doh

Docker-based development environments. Think of it like conda envs or virtual envs on steroids.

Features

• Launch docker containers with strong defaults for interactive usage
  • workdir mounted by default
  • files created inside docker have correct ownership
  • dirs mounted and env vars set can be configured
  • Selected files from home dir can be propagated to fake home inside docker
• Run ssh server for remote development in containers without image modification, with docker on remote host support
• Launch jupyter kernels inside docker (either with vscode ssh development or with external jupyter server)

Quick start

1. Ensure your python is at least 3.8
2. Install doh:
   • With pipx (preferred, dependencies for cli tools installed with pipx are managed independently):

   pipx install 'git+https://github.com/hexfaker/doh.git'

   • To your existing virtualenv (your dependencies may conflict with doh's):

   pip install 'git+https://github.com/hexfaker/doh.git'

3. Cd into your project dir:

mkdir -p my-simple-torch-project && cd my-simple-torch-project

3. Create Dockerfile in it

# my-simple-torch-project/Dockerfile
FROM pytorch/pytorch:1.7.0-cuda11.0-cudnn8-devel

4. Create to-go doh config

doh init

5. Enjoy

doh sh # Spawns a shell inside container
doh ssh # Starts ssh server inside container, follow instructions to connect
doh kernel-install # Writes some configs for jupyterlab(notebook) that allows to run kernel inside container. Requires python and ipython to be present inside container
doh exec # For advanced usage, runs a single command inside container

🛡 License

This project is licensed under the terms of the GNU GPL v3.0 license. See LICENSE for more details.

📃 Citation

@misc{doh,
  author = {Vsevolod Poletaev},
  title = {Docker-based development environments},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/hexfaker/doh}}
}

Credits

This project was generated with python-package-template.