kopia lustrzana https://github.com/simonw/datasette
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README.md
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README.md
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@ -12,9 +12,9 @@ Datasette is a tool for exploring and publishing data. It helps people take data
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Datasette is aimed at data journalists, museum curators, archivists, local governments and anyone else who has data that they wish to share with the world.
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Datasette is aimed at data journalists, museum curators, archivists, local governments and anyone else who has data that they wish to share with the world.
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[Explore a demo](https://fivethirtyeight.datasettes.com/fivethirtyeight), watch [a video about the project](https://simonwillison.net/2018/Oct/25/how-instantly-publish-data-internet-datasette/) or try it out by [uploading and publishing your own CSV data](https://simonwillison.net/2019/Apr/23/datasette-glitch/).
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[Explore a demo](https://fivethirtyeight.datasettes.com/fivethirtyeight), watch [a video about the project](https://www.youtube.com/watch?v=pTr1uLQTJNE) or try it out by [uploading and publishing your own CSV data](https://simonwillison.net/2019/Apr/23/datasette-glitch/).
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* Documentation: http://datasette.readthedocs.io/
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* Comprehensive documentation: http://datasette.readthedocs.io/
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* Examples: https://github.com/simonw/datasette/wiki/Datasettes
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* Examples: https://github.com/simonw/datasette/wiki/Datasettes
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* Live demo of current master: https://latest.datasette.io/
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* Live demo of current master: https://latest.datasette.io/
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@ -54,7 +54,7 @@ sqlite-utils: a Python library and CLI tool for building SQLite databases](https
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pip3 install datasette
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pip3 install datasette
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Datasette requires Python 3.5 or higher.
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Datasette requires Python 3.5 or higher. We also have [detailed installation instructions](https://datasette.readthedocs.io/en/stable/installation.html) covering other options such as Docker.
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## Basic usage
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## Basic usage
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@ -72,76 +72,32 @@ Now visiting http://localhost:8001/History/downloads will show you a web interfa
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![Downloads table rendered by datasette](https://static.simonwillison.net/static/2017/datasette-downloads.png)
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![Downloads table rendered by datasette](https://static.simonwillison.net/static/2017/datasette-downloads.png)
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http://localhost:8001/History/downloads.json will return that data as JSON:
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{
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"database": "History",
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"columns": [
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"id",
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"current_path",
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"target_path",
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"start_time",
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"received_bytes",
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"total_bytes",
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...
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],
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"rows": [
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[
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1,
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"/Users/simonw/Downloads/DropboxInstaller.dmg",
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"/Users/simonw/Downloads/DropboxInstaller.dmg",
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13097290269022132,
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626688,
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0,
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...
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]
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]
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}
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http://localhost:8001/History/downloads.json?_shape=objects will return that data as JSON in a more convenient but less efficient format:
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{
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...
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"rows": [
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{
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"start_time": 13097290269022132,
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"interrupt_reason": 0,
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"hash": "",
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"id": 1,
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"site_url": "",
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"referrer": "https://www.dropbox.com/downloading?src=index",
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...
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}
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]
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}
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## datasette serve options
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## datasette serve options
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$ datasette serve --help
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$ datasette serve --help
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Usage: datasette serve [OPTIONS] [FILES]...
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Usage: datasette serve [OPTIONS] [FILES]...
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Serve up specified SQLite database files with a web UI
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Serve up specified SQLite database files with a web UI
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Options:
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Options:
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-i, --immutable PATH Database files to open in immutable mode
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-h, --host TEXT host for server, defaults to 127.0.0.1
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-h, --host TEXT host for server, defaults to 127.0.0.1
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-p, --port INTEGER port for server, defaults to 8001
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-p, --port INTEGER port for server, defaults to 8001
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--debug Enable debug mode - useful for development
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--debug Enable debug mode - useful for development
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--reload Automatically reload if code change detected -
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--reload Automatically reload if database or code change detected -
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useful for development
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useful for development
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--cors Enable CORS by serving Access-Control-Allow-
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--cors Enable CORS by serving Access-Control-Allow-Origin: *
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Origin: *
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--load-extension PATH Path to a SQLite extension to load
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--load-extension PATH Path to a SQLite extension to load
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--inspect-file TEXT Path to JSON file created using "datasette
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--inspect-file TEXT Path to JSON file created using "datasette inspect"
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inspect"
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-m, --metadata FILENAME Path to JSON file containing license/source metadata
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-m, --metadata FILENAME Path to JSON file containing license/source
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metadata
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--template-dir DIRECTORY Path to directory containing custom templates
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--template-dir DIRECTORY Path to directory containing custom templates
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--plugins-dir DIRECTORY Path to directory containing custom plugins
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--plugins-dir DIRECTORY Path to directory containing custom plugins
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--static STATIC MOUNT mountpoint:path-to-directory for serving static
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--static STATIC MOUNT mountpoint:path-to-directory for serving static files
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files
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--memory Make :memory: database available
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--config CONFIG Set config option using configname:value
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--config CONFIG Set config option using configname:value
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datasette.readthedocs.io/en/latest/config.html
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datasette.readthedocs.io/en/latest/config.html
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--version-note TEXT Additional note to show on /-/versions
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--help-config Show available config options
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--help-config Show available config options
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--help Show this message and exit.
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--help Show this message and exit.
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@ -157,118 +113,22 @@ If you want to include licensing and source information in the generated dataset
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"source_url": "https://github.com/fivethirtyeight/data"
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"source_url": "https://github.com/fivethirtyeight/data"
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}
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}
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Save this in `metadata.json` and run Datasette like so:
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datasette serve fivethirtyeight.db -m metadata.json
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The license and source information will be displayed on the index page and in the footer. They will also be included in the JSON produced by the API.
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The license and source information will be displayed on the index page and in the footer. They will also be included in the JSON produced by the API.
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## datasette publish
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## datasette publish
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If you have [Zeit Now](https://zeit.co/now) or [Heroku](https://heroku.com/) configured, datasette can deploy one or more SQLite databases to the internet with a single command:
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If you have [Heroku](https://heroku.com/), [Google Cloud Run](https://cloud.google.com/run/) or [Zeit Now v1](https://zeit.co/now) configured, Datasette can deploy one or more SQLite databases to the internet with a single command:
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datasette publish now database.db
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Or:
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datasette publish heroku database.db
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datasette publish heroku database.db
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This will create a docker image containing both the datasette application and the specified SQLite database files. It will then deploy that image to Zeit Now or Heroku and give you a URL to access the API.
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Or:
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$ datasette publish --help
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datasette publish cloudrun database.db
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Usage: datasette publish [OPTIONS] PUBLISHER [FILES]...
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Publish specified SQLite database files to the internet along with a
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This will create a docker image containing both the datasette application and the specified SQLite database files. It will then deploy that image to Heroku or Cloud Run and give you a URL to access the resulting website and API.
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datasette API.
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Options for PUBLISHER: * 'now' - You must have Zeit Now installed:
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See [Publishing data](https://datasette.readthedocs.io/en/stable/publish.html) in the documentation for more details.
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https://zeit.co/now * 'heroku' - You must have Heroku installed:
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https://cli.heroku.com/
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Example usage: datasette publish now my-database.db
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Options:
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-n, --name TEXT Application name to use when deploying to Now
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(ignored for Heroku)
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-m, --metadata FILENAME Path to JSON file containing metadata to publish
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--extra-options TEXT Extra options to pass to datasette serve
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--force Pass --force option to now
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--branch TEXT Install datasette from a GitHub branch e.g. master
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--token TEXT Auth token to use for deploy (Now only)
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--template-dir DIRECTORY Path to directory containing custom templates
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--plugins-dir DIRECTORY Path to directory containing custom plugins
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--static STATIC MOUNT mountpoint:path-to-directory for serving static
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files
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--install TEXT Additional packages (e.g. plugins) to install
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--spatialite Enable SpatialLite extension
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--version-note TEXT Additional note to show on /-/versions
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--title TEXT Title for metadata
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--license TEXT License label for metadata
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--license_url TEXT License URL for metadata
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--source TEXT Source label for metadata
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--source_url TEXT Source URL for metadata
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--help Show this message and exit.
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## datasette package
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If you have docker installed you can use `datasette package` to create a new Docker image in your local repository containing the datasette app and selected SQLite databases:
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$ datasette package --help
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Usage: datasette package [OPTIONS] FILES...
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Package specified SQLite files into a new datasette Docker container
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Options:
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-t, --tag TEXT Name for the resulting Docker container, can
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optionally use name:tag format
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-m, --metadata FILENAME Path to JSON file containing metadata to publish
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--extra-options TEXT Extra options to pass to datasette serve
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--branch TEXT Install datasette from a GitHub branch e.g. master
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--template-dir DIRECTORY Path to directory containing custom templates
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--plugins-dir DIRECTORY Path to directory containing custom plugins
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--static STATIC MOUNT mountpoint:path-to-directory for serving static
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files
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--install TEXT Additional packages (e.g. plugins) to install
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--spatialite Enable SpatialLite extension
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--version-note TEXT Additional note to show on /-/versions
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--title TEXT Title for metadata
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--license TEXT License label for metadata
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--license_url TEXT License URL for metadata
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--source TEXT Source label for metadata
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--source_url TEXT Source URL for metadata
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--help Show this message and exit.
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Both publish and package accept an `extra_options` argument option, which will affect how the resulting application is executed. For example, say you want to increase the SQL time limit for a particular container:
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datasette package parlgov.db \
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--extra-options="--config sql_time_limit_ms:2500 --config default_page_size:10"
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The resulting container will run the application with those options.
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Here's example output for the package command:
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$ datasette package parlgov.db --extra-options="--config sql_time_limit_ms:2500"
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Sending build context to Docker daemon 4.459MB
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Step 1/7 : FROM python:3
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---> 79e1dc9af1c1
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Step 2/7 : COPY . /app
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---> Using cache
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---> cd4ec67de656
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Step 3/7 : WORKDIR /app
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---> Using cache
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---> 139699e91621
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Step 4/7 : RUN pip install datasette
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---> Using cache
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---> 340efa82bfd7
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Step 5/7 : RUN datasette inspect parlgov.db --inspect-file inspect-data.json
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---> Using cache
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---> 5fddbe990314
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Step 6/7 : EXPOSE 8001
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---> Using cache
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---> 8e83844b0fed
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Step 7/7 : CMD datasette serve parlgov.db --port 8001 --inspect-file inspect-data.json --config sql_time_limit_ms:2500
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---> Using cache
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---> 1bd380ea8af3
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Successfully built 1bd380ea8af3
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You can now run the resulting container like so:
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docker run -p 8081:8001 1bd380ea8af3
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This exposes port 8001 inside the container as port 8081 on your host machine, so you can access the application at http://localhost:8081/
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