warehouse VS devpi

In the first part of this series, we set up a repository for a universally portable Python app. Today, we will register the package with PyPI, the Python Package Index, and use a GitHub Release Action to automate the distribution so that other Python users can install the app with pipx or pip.

"Roadmap for PEP 458" https://github.com/pypi/warehouse/issues/10672

To name your Python package, you need to check PyPI to see if your chosen name is already in use. Usually, developers use the same name for both PyPI and your package; however, you can choose a different name if you want to.

pip install PackageName: installs a package (you can browse the available packages in the Python Package Index)

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

There are cases where you want the flexibility of installing a python package via pip without having it available to the open public. This article will focus on using devpi to provide a self-hosted pip compatible python package server. Ubuntu will be used for the OS as it's a fairly common Linux distribution and easily available on Windows Linux Subsystem.

When not providing all dependencies yourself, you might suffer from people deleting the packages you depend on (IMHO a very rare scenario). If it is really that critical (hint: usually it isn't), create a local mirror of Pypi (full or only the packages you need). Devpi, Artifactory, etc. can do that or you just dump the necessary files into Cloud storage, so you have a backup.

devpi acts as a caching proxy for PyPI and takes a bit less setup than this. Plus, you can use it for storing your own packages in a separate index.

https://github.com/devpi/devpi

There are several open-source solutions for provisioning your own, personal PyPI server — for example, this can be done using pypiserver or devpi. However, configuring these services takes time and effort, and it costs money to deploy them. Instead, we’ll use Packagr, a cloud-hosted python package server that allows you to provision your own private Python package repository. It also supports NPM packages and even Docker registries and is very easy to set up. You can get started by creating a free trial account on Packagr — when you’ve created your account, you’ll see this:

devpi-server will probably for the bill

> One should probably run their own package server like https://github.com/pypiserver/pypiserver

Never used pypiserver but I’ve had a good experience with https://github.com/devpi/devpi