Press Ctrl+Alt+S and go to Project | Python Interpreter. With the Python interpreter selector, you can quickly create a new environment for your project. Click it and select the target environment from the list. The environment selector is located in the lower-right corner of the DataSpell UI. Navigate to the bin directory of your anaconda installation (for example, anaconda3/bin).Įxecute the conda activate command (for example, conda activate my-conda-env).Ĭhange the environment with the Python interpreter selector In the Terminal window, run the ls command in the /envs directory (for example, /Users/jetbrains/.conda/envs) and select the target environment. There are two basic ways to change your environment in DataSpell: using commands in the Terminal window and the Python interpreter selector in the IDE UI. So, when the environment of the workspace changes, it changes for all directories that use it. By default, this environment is configured for a newly attached directory. Note that the Workspace SDK: prefix indicates the workspace-specific environment.
#Conda install package in environment update
To preview a configured Python environment, modify its settings, and update packages, press Ctrl+Alt+S and go to Project | Python Interpreter.
You can select any other Python environment on your machine or create a new one. In most cases, it is a Conda environment based on your Anaconda installation.
When you attach a directory to the workspace or open a project, the IDE creates a virtual environment for you. You can configure Conda, Virtualenv or Pipenv. To execute notebooks or Python code in DataSpell, you need to configure at least one virtual environment based on a Python interpreter.
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