warehouse VS bandersnatch

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!

2) https://github.com/pypa/bandersnatch//issues/1200#issuecomme...

My work has an isolated network that developers write applications to run inside of. These developers often write Python code. This Python code often requires modules from the Python Package Index (PyPi) to be downloaded using something like pip. In order to allow these developers to run their software on this isolated network, I need to provide them with a PyPi mirror so they can get the modules their software depends upon. To accomplish this, I setup a bandersnatch mirror on a VM in my DMZ and configured our VMs to use this mirror instead of the (unreachable from their perspective) internet. So far, so good.

It looks like DevPi may just work as a caching proxy as well. I also found Bandersnatch too. https://github.com/pypa/bandersnatch which is a configurable mirror with allow / block lists.

Essentially want something like DevPi but add the package to the bandersnatch allow list and mirror it from then on. With some extra large packages in the deny list.

Probably possible to wire that all up reasonably well, but probably just using a caching proxy is 90%+ of the improvement anyways. So may just stick with that.

Whatever is available on PyPI can be installed using pip install. Though it is important to check the package is legit and safe before installing. It is possible to host your own private repository using bandersnatch, nexus or using gitlab among others.