mb | PrinCube / MBrush APP Source Code

tracemalloc was started too late to track the inital block of memory, so it didn't realize it was a reuse. In the example you gave, you free 27999860 bytes and allocate 27999860 bytes, but tracemalloc can't 'see' the free. Consider the following, slightly modified example:

There is no problem with your websocket route. Could you please share how you are triggering this route? Websocket is a different protocol and I'm suspecting that you are using a HTTP client to test websocket. For example in Postman:

Postman New Screen

HTTP requests are different than websocket requests. So, you should use appropriate client to test websocket.

Place the floating label inside another input-group div.

I was able to reproduce this error; in my case the stack trace led back to the barryvdh/laravel-debugbar package, not sure if this is the same for you. I was able to resolve it by changing the enum to a backed enum.

I'd recommend making this change regardless, as I expect in a lot of cases strings will be easier to work with than enum instances. (Though TBH this looks like trying to use a new feature just because it's there, not because it makes sense.)

Does it make sense to iterate through layers like this and keep adding files (to some target, does not matter for now) and deleting the added files in case they are found with a .wh prefix? Or am I totally off and is there a much better way?

There is a much better way, you do not want to reimplement (with worse performances) what Docker already does. The main reason is that Docker uses a mount filesystem called overlay2 by default that allows the creation of images and containers leveraging the concepts of a Union Filesystem: lowerdir, upperdir, workdir and mergeddir.

What you might not expect is that you can reproduce an image or container building process using the mount command available in almost any Unix-like machine.

I found a very interesting article that explains how the overlay storage system works and how Docker internally uses it, I highly recommend the reading.

Actually, if you have read the article, the solution is there: you can mount the image data you have by docker inspecting its LowerDir, UpperDir, WorkDir and by setting the merged dir to a custom path. To make the process simpler, you can run a script like:

As far as I can see here, there isn't a way to clear a textarea without using an onclick function.

You can create your own TextInput and TypedModelListField field to handle this. I think what you're looking for is something which allows the user to both search and provide a recommended selection of choices but validate the input against a model (Ingredient).

I've created one here:

Contrary to common belief Haskell is quite friendly with respect to problems like that. The real issue is that the array library that comes with GHC is total garbage. Another big problem is that everyone is taught in Haskell to use lists where arrays should be used instead, which is usually one of the major sources of slow code and memory bloated programs. So, it is not surprising that GC takes a long time, it is because there is way too much stuff being allocation. Here is a run on the supplied input for the solution provided below:

There appears to be something very wrong with the calculated GC CPU time. It's 41010 secs compared to 2737 sec elapsed, which doesn't make sense if you're only running on three capabilities.

This miscalculation means that the calculated MUT CPU time, which is just total CPU time minus INIT, GC, and EXIT time, is actually a large negative number (5073-41010-2 = -35939). This gives a productivity of -35939/5073=-708%. When the MUT seconds are displayed, negative numbers are truncated at zero, to avoid reporting small negative numbers when MUT is very low and there's a clock precision error, which is why the displayed MUT time is 0 instead of -35939.

I don't know why the GC time is so badly miscalculated. My best guess is this. If you're running on Windows, there are known issues with CPU time clock precision, and it's possible that certain unusual patterns of garbage collection timing might result in precision errors occuring in only one direction, slightly overestimating the actual GC time more often than it underestimates it. Over 2.4 million collections (see your GC stats), this difference could accumulate to a huge positive error.

I looked through GitLab issues, and except for the report on general Windows CPU time imprecision and a couple of probably unrelated negative MUT reports here and here, I didn't see anything helpful.