Mine is comparably simpler. Emacs + Elpy, and I just pip and pyenv for managing packages. Granted I don't deploy
My Python Development Environment, 2018 Edition
81–90 of 224 posts
Re: My Python Development Environment, 2018 Edition
#82I just have latest Python installed and the nice support on Visual Studio. https://www.visualstudio.com/vs/python/
This, me too. I never understood the need for virtualenv and similar. Do people really encounter trouble with conflicting packages that often? I try to write scripts so they run on different versions of python anyway, unless there is a very specific reason why that is not possible; and even then you can run python versions in parallel on a Debian/Ubuntu box, with different pip installs for each of them. As for produc…
I use virtualenv so I can just easily `pip freeze > requirements.txt` for individual projects.
Re: My Python Development Environment, 2018 Edition
#83Every time I use Python I miss NPM and package.json.
Hell, prior to pipenv being a thing, Python package management made me miss Maven of all things!
Re: My Python Development Environment, 2018 Edition
#84What seems to be missing in the comments here is the `--user` option to pip. Lets you install modules on a per-user basis, doesn't mess with system python. All you need to do is add the bin folder this creates to your path.
Re: My Python Development Environment, 2018 Edition
#85I just have latest Python installed and the nice support on Visual Studio. https://www.visualstudio.com/vs/python/
This, me too. I never understood the need for virtualenv and similar. Do people really encounter trouble with conflicting packages that often? I try to write scripts so they run on different versions of python anyway, unless there is a very specific reason why that is not possible; and even then you can run python versions in parallel on a Debian/Ubuntu box, with different pip installs for each of them. As for produc…
> Do people really encounter trouble with conflicting packages that often?
Yes it's quite common. For example I work on multiple projects with different versions of Django being used in each one.
Re: My Python Development Environment, 2018 Edition
#86I’m using Anaconda because it was recommended in a step by step tutorial for playing with deep learning. What would be involved in removing it from my system and moving instead to this set of tools? Not necessarily looking for s step by step answer, just for general suggestions. My guess is: find out which python the deep learning tools are using, remove Anaconda, and reinstall the python version needed, using the to…
Anaconda does most of the stuff mentioned, and also makes it much easier to install packages based on C/C++ libraries (which most deep learning things are). So you're better off staying with anaconda. It's widely used in commercial data science projects so the idea that noone "takes it seriously" as someone else suggests is a bit silly. I assume they're thinking about a different context to data science projects. Tha…
> ... and also makes it much easier to install packages based on C/C++ libraries
I hear this often, though I cannot remember ever running into a pip package where this was an issue. Out of curiosity, could someone point me to a pip package and its conda equivalent where this is the case?
Re: My Python Development Environment, 2018 Edition
#87Earlier quoted context omitted.
You miss a package manager layered on top of the one already in your OS, one that's seemingly run by people with no clue what they're doing, is rife with security issues and can break your entire system as we saw today? I have no clue why a sane person would run npm.
And yet millions do?
And those same millions have been halted simultaneously in development around the world by the removal of key packages due to namespacing issues. Or, today, we find that running the newest version of npm under sudo can rewrite file system permissions across the entire hierarchy.
What was that you were implying about how the choice of millions is probably pretty good?
Re: My Python Development Environment, 2018 Edition
#88Earlier quoted context omitted.
Anaconda does most of the stuff mentioned, and also makes it much easier to install packages based on C/C++ libraries (which most deep learning things are). So you're better off staying with anaconda. It's widely used in commercial data science projects so the idea that noone "takes it seriously" as someone else suggests is a bit silly. I assume they're thinking about a different context to data science projects. Tha…
> ... and also makes it much easier to install packages based on C/C++ libraries I hear this often, though I cannot remember ever running into a pip package where this was an issue. Out of curiosity, could someone point me to a pip package and its conda equivalent where this is the case?
Install scipy on Windows and include the Intel linear matrix libraries.
Re: My Python Development Environment, 2018 Edition
#89Since switching to nixos, my Python development environment couldn't be more satisfying. I use a default.nix file and a requirements.txt file and then with a single command I'm into a shell and virtual environment with all dependencies and packages installed, that I can easily transfer between machines. That is unless I want to use PyQt5.
Nix is one of the most amazing things created lately. IMHO, it doesn't get the attention it deserves as it provides great solutions to really tough problems and it's ready for prime time. A purely functional package manager, distro, devops. And pretty soon, home directory management. Maintaining servers or doing aggressive changes becomes very easy. There's even a Darwin (macOS) implementation now, so you can manage…
I'm a big fan apart from how they version. Depending on when you install the version will point at a different commit hash. In our case, all of our Haskell builds failed on all but 1 machine (day apart in resolutions). How nixos handles environments meant our large package builds would kill the entire os, or underlying lib linking just failed - never figured out why, but it wasn't worth investing more time.
Re: My Python Development Environment, 2018 Edition
#90I just have latest Python installed and the nice support on Visual Studio. https://www.visualstudio.com/vs/python/
This, me too. I never understood the need for virtualenv and similar. Do people really encounter trouble with conflicting packages that often? I try to write scripts so they run on different versions of python anyway, unless there is a very specific reason why that is not possible; and even then you can run python versions in parallel on a Debian/Ubuntu box, with different pip installs for each of them. As for produc…
A rather simple practical example I'm working on right now: moving a Django app from 1.9 to 2.0. There are a few code breaking changes in 2.0. All I need to do is create a new virtualenv with Django 2.0 and I can just switch between both versions simply by changing the environment. I may even need to change some further packages that do not work with 2.0 yet and swap them for something else. I can do that in the new env. Then, when all is working, I export a requirements.txt from my virtual env and can quickly set up the very same virtual env on my production machine.