Click this shortcut, and you’ll launch a PowerShell session with the base environment activated. For instance, in Windows, an Anaconda PowerShell Prompt shortcut appears in the Start menu after you install Anaconda. Just launching Anaconda’s python executable doesn’t do this.Īnaconda provides some shortcuts to launching shell sessions with the base environment activated. Once you’ve completed Anaconda setup, you’ll need to configure command-line access to your Anaconda environments. This can be tricky because of the way Anaconda’s environment system works: For Anaconda to work properly, it has to activate at least one environment, such as the base environment. Using Anaconda virtual environments in a command line Uncheck both of these Advanced Options to ensure that Anaconda doesn’t disrupt any existing Python settings.įinish the rest of the install normally. The second keeps your existing Python installation registered as the default interpreter in the Windows Registry. The first prevents existing Python installations from having their PATH references short-circuited by Anaconda. On the next installation screen, you’ll be presented with two options: “Add Anaconda3 to the system PATH environment variable,” and “Register Anaconda3 as the system Python 3.7.” Uncheck both options. The easier it is to find, the less headache later on. Here’s the big reason you’ll want an easily accessible path: When you set up Anaconda to co-exist unobtrusively with other Python installations, you may need to manually specify the path to the Anaconda interpreter, because it might not always be auto-detected, and because (by design) it won’t be in your system PATH. Use an install directory that is as close to the root of your drive as possible, for the sake of making its path easy to find. You may not be able to use a directory off the root of a drive if you’re installing as Just Me, but the simpler the path to Anaconda, the better. For instance, on my system, I have the D: drive reserved for applications, so I use D:\Anaconda3 as my Anaconda install directory. To make Anaconda easily accessible, place it in a directory (where you have write permissions) that is as high up on the drive as possible. On the next menu page, you’ll be given the chance to change the directory where Anaconda is installed. IDGĬhoose the All Users install option if possible, as this will allow you more freedom in terms of where to place the Anaconda directory. If you choose Just Me, the default choice is a subdirectory in your user profile, which may be a little harder to find by default, but is still accessible as long as you know the path. If you’re on a computer where you have admin privileges, choosing All Users makes life a great deal easier, so select that option if you can. The first option worth changing is in the “Select Installation Type” menu, where you choose between installing Anaconda for Just Me or All Users. But the few options you are presented with make all the difference when getting Anaconda to coexist with other Python installations. When you run the Anaconda installer, you won’t be greeted with a great many options. Note also that most of the guidance here pertains to running Anaconda on Microsoft Windows. This article assumes you already have some version of Python installed and you have a basic working knowledge of Python before getting started. In this article, we’ll look at how to set up and work with Anaconda alongside conventional versions of Python on the same system. What if you’re using Anaconda alongside other Python distributions, and you don’t want them stepping on each other’s toes? How do you integrate Anaconda effectively with your other Python tooling, like IDEs? And if you decide you just want to use regular Python, how do you remove Anaconda without breaking anything else? Anaconda is also useful as a general purpose Python distribution.īut Anaconda comes with its share of snares and subtleties. Its appeal goes beyond scientific number crunching, though. The Anaconda distribution of Python packs a great many libraries and tools for data science and scientific computing under a single roof.
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