pyenv
mamba

pyenv | mamba | |
---|---|---|
269 | 37 | |
40,627 | 7,108 | |
1.5% | 1.0% | |
9.1 | 9.5 | |
5 days ago | 7 days ago | |
Roff | C++ | |
MIT License | 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.
pyenv
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TIL how to profile `zsh` start time
At the top is showing that the __conda_activate is taking up most of the time in my case. Conda is a package manager tool similar to pyenv, which I barely use and only had it when experimenting with something months back.
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12 Steps to Organize and Maintain Your Python Codebase for Beginners
Personally, I’m a big fan of pyenv, so that’s what I’ll be using here. I’ve already got it installed on my laptop since it’s my go-to for work and personal projects.
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Python Project Creation on Mac OS X
PyFabricate queries pyenv for the developer installed Python versions. These are the only ones from which PyFabricate can create Python virtual environments.
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Why you should use environment managers to manage multiple versions?
We actively use environment managers pyenv, goenv and nvm for managing multiple versions of Python, Golang and NodeJS at Mantis. These provide us with an easily manageable, robust development environments.
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Python Version Management with PyEnv
Management of different language versions and interpreters is somewhat of a gray area in the Pythonic world as of September 2024, but of course the community has "unofficial" solutions that circumvent this problem. One particular good one is PyEnv, that borrows heavily from ruby's solutions for version management, which is something ruby does very well. PyEnv is basically a collection of shell scripts that help to install and select a specific python version or interpreter, in both global and localized scopes. It works by inserting a directory of shims in the PATH and will rehash the shim according to specific conditions in order to map the python binary (as well as other setup such as mapping pip, switching the PYTHON_VERSION env, etc). This guide will focus on MacOS and the Debian-family linux distros, and will cover setup on both bash and zsh. It will not cover pyenv-win.
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How Should You Use an Auto-Formatter?
In the case of pre-commit hooks, the runtime either has to be installed manually by every user (in the case of Husky) or is handled in Python (in the case of pre-commit). Running Node.js through Python/pyenv introduces an additional layer of complexity, which can lead to issues like OpenSSL library incompatibilities.
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Create your own card game with OWASP® Cornucopia
Install pyenv or pyenv-win
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Setting up a standalone SQLAlchemy 2.0 ORM application
Let's get some initial setup out of the way, starting by an empty directory and a virtual environment. Create a new directory with any name you like, and a virtual environment with your preferred tool. I personally use Pyenv. It is worth noting that this tutorial was created with Python 3.11.3, and SQLAlchemy version 2.0.27.
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Install Asdf: One Runtime Manager to Rule All Dev Environments
If you have a requirement for multiple, specific Python versions, why not just use pyenv?
https://github.com/pyenv/pyenv
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Setup and Use Pyenv in Python Applications
For more information visit: pyenv repository
mamba
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Generate pip requirements.txt file based on imports of any project
Please consider consolidating python dependency management instead of fragmenting it:
https://github.com/mamba-org/mamba
In other words, bring the thinking here. Whether it's new thinking, or decade old thinking, it's well time to converge. We've had decades of trying it like Heinz catsup varieties. Worth trying more wood behind fewer arrows.
- Mamba 2.0.0
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A pure NumPy implementation of Mamba
Completely - I assumed it was an implementation of https://github.com/mamba-org/mamba
I also assumed that "a pure NumPy implementation" meant that it was built purely numpy, which it isn't smh
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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
What are some alternatives?
Poetry - Python packaging and dependency management made easy
miniforge - A conda-forge distribution.
Pipenv - Python Development Workflow for Humans.
pip - The Python package installer
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
virtualenv - Virtual Python Environment builder
pyre-check - Performant type-checking for python.
Pew - A tool to manage multiple virtual environments written in pure python
conda-lock - Lightweight lockfile for conda environments
devpi - Python PyPi staging server and packaging, testing, release tool
