id,page,ref,title,content,breadcrumbs,references
publish:publish-vercel,publish,publish-vercel,Publishing to Vercel,"Vercel   - previously known as Zeit Now - provides a layer over AWS Lambda to allow for quick, scale-to-zero deployment. You can deploy Datasette instances to Vercel using the  datasette-publish-vercel  plugin. 
                 pip install datasette-publish-vercel
datasette publish vercel mydatabase.db --project my-database-project 
                 Not every feature is supported: consult the  datasette-publish-vercel README  for more details.","[""Publishing data"", ""datasette publish""]","[{""href"": ""https://vercel.com/"", ""label"": ""Vercel""}, {""href"": ""https://github.com/simonw/datasette-publish-vercel"", ""label"": ""datasette-publish-vercel""}, {""href"": ""https://github.com/simonw/datasette-publish-vercel/blob/main/README.md"", ""label"": ""datasette-publish-vercel README""}]"
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:publish-heroku,publish,publish-heroku,Publishing to Heroku,"To publish your data using  Heroku , first create an account there and install and configure the  Heroku CLI tool . 
                 You can publish one or more databases to Heroku using the following command: 
                 datasette publish heroku mydatabase.db 
                 This will output some details about the new deployment, including a URL like this one: 
                 https://limitless-reef-88278.herokuapp.com/ deployed to Heroku 
                 You can specify a custom app name by passing  -n my-app-name  to the publish command. This will also allow you to overwrite an existing app. 
                 Rather than deploying directly you can use the  --generate-dir  option to output the files that would be deployed to a directory: 
                 datasette publish heroku mydatabase.db --generate-dir=/tmp/deploy-this-to-heroku 
                 See  datasette publish heroku  for the full list of options for this command.","[""Publishing data"", ""datasette publish""]","[{""href"": ""https://www.heroku.com/"", ""label"": ""Heroku""}, {""href"": ""https://devcenter.heroku.com/articles/heroku-cli"", ""label"": ""Heroku CLI tool""}]"