Manage Multiple Python Versions with PyEnv

[@henriquealves9879]

It's 11:49 pm now here in Brazil and this video saved me. Thank you very much! It worked just fine.

[@jamesfraser7394]

Wow! Solved my tkinter problem and I learned how to easily switch python versions. As a python newbie I love this channel more then all the others.

[@JesseJuup]

PyEnv or Conda? A: PyEnv is primarily a Python version manager, whereas Conda is a more versatile tool that can manage Python environments along with dependencies for various programming languages. The choice between them depends on your specific needs and whether you require isolation of both Python versions and packages or just Python version management. You could also research Docker - while PyEnv and Conda are primarily used for managing Python environments and dependencies, Docker provides a broader solution for packaging and running applications, including Python-based ones, in containers. The choice of which tool to use depends on your specific use case and requirements.

[@FabianBarajas]

I thought `pyenv virtualenv` provided package isolation along with giving you the ability to also use a named virtualenv and python version which can be automatically loaded just by jumping into a project directory

[@DJ-rr7cj]

Absolutely love your content. Short, sweet, and to the point. Keep up the great work!

[@Ratmirsh]

Great! I needed it few days ago. Glad that I've found your channel)

[@BokoMoko65]

Isn't it better to create a development container ?

[@BokoMoko65]

@@oppenheimer11 Rapid deploy, insulation from the environment, no need to use pyenv. I'm just asking. I don't know if it works for things like pygame

[@jakubedzior]

Are you asking about venv?

[@stevenpham6734]

You do this for all projects regardless of their sizes?

[@BokoMoko65]

@@stevenpham6734 Yes, I do. Whenever I have the chance. It's pretty easy using VS code and some extensions. Add git and you can have multiple versions of different environments. It's so cool. Unfortunately, it's useless if you're using AWS Lambda or Azure Functions :(

[@mai6666]

conda > all, but it cannot be used in enterprise anymore

[@u2sukumar]

please zoom it, text size is very small

[@ahopefiend1867]

There's a lot of stuff missing from this video. I followed these steps on two different raspberry pis with different results. It was a bunch of missing libraries.

[@muhammadaneeqasif572]

hy i love hiur content, please make some videos on design principles

[@kannansingaravelu]

Great find. However installation seems too heavy. Can you do a video on the installations as well?

[@tpag20]

good video. PDM is also a good alternative

[@intelligenceservices]

trying to use pyenv to set up an older version of python and using pip installs, but even though I'm supposedly in a venv, i'm getting the "error externally managed environment". i imagine this is because with pyenv, the shell doesn't know that i'm in a venv even though I've switched to that older version of python. presuming your linux system is up to date, I guess you should have seen this kind of error as well?

[@mikemixsosa4264]

Pycharm already do that with venv files right ? Just with the command venv\Scripts\activate to navigate through virtual environments that you have

[@pintokatendejonathan1740]

thanks a lot for this video Beacause i've some modules that are not compatible with the version of python great than 3.9

[@jmirodg7094]

PyEnv seems to do half of the job that Conda dose, why shall we use it?

[@HousamAlamour]

Lifesaver

[@bennguyen1313]

Doesn't venv come standard with python, so what advantage of doing installing pyenv separately? I suppose I'm asking, what's the difference between venv / virtualenv and pyenv (not pyvenv ) with or without the virtualenv plugin (i.e. pyenv-virtualenv)

[@vaulttectradingco8438]

pyenv will let you switch the python versions easily like if you want to user an older version of python or the bleeding edge.

[@bennguyen1313]

@@vaulttectradingco8438 So if I install different python versions using pyenv, and set the global flag to a specific version.. Then will this cause 'pip install modulename' to install only for that version of python or will it instead be useable for ALL installed python versions? If the latter, and if you want to install a module only for only one particular version of python, then you have to create a virtual environment?

[@alfykerolous1869]

dude can u plz do dap on vimspector debugger i canot debug c c++ or anyother anything on vim plz u r my vim hero

[@ncsgames]

is it a good alternative for conda ??

[@DhavalAhir10]

It's better than conda. There is lots of issue with conda

[@jonakthakuria8508]

First Comment wooo Sir, could you give the Github repo link ?

[@NeuralNine]

Just added it to the video description.

[@jonakthakuria8508]

@@NeuralNine thanks...

[@user-gh4lv2ub2j]

Do not reccommend. It destroyed many paths in windows for me and was very difficult to uninstall. It never worked 100% because of some interaction with pipenv. It's actually easiest to build every subversion from source and do a "sudo make altinstall" and mv the superverion to a subversion (i.e. mv python3.11 python3.11.5). Everything works this way until the end of time.

[@DhavalAhir10]

No. It's very useful. You need to learn how to use pyenv like a Pro. It's your fault bro.