metacpan-web VS warehouse

In January 2018, I proposed a CPAN Butterfly Plan to convert Perl functionality to Raku as closely as possible to the original API. I stated this as a goal because Perl (as a programming language) is so much more than syntax alone. Ask anyone what Perl's unique selling point is, and they will most likely tell you it is CPAN.

MetaCPAN. There are a number of project in the Perl community. This is one of the most interesting ones. source code

Perl has numerous modules for practically everything. Try a search on https://metacpan.org for anything that takes your fancy.

I can point to the module library metacpan.org that has modules to do tons of different things -- I don't know what equivalent resouorce Python has.

A good place for this issue would be https://github.com/metacpan/metacpan-web

All language package index websites are a poor imitation of metacpan.org. Without a doubt it is the single best package website I have used for finding packages, reading docs, examples, version changes, source repo. Everybody should be shamelessly copying it.

While the indicates that this is a Windows-related thing, there are a number of packages on CPAN that are in the Win32 namespace, but also work on Linux. This one, it seems does not. It seems at least one of its dependencies, the Win32-API does not work on anything else besides Windows.

A Perl distribution is an archive of files that includes a Perl module. There are no official rules on what non-module files must be included in a distribution, but they often include (among other things) test scripts, a Makefile.PL, documentation, and the license. These distributions are commonly uploaded to CPAN, which is a place for Perl programmers to upload their Perl distributions for the purpose of sharing their code.

If there are modules being used, you can read their documentation using the perldoc command or looking online at https://metacpan.org

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!