talking about:

So there are few things to notice here:

• the chart is in 1 min intervals
• the scale for the chart is on the right side
• the toolbox on the left is just so it will be easy to see what colour corresponds to what line
• ack_message_count (blue) is the number of acks my cloud functions are performing each minute
• send_message_operation_count (green) is the number of messages published into the topic that is triggering the cloud function
  • notice the spike around 1:01 PM, this is the bulk that is send into the topic, its around 1k new messages
  • aside from the that bulk, there are constantly new messages entering the topic, but much less than the number of acks that is performed
• push_request_count (orange) is the number of time pubsub tries to trigger the cloud function (be it successful or resulting in 429 which means that it has reached the maximum number of instances running)
• num_undelivered_messages (pink) is the number of unacked messages that are waiting inside the queue of the subscription

First I though maybe I just don't perform enough acks with my cloud functions, but that is not the case since there is much more acks than new messages after the peak of the 1k messages.

What I thought I would see is just a steady decline of the number of unacked messages in the subscription's queue.

So essentially what I don't understand is why does the num_undelivered_messages doesn't go down as the number of acks continues (1:01 - 1:10), and then, suddenly it just drops (1:10 - 1:15) really fast?

I am performing a steady state dynamics step in Abaqus und therefore have complex results. Since I need the values of a couple of hundred nodes I am trying to get these results using a python script. I took this script from the documentary and adapted it for my model, which works, but I only get the real values. Is there a way to extract the real values as well as the imaginary values?

I am quite new to Jmeter and just started using it. I have this requirement of setting up 1000 concurrent users with Ramp up - 100 Users every 2 mins and keeping them in steady state for an hour. How should my thread configuration be like? I am using Concurrency thread group.

I want to ensure that my deployment has baked for X hours in the current stage before it is deployed to the next. I was reading about post-deployment gates here. I don't think these gates are the best way to ensure that the deployment has baked.

For post-deployment gates, the delay would be the maximum of the time taken for the deployed app to reach a steady operational state, the time taken for execution of all the required tests on the deployed stage, and the time it takes for incidents to be logged after the deployment.

If the deployed app reaches a healthy state, then would the gate be opened to move to the next?

Or if its always going to wait X hours, if I want my build to bake for 4 hours, but it took 1 hour to deploy it, then it wouldn't bake completely.

I have a 10*10 array for a domain

TT =

I have a dataframe with frequency counts of words and the number of non-NA counts in column size: