python-build-standalone VS warehouse

It also replaces "just" as a task manager for me which is very pleasant.

The fact that the python plugin uses precompiled Python binaries by default instead of building them from source remove common issues I had with the asdf's python plugin at work with missing dependencies.

Just so you know, I encountered two little quirks that needed a fix:

- [Backspace Key Doesn't work in Python REPL](https://github.com/indygreg/python-build-standalone/blob/mai...)

These builds are an alternative: https://github.com/indygreg/python-build-standalone

Those are what Rye and hatch use.

Drawbacks: late availability of patch versions, various quirks from how they are built (missing readline, missing some build info that self-compiled C python modules might need.)

Bundling Python isn't too bad if you find the right tools for it.

I really like https://github.com/indygreg/python-build-standalone and https://github.com/indygreg/PyOxidizer

A bundled, built standalone Python can be 16 to 32MB (including the full standard library, which you can strip down to just the bits you use to save size). Not tiny, but probably not worth switching programming languages over.

I'm trying to build a "portable" Python package based on those available from https://github.com/indygreg/python-build-standalone/releases.

I'm a huge fan of https://github.com/indygreg/python-build-standalone which provides Python builds that CAN be moved around and work independently of any other Python installation.

I used that for my own Python+Electron app, which I wrote about here: https://til.simonwillison.net/electron/python-inside-electro...

I used to build my own Pythons that are the same everywhere, now I use indygreg's Python builds. Rye will automatically download and manage Python builds from there. No compiling, no divergence.

One interesting tidbit is that it completely ignores your system Python installations, and instead uses precompiled installations of Python by indygreg from PyOxidizer. This means you don't have to deal with installing Python. It just auto downloads the right builds.

wget https://github.com/indygreg/python-build-standalone/releases/download/20220630/cpython-3.10.5+20220630-x86_64_v3-unknown-linux-gnu-install_only.tar.gz -O - | tar -xz && mv python PortablePython

The lack of Ruby support instantly rings an alarm for me because CPython (on POSIX) also is not relocatable, but is listed as support. Turns pit Hermit is actually using a third-party build script[1] instead of the official one. While the python-build-standalone project is quite awesome and indeed is useful for a lot of things, it has enough quirks I would recommend against any generic package distributor to advertise as Python for general use. This in turn makes me lose most confidence on Hermit, unfortunately.

Be careful if you’re also interested in Hermit. These kinds of things bit you up way down the road when you least expect them to.

[1] https://github.com/indygreg/python-build-standalone

If you really want to be sure, you can download an install_only standalone Python build from https://github.com/indygreg/python-build-standalone/releases and install the libraries with the included pip. Then just tar it again to archive it, and use the included python to run your project. The downloaded wheel you get with pip wheel may depend on the Python version so you just save the wheels you must make sure the Python point version is exactly the same.

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!