If you want the full version which provides a one-off installation, and if you have 5GB disk space, Anaconda will install Python + 250 packages for you. If you are happy with ToS and don’t need the architecture requirements, we are left with 2 options, Anaconda or miniconda. We will talk about channels on the next part more in detail.Īnother reason to use miniforge is the commercial use restriction(*) on Anaconda/miniconda is due to a recent change on Term Of Service of Anaconda, where it is declared as a violation to use the Repository for commercial activities, which includes usage of the packages installed from the defaults channel.Īlso, there are a couple of open-source projects already moved from mini-conda to miniforge, this and this, which suggests there will be an increase at the community supporting this repo. During the installation, it sets conda-forgeas the default -and the only- channel and does not have the defaults channel. It has also support for PyPy, a light version of Python. If you need specific requirements, like running your models on aarch64(arm64) or ppc64le (POWER8/9) architectures, you should use miniforge installation. The first two are developed by Anaconda, and available on their website, whereas miniforge is created by the community recently as miniconda does not have any not support for aarch64 architecture. The top three installers for installing conda are Anaconda, miniconda and miniforge. Hope you enjoy, and I’ll see you at the end! installing packages from different channels.adding channels globally and specific to your environment.naming environments as unique and standard.So, what am I promising you may get, by the end of this article would be understanding how to set up your conda environment through the lens of the opportunity cost by choosing between: If you have questions on specific versions, please leave a comment. PS: I am on macOS Catalina 10.15.7, and have the Conda version 4.9.0. And the last part is about the relationship of channels with environments and packages, which is also an ignored topic, but very important to show good engineering skills if you want to productionize your work with minimum trouble. The second topic will be about setting up an environment, you can reliably use for multiple projects, and how to modify when you need more configuration.
I will focus on three topics, the first one is about conda installer options, Anaconda, miniconda, and miniforge, what you will be missing by not using one. Hello! Conda is one of the most popular tools at data science community, and yet, it can be confusing to understand the steps and the cost of implementing that step, as there is hardly a single place explains, so I decided to write one up. Photo by veeterzy on Unsplash Motivation:
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