conda: the Python environment manager

Installing conda:
There are several ways to make conda runs on your computer. Here are two tastes, Anaconda is a data science toolkit all-in-one edition that makes sure you are ready to go once you have installed it. While MiniForge needs more configurations but it is pure and minimal, the package size is smaller, compared with Anaconda, MiniForge will only install conda for you.
Anaconda (coming with essential DS tools): https://www.anaconda.com​
MiniForge (minimal edition): https://github.com/conda-forge/miniforge​
Alternatively, you can use the command line to install conda:
macOS:
Needs to install macOS Package Manager brew from https://brew.sh​
# Install Homebrew (It takes long time)
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
​
# Then
brew install miniforge
Windows:
Need to install a package manager choco from https://chocolatey.org​
# Install choco Package Manager first
Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
​
# Then (in Admin Powershell)
choco install anaconda3
The Linux machine I have provided is already installed conda binary. If you are now using Linux in lanqiao.cn, the experiment environment is not connected to the Internet so I recommend you install it on your own PC.
Once you have installed the conda, please make sure you can type conda in the CLI. If not,
# path/to/conda refers to conda bin where you have installed
path/to/conda init
Environment
The environment is a collection of Python and its utilities. It enables you to use different versions of Python on one computer. The following command is for creating an environment named pyml
conda create -n pyml python=3.8
-n refers to specify a name for this environment and python=3.8 refers to this environment needs Python version at 3.8
Then, we can change our current environment to pyml using
conda activate pyml
If you are always want to use this environment, you can add this line to your shell config file (.zshrc or .bashrc ), and when you open your shell, the environment is activated automatically.
Have a look at the python executive.
which python
You can have a path returned by the last command, and it will like:
/opt/homebrew/Caskroom/miniforge/base/envs/webapi/bin/python
That's it, conda can change the python executive path whenever you activate an environment.
If you want to delete the environment, use:
conda env remove -n <env_name>
Last modified 1yr ago