conda-lock
mamba
| conda-lock | mamba | |
|---|---|---|
| 1 | 34 | |
| 441 | 6,312 | |
| 2.3% | 3.4% | |
| 9.3 | 9.5 | |
| 1 day ago | 3 days ago | |
| Python | C++ | |
| GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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-lock
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Why and how to use conda?
where last file was generated by doing pip-compile requirements.in (a list of dependencies unpinned). So I'm unsure which dependency issues you are referring to beyond lock file not being included in pip directly. But conda equivalent lock file is also not included and envionrment.yml is not a fully reproducible thing unless you pin all your transitive dependencies in a conflict free manner which would be a pain to do manually. Looks conda equivalent in conda-lock, https://github.com/conda-incubator/conda-lock.
mamba
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Minimal implementation of Mamba, the new LLM architecture, in 1 file of PyTorch
>"everyone" seems to know Mamba. I never heard of Mamba
Only the "everybody who knows what mamba is" are the ones upvoting and commenting. Think of all the people who ignore it. For me, Mamba is the faster version of Conda [1], and that's why I clicked on the article.
https://github.com/mamba-org/mamba
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Towards a New SymPy
Yes, this is a big disadvantage. But have you tried Mamba that aims at implementing Anaconda more efficiently? It works really well in most cases.
https://mamba.readthedocs.io/
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Why are the bioconda bioconductor packages so slow to update?
Because conda is very slow at resolving dependencies. Mamba (https://github.com/mamba-org/mamba) is faster if that is your goal
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Is pip gaining on conda for python libs?
use mamba instead
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Real-world examples of std::expected in codebases?
We started using tl::expected in https://github.com/mamba-org/mamba/ since the beginning of this year and some other related projects like https://github.com/mamba-org/powerloader . I don't know much other big open-source codebases that use that specific lib.
- Mamba: A Drop-In Replacement for Conda Written in C++
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What's Great about Julia?
Great writeup. Minor comment about the portion of the post mentioning Conda being glacially slow: Mamba [1] is a much better drop-in replacement written in C++. Not only is it significantly faster, but error messages are much more sane and helpful.
That being said, I do agree that Pkg.jl is much more sleek and modern than Conda/Mamba.
[1]: https://github.com/mamba-org/mamba
- Mamba Reaches 1.0
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Given Rust’s rapidly growing popularity and wide range of use cases, it seems almost inevitable that it will overtake Python in the near future.
I thought that python could live a little longer when I learned about mamba. But then I found out it is written in C++? Why write a package manager for a dying language in a language that is almost dead???
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Does anyone use virtual environments (Conan's virtual env. or Conda's) for C++
Yes, I use Conda enviroments (actually I use Mamba to manage them now).
What are some alternatives?
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
miniforge - A conda-forge distribution.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
pip - The Python package installer
Pipenv - Python Development Workflow for Humans.
pyenv - Simple Python version management
open-gov-crawlers - Parse government documents into well formed JSON
pyre-check - Performant type-checking for python.
quetz - The Open-Source Server for Conda Packages
pypiserver - Minimal PyPI server for uploading & downloading packages with pip/easy_install