{"id": "publish:cli-package", "page": "publish", "ref": "cli-package", "title": "datasette package", "content": "If you have docker installed (e.g. using  Docker for Mac ) you can use the  datasette package  command to create a new Docker image in your local repository containing the datasette app bundled together with one or more SQLite databases: \n             datasette package mydatabase.db \n             Here's example output for the package command: \n             datasette package parlgov.db --extra-options=\"--setting sql_time_limit_ms 2500\"\nSending build context to Docker daemon  4.459MB\nStep 1/7 : FROM python:3.11.0-slim-bullseye\n ---> 79e1dc9af1c1\nStep 2/7 : COPY . /app\n ---> Using cache\n ---> cd4ec67de656\nStep 3/7 : WORKDIR /app\n ---> Using cache\n ---> 139699e91621\nStep 4/7 : RUN pip install datasette\n ---> Using cache\n ---> 340efa82bfd7\nStep 5/7 : RUN datasette inspect parlgov.db --inspect-file inspect-data.json\n ---> Using cache\n ---> 5fddbe990314\nStep 6/7 : EXPOSE 8001\n ---> Using cache\n ---> 8e83844b0fed\nStep 7/7 : CMD datasette serve parlgov.db --port 8001 --inspect-file inspect-data.json --setting sql_time_limit_ms 2500\n ---> Using cache\n ---> 1bd380ea8af3\nSuccessfully built 1bd380ea8af3 \n             You can now run the resulting container like so: \n             docker run -p 8081:8001 1bd380ea8af3 \n             This exposes port 8001 inside the container as port 8081 on your host machine, so you can access the application at  http://localhost:8081/ \n             You can customize the port that is exposed by the container using the  --port  option: \n             datasette package mydatabase.db --port 8080 \n             A full list of options can be seen by running  datasette package --help : \n             See  datasette package  for the full list of options for this command.", "breadcrumbs": "[\"Publishing data\"]", "references": "[{\"href\": \"https://www.docker.com/docker-mac\", \"label\": \"Docker for Mac\"}]"}