The default environment, shown in boldface in the list, is the one that Visual Studio uses for any new projects. Selecting an environment doesn't change its relation to any projects. These tabs are also described in the Python Environments window tab reference. Use the drop-down list below the list of environments to switch to different tabs such as Packages, and IntelliSense.
For more information, see Python Environments window tab reference 2022- Overview. The four commands at the bottom of the Overview tab each open a command prompt with the interpreter running. Install Python support in Visual Studioįor example, you can see in the image above that the interpreter's location is C:\Program Files (x86)\Microsoft Visual Studio\Python310.If you're new to Python in Visual Studio, the following articles also provide from general background: In general, if you download and run an installer for a mainline Python distribution, Visual Studio detects that new installation and the environment appears in the Python Environments window and can be selected for projects. To install another Python interpreter, see Install Python interpreters. If you want to install packages in an environment, refer to the Packages tab reference. Other aspects of environments are found in the following articles:įor any given project, you can select a specific environment rather than use the default.įor details on creating and using virtual environments for Python projects, see Use virtual environments. In Visual Studio on Windows, you use the Python Environments window, as described in this article, to manage environments and select one as the default for new projects. These components together determine valid language constructs and syntax, operating-system functionality that you can access, and packages you can use. An environment consists of an interpreter, a library (typically the Python Standard Library), and a set of installed packages. Applies to: Visual Studio Visual Studio for Mac Visual Studio CodeĪ Python environment is a context in which you run Python code and includes global, virtual, and conda environments.
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