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Conda Installation

Conda Installation

Conda is an open-source package and environment management system, primarily used in data science, scientific computing, and machine learning fields.

tip

Conda has two versions: Anaconda and Miniconda. This tutorial mainly introduces the installation and usage of Anaconda.

  • Anaconda: A complete distribution with a rich set of pre-installed packages.
  • Miniconda: A lightweight distribution that only includes Conda itself, requiring manual installation of additional packages.

Features of Conda​

  • Easy Management

Fully isolated Python environments managed with the conda command, automatically resolving dependencies.

  • Cross-Platform

Supports Windows, macOS, and Linux systems.

  • Portability

Supports exporting environment configurations, making it easy to replicate the same development environment on other machines.

  • Multi-Language Support

Supports multiple programming languages, not limited to Python.

Conda Installation​

Download Installation Script​

Visit the Anaconda Official Website to download the installation script for Linux ARM64.

Run Installation Script​

After downloading, navigate to the download directory, open a terminal, and run the installation script. Replace the script name with the actual downloaded file name.

radxa@device$
bash Anaconda3-xxx-Linux-aarch64.sh

During installation, press Enter to proceed through the steps. Then type yes to accept the license agreement.

The terminal will display information similar to the following:

Welcome to Anaconda3 xxx

In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue

> > > By continuing installation, you hereby consent to the Anaconda Terms of Service available at https://anaconda.com/legal.

Do you accept the license terms? [yes|no]

> > > yes

Finally, you will be asked whether to initialize Conda automatically in the terminal. Type yes to confirm.

Verify Installation​

Reopen the terminal. If (base) appears before the username in the terminal prompt, it indicates that Conda has been successfully installed and initialized.

tip

The base environment is Conda's default environment, which includes some commonly used tools for data science and machine learning.

Check Conda Version​

Open the terminal and use the conda --version command to check the Conda version:

radxa@device$
conda --version

If the terminal outputs information similar to the following, the installation was successful:

conda 24.9.2

Exit Conda Environment​

To exit the Conda environment, use the conda deactivate command.

radxa@device$
conda deactivate

After exiting the Conda environment, the (base) prefix will disappear from the terminal prompt.

Configure Conda (Optional)​

Modify Conda's configuration to add Tsinghua University's mirror source for faster downloads in China (optional).

Generate Configuration File​

radxa@device$
conda config --set show_channel_urls yes

Edit Configuration File​

radxa@device$
vi ~/.condarc

Add the following content to the configuration file:

radxa@device$
channels:

- defaults
  show_channel_urls: true
  default_channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
  custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

Clear Cache​

Use the conda clean command to clear the cache and temporary files.

radxa@device$
conda clean -i

Verify Configuration​

Open the terminal and use the conda config --show-sources command to view all loaded configuration files and their priority order.

radxa@device$
conda config --show-sources

If the configuration is successful, the terminal will display information similar to the following:

==> /home/radxa/anaconda3/.condarc <==
channels:

- defaults

==> /home/radxa/.condarc <==
channels:

- defaults
  custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  default_channels:
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
  show_channel_urls: True

==> envvars <==
allow_softlinks: False