JNA VS warehouse

As far as I understand it, with JNA, all calls into C code go through libffi: https://github.com/java-native-access/jna/blob/master/www/Fu...

This means that every call sets up some libffi data structures and libffi uses this information to perform the native call. Likewise in the other direction for return values. With JNI (and Panama), Hotspot can directly emit the argument/return code a the call, not too dissimilar from what a C or C++ compiler would do. There is still some overhead from maintaining JVM invariants. For example, I think a thread blocked in an FFI call can still participate in a safepoint. But that applies to JNI as well.

If you were prepared to go to the JVM you might try JNA. https://github.com/java-native-access/jna

Other good example, but for Java platform is JNA library. Do not mix it with Java's JNI, which is a bad example of how it could be done.

In case you haven't used it (assuming that you already know about JNI, for comparison) - https://github.com/java-native-access/jna is about as easy as it gets for native interop. Also, as mentioned in another comment, with the Java FFM (Foreign Function and Memory) API already in preview mode, pretty soon, there will be no external dependencies at all, and Java should be able to interop with any language that can talk to C.

The complexity of JNI has given rise to some community-driven libraries that make it simpler to do FFI in Java. Java Native Access (JNA) is one of them. It's built on top of JNI and at least makes FFI easier to use, especially as it removes the need to write any C binding code manually and reduces the chances of memory safety issues. Still, it has some of the disadvantages of being JNI-based and is slightly slower than JNI in many cases. However, JNA is widely used and battle-tested, so definitely a better option than using JNI directly.

This is about calling into any native operating system APIs, as long as they are callable via C or C++ (which these days means "all" operating system APIs).

JNI is somewhat harder to use, because you need custom glue on both sides of the border: Some custom classes in Java and some custom code on the C (and C++) side.

This proposal would remove the need for the glue on the C side and would allow a pure java solution.

Something like this has existed in third-party form for a while as JNA (https://github.com/java-native-access/jna), but now it's going to be built into the JRE itself (if the proposal passes through review)

I use JNA https://github.com/java-native-access/jna , as you can write the entire interface in Java faster as well as easier without the need of messing with the complexities of JNI.

python3 -m pip install \ --trusted-host test.pypi.org --trusted-host test-files.pythonhosted.org \ --index-url https://test.pypi.org/simple/ \ --extra-index-url https://pypi.org/simple/ \ piper_whistle==$(python3 -m src.piper_whistle.version)

In my experience so far, I can use a vast amount of the Python Standard Library to build Wasm-powered serverless applications. The caveat I currently understand is that Python’s implementation of TCP and UDP sockets, as well as Python libraries that use threads, processes, and signal handling behind the scenes, will not compile to Wasm. It is worth noting that a similar caveat exists with libraries that I find on The Python Package Index (PyPI) site. While these caveats might limit what can be compiled to Wasm, there are still a ton of extremely powerful libraries to leverage.

We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.

From there, I needed to learn a bit about PyPi or Python Package Index, which is the home for all the wonderful packages that you know if you have ever run the handy pip install command. PyPi has a pretty quick and easy onboarding, which requires a secured account be created and, for the purposes of submitting packages from CLI, an API token be generated. This can be done in your PyPi profile. Once logg just navigate to https://pypi.org/manage/account/ and scroll down to the API tokens section. Click “Add Token” and follow the few steps to generate an API token which is your access point to uploading packages. With all this in place, I was able to use twine to handle the package upload. First I needed to install twine, again as simple as pip install twine. In order for twine to access my API token during the package upload process, it needed to read it from .pypirc file that contains the token info. For some that file may exist already, for me I was required to create it. Working in windows I simply used a text editor to create it in my home user directory ($HOME/.pypirc). The file contents had a TOML like format looked like this:

I have published the package to Python Package Index, commonly called PyPi, and in this post, I'll be sharing the steps I had to follow in the process.

Register at PyPI.org

According to the stats on the original link, there are over 25,000 identified secret ids/keys/tokens in the data. And it looks like that's just identifiable secrets, e.g. "Google API Keys" that I'm guessing are identifiable because they have a specific pattern, and may be missing other secrets that use less recognizable patterns.

I mean, sure, compared to the 478,876 Projects claimed on https://pypi.org/, that's a pretty small minority. On the other hand, I'd guess a many Python packages don't use these particular services, or even need to connect to a remote service at all, so the area for this class of mistake should be even smaller.

And mistakes do happen, but that's a pretty big thing to miss if you are knowingly publishing your code with the expectation other people will be reading it.

PyPi package

Does pypi.org display the Union of all keywords, the keywords of the most recent release, the keywords of the first release or some other weird combination like the intersection?

https://peps.python.org/pep-0458/

Here's the in-progress roadmap: https://github.com/pypi/warehouse/issues/10672

If there's particular issues you believe you could pick off to help achieve the goal, much appreciated!