Installing Python

Installing Python

The best approach for installing Python is to install an environment manager such as Anaconda or Miniconda. This will allow you to create isolated environments for different projects and manage dependencies.

Anaconda comes with many packages pre-installed, which we don’t necessarily need. Instead, it is typically better to use Miniconda, which is a minimal installer for conda. This allows you to install only the packages you need, which can be useful for keeping your environment clean and avoiding conflicts between packages.

Installing Miniconda#

The quickest way to install Miniconda is via the terminal, as detailed in this guide.

In Linux:

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh

In MacOS:

mkdir -p ~/miniconda3
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh

In Windows powershell:

curl https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe -o miniconda.exe
Start-Process -FilePath ".\miniconda.exe" -ArgumentList "/S" -Wait
del miniconda.exe

Once installed (you may need to restart your terminal), you should be able to call conda from the terminal (it won’t do anything without other options, but it should at least not complain that it doesn’t exist).

Creating a new environment#

To create a new environment, you can use the following command:

conda create --name myenv python=3.10

You can replace myenv with the name of your environment, and 3.10 with the version of Python you want to use. You can also install other packages at the same time, for example:

Installing packages#

You can then install packages as needed using conda install or pip install. For example:

pip install numpy

Installing jupyter#

If you want to run Jupyter notebooks you may wish to install Jupyter Lab. This can be done using the following command:

pip install jupyterlab

You can then run Jupyter Lab using the following command:

jupyter lab

This will open a new tab in your browser with Jupyter Lab running. You can then create a new notebook by clicking on the + symbol in the top left corner.

Running notebooks in VS Code#

If you prefer to use VS Code, you can also run Jupyter notebooks in VS Code. To do this, you will need to install the Python extension for VS Code, which can be found here. You can then open a Jupyter notebook in VS Code. It should automatically detect Conda environments and allow you to choose which one to use.

If the environment doesn’t seem to be present, you may need to install an ipykernel in your environment:

conda activate myenv
pip install ipykernel
python -m ipykernel install --user --name=myenv

You should then be able to select your environment in the top right corner of the notebook.