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Richard Trotta, 05/29/2024 12:25 PM


ML beam test PID Meetings


Summer 2024


May 27th, 2024

  • Darren ran with Python3.9
  • Docker (containerization) Definition
    • Containerization is a technology that allows developers to package and run applications along with all their dependencies in isolated environments called containers. This ensures that the application runs consistently across different computing environments, from a developer's laptop to testing, staging, and production.
    • Docker is a popular platform that simplifies containerization. It provides tools to create, deploy, and manage containers. With Docker, developers can write code locally, share their work with colleagues, and deploy to production in a seamless and efficient manner. Docker containers are lightweight, fast, and portable, making them ideal for modern software development and deployment.

Near-term Goals

  1. Setup Linux Subsystem for Windows
  2. Fork the ML Beam Testing GitHub repository
  3. Containerize ML Beam Testing GitHub repository with Docker

Homework


May 27th, 2024

Setting Up Jupyter Notebooks in Docker

  1. Create a directory to store, build, and run Docker container
    cd /path/to/directory
    mkdir beamtest_dir
    cd beamtest_dir
    
  2. Once in your new directory, create a Dockerfile
    touch Dockerfile
    
  3. Using the text editor (e.g., vim, gedit, or emacs) of your choice, edit the Dockerfile
    # Use the official Python 3.9 image as the base image
    FROM python:3.9
    
    # Install Jupyter Notebook and other dependencies
    RUN pip install --no-cache-dir jupyter
    
    # Create a working directory
    WORKDIR /workspace
    
    # Expose the Jupyter Notebook port
    EXPOSE 8888
    
    # Set the default command to start Jupyter Notebook
    CMD ["jupyter", "notebook", "--ip=0.0.0.0", "--port=8888", "--no-browser", "--allow-root"]
    

Updated by Richard Trotta 4 months ago · 20 revisions