jnote

Description

jnote is a Jupyter notebook based project initially created for personal use and now shared with the community. It comes with pre-installed libraries for various tasks including visualization, computer vision, natural language processing, and automation of day-to-day management responsibilities. Whether you're a data scientist, a manager, or someone who loves automating tasks, jnote could be a useful tool for you. It aims to provide a ready-to-use environment to perform daily tasks efficiently.

Prerequisites

Before you begin, ensure you have met the following requirements:

• You have installed the latest version of Docker.

Installation

To install jnote, follow these steps:

1. Pull the Docker image:

   docker pull ghcr.io/agitolyev/jnote

2. Run the Docker image:

   Linux

   docker run -d --rm --name jnote -p 8888:8888 -v "$PWD":/home/jovyan/work ghcr.io/agitolyev/jnote:latest

   MacOS

   docker run -d --platform linux/amd64 --rm --name jnote -p 8888:8888 -v "$PWD":/home/jovyan/work ghcr.io/agitolyev/jnote:latest

   • docker run: This command is used to start a new Docker container.

   • -d: This option runs the container in detached mode, which means it runs in the background and doesn't block your terminal.

   • --rm: This option automatically removes the container when it exits. This is useful to not fill up your system with old, unused containers.

   • --name jnote: This option assigns the name jnote to the container. This can be useful for referencing the container in other Docker commands.

   • -p 8888:8888: This option maps the port 8888 of the container to the port 8888 of the host machine. This is necessary for accessing the Jupyter notebook, which by default runs on port 8888.

   • -v "$PWD":/home/jovyan/work: This option mounts the current directory ($PWD) on the host machine to the /home/jovyan/work directory in the container. This allows you to access and save files from your Jupyter notebook to your local machine.

   • ghcr.io/agitolyev/jnote:latest: This is the name of the Docker image to run. ghcr.io/agitolyev/jnote:latest refers to the latest version of the jnote image from the GitHub Container Registry (ghcr.io) under the user agitolyev.

The command for MacOS is the same, with the addition of --platform linux/amd64. This option specifies that the Docker engine should run the image as a Linux platform with AMD64 architecture. This is necessary because Docker on MacOS runs containers within a Linux VM, and this option ensures compatibility.

3. Add the following line to your rc file (e.g., .bashrc, .zshrc):

   This will allow you to start jnote by simply typing jnote in your terminal.

   Note: After adding the alias to your rc file, you need to relaunch your terminal for the changes to take effect.

   Linux

   alias jnote='docker run -d --rm --name jnote -p 8888:8888 -v "$PWD":/home/jovyan/work ghcr.io/agitolyev/jnote:latest'

   MacOS

   alias jnote='docker run -d --platform linux/amd64 --rm --name jnote -p 8888:8888 -v "$PWD":/home/jovyan/work ghcr.io/agitolyev/jnote:latest'

Usage

To use jnote, follow these steps:

1. Navigate to the directory you want to mount:

   cd /path/to/your/directory

2. If you've added jnote as an alias, you can start it with:

   jnote

   If you haven't added jnote as an alias, run the Docker image:

   docker run -d --rm --name jnote -p 8888:8888 -v "$PWD":/home/jovyan/work ghcr.io/agitolyev/jnote:latest

3. Check the logs for the access URL:

   docker logs jnote

   Look for a line that says something like http://127.0.0.1:8888/?token=.... This is your access URL.

4. Open your web browser and visit the access URL. You should now have access to a Jupyter notebook with your directory mounted in work directory.

5. Go to work directory to see your mounted directory.

Remember, any changes you make in the Jupyter notebook will be saved to your local directory.