Using DPF Through Docker#
You can run DPF within a container on any OS using Docker.
Advantages of running DPF in a containerized environment, such as Docker or Singularity, include:
Running in a consistent environment regardless of the host operating system
Offering portability and ease of install
Supporting large-scale cluster deployment using Kubernetes
Providing genuine application isolation through containerization
Installing the DPF Image#
Using your GitHub credentials, you can download the Docker image in the DPF-Core GitHub repository.
If you have Docker installed, you can get started by authorizing Docker to
access this repository using a GitHub personal access token with
packages read permissions. For more information, see
Save the token to a file:
echo XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX > GH_TOKEN.txt
This lets you send the token to Docker without leaving the token value in your history.
Next, authorize Docker to access the repository:
GH_USERNAME=<my-github-username> cat GH_TOKEN.txt | docker login docker.pkg.github.com -u $GH_USERNAME --password-stdin
You can now launch DPF directly from Docker with a short script or directly from the command line.
docker run -it --rm -v `pwd`:/dpf -p 50054:50054 docker.pkg.github.com/pyansys/dpf-core/dpf:v2021.1
Note that this command shares the current directory to the
directory contained within the image. This is necessary as the DPF
binary within the image must access the files within the image
itself. Any files that you want to have DPF read must be placed in
pwd. You can map other directories as needed, but these
directories must be mapped to the
/dpf directory for the server to
see the files you want it to read.
Using the DPF Container from Python#
ansys.dpf.core attempts to start the DPF server at the first
usage of a DPF class. If you do not have Ansys installed and simply want
to use the Docker image, you can override this behavior by connecting to the
DPF server on the port you mapped:
from ansys.dpf import core as dpf_core # uses 127.0.0.1 and port 50054 by default dpf_core.connect_to_server()
If you want to avoid having to run
connect_to_server at the start of
every script, you can tell
ansys.dpf.core to always attempt to
connect to DPF running within the Docker image by setting environment variables:
export DPF_START_SERVER=False export DPF_PORT=50054
set DPF_START_SERVER=False set DPF_PORT=50054
The environment variable
DPF_PORT is the port exposed from the
DPF container. It should match the first value within the
-p 50054:50054 pair.
The environment variable
ansys.dpf.core not to start an
instance but rather look for the service running at
DPF_PORT. If these environment variables are undefined, they
default to 127.0.0.1 and 50054 for