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Pixi is a Rust-based, modern re-implementation of the conda package manager, offering ~10× faster performance and built-in lockfile support, with a strong focus on reproducibility in scientific environments. https://prefix.dev/blog/pixi_a_fast_conda_alternative
A minimal example for faiss installation would be:
We have been using Pixi in research projects involving faiss for nearly a year, including GPU/CUDA versions and cuVS, and everything has worked smoothly.
Examples: https://github.com/denkiwakame/pixi-faiss-examples
Recently, some users have expressed serious concerns about licensing issues, and this has sometimes led to a kind of cancel-culture sentiment not only toward Anaconda Inc., but unfortunately toward the broader conda ecosystem including conda-forge, which is fully open and community-driven. uv pip install support #4510
These discussions often reflect a broader trend:
many users still develop misconceptions around “conda” vs “defaults” vs "conda-forge" vs “Anaconda Inc.” which sometimes leads to unnecessary confusion or negativity.
As a result, discussions can sometimes drift away from what really matters for the research community, reproducibility, and toward debates about modern package managers.
Although I regularly use both uv and pixi, Pixi is by far the most reliable option when dealing with non-Python dependencies (make, cmake, clang, swig, boost, OpenMP, BLAS, CUDA, ...) and when strict reproducibility is required. (we can lock everything).
If there is any openness to this idea, I would be more than happy to contribute a draft PR.
Thank you again for your continued work on faiss.
Would it be possible to consider adding Pixi as an installation option (primarily as a modern alternative to conda written in Rust) in the installation guide? https://github.com/facebookresearch/faiss/blob/main/INSTALL.md
Pixi is a Rust-based, modern re-implementation of the conda package manager, offering ~10× faster performance and built-in lockfile support, with a strong focus on reproducibility in scientific environments. https://prefix.dev/blog/pixi_a_fast_conda_alternative
A minimal example for faiss installation would be:
pixi init -c pytorch -c nvidia -c conda-forge pixi add faiss-cpu=1.13.1 # blazing fast 🚀 (0.47s)pixi init -c pytorch -c nvidia -c conda-forge pixi add faiss-gpu=1.13.1 # blazing fast 🚀 (0.63s)Pixi is increasingly adopted across the scientific Python + non-Python (C++,BLAS, etc.) ecosystem. For example:
Additional context:
Examples: https://github.com/denkiwakame/pixi-faiss-examples
many users still develop misconceptions around “conda” vs “defaults” vs "conda-forge" vs “Anaconda Inc.” which sometimes leads to unnecessary confusion or negativity.
If there is any openness to this idea, I would be more than happy to contribute a draft PR.
Thank you again for your continued work on faiss.