optimized workflow and used the Dockerfile in .

Dockerfile

@@ -395,6 +395,12 @@ RUN conda update -n base conda -y
 
 USER root
 
+# Install elasticsearch libs
+USER root
+RUN apt-get update \
+ && curl -sL https://repo1.maven.org/maven2/org/elasticsearch/elasticsearch-hadoop/6.8.1/elasticsearch-hadoop-6.8.1.jar
+RUN pip install --no-cache-dir elasticsearch==7.1.0
+
 # Install rpy2 to share data between Python and R
 RUN conda install rpy2=2.9.4 plotly=4.4.1
 RUN conda install -c conda-forge ipyleaflet

docker-compose-swarm.yml

@@ -2,7 +2,7 @@ version: "3.4"
 services:
   gpu-jupyter:
     image: 127.0.0.1:$REGISTRY_PORT/gpu-jupyter
-    build: ./src/
+    build: .
     ports:
       - $JUPYTER_PORT:8888
     volumes:

docker-compose.yml

@@ -2,7 +2,7 @@ version: "3.4"
 services:
   gpu-jupyter:
     image: 127.0.0.1:5001/gpu-jupyter
-    build: ./src/
+    build: .
     ports:
       - ${JUPYTER_PORT}:8888
     volumes:

generate_Dockerfile.sh

@@ -9,7 +9,8 @@ export STACKS_DIR=".build/docker-stacks"
 # Clone if docker-stacks doesn't exist, and pull.
 ls $STACKS_DIR/README.md  > /dev/null 2>&1  || (echo "Docker-stacks was not found, cloning repository" \
  && git clone https://github.com/jupyter/docker-stacks.git $STACKS_DIR)
-git pull -f $STACKS_DIR
+cd $STACKS_DIR && git pull && cd -
+
 
 # Write the contents into the DOCKERFILE and start with the header
 cat src/Dockerfile.header > $DOCKERFILE

run_Dockerfile.sh

@@ -1,28 +0,0 @@
-#!/usr/bin/env bash
-cd $(cd -P -- "$(dirname -- "$0")" && pwd -P)
-
-# Fetching port
-PORT=0
-HELP=0
-while [[ "$#" -gt 0 ]]; do case $1 in
-  -p|--port) PORT="$2"; shift;;
-  -h|--help) HELP=1;;
-  *) echo "Unknown parameter passed: $1"; exit 1;;
-esac; shift; done
-
-# Print help
-if [[ $HELP != 0 ]]; then
-    echo "Usage: $0 -p [port] # port must be an integer with 4 or more digits."
-    exit 21
-fi
-
-# Check if port is valid
-if [[ $PORT != [0-9][0-9][0-9][0-9]* ]]; then
-    echo "The port is not set or invalid."
-    echo "Usage: $0 -p [port] # port must be an integer with 4 or more digits."
-    exit 22
-fi
-
-# Build and run the Dockerfile
-docker build -t gpu-jupyter .
-docker run -d -p "$PORT":8888 gpu-jupyter