Python Development Environment with SSH, VSCode, Jupyter, and pystan

This Docker image is based on python:3.10.0-bullseye and is designed to provide a comprehensive development environment with the following features:

• Python 3.10: A modern version of Python for all your scripting and development needs.
• pystan: Pre-installed for your specific library requirements.
• matplotlib and scipy: Additional pre-installed scientific libraries.
• SSH Access: Secure shell access is enabled, allowing you to connect remotely to the container.
• VSCode (code-server): A web-based version of Visual Studio Code for a full-featured code editor accessible from your browser.
• Jupyter Notebook: An interactive computing environment that enables you to create and share documents containing live code, equations, visualizations, and narrative text.
• Pre-loaded Notebooks: Includes a Notesbook directory in the root user's home directory, allowing you to start with pre-defined Jupyter Notebooks.

Features

1. SSH Server:

   • Accessible on port 22.
   • Allows remote connection to the container.
   • Default root password: rootpassword (this should be changed for security purposes).

2. VSCode (code-server):

   • Accessible on port 8080.
   • Provides a robust, web-based code editor with extensions support.

3. Jupyter Notebook:

   • Accessible on port 8888.
   • No password or token required for easy access.
   • Ideal for data analysis, machine learning, and interactive coding.

4. Pre-installed Python Packages:

   • pystan, matplotlib, scipy, and other dependencies specified in requirements.txt are pre-installed.

5. Pre-loaded Notebooks:

   • A Notesbook directory is copied to /root/Notesbook, ready for your use.

Usage

Building the Image

To build the Docker image, ensure you have Docker installed and run the following command in the directory containing your Dockerfile and requirements.txt:

docker build -t python-pystan-ssh-vscode-jupyter .

Running the Container

Run the Docker container with the following command:

docker run -d -p 2222:22 -p 8080:8080 -p 8888:8888 --name dev-container python-pystan-ssh-vscode-jupyter

Connecting via SSH

To connect to the container via SSH, use the following command:

ssh root@localhost -p 2222

Use the password rootpassword.

Accessing VSCode

Open your browser and navigate to http://localhost:8080. You should see the code-server (VSCode) interface.

Accessing Jupyter Notebook

Open your browser and navigate to http://localhost:8888. You should see the Jupyter Notebook interface.

Customization

Changing the Root Password

For security, it is recommended to change the default root password by modifying the Dockerfile or changing it manually after connecting via SSH:

passwd

Adding Additional Python Packages

Update the requirements.txt file to include any additional packages you need and rebuild the Docker image.

Pre-loading More Files

Modify the Dockerfile to copy additional directories or files into the container as needed.

Dockerfile

Here is the Dockerfile used to build this image:

# Start from the python:3.10.0-bullseye image
FROM python:3.10.0-bullseye

# Set environment variables to prevent Python from writing pyc files to disc and buffering stdout and stderr
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1

# Install SSH and other necessary packages
RUN apt-get update && \
    apt-get install -y openssh-server sudo vim wget curl && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Set root password
RUN echo 'root:rootpassword' | chpasswd

# Configure SSH
RUN mkdir /var/run/sshd
RUN echo 'PasswordAuthentication yes' >> /etc/ssh/sshd_config
RUN echo 'PermitRootLogin yes' >> /etc/ssh/sshd_config
RUN echo 'UsePAM yes' >> /etc/ssh/sshd_config

# Install code-server (VSCode) and Jupyter Notebook
RUN curl -fsSL https://code-server.dev/install.sh | sh
RUN pip install --no-cache-dir jupyter

# Expose the SSH port, code-server port, and Jupyter Notebook port
EXPOSE 22
EXPOSE 8080
EXPOSE 8888

# Copy requirements.txt and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy the Notesbook folder to /root/Notesbook
COPY Notesbook /root/Notesbook

# Set the working directory
WORKDIR /root

# Start the SSH, code-server, and Jupyter Notebook services
CMD service ssh start && \
    code-server --bind-addr 0.0.0.0:8080 & \
    jupyter notebook --ip=0.0.0.0 --no-browser --allow-root --NotebookApp.token='' --NotebookApp.password='' & \
    tail -f /dev/null

# Grant necessary permissions
RUN chmod +x /root

requirements.txt

pystan
matplotlib
scipy

Acknowledgements

This Dockerfile was created as part of the course that I follow in my MSc at Imperial College London, Machine Learning and Data Science (MLDS) for the Bayesian Methods and Computation course taught by Nick Heard.