Add a starting Dockerfile

Author: edoardob90

Dockerfile

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+# Use the jupyter/minimal-notebook as the base image
+FROM quay.io/jupyter/minimal-notebook:latest
+
+# Switch to root user to install additional dependencies (if needed)
+USER root
+
+# Install additional dependencies
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    build-essential \
+    gcc \
+    g++ \
+    libffi-dev \
+    && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Copy the script to setup the environment
+COPY docker/setup_custom_env.py /opt/setup-scripts/
+# Make the script executable
+RUN chmod +x /opt/setup-scripts/setup_custom_env.py
+
+# Copy the script to activate the Conda environment
+COPY docker/activate-custom-env.sh /usr/local/bin/before-notebook.d/
+
+# Switch back to the default notebook user
+USER ${NB_UID}
+
+# Set a shortcut to the tutorial name
+ENV BASENAME="python-tutorial"
+
+# Set the working directory to the home directory of the notebook user
+WORKDIR ${HOME}
+
+# Clone the tutorial repository
+RUN git clone \
+    --branch main \
+    --depth 1 \
+    https://github.com/empa-scientific-it/${BASENAME}
+
+WORKDIR ${HOME}/${BASENAME}
+
+# Create the Conda environment defined in environment.yml
+RUN mamba env create -f binder/environment.yml && \
+    mamba clean --all -f -y && \
+    fix-permissions "${CONDA_DIR}" && \
+    fix-permissions "/home/${NB_USER}"
+
+# Register the Jupyter kernel from the custom environment
+RUN /opt/setup-scripts/setup_custom_env.py ${BASENAME}
+
+# Copy the IPython configuration file
+RUN mkdir -p ${HOME}/.ipython/profile_default
+COPY binder/ipython_config.py ${HOME}/.ipython/profile_default/
+
+# Set the environment variable IPYTHONDIR
+ENV IPYTHONDIR="${HOME}/.ipython"
+
+# Use the default ENTRYPOINT from the base image to start Jupyter Lab
+ENTRYPOINT ["tini", "-g", "--", "start.sh"]

docker/activate-custom-env.sh

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+#!/bin/bash
+conda activate python-tutorial

docker/post-build.sh

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+#!/bin/bash
+set -e
+
+mkdir -p ${HOME}/.ipython/profile_default
+cp binder/ipython_config.py ${HOME}/.ipython/profile_default/

docker/setup_custom_env.py

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+#!/usr/bin/env python3
+import json
+import os
+import sys
+from pathlib import Path
+
+# Retrieve the environment name from the command-line arguments
+env_name = sys.argv[1]
+
+# Get the Conda directory from the environment variables
+CONDA_DIR = os.environ["CONDA_DIR"]
+
+# Define the path to the kernel.json file
+kernel_dir = Path.home() / f".local/share/jupyter/kernels/{env_name}"
+kernel_file = kernel_dir / "kernel.json"
+
+# Ensure the kernel directory exists
+kernel_dir.mkdir(parents=True, exist_ok=True)
+
+# Define default kernel.json content
+default_content = {
+    "argv": [
+        f"{CONDA_DIR}/envs/{env_name}/bin/python",
+        "-m",
+        "ipykernel_launcher",
+        "-f",
+        "{connection_file}",
+    ],
+    "display_name": f"Python ({env_name})",
+    "language": "python",
+}
+
+# If the kernel.json file doesn't exist, create it with default content
+if not kernel_file.exists():
+    kernel_file.write_text(json.dumps(default_content, indent=1))
+
+# Read the existing kernel.json content
+content = json.loads(kernel_file.read_text())
+
+# Add the environment variables to the kernel configuration
+content["env"] = {
+    "XML_CATALOG_FILES": "",
+    "PATH": f"{CONDA_DIR}/envs/{env_name}/bin:$PATH",
+    "CONDA_PREFIX": f"{CONDA_DIR}/envs/{env_name}",
+    "CONDA_PROMPT_MODIFIER": f"({env_name}) ",
+    "CONDA_SHLVL": "2",
+    "CONDA_DEFAULT_ENV": env_name,
+    "CONDA_PREFIX_1": CONDA_DIR,
+}
+
+# Write the updated content back to the kernel.json file
+kernel_file.write_text(json.dumps(content, indent=1))