miniforge
A conda-forge distribution. (by conda-forge)
pyenv
Simple Python version management (by pyenv)
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miniforge | pyenv | |
---|---|---|
56 | 260 | |
5,208 | 36,496 | |
6.3% | 2.6% | |
7.7 | 8.9 | |
3 days ago | 8 days ago | |
Shell | Roff | |
GNU General Public License v3.0 or later | 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.
miniforge
Posts with mentions or reviews of miniforge.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-10-02.
- Python 3.12
- 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.
Mambaforge!
See the section on the miniforge github repo. It's just like miniconda/miniforge in that its quite a small download vs full-fat Anaconda.
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A quick guide to using mamba-forge for python virtual environment management
Just to further clarify: you don't need mamba to avoid the Anaconda distribution. The place you get mambaforge also supplies (and originally supplied) miniforge, which is miniconda with conda-forge set as the default channel. All the *forge installers do in this regard is automatically set conda-forge as the default (and only) channel, which is something one can do manually with miniconda.
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How to get the best Conda environment experience in Codespaces
Tip 1: To use less of your Codespaces resources start with a smaller image like Miniconda or Miniforge and install only what you need.
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Ask HN: Programs that saved you 100 hours? (2022 edition)
miniforge, no need to deal with conda environments anymore. https://github.com/conda-forge/miniforge
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Using my Steam Deck as my main personal Desktop PC.
gcc yes but IIRC it's missing a lot of build-essential, and the collection of available headers and development libraries is fairly small. I used conda / mambaforge to build my own toolchain, and I know others have had succeess with Homebrew or pacman - r.
Since you mentioned Homebrew, I'll shout out conda / mamba as well. While it was developed for data science and numerical python, conda-forge has a surprising breadth of packages, and I managed to get the entire gcc toolchain plus development libraries installed, all not only in the userspace, but isolated to a single virtual environment.
Talk about easy mode. conda mamba or poetry, and you're done. I think SteamOS even ships with vim and not just vi, but if you need a different version, it's available via conda.
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
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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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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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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
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Installing kohya_ss GUI on AWS
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.
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Getting started with Python and Playwright
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.
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pyenv - manage python versions
There are many more features provided by the pyenv-tool that can be explored, read more at GitHub.
What are some alternatives?
When comparing miniforge and pyenv you can also consider the following projects:
mamba - The Fast Cross-Platform Package Manager
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.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
virtualenv - Virtual Python Environment builder
Pew - A tool to manage multiple virtual environments written in pure python
SDKMan - The SDKMAN! Command Line Interface
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