Adding python packages via virtual environment

To enhance the functionality of a containerized environment, you can add additional Python packages using a virtual environment. This guide outlines the steps to create and utilize a virtual environment within your directory on AI-LAB.

Step 1: Create a Virtual Environment

Begin by creating a virtual environment in your home directory. This allows you to install packages locally, making them accessible from within your container.

python3 -m venv my-virtual-env

Step 2: Activate the Virtual Environment

Activate your virtual environment:

source my-virtual-env/bin/activate

Remember to always activate the virtual environment when you want to use it

Remember that you must always activate the virtual environment (source my-virtual-env/bin/activate) to ensure that Python knows where to find the installed packages.

Step 3: Install Python Packages

With the virtual environment activated, install the Python packages you need. For example, to install numpy, pandas, and matplotlib:

srun --mem=24G --cpus-per-task=15 pip install numpy pandas matplotlib

This command will download and install the specified packages into your virtual environment.

Step 4: Verify the Installation

To confirm that the packages were installed correctly, you can check their versions or run a basic script. For instance, to check the installed version of matplotlib:

srun python3 -c "import matplotlib; print(matplotlib.__version__)"

Step 5: Use the Virtual Environment with Containers

You can also use this method to expand containers, such as a PyTorch container.

To do this, you will need to use the Singularity --bind option to bind your virtual environment directory to a location inside the container, and point Python to the path where it can find the installed packages.

srun singularity exec --bind ~/my-virtual-env:/my-virtual-env /ceph/container/pytorch/pytorch_24.09.sif python3 -c "import matplotlib; print(matplotlib.__version__)"

Here, ~/my-virtual-env:/my-virtual-env binds your virtual environment ~/my-virtual-env to a new directory /my-virtual-env inside the container.

Then to use the packages inside the virtual environment you need to define the path to Python3 /my-virtual-env/bin/python3.