A conda-forge distribution. (by conda-forge)


Basic miniforge repo stats
12 days ago

conda-forge/miniforge is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.

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NOTE: The number of mentions on this list indicates mentions on common posts. Hence, a higher number means a better miniforge alternative or higher similarity.


Posts where miniforge has been mentioned. We have used some of these posts to build our list of alternatives and similar projects - the last one was on 2021-04-27.
  • Terminal killing my command to initialize conda for Miniforge3
    Following this site's instructions, I tried multiple ways of downloading and installing Miniforge, including Homebrew, CI pipeline, and by downloading the shell files from here.
  • I’ve bought a base-line MBA M1. Would you guys guide me through the installation of Python and its libraries? | 2021-03-23
    here's the link to installing miniforge3:
  • Numpy building from source vs pip install on M1 MacBook Air. How does it work?
    I’d strongly recommend using miniforge (basically anaconda), which has ARM builds ready to go (and includes numpy, pandas, etc). Compiling the project from scratch is a giant headache.
  • M1 MacBook Air Hits 900GFlops in the Browser with Safari's Experimental WebGPU | 2021-03-03
    This kind of matches the performance I recorded when numpy is linked to vecLib for large matrix matrix multiplication in float32:

    Note however there is currently no way to build and link numpy and scipy against vecLib to get correct results when calling LAPACK routines (to get Singular Value Decomposition for instance). It might be related to low level fortran ABI problems but I am not an expert so I don't know for sure.

    It's possible to get a fully working numpy / scipy stack with OpenBLAS and gfortran by using the conda-forge distribution:

    The performance is not as good as with vecLib (see the linked benchmark) but it's already very good (e.g. compared to a similarly priced Intel or AMD laptop with OpenBLAS and maybe even MKL).

  • I want to use Python commercially for free. Is Miniconda the best way to go (as opposed to Anaconda)? | 2021-03-01
    Would Miniconda be the best way to go? Or would Miniforge be a good alternative? I guess I'm concerned that I will accidentally install something through Miniconda that would then require me to pay for Anaconda, although this concern may be unfounded.
  • How to get Python, Numpy and Pandas running natively on Apple Silicon. | 2021-02-27
    We will start by installing Python using Miniforge, download the arm64 (Apple Silicon) version of the software on the miniforge GitHub-page
  • [poll] State of package managers in 2021 | 2021-02-17
  • Installing Scikit-Learn on an Apple M1 | 2021-01-30
    It turns out the solution is to use Miniforge, a version of Conda that is comparable to Miniconda, but supports various CPU architectures. Whatever that means. As I said, I'm no Python expert, but this tool essentially allows me to create virtual environments and install packages compiling them for the M1 chip! Any packages it doesn't support can then be installed from pip.