Conda environments in PyCharm
- Conda
- Package and environment manager from Anaconda. Handles Python and non-Python dependencies.
- Anaconda
- Full data science distribution — Python + Conda + 1500+ pre-installed packages.
- Miniconda
- Minimal Conda installer. Just Python + Conda, install packages as needed. Recommended.
- conda env
- Isolated Python environment managed by Conda. Each project can have its own.
Configure Conda interpreter in PyCharm on Windows
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Open PyCharm Settings
File → Settings (Ctrl+Alt+S) → Project: [your project] → Python Interpreter.
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Add Conda interpreter
Click the gear icon → Add Interpreter → Conda Environment. PyCharm shows existing environments or lets you create a new one.
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Create or select environment
# Or create manually in Anaconda Prompt:(base) C:\> conda create -n myproject python=3.11(base) C:\> conda activate myproject# Then select in PyCharm: existing environment > browse to conda env
Fix Conda issues in PyCharm on Windows
Conda questions
PyCharm conda environment — how to add existing env?
File → Settings → Python Interpreter → gear icon → Add Interpreter → Conda Environment → select "Existing environment" → choose from the dropdown (PyCharm lists all Conda envs it finds) or browse to the Python executable in the environment folder.
PyCharm configure conda interpreter official documentation
The official JetBrains documentation for configuring Conda is at jetbrains.com/help/pycharm/conda-support. It covers creating environments, adding existing ones and troubleshooting.
PyCharm miniconda — which to install, Anaconda or Miniconda?
For most developers: Miniconda. It is smaller (~100 MB vs ~5 GB for Anaconda), faster to install and you install only the packages you need. Anaconda is better if you want all data science packages pre-installed and do not mind the disk space.