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A tool for developing Node.js and Python projects


dotrun makes use of a Docker image to provide a predictable sandbox for running Node and Python projects.


  • Make use of standard package.json script entrypoints:
    • dotrun runs yarn run start within the Docker container
    • dotrun foo runs yarn run foo within the Docker container
  • Detect changes in package.json and only run yarn install when needed
  • Detect changes in requirements.txt and only run pip3 install when needed
  • Run scripts using environment variables from .env and .env.local files
  • Keep python dependencies in .venv in the project folder for easy access


$ dotrun          # Install dependencies and run the `start` script from package.json
$ dotrun clean    # Delete `node_modules`, `.venv`, `.dotrun.json`, and run `yarn run clean`
$ dotrun install  # Force install node and python dependencies
$ dotrun exec     # Start a shell inside the dotrun environment
$ dotrun exec {command}          # Run {command} inside the dotrun environment
$ dotrun {script-name}           # Install dependencies and run `yarn run {script-name}`
$ dotrun -s {script}             # Run {script} but skip installing dependencies
$ dotrun --env FOO=bar {script}  # Run {script} with FOO environment variable


To install dotrun run:

sudo pip3 install dotrun


  • Linux / macOS
  • Docker (Get Docker)
  • Python > 3.6 and PIP

macOS performance

For optimal performance on Docker we recommend enabling a new experimental file sharing implementation called virtiofs. Virtiofs is only available to users of the following macOS versions:

  • macOS 12.2 and above (for Apple Silicon)
  • macOS 12.3 and above (for Intel)

How to enable virtiofs

Add dotrun on new projects

To fully support dotrun in a new project you should do the following:

  • For Python projects, ensure Talisker is at 0.16.0 or greater in requirements.txt
  • Add .dotrun.json and .venv to .gitignore
  • Create a start script in package.json to do everything needed to set up local development. E.g.: "start": "concurrently --raw 'yarn run watch' 'yarn run serve'"
    • The above command makes use of concurrently - you might want to consider this
  • Older versions of Gunicorn are incompatible with strict confinement so we need Gunicorn >= 20
    • The update landed in Talisker but at the time of writing hasn't made it into a new version
    • If there's no new version of Talisker, simply add gunicorn==20.0.4 to the bottom of requirements.txt

However, once you're ready to completely switch over to dotrun, simply go ahead and remove the run script.

Automated tests of pull requests

The "PR" action builds the Python package and runs a project with dotrun. This will run against every pull request.


All the changes made to the main branch will be automatically published as a new version on PyPI.

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