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Richard Trotta, 05/30/2024 11:56 AM
- Table of contents
- ML beam test PID Meetings
ML beam test PID Meetings¶
Summer 2024¶
May 28th, 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.
- A Crash Course for Summer Research\
- GitHub and Python Introduction
- Navigate to python_tutorials and read through the two html files (Introduction and python_tutorial_2)
- Note, these are html files so you'll need
- Navigate to python_tutorials and read through the two html files (Introduction and python_tutorial_2)
Near-term Goals¶
- Setup Linux Subsystem for Windows
- Fork the ML Beam Testing GitHub repository
- Containerize ML Beam Testing GitHub repository with Docker
Homework¶
May 29th, 2024¶
Setting Up Jupyter Notebooks in Docker¶
- Create a directory to store, build, and run Docker container
cd /path/to/directory mkdir beamtest_dir cd beamtest_dir
- Once in the new directory, create a Dockerfile
touch Dockerfile
- Using the text editor (e.g., vim, gedit, or emacs) of your choice, edit the Dockerfile with the following information
# 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"]
- Build the Docker image (e.g., helloworld)
docker build -t helloworld .
- Run the Docker container
docker run -p 8888:8888 helloworld
- Jupyter Notebook is now running. Navigate to a browser and type in either
- The custom token authorization screen
http://localhost:8888
- To bypass the token screen, copy/paste the URL that splashes in the terminal into your browser
Near-term Goals¶
- Try and get the python tutorial Jupyter notebooks working in a container.
Homework¶
May 30th, 2024¶
Setting Up Bash Script for Running Docker¶
Useful commands¶
- To see all docker images
docker images
- To see all docker containers running
docker ps
- To end specific docker container
docker end <container_id>
- To end all docker container
docker end $(docker ps -q)
Updated by Richard Trotta 4 months ago · 27 revisions