Now, what are the main differences between these two? Let’s take a closer look at the free tools, Anaconda and Miniconda. Anaconda Enterprise platform (it is a commercial product that allows organizations to apply Python and R in enterprise environments).InstallerĬurrently, there are 3 different installers: Installing your Conda system is a bit more complicated than downloading a nice picture from Unsplash or buying a new ebook. How to choose an appropriate Conda download option They are described in this changelog entry. In the case of Conda 4.4, there have been recent changes affecting Linux/Mac OS X users. Multipurpose: It is not only for managing Python environments and packages - you can also use it for R (a programming language for statistical computing)Īt the time of writing this article, I use the 4.3.x versions of Conda, but the new 4.4.x versions are also available.Flexibility: It contains a lot of packages (PIP packages are also installable into Conda environments).Transparent File Management: It doesn’t install files outside its directory.Clear Structure: It is easy to understand its directory structure. In this article, I cover how to use Conda. Conda (a package and environment manager).PIP (a Python package manager funnily enough, it stands for “Pip Installs Packages”) with virtualenv (a tool for creating isolated environments). The two most popular tools for setting up environments are: Now that we’ve discussed why environments are useful, let’s dive in and talk about some of the most important aspects of managing them. Consequently, if you want to develop or use applications with different Python or package version requirements, you need to set up different environments.
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