If you’re new to Python and using a Mac, the term “Virtual Environment” might sound a bit confusing. This guide is designed to simplify the concept, focusing specifically on the macOS environment.
What is a Virtual Environment?
A Virtual Environment is like a separate room for each of your Python projects. Imagine having multiple closets for different types of clothes. Just like each closet would contain specific items, each Virtual Environment contains its own set of Python libraries and tools.
Why Use a Virtual Environment?
Using Virtual Environments allows you to isolate project-specific libraries and versions. This way, you avoid conflicts between projects that require different versions of the same library.
Types of Virtual Environments
1. venv
- Built into Python: No extra installations needed.
- Beginner-Friendly: Simple and straightforward to use.
2. virtualenv
- More Features: Options for custom prompts, different Python interpreters, etc.
- Requires Installation: You have to install it separately.
3. conda
- Comprehensive: Ideal for data science and complex projects.
- Separate Installation: Comes with Anaconda or Miniconda distributions.
How to Install a Virtual Environment
For venv
- Open your Terminal app.
- Navigate to your project folder using
cd your_project_folder
. - Run
python3 -m venv your_environment_name
.
For virtualenv
- Open Terminal and install virtualenv with
pip install virtualenv
. - Navigate to your project folder.
- Run
virtualenv your_environment_name
.
For conda
- Download and install Anaconda or Miniconda.
- Open a new Terminal window.
- Run
conda create --name your_environment_name
.
How to List Virtual Environments

For venv and virtualenv
macOS doesn’t provide a built-in command to list virtual environments. You’ll need to manually check the directory where you’ve stored them.
For conda
Run conda env list
or conda info --envs
in the Terminal.
How to Manage Virtual Environments
To Activate:
- venv and virtualenv: In the Terminal, run
source your_environment_name/bin/activate
. - conda: Run
conda activate your_environment_name
in the Terminal.
To Deactivate:
- venv and virtualenv: Just type
deactivate
and press Enter. - conda: Run
conda deactivate
in the Terminal.
In Summary
Understanding and using Virtual Environments in Python on macOS helps you maintain cleaner and conflict-free projects. Whether you go with venv, virtualenv, or conda, the ultimate aim is to segregate your projects and their dependencies neatly.
Congratulations, you’ve successfully untangled the concept of a Virtual Environment in Python on macOS. Now, you’re ready to manage your Python projects more effectively. Happy coding!