pyenv
Simple Python version management (by pyenv)
conda
A system-level, binary package and environment manager running on all major operating systems and platforms. (by conda)
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pyenv | conda | |
---|---|---|
260 | 30 | |
36,626 | 6,086 | |
2.9% | 1.4% | |
8.9 | 9.8 | |
17 days ago | 1 day ago | |
Roff | Python | |
MIT License | GNU General Public License v3.0 or later |
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
conda
Posts with mentions or reviews of conda.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-02-09.
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How to Create Virtual Environments in Python
Python's venv module is officially recommended for creating virtual environments since Python 3.5 comes packaged with your Python installation. While there still are additional older tools available, such as conda and virtualenv, if you are new to virtual environments, it is best to use venv now.
- Why does creating my conda environment use so much memory?
- Installing Anaconda on ChromeOS using Linux
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PSA: conda-libmamba-solver can cut two hours off of your Anaconda install, but has only 47 GitHub stars. It deserves more praise.
conda's dependency solver solves a harder problem than pip's. This quote alludes to it "Conda will never be as fast as pip, so long as we're doing real environment solves and pip satisfies itself only for the current operation." (from https://github.com/conda/conda/issues/7239). Thus mamba was created to improve performance and now conda is bringing in that performance boost.
- Is Anaconda still open source?
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How to get the best Conda environment experience in Codespaces
The other challenge I ran into sometimes was that if I was running a lower memory/storage Codespace instance, when I tried to use Conda from the command line to modify environments, the process would be killed after a few seconds. This turns out to be related to some performance issues Conda has that make it consume a lot of memory when trying to work with the conda-forge installation channel. You can always then just increase the size of the Codespace your are working with (just go to your Codespaces list and use the triple dots to change the settings for a Codespace).
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What is the status of Python 3.11?
It's worth noting that [ana]conda isn't even fully compatible yet with 3.11 (you can use it to create 3.11 environments--and you really should rather than waiting on relying on the system python--but conda itself can only run on 3.10.
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Miniconda finally released for Python 3.10
It took some time but as great Christmas present Miniconda was finally released with Python 3.10!
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TW: ZSH (and BASH?) does not show current working dir etc anymore
The September update broke it.
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Python 3.11.0 is now available
According to this this issue is high on their priority list (whatever that means).
What are some alternatives?
When comparing pyenv and conda you can also consider the following projects:
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
mamba - The Fast Cross-Platform Package Manager
Poetry - Python packaging and dependency management made easy
Pipenv - Python Development Workflow for Humans.
miniforge - A conda-forge distribution.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
virtualenv - Virtual Python Environment builder
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
Pew - A tool to manage multiple virtual environments written in pure python
pip - The Python package installer