31 January 2025

How to Install Conda on an SSH Server: A Step-by-Step Guide

Working on an SSH server often requires a robust tool for managing packages and dependencies. Conda, a popular package manager, fits this description perfectly, but many people feel intimidated by the installation process in an SSH environment. In this step-by-step guide, we’ll walk you through how to install Conda on an SSH server so you can streamline your workflow. Follow these carefully laid-out steps, and you’ll have Conda up and running in no time.

Why Install Conda on an SSH Server?

Conda is a versatile package and environment manager that can help you handle projects involving Python, R, and other programming languages. Its ability to create isolated environments ensures different projects’ dependencies don’t collide. On an SSH server, Conda enables remote users to set up their own environments with ease, without needing administrative privileges.

Step 1: Connect to the SSH Server

The first step is to gain access to your SSH server. Open a terminal on your local machine and log in using the following command:

ssh username@server_address

Replace username with your SSH account name and server_address with your server’s address. You may also need to enter your secure password or SSH key for authentication.

Step 2: Check for Basic Tools

Before proceeding, ensure your server has essential tools installed, such as curl or wget. You can verify this by running:

curl --version

wget --version

If neither is available, you may need to request administrative help to install these utilities.

Step 3: Download the Miniconda Installer

Conda is bundled with Miniconda, a lightweight installer with fewer pre-installed packages. To download Miniconda on your server, use wget or curl:

• Using wget:

  wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

• Using curl:

  curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

This will download the latest Conda installer for a Linux system.

Step 4: Run the Installer

Make the downloaded file executable by running:

chmod +x Miniconda3-latest-Linux-x86_64.sh

Now execute the installer with:

./Miniconda3-latest-Linux-x86_64.sh

Follow the on-screen instructions. Pay close attention to the installation destination. If you don’t have root privileges, select a directory within your user home directory (e.g., /home/username/miniconda3).

Once the installation completes, close and reopen your terminal, or run:

source ~/.bashrc

This ensures that Conda is added to your environment’s PATH.

Step 5: Verify the Installation

To confirm that Conda has been installed successfully, use the following command:

conda --version

You should see the version of Conda displayed in the terminal. If you encounter an error, double-check that the PATH variable has been updated properly.

Step 6: Update Conda

Once installed, it’s a good idea to update Conda to the latest version, as this ensures you have the latest features and bug fixes. Run:

conda update -n base -c defaults conda

This process may take a few minutes, depending on the speed of your server.

Step 7: Create Your First Environment

Conda’s power lies in its ability to create isolated environments. To create one for a Python 3.9 project, use:

conda create -n my_env python=3.9

Replace my_env with your desired environment name. After creation, activate the environment:

conda activate my_env

Tips for Managing Conda on an SSH Server

Here are some additional tips to enhance your Conda experience:

• Save storage: Regularly clean unused packages by running conda clean --all.
• Export environments: Share environments with collaborators by exporting them: conda env export > environment.yml.
• Back up Conda: Periodically back up the .conda folder to safeguard your environments.

Conclusion

Installing Conda on an SSH server doesn’t have to be an overwhelming task. By following this step-by-step guide, you can equip yourself with a powerful package management tool that improves productivity in remote server workflows. Whether you’re managing isolated environments for multiple projects or updating dependencies effortlessly, Conda is a valuable asset for any developer or data scientist working in a team or on their own.