checksums | Tool for making/verifying checksums of directory trees | File Utils library

If the Bluetooth stack crashes in the phone, then it's most likely a bug in the Bluetooth stack which you can not do anything about, except sending in a bug report to the phone manufacturer.

You could however try to see if you can find out under which circumstances this happens and perform some workaround to avoid this. The hci snoop log in combination with logcat could maybe be a help.

In any case, if you program your app correctly, it should not crash itself just because the Bluetooth stack crashes. You should be able to recover when the Bluetooth stack later restarts. See How to detect Bluetooth state change using a broadcast receiver? how you can get notified of Bluetooth state changes.

Git stores certain information in the index, which reflects things like the file size, device and inode numbers, modification and inode change times, and various other attributes. If this information is changed, or is potentially stale, then Git will re-read the file to see if it's modified. This is potentially expensive, as you've noticed, and Git's detection here is the reason that Git LFS has this same performance problem: Git is telling Git LFS to reprocess the file.

What you want to do is find out what's modifying the attributes of your files. For example, if you have some sort of file monitoring or backup software, then that can cause this problem, or if you're using some sort of cloud syncing service (which you should avoid anyway because it will probably corrupt your repository). This can also happen if you mount the repository into a container, since the container will have different device and inode numbers, and then each time you alternate in which environment you run git status, the entire repository must be re-read.

For example, on my systems, I don't have this problem and my system performs just fine. However, if you really can't figure it out, you can try setting core.trustctime to false and/or core.checkstat to minimal (which you should try in that order). That will put less data in the index, and then it's less likely to become stale when nothing's changed. However, it also means that it's more likely that Git will fail to detect a legitimate change, so if you can avoid needing to do this, you should.

Yes, it correct to say the modules really "used" by the application are listed by go list -m all (as per documentation you provided the link of). By "used", it means the package selected at build time for the compilation of the go code of your application.

We had a similar issue with a static analysis tool and we had to change the configuration to use the output of go list -m all (dumped in a file) instead of go.sum.

This helped me out: https://blog.testdouble.com/posts/2021-01-28-how-to-completely-uninstall-homebrew-postgres/

Therefore, my guess was that the bin folder would contain binaries of the package.

That's incorrect. Django just happens to have a bin directory, since it houses the django-admin command line tool.

Does python wheel actually contain a binary? If yes, then how to locate the binary within the .whl file?

Yes, if there is something that needs to be a compiled binary. For instance, a NumPy wheel would have multiple .so (Linux/macOS) or .pyd (Windows) files (Python extension modules). Their location within the .whl depends on the package.

You can tell whether a .whl contains binary Pyt .whl does not contain binary modules from the name: Django-3.2.9-py3-none-any.whl. Compare to e.g. Numpy's numpy-1.21.4-cp310-cp310-win_amd64.whl (containing binary modules for CPython 3.10 on Windows, AMD64 architecture).

If there's other binary package data, such as an image that the package requires, that would be in the .whl too. For Django, you will likely find Gettext .mo files.

If the python wheel distributes a binary, then how does wheel distribution ensure that the binary is built from the same source code present in the .whl file?

Source code for binary modules is just generally not included in .whls.

Your issue is that the NOT MATCHED condition is only considering the ID values specified in the ON condition.

If you want duplicate, but distinct records, include SCD to the ON condition.

If (more likely) your intent is that record ID = 1 be updated with the new SALARY, you will need to add a WHEN MATCHED AND SOURCE.SCD <> TARGET.SCD THEN UPDATE ... clause.

That said, the 32-bit int value returned by the `binary_checksum()' function is not sufficiently distinct to avoid collisions and unwanted missed updates. Take a look at HASHBYTES instead. See Binary_Checksum Vs HashBytes function.

Even that may not yield your intended performance gain. Assuming that you have to calculate the hash for all records in the staging table for each update cycle, you may find that it is simpler to just compare each potentially different field before the update. Something like:

The issue comes from your dependency "hero-slider", which in turn specifies a peer dependency of the package styled-components as follow:

is it possible to extract the layers while preserving the timestamps?

Spring Boot's layer tools doesn't support this at the moment. It sounds like a useful feature to add, though, and I think it should probably be the default behaviour. We already take care to preserve the timestamps when creating the jar so I think it makes sense to preserve them during extraction as well.

Please open a Spring Boot issue and we'll take a look.

I've also tried using the amazon.aws.aws_rds module in the amazon.aws.rds collection, which has an include_clusters parameter:

One will observe from the documentation you linked to that the aws_rds is an inventory plugin and not a module; it's unfortunate that they have a copy-paste error at the top alleging that one can use it in a playbook, but the examples section shows the correct usage by putting that yaml in a file named WHATEVER.aws_rds.yaml and then confirming the selection by running ansible-inventory -i ./WHATEVER.aws_rds.yaml --list

Based solely upon some use of grep -r, it seems that inventory plugin or command: aws rds describe-db-clusters ... are the only two provided mechanisms that are aurora-aware

Working example:

test.aws_rds.yml inventory file: