Poetry VS cryptography

You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.

Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:

Poetry

The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:

Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?

https://github.com/python-poetry/poetry/issues/6409

Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.

Not sure where I would stand if I fully investigated it tho.

[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...

We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.

Here are the two main packaging issues I run into, specifically when using Poetry:

1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.

2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.

I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.

Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.

[0] https://github.com/python-poetry/poetry/issues/2740

[1] https://github.com/python-poetry/poetry/issues/2184

[2] https://pypi.org/project/pypiserver/

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.

I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github

Congratulations to the authors, this was a feature that was dearly missing from pyca/cryptography. It took a long time to get right.

For the history: https://github.com/pyca/cryptography/issues/2381

Some context:

- The cryptography dependency used by the current release of mitmproxy has a CVE related to an OpenSSL vulnerability (https://github.com/pyca/cryptography/security/advisories/GHS...)

- The main branch of mitmproxy has already upgraded to the latest version of the cryptography package

- The author of the package does not believe the CVE impacts users of mitmproxy so a release including this commit has not been made

Also you'll use https://github.com/pyca/cryptography

first, I did see a correlation between an endpoint being heavily hit in a given time window, and an increase of memory usage that didn't went down afterwards. The endpoint didn't do much so I went through every instruction - is a global variable appended indefinitely ? Is a cache decorator growing without a limit set ? Do I use a 3rd party that has a known issue ? Turns out, it was using cryptography, so I looked up known issues. Saw an issue about a leak when using load_pem_x509_certificate https://github.com/pyca/cryptography/issues/4833 - which I used ! I could fortunately just upgrade the library

Après le kerfuffle du paquet de cryptographie cette semaine (https://github.com/pyca/cryptography/issues/5771), J’ai passé en revue l’état des outils de gestion des dépendances en Python.

> A big problem with Rust, long-term, is that the kind of programs that really need it are somewhat out of today's mainstream. It's not that useful for webcrap. It's not that useful for phone apps. The AI people use Jupyter notebooks and Python to drive code on GPUs.

One thing this is missing is that Rust is useful for libraries callable by many different languages. You may or may not want to use it to build an actual Web app (I personally think it's a solid choice, but reasonable people can disagree). But for building, say, the Python cryptography library [1], which is used as a part of "webcrap" and Jupyter notebooks, Rust is clearly an excellent option. Nobody is going to build core Python infrastructure in Go or Node, and there will always be a need for plumbing libraries.

[1]: https://github.com/pyca/cryptography

Also, I see more and more examples where rust gets included in different technologies using FFI. Ie for python https://github.com/pyca/cryptography for security/performance critical pieces.

> I am curious. Could you give some more context?

Probably talking about this: https://github.com/pyca/cryptography/issues/5771

You will be hard pressed to find a cryptography library that doesn't depend on openssl. Fortunately openssl bindings can be installed on Windows. One of the more popular libraries for python is cryptography, but it does depend on libssl.