conda environments:

In the previous article, we discussed how to activate and deactivate environments using conda. Now that you know how to switch between environments, let’s learn how to list all created environments—making it easy to review and manage your virtual environments.

Listing Created Environments

Using virtual environments is a best practice in Python development, as they help isolate project dependencies. After creating multiple virtual environments, how do you view them? conda provides straightforward commands to list all environments you’ve created.

Listing Environments via Command Line

Open your terminal (or Anaconda Prompt) and run:

conda env list

Alternatively, you can use:

conda info --envs

Both commands produce identical output—for example:

# conda environments:
#
base                  *  /home/user/anaconda3
data_science             /home/user/anaconda3/envs/data_science
web_dev                 /home/user/anaconda3/envs/web_dev
ml_project              /home/user/anaconda3/envs/ml_project

This output displays all created environments, including the currently active one (marked with an asterisk *) and the full filesystem path for each environment.

Environment Directory Structure

conda creates a dedicated directory for each environment, containing its specific Python version and all installed packages. For instance, /home/user/anaconda3/envs/data_science is the root directory of the data_science environment—housing all packages and configuration files used exclusively by that environment.

Practical Example

Suppose you’ve already created the following environments:

1. data_science — for data science projects
2. web_dev — for web development projects
3. ml_project — for machine learning projects

To quickly inspect them, simply run:

conda env list

You’ll see output similar to the example above—giving you a clear, at-a-glance overview of your current environment setup per project.

Quick Tip

When an environment is no longer needed, you can remove it to free up disk space:

conda env remove -n environment_name

Replace environment_name with the actual name of the environment—for example:

conda env remove -n web_dev

This command permanently deletes the web_dev environment.

Conclusion

With just a single command, you can efficiently list all your conda environments. Mastering this basic management capability not only improves team collaboration but also makes Python dependency handling significantly more robust and scalable. In the next article, we’ll explore how to install packages using conda—a critical skill for both software development and data analysis workflows.