conda
A system-level, binary package and environment manager running on all major operating systems and platforms. (by conda)
miniforge
A conda-forge distribution. (by conda-forge)
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conda | miniforge | |
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30 | 56 | |
6,086 | 5,243 | |
1.4% | 7.0% | |
9.8 | 7.7 | |
2 days ago | 12 days ago | |
Python | Shell | |
GNU General Public License v3.0 or later | 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.
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).
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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What is the difference between chat, cai-chat, and instruct, and how to use them?
Nope they don't use venv for any of the oobabooga# variants nor is it recommended for the git version. I'm using https://github.com/conda-forge/miniforge#mambaforge-pypy3 (better version of the recommended conda) for the git variant. The oobabooga* variant uses micro/miniconda (I suck with names) which you can easily drop into with cmd_?something? and does it all internally. Like whoever built that whole environment setup for the _windows/linux/mac did a great job.
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Build llama.cpp on Jetson Nano 2GB
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh .
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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!
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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.
- Recommendations for Data Science Workflow
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path issue - cannot import modules in jupyter installed via pip3 (m1 mac)
I'd recommend using miniforge if you're comfortable with CLIs, otherwise https://www.anaconda.com/.
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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
What are some alternatives?
When comparing conda and miniforge you can also consider the following projects:
mamba - The Fast Cross-Platform Package Manager
Poetry - Python packaging and dependency management made easy
pyenv - Simple Python version management
PDM - A modern Python package and dependency manager supporting the latest PEP standards
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
pip - The Python package installer
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
wheel - Adoption analysis of Python Wheels: https://pythonwheels.com/