111–120 of 241 posts
https://github.com/sdispater/poetry/issues/571
the OP himself has a fix for this in his own dotfiles repo:
https://github.com/jacobian/dotfiles/commit/e7889c5954daacfe...
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Yes. As someone who has never dove deep into python, but has had some contact with it: the package manager ecosystem is the #1 thing keeping me away from it. npm sucks and all, but at least it just works and doesn't get in my way as much.
What does npm do that python can’t? I’m curious.
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What does npm do that python can’t? I’m curious.
npm is equivalent to combining pip and virtualenv into a single tool. This gives better ergonomics when switching between projects since you never have to "activate" your environment, it's always activated when standing in the project directory.
I imagine if you're deploying docker, you probably should be developing in docker (e.g. using PyCharm's remote interpreter/docker interpreter integration).
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To be fair, he says in the article that his requirements are somewhat different from most Python developers, to wit: * "I need to develop against multiple Python versions - various Python 3 versions (3.6, 3.7, 3.8, mostly), PyPy, and occasionally Python 2.7 (less and less often, thankfully)." * "I work on many projects simultaneously, each with different sets of dependencies, so some sort of virtual environment or is…
It's kind of shocking to hear these two quoted as "different than most" requirements – as a Ruby developer, this sounds like exactly a thing that any engineer supporting production systems would need routinely. RVM and bundler are standard developer tools and I would never question the need for supporting multiple versions on the same machine, unless in a very well-defined scenario where RVM was unneeded (like in a c…
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To be fair, he says in the article that his requirements are somewhat different from most Python developers, to wit: * "I need to develop against multiple Python versions - various Python 3 versions (3.6, 3.7, 3.8, mostly), PyPy, and occasionally Python 2.7 (less and less often, thankfully)." * "I work on many projects simultaneously, each with different sets of dependencies, so some sort of virtual environment or is…
It's kind of shocking to hear these two quoted as "different than most" requirements – as a Ruby developer, this sounds like exactly a thing that any engineer supporting production systems would need routinely. RVM and bundler are standard developer tools and I would never question the need for supporting multiple versions on the same machine, unless in a very well-defined scenario where RVM was unneeded (like in a c…
These days, most productions environments are effectively isolated containers. If your production environment is a container, you probably should develop in a container as well. In that case you don't need much tooling for isolating an application's dependencies from other applications.
The tooling that you need is to build a python application, which means (1) get the dependencies (2) copy over some source code (or invoke the C-compiler if build a CPython extension) (3) run tests. Python's builtin setuptools does that fine. It didn't strike me as amazingly simple, but it's not amazingly complex either. pip is essentially a convenience wrapper for setuptools, i.e. pip is to setuptools as apt is to dpkg.
Basically, I believe that because of docker isolation is a irrelevant criterion by which to judge a language/ecosystem.
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Pyenv is for installing multiple versions of python. Virtualenvs are a layer beneath that. It’s super useful for maintaining static versions of python, like 2.7, 3.6 and 3.7 when you have many projects that have different python requirements.
I understand how this was needed historically, when using the official installer might overwrite the Python you already had installed. But as far as I know, you can download an installer for a new version, run it, and it doesn't touch your previous installation. For example I've had 3.7 on my macOS system for a while, installed from the official installer, not through Homebrew. I just installed 3.8, which pointed my…
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> There is also usually no "system Java", so there is nothing to break along those lines. Oh, but there is :( `jenv shell 1.8` is muscle memory for me now.
You can have multiple JVMs or JDKs installed, and therefore the need to change environment variables depending on your use cases, but I was referring to Java being part of the operating system in the same way that Python is part of some operating systems, for example several Linux distributions (Fedora, RHEL, and practically all derivatives).
But in any case, it just becomes one more version of Python to consider. If you're already dealing with multiple versions, what difference does it make?
Does anyone else think this reflects badly on Python? The fact that the author has to use a bunch of different tools to manage Python versions/projects is intimidating. I don't say this out of negativity for the sake of negativity. Earlier today, I was trying to resurrect an old Python project that was using pipenv. "pipenv install" gave me an error about accepting 1 argument, but 3 were provided. Then I switched to…
Yes. As someone who has never dove deep into python, but has had some contact with it: the package manager ecosystem is the #1 thing keeping me away from it. npm sucks and all, but at least it just works and doesn't get in my way as much.
> Although Docker meets all these requirements, I don't really like using it. I find it slow, frustrating, and overkill for my purposes. How so? I've been using Docker for development for years now and haven't experienced this EXCEPT with some slowness I experienced with Docker Compose upon upgrading to MacOS Catalina (which turned out to be bug with PyInstaller, not Docker or Docker Compose). This is on a Mac, btw;…
The build step for installing or upgrading a package can be a killer with nontrivial projects.
What's the situation where your application needs to go first in the Dockerfile, and then you need to put a bunch of stuff that doesn't depend on your application?
I’ve been manually deploying my projects for years. Can anyone comment on the Docker learning & troubleshooting story for python?