Since Python version 3.5, the docs officially recommend venv for managing environments. It is basically an alternative to pip, Python’s native package manager that comes preinstalled with most modern Python-versions You won’t be able to use your Web Development packages inside your machine learning environment.Īgain, if you want to read about the benefits of using virtual environments versus putting all of your packages into one global environment, check out the article linked above.Ĭonda is exactly such a package manager. You then need to activate an environment to use the packages inside of it. create an environment for Web Development and one for Machine Learning. A package manager now creates new environments, thus allowing you to put certain packages only inside one specific environment. By default, you always have full access to all of the packages that are inside your (global) environment. If you install external packages, they are added to your environment. If you know how virtual environments work, but would still like a quick refresher, here we go:Ī package manager (in the context of Python) is a piece of software that manages external packages on top of your local Python installation inside of a “box” called “(virtual) environment”. Even if you have used package managers before, you still might pick up a nugget of wisdom or two, so I really do recommend that you read that article. In that article, I explain these concepts in great detail, going one step at a time. If you are unfamiliar with the term package manager, or with virtual environments in general, I highly recommend that you read the article Package Managers and Virtual Environments Explained, Step by Step first. The most important component of Anaconda is conda, Anaconda’s package manager. You can imagine it being a sort of “flavor” of Python.
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