Environments

Environments in conda are self-contained, isolated spaces where you can install specific versions of software packages, including dependencies, libraries, and Python versions. This isolation helps avoid conflicts between package versions and ensures that your projects have the exact libraries and tools they need.

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Why should I create a new environment?

There are several reasons you might want to create a new environment:

Isolation of dependencies - Environments isolate software and their dependencies from the rest of the software installed on your machine. This means you can have both Python 3.9 and Python 3.10 installed on your machine and use both versions without encountering issues.

Reproducibility - By creating an environment for each project, you can ensure that your code runs consistently across different machines. Lock your environment to ensure that it remains reproducible indefinitely, then share the environment configuration to allow others to replicate your setup.

Ease of management - Conda provides tools to easily create, manage, and delete environments. You can quickly switch between environments, making it simple to manage multiple projects with different requirements.

Testing and development - Environments are perfect for testing new packages or libraries without affecting your stable development setups. You can experiment freely and remove the environment if things don’t work out, without impacting your other projects.

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Why shouldn’t I work in the base environment?

When first installing and using conda, you probably saw references to something called base or a “base environment”. This environment is where conda itself is installed, and should only be used for installing anaconda, conda, and conda-related packages, such as anaconda-client or conda-build.

For your projects, however, Anaconda strongly recommends creating new environments to work in. This protects your base environment from breaking due to complex dependency conflicts and allows you to easily manage and reproduce your environment on other machines.

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Working with environments

For convenience, the most common actions users take when managing environments are detailed here. For a full list of actions and more comprehensive guide, see Manage environments in the official conda documentation. Alternatively, follow along with our Getting started with conda environments tutorial on Anaconda Cloud.

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Creating an environment

Create a conda environment by opening Anaconda Prompt (Terminal on macOS/Linux) and following the steps for your use case below:

# Replace <ENV_NAME> with a name for your environment
# Replace <PACKAGE> with your desired package
# Replace <VERSION> with your desired version (optional)
conda create --name <ENV_NAME> <PACKAGE>=<VERSION>

conda create --name myenv python=3.11 beautifulsoup4 docutils jinja2=3.1.4 wheel

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Activating an environment

Because environments are isolated spaces, you can only work with one at a time. Selecting an environment to work with is called activating it.

Activate an environment by running the following command:

# Replace <ENV_NAME> with the name of the environment you want to activate
conda activate <ENV_NAME>

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Switching between environments

When you’re ready to switch between projects, simply activate the environment of your other project. Activating a different environment will deactivate your current one.

1. (Optional) View a list of all your environments by running the following command:

   conda info --envs
   

2. To switch to a different environment, activate it by running the following command:

   # Replace <ENV_NAME> with the name of the environment you want to switch to
   conda activate <ENV_NAME>
   

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Locking an environment

The most reliable way to ensure your project remains reproducible indefinitely is to “lock” its environment. Locking an environment creates a fully specified environment, one that has all packages used in the project and their dependencies configured to a specific version. This ensures that your project will be reproduced exactly as it was initially configured, because there will never be an unexpected update or change if new package dependencies are released.

Locking your project requires the conda-project package to be installed in the environment you want to lock. Install the package by running the following commands:

# Replace <ENV> with the environment you want to lock
conda activate <ENV>
conda install conda-project

If your project doesn’t contain an environment.yml file, create one by running the following command:

conda-project init

You can then lock your project’s environment by running the following command:

conda-project lock

Locking your project produces a conda-lock.default.yml file that you can export to share with others.

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Sharing an environment

Sharing your environment with someone else allows them to use conda to recreate your environment on their machine.

To share an environment and its software packages, you must export your environment’s configurations into a .yml file.

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Exporting the environment configuration .yml file

1. Activate the environment you want to export by running the following command:

   # Replace <ENV_NAME> with the name of the environment you want exported
   conda activate <ENV_NAME>
   

2. Export the environment by running the following command:

   conda env export > environment.yml
   

   This file handles both the environment’s pip packages and conda packages.

3. Share the exported environment configuration .yml file with another user.

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Deactivating an environment

It is best practice to deactivate your environment when you are finished working in it.

To deactivate your active environment, run the following command:

conda deactivate