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README for ds-lab

Overview

This repository contains the necessary configuration files to set up a data science lab environment using Docker. The environment includes JupyterLab, Anaconda3, and other essential tools for data science.

Prerequisites

  • Docker
  • Docker Compose

Setup for Apple Silicon Mac Users

If you are using an Apple Silicon Mac, you need to set the Docker default platform to linux/x86_64 before starting the containers. Run the following command:

export DOCKER_DEFAULT_PLATFORM=linux/x86_64

Building and Running the DS-Lab Environment

  1. Clone this repository: 
    git clone https://github.com/tkm5/ds-env.git
cd ds-env
  2. Build and start the DS-Lab container: 
    docker-compose up
    Once the container is up and running, you can access JupyterLab by navigating to http://localhost:8888 in your web browser.

Directory Structure

  • The Dockerfile contains the instructions to build the DS-Lab Docker image.
  • The docker-compose.yml file defines the services, networks, and volumes for the DS-Lab environment.
  • The docker/work directory on your host machine is mapped to the /work directory inside the container. You can place your notebooks and data files in this directory to access them from JupyterLab.

Customizing JupyterLab Settings

The provided configuration files allow you to customize JupyterLab's appearance and behavior. The settings are located in the settings directory and are copied to the appropriate locations inside the container during the build process.

Conclusion

This DS-Lab environment provides a consistent and reproducible workspace for data science projects. If you encounter any issues or have suggestions for improvements, please raise an issue or submit a pull request.