poetry-core | Poetry PEP 517 Build Backend & Core Utilities | DevOps library

When a project is specified only via pyproject.toml (i.e. no setup.{py,cfg} files), how can it be installed in editable mode via pip (i.e. python -m pip install -e .)?

I tried both setuptools and poetry for the build system, but neither worked:

I'm trying to build a Python Plugin for Saleor using Poetry and I'm having issues installing the plugin on Saleor. I run poetry add ../social_auth to install the plugin on saleor and it succeeds but when I try to run Saleor I get this Error:

I am running into an error when trying to run my container where it is saying it can't find a module while trying to import. Specifically:

ModuleNotFoundError: No module named 'sentry_sdk'

The following is my DockerFile which is a multistage build, it seems to install all the packages according to the console output.

Does it make sense to use Conda + Poetry for a Machine Learning project? Allow me to share my (novice) understanding and please correct or enlighten me:

As far as I understand, Conda and Poetry have different purposes but are largely redundant:

• Conda is primarily a environment manager (in fact not necessarily Python), but it can also manage packages and dependencies.
• Poetry is primarily a Python package manager (say, an upgrade of pip), but it can also create and manage Python environments (say, an upgrade of Pyenv).

My idea is to use both and compartmentalize their roles: let Conda be the environment manager and Poetry the package manager. My reasoning is that (it sounds like) Conda is best for managing environments and can be used for compiling and installing non-python packages, especially CUDA drivers (for GPU capability), while Poetry is more powerful than Conda as a Python package manager.

I've managed to make this work fairly easily by using Poetry within a Conda environment. The trick is to not use Poetry to manage the Python environment: I'm not using commands like poetry shell or poetry run, only poetry init, poetry install etc (after activating the Conda environment).

For full disclosure, my environment.yml file (for Conda) looks like this:

I have a trivial python lambda function defined in index.py:

I've read dozens of articles, blog posts, docs, and Q&A posts on this site on this issue, and I haven't found a solution.

My Python code in index.py is simple:

I'm using poetry 1.1.12 with python 3.10. My project depends on numpy 1.21.1 that takes 5 minutes to install each time I run my continuous integration pipeline.

Is there a way to make poetry use some kind of compiled numpy package instead of rebuilding it each build ?

I've already mitigated this issue by caching my virtual environment repository following steps described in this answer, but I want a solution that works even if I change my poetry.lock file or if my cache is expired.

I can only use ubuntu-latest image in github actions due to corporate policy rules

I've been working on a project which so far has just involved building some cloud infrastructure, and now I'm trying to add a CLI to simplify running some AWS Lambdas. Unfortunately both the sdist and wheel packages built using poetry build don't seem to include the dependencies, so I have to manually pip install all of them to run the command. Basically I

1. run poetry build in the project,
2. cd "$(mktemp --directory)",
3. python -m venv .venv,
4. . .venv/bin/activate,
5. pip install /path/to/result/of/poetry/build/above, and then
6. run the new .venv/bin/ executable.

At this point the executable fails, because pip did not install any of the package dependencies. If I pip show PACKAGE the Requires line is empty.

The Poetry manual doesn't seem to specify how to link dependencies to the built package, so what do I have to do instead?

I am using some optional dependencies, could that be interfering with the build process? To be clear, even non-optional dependencies do not show up in the package dependencies.

pyproject.toml:

Trying out poetry 1.1.11 and have pandas in my pyproject.toml in the tool.poetry.dependencies section. Pandas depends on numpy