CLcl3misch·Aug 18, 2025Submission
Miniforge: Community-led conda-forge distribution
1 points · Open discussionconda-forge
miniforge
Shell2020–2025
conda-forge / miniforge
miniforge
A conda-forge distribution.
11Distinct people
12Mentions
0Explicit recommenders
10.4KGitHub stars
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What it is
A conda-forge distribution.
GitHub
Where it is used
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What people are saying
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year12 dated mentions
Observed mentions: 2020-08-20 16:17:07 UTC to 2025-08-18 08:22:41 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 2 | 0 |
What Hacker News says
12 sourcesGoogle bug blocked Miniforge on GitHub
3 points · Open discussionMiniforge [1] provides almost all the same benefits and features without the licensing headaches. The commercial/sign-up nagging is gone, and the GUI launcher is the only thing I've noticed is missing, but I don't use that as it's extraordinarily slow.
[1] https://github.com/conda-forge/miniforge
In Escaping from Anaconda's Stranglehold on macOSJust run the miniforge install script if you want a very friction-free install. I'm not a big conda fan, but the "install in my home directory" use case is very well covered by miniforge.
https://github.com/conda-forge/miniforge/
In Python 3.12miniforge, no need to deal with conda environments anymore. https://github.com/conda-forge/miniforge
In Ask HN: Programs that saved you 100 hours? (2022 edition)If you use miniforge (https://github.com/conda-forge/miniforge) you can just 'pip install torch' and it works.
In PyTorch 1.13Perhaps not that OT, but FWIW I just explained exactly this in a tweet:
> Mambaforge-pypy3 for Linux, OSX, Windows installs from conda-forge by default. (@condaforge builds packages with CI for you without having to install local xcode IIRC)
conda install -c conda-forge -y nodejs
mamba install -y nodejs
https://github.com/conda-forge/miniforge#mambaforge-pypy3
In macOS Subsystem for Linuxconda might be another option. Apparently it does anything (not just python packages).
https://github.com/conda-forge/miniforge
In JDeploy – Deploy desktop Java apps as native bundles on Mac, Linux, and WindowsDoes it not work with miniforge/mambaforge? (https://github.com/conda-forge/miniforge)
I use this with my m1 mac, and it works great.
In Python Best Practices for a New Project in 2021This kind of matches the performance I recorded when numpy is linked to vecLib for large matrix matrix multiplication in float32:
https://gist.github.com/ogrisel/87dcf2c3ab8a304ededf75934b11...
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:
https://github.com/conda-forge/miniforge#download
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 MK
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L).
Does Anaconda not work on ARM? Anyone tried this yet:
https://github.com/conda-forge/miniforge/
In Run Homebrew Natively on Apple Silicon Arm M1There are Alpine [1] and Debian [2] miniconda images (within which you can `conda install python==3.8` and 2.7 and 3.4 in different conda envs)
[1] https://github.com/ContinuumIO/docker-images/blob/master/min...
[2] https://github.com/ContinuumIO/docker-images/blob/master/min...
If you build manylinux wheels with auditwheel [3], they should install without needing compilation for {CentOS, Debian, Ubuntu, and Alpine}; though standard Alpine images have MUSL instead of glibc by default, this [4] may work:
echo "manylinux1_compatible = True" > $PYTHON_PATH/_manylinux.py
[3] https://github.com/pypa/auditwheel
[4] https://github.com/docker-library/docs/issues/904#issuecomme...
The miniforge docker images aren't yet [5][6] multi-arch, which means it's not as easy to take advantage of
all of the ARM64 / aarch64 packages that conda-forge bui
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lds now.
[5] https://github.com/conda-forge/docker-images/issues/102#issu...
[6] https://github.com/conda-forge/miniforge/issues/20
There are i686 and x86-64 docker containers for building manylinux wheels that work with many distros:
https://github.com/pypa/manylinux/tree/master/docker
A multi-stage Dockerfile build can produce a wheel in the first stage and install that wheel (with `COPY --from=0`) in a later stage; leaving build dependencies out of the production environment for security and performance: https://docs.docker.com/develop/develop-images/multistage-bu...