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The instructions on this page show how to run a simple ParaView example using an E4S base container from DockerHub.

Step 1: Docker Image

Download E4S base image ecpe4s/e4s-spack-cpu.

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This image includes Spack and MPI, making it a strong starting point for installing ParaView.

Step 2: Run Container

Start an interactive container session.

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Mount your working directory so your script and outputs persist on your host machine.

Step 3: Install and Load ParaView

Use Spack to install and load ParaView.

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Spack resolves dependencies and prepares your environment for pvpython and other ParaView tools.

Step 4: Create Example Script

Create a simple ParaView Python script.

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Use cat > pv_wavelet.py to build a minimal example pipeline.

Step 5: Run Example

Execute the script with pvpython.

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The script creates synthetic data and writes a VTK output file.

Step 6: View Output

Open the generated file in ParaView.

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Use ParaView on your host machine to inspect the wavelet.vti dataset.

Getting Started with ParaView Using the E4S Base Container

(Docker Desktop on macOS or Linux)

This short guide walks you through a complete ParaView beginner workflow.

1. Download the E4S Base Image

Pull the E4S base container:

docker pull ecpe4s/e4s-spack-cpu:latest

Optional check:

docker images ecpe4s/e4s-spack-cpu

2. Run the Container in Interactive Mode

Create a working directory:

mkdir -p ~/paraview-quickstart
cd ~/paraview-quickstart

Start an interactive shell inside the container:

docker run -it --rm \
  --entrypoint bash \
  -v "$PWD:/work" \
  -w /work \
  ecpe4s/e4s-spack-cpu:latest

You are now inside the container.

3. Install and Load ParaView with Spack

Inside the container, load MPI:

spack load mpich

Install ParaView (this can take several minutes):

spack install paraview +mpi ^mpich

Load ParaView:

spack load paraview +mpi ^mpich

Confirm loaded packages:

spack find --loaded

Confirm ParaView Python is available:

pvpython --version

4. Create a Simple ParaView Example Script

Create a file named pv_wavelet.py.

You can do this with an editor, or directly in the terminal using:

cat > pv_wavelet.py

Then paste the following code and press Ctrl-D to save:

from paraview.simple import Wavelet, SaveData

source = Wavelet()
SaveData("wavelet.vti", proxy=source)

print("Wrote wavelet.vti")

5. Run the Example

Run the script:

pvpython pv_wavelet.py

Verify the output file exists:

ls -lh wavelet.vti

Expected output includes:

Wrote wavelet.vti

6. View the Output File

Exit the container shell:

exit

If your host does not already have ParaView installed, choose one of these options:

  • macOS (Homebrew):
brew install --cask paraview
  • Ubuntu/Debian:
sudo apt update
sudo apt install -y paraview
  • Windows (winget in PowerShell):
winget install Kitware.ParaView
  • Any platform: download an official binary package from https://www.paraview.org/download/

On your host machine, start ParaView and open the generated file:

paraview wavelet.vti

In the ParaView UI:

  1. Click Apply in the Properties panel.
  2. Use the coloring dropdown to color by RTData.
  3. Rotate/zoom to inspect the dataset.

What You Learned

  • How to use an E4S base container for a reproducible ParaView environment
  • How to install and load ParaView with Spack
  • How to run a simple ParaView Python example, generate output data, and view it

Next, you can extend the script with filters such as Contour, Clip, and Slice.