Disabling the anaconda-anon-usage package#

The anaconda-anon-usage package enables Anaconda to collect anonymous usage data and is installed with Anaconda Distribution and Miniconda. The package augments the request header data that conda delivers to package servers during index and package requests. The three randomly generated tokens used for this process are designed to reveal no personal identifying information. For more specific information on how anaconda-anon-usage works, see the package’s public Readme file on Github.

Note

The anaconda-anon-usage package is not a dependency of conda itself and Anaconda only wishes to collect data associated with usage of Anaconda products. If you exclusively use community installers like Miniforge and community channels like conda-forge, you are not affected by this package.

There are two main methods to disabling the anaconda-anon-usage package:

Set the anaconda_anon_usage configuration to false in your .condarc file
Set the CONDA_ANACONDA_ANON_USAGE environment variable to no

Conda configuration command

Open Anaconda Prompt (Terminal on macOS/Linux).
Disable anaconda-anon-usage by running the following command:
```
conda config --set anaconda_anon_usage off
```

To re-enable anaconda-anon-usage, run the following command:

conda config --set anaconda_anon_usage on

For more information on updating your .condarc file, see Using the .condarc conda configuration file in the conda documentation.

Conda environment variable

In order to support various platform and shell (terminal) combinations, conda enables several ways to set conda environment variables.

One primary way is by editing your shell’s startup script:

Open your shell’s startup script (e.g. ~/.profile, ~/.bashrc, ~/.zshrc, etc.) in your text editor of choice.
Add the following line:
```
export CONDA_ANACONDA_ANON_USAGE=no
```
Save the file and restart your shell(s).

Note

Users on Posix-style platforms can also run export CONDA_ANACONDA_ANON_USAGE=no in their shell to disable anonymous usage tracking.

For more information on conda’s underlying activation classes, see the Conda activate deep dive in the conda documentation.