Merge branch 'main' into ubuntu-24.04

Makefile

@@ -38,7 +38,7 @@ help:
 build/%: DOCKER_BUILD_ARGS?=
 build/%: ROOT_CONTAINER?=ubuntu:24.04
 build/%: ## build the latest image for a stack using the system's architecture
-	docker build $(DOCKER_BUILD_ARGS) --rm --force-rm --tag "$(REGISTRY)/$(OWNER)/$(notdir $@):latest" "./images/$(notdir $@)" --build-arg REGISTRY="$(REGISTRY)" --build-arg OWNER="$(OWNER)"
+	docker build $(DOCKER_BUILD_ARGS) --rm --force-rm --tag "$(REGISTRY)/$(OWNER)/$(notdir $@):latest" "./images/$(notdir $@)" --build-arg REGISTRY="$(REGISTRY)" --build-arg OWNER="$(OWNER)" --build-arg ROOT_CONTAINER="$(ROOT_CONTAINER)"
 	@echo -n "Built image size: "
 	@docker images "$(REGISTRY)/$(OWNER)/$(notdir $@):latest" --format "{{.Size}}"
 build-all: $(foreach I, $(ALL_IMAGES), build/$(I)) ## build all stacks

README.md

@@ -37,7 +37,7 @@ It then starts a container running a Jupyter Server with the JupyterLab frontend
 docker run -p 10000:8888 quay.io/jupyter/scipy-notebook:2024-05-27
 ```
 
-You can modify the port on which the container's port is exposed by [changing the value of the `-p` option](https://docs.docker.com/engine/reference/run/#exposed-ports) to `-p 8888:8888`.
+You can modify the port on which the container's port is exposed by [changing the value of the `-p` option](https://docs.docker.com/engine/containers/run/#exposed-ports) to `-p 8888:8888`.
 
 Visiting `http://<hostname>:10000/?token=<token>` in a browser loads JupyterLab,
 where:

docs/using/common.md

@@ -62,8 +62,8 @@ You do so by passing arguments to the `docker run` command.
   This feature is useful when mounting host volumes with specific owner permissions.
   You **must** run the container with `--user root` for this option to take effect.
   (The startup script will `su ${NB_USER}` after adjusting the user ID.)
-  Instead, you might consider using the modern Docker-native options [`--user`](https://docs.docker.com/engine/reference/run/#user) and
-  [`--group-add`](https://docs.docker.com/engine/reference/run/#additional-groups) - see the last bullet in this section for more details.
+  Instead, you might consider using the modern Docker-native options [`--user`](https://docs.docker.com/engine/containers/run/#user) and
+  [`--group-add`](https://docs.docker.com/engine/containers/run/#additional-groups) - see the last bullet in this section for more details.
   See bullet points regarding `--user` and `--group-add`.
 
 - `-e NB_GID=<numeric gid>` - Instructs the startup script to change the primary group of `${NB_USER}` to `${NB_GID}`

docs/using/faq.md

@@ -17,8 +17,8 @@ There are 2 types of data, which you might want to persist.
 
 2. If you want to persist user data (files created by you, like `Python` scripts, notebooks, text files, and so on),
    then you should use a
-   [Docker bind mount](https://docs.docker.com/storage/bind-mounts/) or
-   [Docker Volume](https://docs.docker.com/storage/volumes/).
+   [Docker bind mount](https://docs.docker.com/engine/storage/bind-mounts/) or
+   [Docker Volume](https://docs.docker.com/engine/storage/volumes/).
    You can find [an example of using a bind mount here](./running.md#example-2).
    There is also [a mount troubleshooting section](./troubleshooting.md#permission-denied-when-mounting-volumes) if you experience any issues.
 

docs/using/recipe_code/microsoft_odbc.dockerfile

@@ -6,7 +6,7 @@ SHELL ["/bin/bash", "-o", "pipefail", "-c"]
 
 USER root
 
-ENV MSSQL_DRIVER "ODBC Driver 18 for SQL Server"
+ENV MSSQL_DRIVER="ODBC Driver 18 for SQL Server"
 ENV PATH="/opt/mssql-tools18/bin:${PATH}"
 
 RUN apt-get update --yes && \

docs/using/recipe_code/oracledb.dockerfile

@@ -34,8 +34,8 @@ RUN wget --progress=dot:giga "${INSTANTCLIENT_URL}/oracle-instantclient-basiclit
 
 # And configure variables
 RUN echo "ORACLE_HOME=/usr/lib/oracle/${INSTANTCLIENT_MAJOR_VERSION}/client64" >> "${HOME}/.bashrc" && \
-    echo "PATH=${ORACLE_HOME}/bin:${PATH}" >> "${HOME}/.bashrc" && \
-    echo "LD_LIBRARY_PATH=${ORACLE_HOME}/lib:${LD_LIBRARY_PATH}" >> "${HOME}/.bashrc" && \
+    echo "PATH=\"${ORACLE_HOME}/bin:${PATH}\"" >> "${HOME}/.bashrc" && \
+    echo "LD_LIBRARY_PATH=\"${ORACLE_HOME}/lib:${LD_LIBRARY_PATH}\"" >> "${HOME}/.bashrc" && \
     echo "export ORACLE_HOME" >> "${HOME}/.bashrc" && \
     echo "export PATH" >> "${HOME}/.bashrc" && \
     echo "export LD_LIBRARY_PATH" >> "${HOME}/.bashrc"

docs/using/recipes.md

@@ -301,10 +301,10 @@ This recipe is not tested and might be broken.
 FROM quay.io/jupyter/all-spark-notebook
 
 # Set env vars for pydoop
-ENV HADOOP_HOME /usr/local/hadoop-2.7.3
-ENV JAVA_HOME /usr/lib/jvm/java-8-openjdk-amd64
-ENV HADOOP_CONF_HOME /usr/local/hadoop-2.7.3/etc/hadoop
-ENV HADOOP_CONF_DIR /usr/local/hadoop-2.7.3/etc/hadoop
+ENV HADOOP_HOME=/usr/local/hadoop-2.7.3
+ENV JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64
+ENV HADOOP_CONF_HOME=/usr/local/hadoop-2.7.3/etc/hadoop
+ENV HADOOP_CONF_DIR=/usr/local/hadoop-2.7.3/etc/hadoop
 
 USER root
 # Add proper open-jdk-8 not the jre only, needed for pydoop

docs/using/running.md

@@ -9,7 +9,7 @@ This section provides details about the second.
 
 ## Using the Docker CLI
 
-You can launch a local Docker container from the Jupyter Docker Stacks using the [Docker command-line interface](https://docs.docker.com/engine/reference/commandline/cli/).
+You can launch a local Docker container from the Jupyter Docker Stacks using the [Docker command-line interface](https://docs.docker.com/reference/cli/docker/).
 There are numerous ways to configure containers using CLI.
 The following are some common patterns.
 

docs/using/troubleshooting.md

@@ -77,7 +77,7 @@ The following sections cover a few of these scenarios and how to fix them.
       - If you are mounting your volume inside the `/home/` directory, you can use the `-e CHOWN_HOME=yes` and `CHOWN_HOME_OPTS="-R"` flags
       instead of the `-e CHOWN_EXTRA` and `-e CHOWN_EXTRA_OPTS` in the example above.
       - This solution should work in most cases where you have created a docker volume
-      (i.e. using the [`docker volume create --name <my-volume>`command](https://docs.docker.com/storage/volumes/#create-and-manage-volumes)) and mounted it using the `-v` flag in `docker run`.
+      (i.e. using the [`docker volume create --name <my-volume>`command](https://docs.docker.com/engine/storage/volumes/#create-and-manage-volumes)) and mounted it using the `-v` flag in `docker run`.
    ```
 
 2. **Matching the container's UID/GID with the host's**
@@ -229,7 +229,7 @@ If you have also **created a new user**, you might be experiencing any of the fo
   to modify the files in the default `/home` and `/opt/conda` directories.
   Further avoiding issues when trying to `conda install` additional packages.
 
-- Use `docker inspect <container_id>` and look for the [`Mounts` section](https://docs.docker.com/storage/volumes/#start-a-container-with-a-volume)
+- Use `docker inspect <container_id>` and look for the [`Mounts` section](https://docs.docker.com/engine/storage/volumes/#start-a-container-with-a-volume)
   to verify that the volume was created and mounted accordingly:
 
   ```json

images/all-spark-notebook/Dockerfile

@@ -14,7 +14,7 @@ SHELL ["/bin/bash", "-o", "pipefail", "-c"]
 USER root
 
 # RSpark config
-ENV R_LIBS_USER "${SPARK_HOME}/R/lib"
+ENV R_LIBS_USER="${SPARK_HOME}/R/lib"
 RUN fix-permissions "${R_LIBS_USER}"
 
 # R pre-requisites

images/docker-stacks-foundation/Dockerfile

@@ -20,7 +20,7 @@ USER root
 
 # Install all OS dependencies for the Server that starts
 # but lacks all features (e.g., download as all possible file formats)
-ENV DEBIAN_FRONTEND noninteractive
+ENV DEBIAN_FRONTEND=noninteractive
 RUN apt-get update --yes && \
     # - `apt-get upgrade` is run to patch known vulnerabilities in system packages
     #   as the Ubuntu base image is rebuilt too seldom sometimes (less than once a month)

images/pytorch-notebook/cuda11/Dockerfile

@@ -21,10 +21,10 @@ RUN pip install --no-cache-dir --extra-index-url=https://pypi.nvidia.com --index
     fix-permissions "/home/${NB_USER}"
 
 # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html#dockerfiles
-ENV NVIDIA_VISIBLE_DEVICES all
-ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
+ENV NVIDIA_VISIBLE_DEVICES="all" \
+    NVIDIA_DRIVER_CAPABILITIES="compute,utility"
 
 # Puts the nvidia-smi binary (system management interface) on path
 # with associated library files to execute it
-ENV PATH=${PATH}:/usr/local/nvidia/bin
-ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64
+ENV PATH="${PATH}:/usr/local/nvidia/bin" \
+    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64"

images/pytorch-notebook/cuda12/Dockerfile

@@ -21,10 +21,10 @@ RUN pip install --no-cache-dir --extra-index-url=https://pypi.nvidia.com --index
     fix-permissions "/home/${NB_USER}"
 
 # https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/docker-specialized.html#dockerfiles
-ENV NVIDIA_VISIBLE_DEVICES all
-ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
+ENV NVIDIA_VISIBLE_DEVICES="all" \
+    NVIDIA_DRIVER_CAPABILITIES="compute,utility"
 
 # Puts the nvidia-smi binary (system management interface) on path
 # with associated library files to execute it
-ENV PATH=${PATH}:/usr/local/nvidia/bin
-ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64
+ENV PATH="${PATH}:/usr/local/nvidia/bin" \
+    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64"

images/tensorflow-notebook/cuda/Dockerfile

@@ -32,5 +32,5 @@ ENV NVIDIA_VISIBLE_DEVICES="all" \
 
 # Puts the nvidia-smi binary (system management interface) on path
 # with associated library files to execute it
-ENV PATH=${PATH}:/usr/local/nvidia/bin
-ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64
+ENV PATH="${PATH}:/usr/local/nvidia/bin" \
+    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64"