pyenv-virtualenv VS pyenv

Compare pyenv-virtualenv vs pyenv and see what are their differences.

pyenv-virtualenv

a pyenv plugin to manage virtualenv (a.k.a. python-virtualenv) (by pyenv)

pyenv

Simple Python version management (by pyenv)
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pyenv-virtualenv pyenv
31 259
5,987 35,990
1.9% 2.2%
4.3 8.9
about 1 month ago 7 days ago
Shell Roff
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pyenv-virtualenv

Posts with mentions or reviews of pyenv-virtualenv. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-14.
  • Integrating GPT in Your Project: Create an API for Anything Using LangChain and FastAPI
    2 projects | dev.to | 14 Jan 2024
    First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.
  • Can't Get Any LoRA Training Repos To Work
    3 projects | /r/SDtechsupport | 28 Mar 2023
  • shell personalization- my custom setup
    3 projects | dev.to | 18 Dec 2022
    git clone https://github.com/pyenv/pyenv-virtualenv.git $(pyenv root)/plugins/pyenv-virtualenv
  • Ask HN: Programming Without a Build System?
    15 projects | news.ycombinator.com | 12 Nov 2022
    > trying to build a lifeboat for Twitter, Python works, but then modules require builds that break.

    > Alternatively, any good resources for the above?

    There are many, _unbelievably many_ writeups and tools for Python building and packaging. Some of them are really neat! But paralysis of choice is real. So is the reality that many of the new/fully integrated/cutting edge tools, however superior they may be, just won't get long term support to catch on and stay relevant.

    When getting started with Python, I very personally like to choose from a few simple options (others are likely to pipe up with their own, and that's great; mine aren't The One Right Way, just some fairly cold/mainstream takes).

    1. First pick what stack you'll be using to develop and test software. In Python this is sadly often going to be different from the stack you'll use to deploy/run it in production, but here we are. There are two sub-choices to be made here:

    1.a. How will you be running the _python interpreter_ in dev/test? "I just want to use the Python that came with my laptop" is fine to a point, but breaks down a lot sooner than folks expect (again, the reasons for this are variously reasonable and stupid, but here we are). Personally, I like pyenv (https://github.com/pyenv/pyenv) here. It's a simple tool that builds interpreters on your system and provides shell aliases to adjust pathing so they can optionally be used. At the opposite extreme from pyenv, some folks choose Python-in-Docker here (pros: reproducible, makes deployment environments very consistent with dev; cons: IDE/quick build-and-run automations get tricker). There are some other tools that wrap/automate the same stuff that pyenv does.

    1.b. How will you be isolating your project's dependencies? "I want to install dependencies globally" breaks down (or worse, breaks your laptop!) pretty quickly, yes it's a bummer. There are three options here: if you really eschew automations/wrappers/thick tools in general, you can do this yourself (i.e. via "pip install --local", optionally in a dedicated development workstation user account); you can use venv (https://docs.python.org/3/library/venv.html stdlib version of virtualenv, yes the names suck and confusing, here we are etc. etc.), which is widely standardized upon and manually use "pip install" while inside your virtualenv, and you can optionally integrate your virtualenv with pyenv so "inside your virtualenv" is easy to achieve via pyenv-virtualenv (https://github.com/pyenv/pyenv-virtualenv); or you can say "hell with this, I want maximum convenience via a wrapper that manages my whole project" and use Poetry (https://python-poetry.org/). There's no right point on that spectrum, it's up to you to decide where you fall on the "I want an integrated experience and to start prototyping quickly" versus "I want to reduce customizations/wrappers/tooling layers" spectrum.

    2. Then, pick how you'll be developing said software: what frameworks or tools you'll be using. A Twitter lifeboat sounds like a webapp, so you'll likely want a web framework. Python has a spectrum of those of varying "thickness"/batteries-included-ness. At the minimum of thickness are tools like Flask (https://flask.palletsprojects.com/en/2.2.x/) and Sanic (like Flask, but with a bias towards performance at the cost of using async and some newer Python programming techniques which tend, in Python, to be harder than the traditional Flask approach: https://sanic.dev). At the maximum of thickness are things like Django/Pyramid. With the minimally-thick frameworks you'll end up plugging together other libraries for things like e.g. database access or web content serving/templating, with the maximally-thick approach that is included but opinionated. Same as before: no right answers, but be clear on the axis (or axes) along with you're choosing.

    3. Choose how you'll be deploying/running the software, maybe after prototyping for awhile. This isn't "lock yourself into a cloud provider/hosting platform", but rather a choice about what tools you use with the hosting environment. Docker is pretty uncontentious here, if you want a generic way to run your Python app on many environments. So is "configure Linux instances to run equivalent Python/package versions to your dev/test environment". If you choose the latter, be aware that (and this is very important/often not discussed) many tools that the Python community suggests for local development or testing are very unsuitable for managing production environments (e.g. a tool based around shell state mutation is going to be extremely inconvenient to productionize).

    Yeah, that's a lot of choices, but in general there are some pretty obvious/uncontentious paths there. Pyenv-for-interpreters/Poetry-for-packaging-and-project-management/Flask-for-web-serving/Docker-for-production is not going to surprise anyone or break any assumptions. Docker/raw-venv/Django is going to be just as easy to Google your way through.

    Again, no one obvious right way (ha!) but plenty of valid options!

    Not sure if that's what you were after. If you want a "just show me how to get started"-type writeup rather than an overview on the choices involved, I'm sure folks here or some quick googling will turn up many!

  • Pyenv and Virtualenvs Quick-start
    3 projects | dev.to | 28 Oct 2022
    For this, I will use pyenv and the pyenv-virtualenv tools.
  • I can I roll python3 back to pre 3.11 in F37 ?
    2 projects | /r/Fedora | 26 Oct 2022
    I would suggest using pyenv and the pyenv-virtualenv plugin to manage various python versions and virtualenvs
  • Will updating Python break my existing Django app?
    2 projects | /r/django | 8 Oct 2022
    To help, check out pyenv and pyenv-virtualenv (or pyenv with Poetry if you want the new hotness). You essentially can install multiple python versions and create a virtualenv that uses a specific python version. So you could have `myapp-3.7` and `myapp-3.10` each isolated with their own package versions, etc.
  • Created a CLI to manage virtual envs with pyenv-win
    4 projects | /r/Python | 28 Sep 2022
    Recently moved to Windows from Linux and was looking for a replacement for pyenv which I was using to manage multiple versions of Python. Found pyenv-win but it was missing the pyenv-virtualenv plugin which can be used to create virtualenvs for different Python versions. Frustrated with the lack of options, I decided to create my own CLI called pyenv-win-venv to do the same thing. I created it only for my personal use but later decided to open source it so it has some of the basic features of pyenv-virtualenv and I hope it is useful to other users of pyenv-win.
  • 9 shell tools for productivity
    11 projects | dev.to | 4 Sep 2022
    Pyenv lets you install different versions of python on your system simultaneously, without breaking a thing. You can switch between any of them in one command. You can also bind a specific version to a directory, which will activate every time you enter it. There is an extension that adds support for virtual environments.
  • Run Python venv from nvim
    10 projects | /r/neovim | 21 Jun 2022
    Install https://github.com/pyenv/pyenv-virtualenv

pyenv

Posts with mentions or reviews of pyenv. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-25.
  • Pyenv – lets you easily switch between multiple versions of Python
    20 projects | news.ycombinator.com | 25 Mar 2024
  • How to Create Virtual Environments in Python
    4 projects | dev.to | 9 Feb 2024
    Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.
  • How to debug Django inside a Docker container with VSCode
    6 projects | dev.to | 26 Jan 2024
    Python version manager pyenv
  • Integrating GPT in Your Project: Create an API for Anything Using LangChain and FastAPI
    2 projects | dev.to | 14 Jan 2024
    First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.
  • Introducing Flama for Robust Machine Learning APIs
    11 projects | dev.to | 18 Dec 2023
    When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.
  • Python Versions and Release Cycles
    4 projects | dev.to | 29 Nov 2023
    For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.
  • Почему я программирую на Ruby
    11 projects | dev.to | 20 Oct 2023
  • Installing kohya_ss GUI on AWS
    2 projects | /r/narrative_ai_art | 28 Sep 2023
    I had previously installed pyenv, and then used that to install Python 3.10.6. Amazon's Linux 2 has an older version of Python installed by default, and using pyenv seemed like the best solution to installing a newer version of Python. I am also familiar with pyenv, having used it before, and it plays nicely with Pipenv. The Python community has developed a few solutions for package/dependency management in the last several years. There are also a few options when it comes to virtual environment creation and management. Poetry is a popular choice, and while I don't have strong opinions on which solution is best, I tend to use Pipenv. So, considering all the available solutions for handling multiple Python versions, recommending people to use python3.10-venv was a strange decision.
  • Getting started with Python and Playwright
    3 projects | dev.to | 7 Sep 2023
    We then use pyenv which is a command line tool used to manage multiple versions of Python. This is useful if you are working on multiple projects that use different versions of Python. Check out the GitHub readme of the 'pyenv' project for more information on how to install it on your operating system. For windows check out pyenv-win or you can use venv Python's Built-in Virtual Environment.
  • pyenv - manage python versions
    2 projects | dev.to | 8 Jul 2023
    There are many more features provided by the pyenv-tool that can be explored, read more at GitHub.

What are some alternatives?

When comparing pyenv-virtualenv and pyenv you can also consider the following projects:

asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more

Poetry - Python packaging and dependency management made easy

Pipenv - Python Development Workflow for Humans.

miniforge - A conda-forge distribution.

virtualenv - Virtual Python Environment builder

spaceship-prompt - :rocket::star: Minimalistic, powerful and extremely customizable Zsh prompt

Pew - A tool to manage multiple virtual environments written in pure python

pyenv-win - pyenv for Windows. pyenv is a simple python version management tool. It lets you easily switch between multiple versions of Python. It's simple, unobtrusive, and follows the UNIX tradition of single-purpose tools that do one thing well.

SDKMan - The SDKMAN! Command Line Interface

mamba - The Fast Cross-Platform Package Manager

PDM - A modern Python package and dependency manager supporting the latest PEP standards

nvm - Node Version Manager - POSIX-compliant bash script to manage multiple active node.js versions