Important
Binder lets you run and test our RCT notebooks. You should not expect Binder to match the performance achievable by RCT on local or high performance computing (HPC) platforms. If performance is a consideration, please consider executing our RCT Docker container locally or in a suitable HPC environment.
The RCT Tutorials container is based on
jupyter/minimal-notebook image.
We prepared a container image with all the latest tutorials in this
repository, and uploaded this image to
DockerHub
(radicalcybertools/tutorials:latest
). The following command pulls and runs
the RCT Tutorials container locally (NOTE: docker
is required to be
installed locally):
docker run --rm -it -p 8888:8888 radicalcybertools/tutorials:latest
Tutorial name is a subdirectory within /src
with the target notebook(s).
# provide a tutorial name and a corresponding tag either as arguments OR
# with the env variables (will be considered only if arguments are skipped):
# export RCT_TUTORIAL_NAME=radical-entk
# export RCT_TUTORIAL_TAG=latest-entk
./docker/build.sh [-n tutorial_name] [-t tag]
# set a tag with which container was built or if it is not available locally,
# then it will be pulled:
# export RCT_TUTORIAL_TAG=latest-entk
docker run --rm -it -p 8888:8888 \
radicalcybertools/tutorials:${RCT_TUTORIAL_TAG:-latest}
This subsection outlines steps necessary to take for setting up a corresponding environment for a tutorial development.
-
Build a basic container for development (
devel
-branches of the RADICAL stack):./docker/build.sh -n devel -t devel
-
Run the basic container with the mounted tutorials source directory:
docker run --rm -it -p 8888:8888 \ --mount type=bind,source="$(pwd)/src",target=/tutorials \ radicalcybertools/tutorials:devel
-
Access Jupyter server with the provided URL (e.g.,
http://127.0.0.1:8888/lab?token=<token>
); -
Create a corresponding directory (i.e., tutorial name) within the working directory and create files
setup.sh
andenvironment.yml
if needed by following templates located in/default
; -
Start creating Jupyter notebooks.
Created tutorial (with the corresponding notebooks) will be preserved locally after container being shut down.