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2 rows where breadcrumbs = "["Publishing data"]" and breadcrumbs contains "Publishing data"
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| id ▼ | page | ref | title | content | breadcrumbs | references |
|---|---|---|---|---|---|---|
| publish:cli-package | publish | cli-package | datasette package | 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: datasette package mydatabase.db Here's example output for the package command: $ datasette package parlgov.db --extra-options="--setting sql_time_limit_ms 2500" Sending build context to Docker daemon 4.459MB Step 1/7 : FROM python:3.11.0-slim-bullseye ---> 79e1dc9af1c1 Step 2/7 : COPY . /app ---> Using cache ---> cd4ec67de656 Step 3/7 : WORKDIR /app ---> Using cache ---> 139699e91621 Step 4/7 : RUN pip install datasette ---> Using cache ---> 340efa82bfd7 Step 5/7 : RUN datasette inspect parlgov.db --inspect-file inspect-data.json ---> Using cache ---> 5fddbe990314 Step 6/7 : EXPOSE 8001 ---> Using cache ---> 8e83844b0fed Step 7/7 : CMD datasette serve parlgov.db --port 8001 --inspect-file inspect-data.json --setting sql_time_limit_ms 2500 ---> Using cache ---> 1bd380ea8af3 Successfully built 1bd380ea8af3 You can now run the resulting container like so: docker run -p 8081:8001 1bd380ea8af3 This exposes port 8001 inside the container as port 8081 on your host machine, so you can access the application at http://localhost:8081/ You can customize the port that is exposed by the container using the --port option: datasette package mydatabase.db --port 8080 A full list of options can be seen by running datasette package --help : See datasette package for the full list of options for this command. | ["Publishing data"] | [{"href": "https://www.docker.com/docker-mac", "label": "Docker for Mac"}] |
| publish:cli-publish | publish | cli-publish | datasette publish | Once you have created a SQLite database (e.g. using csvs-to-sqlite ) you can deploy it to a hosting account using a single command. You will need a hosting account with Heroku or Google Cloud . Once you have created your account you will need to install and configure the heroku or gcloud command-line tools. | ["Publishing data"] | [{"href": "https://github.com/simonw/csvs-to-sqlite/", "label": "csvs-to-sqlite"}, {"href": "https://www.heroku.com/", "label": "Heroku"}, {"href": "https://cloud.google.com/", "label": "Google Cloud"}] |
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CREATE TABLE [sections] ( [id] TEXT PRIMARY KEY, [page] TEXT, [ref] TEXT, [title] TEXT, [content] TEXT, [breadcrumbs] TEXT, [references] TEXT );