pyenv
Simple Python version management (by pyenv)
Autoenv
Directory-based environments. (by hyperupcall)
Our great sponsors
pyenv | Autoenv | |
---|---|---|
260 | 6 | |
36,626 | 5,549 | |
2.9% | - | |
8.9 | 5.9 | |
16 days ago | 8 days ago | |
Roff | Shell | |
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.
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
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.
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Setup and Use Pyenv in Python Applications
For more information visit: pyenv repository
- Pyenv – lets you easily switch between multiple versions of Python
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How to Create Virtual Environments in Python
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.
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How to debug Django inside a Docker container with VSCode
Python version manager pyenv
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Integrating GPT in Your Project: Create an API for Anything Using LangChain and FastAPI
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.
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Manage your Python Project End-to-End with PDM
Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.
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Introducing Flama for Robust Machine Learning APIs
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.
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Is KDE Desktop really snappier than XFCE these days as claimed?
For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.
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Python Versions and Release Cycles
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
Autoenv
Posts with mentions or reviews of Autoenv.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-22.
- Autoenv: Directory-Based Environments
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How do people manage virtual environments so that they don't take up too much space?
the way I manage (2) is with a kind of DIY pipenv system i've come up with. i have a tool installed in my terminal called autoenv. when i navigate to a new directory, if there's a .env file in it, autoenv executes it. that's basically all autoenv does. I have a .env in my home folder that, among other things, activates my "master" venv. when I create a new project that I want to have its own venv, I just add a .env file to that folder to activate it. otherwise, the master venv is active whenever I roam around my filesystem, functionally serving as a default environment i reuse.
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Introducing pyautoenv: Activate and deactive python environments as you move around the file system
Inspired by autoenv, pyautoenv hooks into the cd command in your shell and will automatically activate a poetry or venv Python environment if that environment is defined in the directory you're cd-ing into. Zsh, Bash, and PowerShell are supported.
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After using Python for over 2 years I am still really confused about all of the installation stuff and virtual environments
There is an autoenv tool you can use to automatically activate a python virtualenv when you cd into a directory but it’s a little annoying to set up https://github.com/hyperupcall/autoenv
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Repeatedly typing export FLASK_ENV=development and export FLASK_APP=hello.py before running flask
But IMO the best solution by far is to use autoenv. There is autoenv for bash and autoenv for zsh.
- How to activate an environment forever?
What are some alternatives?
When comparing pyenv and Autoenv you can also consider the following projects:
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
Pipenv - Python Development Workflow for Humans.
Poetry - Python packaging and dependency management made easy
rez - An integrated package configuration, build and deployment system for software
miniforge - A conda-forge distribution.
virtualenvwrapper
virtualenv - Virtual Python Environment builder
Pew - A tool to manage multiple virtual environments written in pure python