disrupt | A python tool | Command Line Interface library

I'm trying to deploy the ELK stack to my developing kubernetes cluster. It seems that I do everything as described in the tutorials, however, the pods keep failing with Java errors (see below). I will describe the whole process from installing the cluster until the error happens.

Step 1: Installing the cluster

I’m wanting to do successive animations, like one after another instead of on a loop or one at a time. What does it look like when coding that?

Example: fade in @ 100% opacity, then fade out @ 20% opacity, then fade in 80%, then fade out 10%... so like a pulsing then at 0% change the label text and do the inverse (basically the same as the picture only every time I try and make it progressively fade out- it disrupts the whole animation)

The gif shows it's current state, not what I've tried thus far that didnt work.

I would like to run on Colab a C++ library which requires a version of libstdc++.so which is newer than the one provided by the default g++ 7.x installed on Colab. Such requirement is due to C++17 features not supported by g++ 7.x.

In order to do so, I install a recent g++ compiler (and corresponding libstdc++.so) from a PPA. However, when I try to import libraries compiled with the updated g++ compiler it seems that the python runtime is not aware of the update to libstdc++.so, unless one restarts the runtime via "Runtime -> Restart runtime".

Since restarting the runtime is an ugly workaround, and might be disruptive for my end users, is there a better way to make the current runtime aware that libstdc++.so has changed?

I have prepared a standalone notebook which shows my problem on a simple case (using pybind11).

Thanks

I have a Kubernetes cluster and do all my deployments in a declarative manner, by executing the "apply" command in CI/CD pipeline.

"Apply" works in such a way that it merges the state of an object with the manifest that came with the command. As the result, you may make manual changes - for example, add a new key-value to a ConfigMap and "apply" will leave it intact, even though this key doesn't exist in source code.

So I wonder, how can I detect such issues? Doing "delete" and "create" is not an option since it disrupts the availability. I don't want to change deployment from "apply" since it's production. I just to find manual modifications in a namespace.

According to this documentation: the classifyText method requires at least 20 words.

https://cloud.google.com/natural-language/docs/classifying-text#language-classify-content-nodejs

If I send in less than 20 words I get this no matter how clear the content is:

Let me start by saying that I am somewhat new to SQL/Snowflake and have been putting together queries for roughly 2 months. Some of my query language may not be ideal and I fully understand if there's a better, more efficient way to execute this query. Any and all input is appreciated. Also, this particular query is being developed in Snowflake.

My current query is pulling customer volumes by department and date based on a 45 day window with a 24 day lookback from current date and a 21 day look forward based on scheduled appointments. Each date is grouped based on where it falls within that 45 day window: current week (today through next 7 days), Week 1 (forward-looking days 8-14), and Week 2 (forward-looking days 15-21). I have been working to try and build out a comparison column that, for any date that lands within either the Week 1 or Week 2 group, will pull in prior period volumes from either 14 days prior (Week 1) or 21 days prior (Week 2) but am getting nowhere. Is there a best-practice for this type of column? Generic example of the current output is attached. Please note that the 'Prior Wk' column in the sample output was manually populated in an effort to illustrate the way this column should ideally work.

I have tried several different iterations of count(case...) similar to that listed below; however, the 'Prior Wk' column returns the count of encounters/scheduled encounters for the same day rather than those that occurred 14 or 21 days ago.

I have an application deployed to Kubernetes that depends on an outside application. Sometimes the connection between these 2 goes to an invalid state, and that can only be fixed by restarting my application.

To do automatic restarts, I have configured a liveness probe that will verify the connection.

This has been working great, however, I'm afraid that if that outside application goes down (such that the connection error isn't just due to an invalid pod state), all of my pods will immediately restart, and my application will become completely unavailable. I want it to remain running so that functionality not depending on the bad service can continue.

I'm wondering if a pod disruption budget would prevent this scenario, as it limits the # of pods down due to a "voluntary" disruption. However, the K8s docs don't state whether liveness probe failure are a voluntary disruption. Are they?

This issue is causing me quite a bit of worry... any help would be much appreciated.

I have have three spreadsheets, A, B, and C (I own all of them). I then create a script that lets one user transfer money from A to C, while another user transfers money from B to C. Both of those users always send the money to the exact same cell in C (let's call that cell "the bank account"). And, the money transfers tend to happen either simultaneously or almost simultaneously, so there is a high risk of collision-errors. And, just in case it matters, the script always runs "as me" (the admin), no matter which user ordered the execution of the script.

So here is the heart of my question: how can I temporarily lock the "bank account" cell in C while someone is transferring money from A to C, and then, once the transfer from A to C is complete, the transfer from B to C will automatically begin? And how can I do this without locking C entirely (a lot of people modify C all the time, and it would disrupt their productivity quite a bit for me to lock the entire spreadsheet, even if just for a few seconds).

Or maybe it would be better to create some sort of buffering system, instead of temporarily locking the cell?

Here is an example of what exactly I meant by "collision-error":

I will use the term "the bank account" to refer to the cell that is receiving the money.

The starting value of the bank account is 100 dollars.

Alice activates a script to add 800 dollars to the bank account and Bob activates a script to add 100 dollars to the bank account.

Alice's script reads the the bank account's current value as 100.

Bob's script reads the bank account's current value as 100.

Alice's script figures that the sum should be 900, and sets the new value of the bank account to be 900.

Bob's script figures that the sum should be 200, and sets the new value of the bank account to be 200.

The final output should have been 1000 dollars, but became 200 instead. So 800 dollars were lost.

Again, any help would be much appreciated.

I need to create a Neural Network where I use binary gates to zero-out certain tensors, which are the output of disabled circuits.

To improve runtime speed, I was looking forward to use torch.bool binary gates to stop backpropagation along disabled circuits in the network. However, I created a small experiment using the official PyTorch example for the CIFAR-10 dataset, and the runtime speed is exactly the same for any values for gate_A and gate_B: (this means that the idea is not working)