![]() ![]() Next, select Add Interpreter next to the dropdown menu in the upper right-hand corner, and select the On WSL… option. ![]() I prefer to set an interpreter per workspace, so I’ve selected clothing_image_classification from the list on the left however, if you’re fine having a general interpreter for all of your projects, you can just leave the selection as workspace. To set this up, go to File | Settings | Project Workspace | Python Interpreter. You probably already have Python running in Windows, but to use WSL 2 with DataSpell, we need to tell it to use the Python interpreter from the WSL 2 distribution. An interpreter is specific to each processor and operating system. The Python interpreter is what converts the Python code into something that can be executed by our machine’s processor, as explained in this video. Most of the time this is the python command we use to run our scripts. Python is an interpreted language, which means it requires an interpreter to run. Configuring your interpreter in DataSpell using WSL 2 You can exit WSL 2 at any time by entering exit in the command prompt. Finally, while within WSL 2, make sure that you have the required version of Python 3 installed otherwise, you should install or update it. Using Powershell, you can now use WSL 2 by typing wsl into the command line. There are several steps in this guide, so make sure you complete them all carefully before continuing. Next, follow the guide from Microsoft to set up WSL 2 with your selected Linux distribution. Ubuntu and a number of other distributions are available from the Microsoft Store and can be installed directly from there. You’ll then need to install Ubuntu or whatever your preferred Linux distribution is. Windows 10 version 2004 and higher (Home edition and above) and all versions of Windows 11 support WSL 2. Setting up WSL 2īefore using WSL 2, you’ll need to make sure that you are using a compatible version of Windows. The good news is that DataSpell 2022.2 comes with the ability to configure your Python interpreter through WSL 2, meaning you can now run all of those Linux-compatible packages you’d like to use from the comfort of DataSpell on Windows. WSL 2 is more lightweight than traditional virtual machines, providing only command line capabilities, which has traditionally limited development environment options in Python to Jupyter Notebooks. This is perfect for analyses or models that use Linux-exclusive packages, saving you the pain of having to try and compile it yourself! This gives you the best of both worlds when it comes to data science or machine learning tasks: you can access all of your applications or files on Windows, but use Linux to run your Python code. WSL 2 allows you to have a full installation of a Linux distribution running on Windows 10 or 11, using Hyper-V virtualization. If you’re a data scientist or machine learning engineer using Windows, you’ll likely already be familiar with the benefits of using Windows Subsystem for Linux 2 (WSL 2).
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