{"id": "authentication:authentication", "page": "authentication", "ref": "authentication", "title": "Authentication and permissions", "content": "Datasette doesn't require authentication by default. Any visitor to a Datasette instance can explore the full data and execute read-only SQL queries. \n         Datasette's plugin system can be used to add many different styles of authentication, such as user accounts, single sign-on or API keys.", "breadcrumbs": "[]", "references": "[]"}
{"id": "binary_data:binary", "page": "binary_data", "ref": "binary", "title": "Binary data", "content": "SQLite tables can contain binary data in  BLOB  columns. \n         Datasette includes special handling for these binary values. The Datasette interface detects binary values and provides a link to download their content, for example on  https://latest.datasette.io/fixtures/binary_data \n         \n         Binary data is represented in  .json  exports using Base64 encoding. \n         https://latest.datasette.io/fixtures/binary_data.json?_shape=array \n         [\n    {\n        \"rowid\": 1,\n        \"data\": {\n            \"$base64\": true,\n            \"encoded\": \"FRwCx60F/g==\"\n        }\n    },\n    {\n        \"rowid\": 2,\n        \"data\": {\n            \"$base64\": true,\n            \"encoded\": \"FRwDx60F/g==\"\n        }\n    },\n    {\n        \"rowid\": 3,\n        \"data\": null\n    }\n]", "breadcrumbs": "[]", "references": "[{\"href\": \"https://latest.datasette.io/fixtures/binary_data\", \"label\": \"https://latest.datasette.io/fixtures/binary_data\"}, {\"href\": \"https://latest.datasette.io/fixtures/binary_data.json?_shape=array\", \"label\": \"https://latest.datasette.io/fixtures/binary_data.json?_shape=array\"}]"}
{"id": "changelog:id1", "page": "changelog", "ref": "id1", "title": "Changelog", "content": "", "breadcrumbs": "[]", "references": "[]"}
{"id": "cli-reference:id1", "page": "cli-reference", "ref": "id1", "title": "CLI reference", "content": "The  datasette  CLI tool provides a number of commands. \n         Running  datasette  without specifying a command runs the default command,  datasette serve .  See  datasette serve  for the full list of options for that command. \n         [[[cog\nfrom datasette import cli\nfrom click.testing import CliRunner\nimport textwrap\ndef help(args):\n    title = \"datasette \" + \" \".join(args)\n    cog.out(\"\\n::\\n\\n\")\n    result = CliRunner().invoke(cli.cli, args)\n    output = result.output.replace(\"Usage: cli \", \"Usage: datasette \")\n    cog.out(textwrap.indent(output, '    '))\n    cog.out(\"\\n\\n\") \n         ]]] \n         [[[end]]]", "breadcrumbs": "[]", "references": "[]"}
{"id": "configuration:id1", "page": "configuration", "ref": "id1", "title": "Configuration", "content": "Datasette offers several ways to configure your Datasette instances: server settings, plugin configuration, authentication, and more. \n         Most configuration can be handled using a  datasette.yaml  configuration file, passed to datasette using the  -c/--config  flag: \n         datasette mydatabase.db --config datasette.yaml \n         This file can also use JSON, as  datasette.json . YAML is recommended over JSON due to its support for comments and multi-line strings.", "breadcrumbs": "[]", "references": "[]"}
{"id": "contributing:id1", "page": "contributing", "ref": "id1", "title": "Contributing", "content": "Datasette is an open source project. We welcome contributions! \n         This document describes how to contribute to Datasette core. You can also contribute to the wider Datasette ecosystem by creating new  Plugins .", "breadcrumbs": "[]", "references": "[]"}
{"id": "csv_export:id1", "page": "csv_export", "ref": "id1", "title": "CSV export", "content": "Any Datasette table, view or custom SQL query can be exported as CSV. \n         To obtain the CSV representation of the table you are looking, click the \"this\n            data as CSV\" link. \n         You can also use the advanced export form for more control over the resulting\n            file, which looks like this and has the following options: \n         \n         \n             \n                 download file  - instead of displaying CSV in your browser, this forces\n                    your browser to download the CSV to your downloads directory. \n             \n             \n                 expand labels  - if your table has any foreign key references this option\n                    will cause the CSV to gain additional  COLUMN_NAME_label  columns with a\n                    label for each foreign key derived from the linked table.  In this example \n                    the  city_id  column is accompanied by a  city_id_label  column. \n             \n             \n                 stream all rows  - by default CSV files only contain the first\n                     max_returned_rows  records. This option will cause Datasette to\n                    loop through every matching record and return them as a single CSV file. \n             \n         \n         You can try that out on  https://latest.datasette.io/fixtures/facetable?_size=4", "breadcrumbs": "[]", "references": "[{\"href\": \"https://latest.datasette.io/fixtures/facetable.csv?_labels=on&_size=max\", \"label\": \"In this example\"}, {\"href\": \"https://latest.datasette.io/fixtures/facetable?_size=4\", \"label\": \"https://latest.datasette.io/fixtures/facetable?_size=4\"}]"}
{"id": "custom_templates:customization", "page": "custom_templates", "ref": "customization", "title": "Custom pages and templates", "content": "Datasette provides a number of ways of customizing the way data is displayed.", "breadcrumbs": "[]", "references": "[]"}
{"id": "deploying:deploying", "page": "deploying", "ref": "deploying", "title": "Deploying Datasette", "content": "The quickest way to deploy a Datasette instance on the internet is to use the  datasette publish  command, described in  Publishing data . This can be used to quickly deploy Datasette to a number of hosting providers including Heroku, Google Cloud Run and Vercel. \n         You can deploy Datasette to other hosting providers using the instructions on this page.", "breadcrumbs": "[]", "references": "[]"}
{"id": "ecosystem:ecosystem", "page": "ecosystem", "ref": "ecosystem", "title": "The Datasette Ecosystem", "content": "Datasette sits at the center of a growing ecosystem of open source tools aimed at making it as easy as possible to gather, analyze and publish interesting data. \n         These tools are divided into two main groups: tools for building SQLite databases (for use with Datasette) and plugins that extend Datasette's functionality. \n         The  Datasette project website  includes a directory of plugins and a directory of tools: \n         \n             \n                 Plugins directory on datasette.io \n             \n             \n                 Tools directory on datasette.io", "breadcrumbs": "[]", "references": "[{\"href\": \"https://datasette.io/\", \"label\": \"Datasette project website\"}, {\"href\": \"https://datasette.io/plugins\", \"label\": \"Plugins directory on datasette.io\"}, {\"href\": \"https://datasette.io/tools\", \"label\": \"Tools directory on datasette.io\"}]"}
{"id": "events:id1", "page": "events", "ref": "id1", "title": "Events", "content": "Datasette includes a mechanism for tracking events that occur while the software is running. This is primarily intended to be used by plugins, which can both trigger events and listen for events. \n         The core Datasette application triggers events when certain things happen. This page describes those events. \n         Plugins can listen for events using the  track_event(datasette, event)  plugin hook, which will be called with instances of the following classes - or additional classes  registered by other plugins . \n         \n         \n         \n         \n             class   datasette.events. LoginEvent actor :   dict   |   None \n             \n                 Event name:  login \n                 A user (represented by  event.actor ) has logged in. \n             \n         \n         \n         \n             class   datasette.events. LogoutEvent actor :   dict   |   None \n             \n                 Event name:  logout \n                 A user (represented by  event.actor ) has logged out. \n             \n         \n         \n         \n             class   datasette.events. CreateTokenEvent actor :   dict   |   None expires_after :   int   |   None restrict_all :   list restrict_database :   dict restrict_resource :   dict \n             \n                 Event name:  create-token \n                 A user created an API token. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     expires_after  -- Number of seconds after which this token will expire. \n                                 \n                                 \n                                     restrict_all  -- Restricted permissions for this token. \n                                 \n                                 \n                                     restrict_database  -- Restricted database permissions for this token. \n                                 \n                                 \n                                     restrict_resource  -- Restricted resource permissions for this token. \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. CreateTableEvent actor :   dict   |   None database :   str table :   str schema :   str \n             \n                 Event name:  create-table \n                 A new table has been created in the database. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the table was created. \n                                 \n                                 \n                                     table  -- The name of the table that was created \n                                 \n                                 \n                                     schema  -- The SQL schema definition for the new table. \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. DropTableEvent actor :   dict   |   None database :   str table :   str \n             \n                 Event name:  drop-table \n                 A table has been dropped from the database. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the table was dropped. \n                                 \n                                 \n                                     table  -- The name of the table that was dropped \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. AlterTableEvent actor :   dict   |   None database :   str table :   str before_schema :   str after_schema :   str \n             \n                 Event name:  alter-table \n                 A table has been altered. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the table was altered \n                                 \n                                 \n                                     table  -- The name of the table that was altered \n                                 \n                                 \n                                     before_schema  -- The table's SQL schema before the alteration \n                                 \n                                 \n                                     after_schema  -- The table's SQL schema after the alteration \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. InsertRowsEvent actor :   dict   |   None database :   str table :   str num_rows :   int ignore :   bool replace :   bool \n             \n                 Event name:  insert-rows \n                 Rows were inserted into a table. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the rows were inserted. \n                                 \n                                 \n                                     table  -- The name of the table where the rows were inserted. \n                                 \n                                 \n                                     num_rows  -- The number of rows that were requested to be inserted. \n                                 \n                                 \n                                     ignore  -- Was ignore set? \n                                 \n                                 \n                                     replace  -- Was replace set? \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. UpsertRowsEvent actor :   dict   |   None database :   str table :   str num_rows :   int \n             \n                 Event name:  upsert-rows \n                 Rows were upserted into a table. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the rows were inserted. \n                                 \n                                 \n                                     table  -- The name of the table where the rows were inserted. \n                                 \n                                 \n                                     num_rows  -- The number of rows that were requested to be inserted. \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. UpdateRowEvent actor :   dict   |   None database :   str table :   str pks :   list \n             \n                 Event name:  update-row \n                 A row was updated in a table. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the row was updated. \n                                 \n                                 \n                                     table  -- The name of the table where the row was updated. \n                                 \n                                 \n                                     pks  -- The primary key values of the updated row. \n                                 \n                             \n                         \n                     \n                 \n             \n         \n         \n         \n             class   datasette.events. DeleteRowEvent actor :   dict   |   None database :   str table :   str pks :   list \n             \n                 Event name:  delete-row \n                 A row was deleted from a table. \n                 \n                     \n                         Variables \n                         \n                             \n                                 \n                                     database  -- The name of the database where the row was deleted. \n                                 \n                                 \n                                     table  -- The name of the table where the row was deleted. \n                                 \n                                 \n                                     pks  -- The primary key values of the deleted row.", "breadcrumbs": "[]", "references": "[]"}
{"id": "facets:id1", "page": "facets", "ref": "id1", "title": "Facets", "content": "Datasette facets can be used to add a faceted browse interface to any database table.\n            With facets, tables are displayed along with a summary showing the most common values in specified columns.\n            These values can be selected to further filter the table. \n         Here's  an example : \n         \n         Facets can be specified in two ways: using query string parameters, or in  metadata.json  configuration for the table.", "breadcrumbs": "[]", "references": "[{\"href\": \"https://congress-legislators.datasettes.com/legislators/legislator_terms?_facet=type&_facet=party&_facet=state&_facet_size=10\", \"label\": \"an example\"}]"}
{"id": "full_text_search:id1", "page": "full_text_search", "ref": "id1", "title": "Full-text search", "content": "SQLite includes  a powerful mechanism for enabling full-text search  against SQLite records. Datasette can detect if a table has had full-text search configured for it in the underlying database and display a search interface for filtering that table. \n         Here's  an example search : \n         \n         Datasette automatically detects which tables have been configured for full-text search.", "breadcrumbs": "[]", "references": "[{\"href\": \"https://www.sqlite.org/fts3.html\", \"label\": \"a powerful mechanism for enabling full-text search\"}, {\"href\": \"https://register-of-members-interests.datasettes.com/regmem/items?_search=hamper&_sort_desc=date\", \"label\": \"an example search\"}]"}
{"id": "getting_started:getting-started", "page": "getting_started", "ref": "getting-started", "title": "Getting started", "content": "", "breadcrumbs": "[]", "references": "[]"}
{"id": "index:datasette", "page": "index", "ref": "datasette", "title": "Datasette", "content": "An open source multi-tool for exploring and publishing data \n         Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API. \n         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. It is part of a  wider ecosystem of tools and plugins  dedicated to making working with structured data as productive as possible. \n         Explore a demo , watch  a presentation about the project  or  Try Datasette without installing anything using Glitch . \n         Interested in learning Datasette? Start with  the official tutorials . \n         Support questions, feedback? Join the  Datasette Discord .", "breadcrumbs": "[]", "references": "[{\"href\": \"https://pypi.org/project/datasette/\", \"label\": null}, {\"href\": \"https://docs.datasette.io/en/stable/changelog.html\", \"label\": null}, {\"href\": \"https://pypi.org/project/datasette/\", \"label\": null}, {\"href\": \"https://github.com/simonw/datasette/actions?query=workflow%3ATest\", \"label\": null}, {\"href\": \"https://github.com/simonw/datasette/blob/main/LICENSE\", \"label\": null}, {\"href\": \"https://hub.docker.com/r/datasetteproject/datasette\", \"label\": null}, {\"href\": \"https://datasette.io/discord\", \"label\": null}, {\"href\": \"https://pypi.org/project/datasette/\", \"label\": null}, {\"href\": \"https://docs.datasette.io/en/stable/changelog.html\", \"label\": null}, {\"href\": \"https://pypi.org/project/datasette/\", \"label\": null}, {\"href\": \"https://github.com/simonw/datasette/actions?query=workflow%3ATest\", \"label\": null}, {\"href\": \"https://github.com/simonw/datasette/blob/main/LICENSE\", \"label\": null}, {\"href\": \"https://hub.docker.com/r/datasetteproject/datasette\", \"label\": null}, {\"href\": \"https://datasette.io/discord\", \"label\": null}, {\"href\": \"https://fivethirtyeight.datasettes.com/fivethirtyeight\", \"label\": \"Explore a demo\"}, {\"href\": \"https://static.simonwillison.net/static/2018/pybay-datasette/\", \"label\": \"a presentation about the project\"}, {\"href\": \"https://datasette.io/tutorials\", \"label\": \"the official tutorials\"}, {\"href\": \"https://datasette.io/discord\", \"label\": \"Datasette Discord\"}]"}
{"id": "installation:id1", "page": "installation", "ref": "id1", "title": "Installation", "content": "If you just want to try Datasette out you don't need to install anything: see  Try Datasette without installing anything using Glitch \n         \n         There are two main options for installing Datasette. You can install it directly on to your machine, or you can install it using Docker. \n         If you want to start making contributions to the Datasette project by installing a copy that lets you directly modify the code, take a look at our guide to  Setting up a development environment . \n         \n             \n                 \n                     Basic installation \n                     \n                         \n                             Datasette Desktop for Mac \n                         \n                         \n                             Using Homebrew \n                         \n                         \n                             Using pip \n                         \n                     \n                 \n                 \n                     Advanced installation options \n                     \n                         \n                             Using pipx \n                             \n                                 \n                                     Installing plugins using pipx \n                                 \n                                 \n                                     Upgrading packages using pipx \n                                 \n                             \n                         \n                         \n                             Using Docker \n                             \n                                 \n                                     Loading SpatiaLite \n                                 \n                                 \n                                     Installing plugins \n                                 \n                             \n                         \n                     \n                 \n                 \n                     A note about extensions", "breadcrumbs": "[]", "references": "[]"}
{"id": "internals:internals", "page": "internals", "ref": "internals", "title": "Internals for plugins", "content": "Many  Plugin hooks  are passed objects that provide access to internal Datasette functionality. The interface to these objects should not be considered stable with the exception of methods that are documented here.", "breadcrumbs": "[]", "references": "[]"}
{"id": "introspection:id1", "page": "introspection", "ref": "id1", "title": "Introspection", "content": "Datasette includes some pages and JSON API endpoints for introspecting the current instance. These can be used to understand some of the internals of Datasette and to see how a particular instance has been configured. \n         Each of these pages can be viewed in your browser. Add  .json  to the URL to get back the contents as JSON.", "breadcrumbs": "[]", "references": "[]"}
{"id": "javascript_plugins:id1", "page": "javascript_plugins", "ref": "id1", "title": "JavaScript plugins", "content": "Datasette can run custom JavaScript in several different ways: \n         \n             \n                 Datasette plugins written in Python can use the  extra_js_urls()  or  extra_body_script()  plugin hooks to inject JavaScript into a page \n             \n             \n                 Datasette instances with  custom templates  can include additional JavaScript in those templates \n             \n             \n                 The  extra_js_urls  key in  datasette.yaml   can be used to include extra JavaScript \n             \n         \n         There are no limitations on what this JavaScript can do. It is executed directly by the browser, so it can manipulate the DOM, fetch additional data and do anything else that JavaScript is capable of. \n         \n             Custom JavaScript has security implications, especially for authenticated Datasette instances where the JavaScript might run in the context of the authenticated user. It's important to carefully review any JavaScript you run in your Datasette instance.", "breadcrumbs": "[]", "references": "[]"}
{"id": "json_api:id1", "page": "json_api", "ref": "id1", "title": "JSON API", "content": "Datasette provides a JSON API for your SQLite databases. Anything you can do\n            through the Datasette user interface can also be accessed as JSON via the API. \n         To access the API for a page, either click on the  .json  link on that page or\n            edit the URL and add a  .json  extension to it.", "breadcrumbs": "[]", "references": "[]"}
{"id": "metadata:id1", "page": "metadata", "ref": "id1", "title": "Metadata", "content": "Data loves metadata. Any time you run Datasette you can optionally include a\n            YAML or JSON file with metadata about your databases and tables. Datasette will then\n            display that information in the web UI. \n         Run Datasette like this: \n         datasette database1.db database2.db --metadata metadata.yaml \n         Your  metadata.yaml  file can look something like this: \n         [[[cog\nfrom metadata_doc import metadata_example\nmetadata_example(cog, {\n    \"title\": \"Custom title for your index page\",\n    \"description\": \"Some description text can go here\",\n    \"license\": \"ODbL\",\n    \"license_url\": \"https://opendatacommons.org/licenses/odbl/\",\n    \"source\": \"Original Data Source\",\n    \"source_url\": \"http://example.com/\"\n}) \n         ]]] \n         [[[end]]] \n         Choosing YAML over JSON adds support for multi-line strings and comments. \n         The above metadata will be displayed on the index page of your Datasette-powered\n            site. The source and license information will also be included in the footer of\n            every page served by Datasette. \n         Any special HTML characters in  description  will be escaped. If you want to\n            include HTML in your description, you can use a  description_html  property\n            instead.", "breadcrumbs": "[]", "references": "[]"}
{"id": "pages:pages", "page": "pages", "ref": "pages", "title": "Pages and API endpoints", "content": "The Datasette web application offers a number of different pages that can be accessed to explore the data in question, each of which is accompanied by an equivalent JSON API.", "breadcrumbs": "[]", "references": "[]"}
{"id": "performance:performance", "page": "performance", "ref": "performance", "title": "Performance and caching", "content": "Datasette runs on top of SQLite, and SQLite has excellent performance.  For small databases almost any query should return in just a few milliseconds, and larger databases (100s of MBs or even GBs of data) should perform extremely well provided your queries make sensible use of database indexes. \n         That said, there are a number of tricks you can use to improve Datasette's performance.", "breadcrumbs": "[]", "references": "[]"}
{"id": "plugin_hooks:id1", "page": "plugin_hooks", "ref": "id1", "title": "Plugin hooks", "content": "Datasette  plugins  use  plugin hooks  to customize Datasette's behavior. These hooks are powered by the  pluggy  plugin system. \n         Each plugin can implement one or more hooks using the  @hookimpl  decorator against a function named that matches one of the hooks documented on this page. \n         When you implement a plugin hook you can accept any or all of the parameters that are documented as being passed to that hook. \n         For example, you can implement the  render_cell  plugin hook like this even though the full documented hook signature is  render_cell(row, value, column, table, database, datasette) : \n         @hookimpl\ndef render_cell(value, column):\n    if column == \"stars\":\n        return \"*\" * int(value) \n         \n             List of plugin hooks \n             \n                 \n                     prepare_connection(conn, database, datasette) \n                 \n                 \n                     prepare_jinja2_environment(env, datasette) \n                 \n                 \n                     Page extras \n                     \n                         \n                             extra_template_vars(template, database, table, columns, view_name, request, datasette) \n                         \n                         \n                             extra_css_urls(template, database, table, columns, view_name, request, datasette) \n                         \n                         \n                             extra_js_urls(template, database, table, columns, view_name, request, datasette) \n                         \n                         \n                             extra_body_script(template, database, table, columns, view_name, request, datasette) \n                         \n                     \n                 \n                 \n                     publish_subcommand(publish) \n                 \n                 \n                     render_cell(row, value, column, table, database, datasette, request) \n                 \n                 \n                     register_output_renderer(datasette) \n                 \n                 \n                     register_routes(datasette) \n                 \n                 \n                     register_commands(cli) \n                 \n                 \n                     register_facet_classes() \n                 \n                 \n                     register_permissions(datasette) \n                 \n                 \n                     asgi_wrapper(datasette) \n                 \n                 \n                     startup(datasette) \n                 \n                 \n                     canned_queries(datasette, database, actor) \n                 \n                 \n                     actor_from_request(datasette, request) \n                 \n                 \n                     actors_from_ids(datasette, actor_ids) \n                 \n                 \n                     jinja2_environment_from_request(datasette, request, env) \n                 \n                 \n                     filters_from_request(request, database, table, datasette) \n                 \n                 \n                     permission_allowed(datasette, actor, action, resource) \n                 \n                 \n                     register_magic_parameters(datasette) \n                 \n                 \n                     forbidden(datasette, request, message) \n                 \n                 \n                     handle_exception(datasette, request, exception) \n                 \n                 \n                     skip_csrf(datasette, scope) \n                 \n                 \n                     get_metadata(datasette, key, database, table) \n                 \n                 \n                     menu_links(datasette, actor, request) \n                 \n                 \n                     Action hooks \n                     \n                         \n                             table_actions(datasette, actor, database, table, request) \n                         \n                         \n                             view_actions(datasette, actor, database, view, request) \n                         \n                         \n                             query_actions(datasette, actor, database, query_name, request, sql, params) \n                         \n                         \n                             row_actions(datasette, actor, request, database, table, row) \n                         \n                         \n                             database_actions(datasette, actor, database, request) \n                         \n                         \n                             homepage_actions(datasette, actor, request) \n                         \n                     \n                 \n                 \n                     Template slots \n                     \n                         \n                             top_homepage(datasette, request) \n                         \n                         \n                             top_database(datasette, request, database) \n                         \n                         \n                             top_table(datasette, request, database, table) \n                         \n                         \n                             top_row(datasette, request, database, table, row) \n                         \n                         \n                             top_query(datasette, request, database, sql) \n                         \n                         \n                             top_canned_query(datasette, request, database, query_name) \n                         \n                     \n                 \n                 \n                     Event tracking \n                     \n                         \n                             track_event(datasette, event) \n                         \n                         \n                             register_events(datasette)", "breadcrumbs": "[]", "references": "[{\"href\": \"https://pluggy.readthedocs.io/\", \"label\": \"pluggy\"}]"}
{"id": "plugins:id1", "page": "plugins", "ref": "id1", "title": "Plugins", "content": "Datasette's plugin system allows additional features to be implemented as Python\n            code (or front-end JavaScript) which can be wrapped up in a separate Python\n            package. The underlying mechanism uses  pluggy . \n         See the  Datasette plugins directory  for a list of existing plugins, or take a look at the\n             datasette-plugin  topic on GitHub. \n         Things you can do with plugins include: \n         \n             \n                 Add visualizations to Datasette, for example\n                     datasette-cluster-map  and\n                     datasette-vega . \n             \n             \n                 Make new custom SQL functions available for use within Datasette, for example\n                     datasette-haversine  and\n                     datasette-jellyfish . \n             \n             \n                 Define custom output formats with custom extensions, for example  datasette-atom  and\n                     datasette-ics . \n             \n             \n                 Add template functions that can be called within your Jinja custom templates,\n                    for example  datasette-render-markdown . \n             \n             \n                 Customize how database values are rendered in the Datasette interface, for example\n                     datasette-render-binary  and\n                     datasette-pretty-json . \n             \n             \n                 Customize how Datasette's authentication and permissions systems work, for example  datasette-auth-passwords  and\n                     datasette-permissions-sql .", "breadcrumbs": "[]", "references": "[{\"href\": \"https://pluggy.readthedocs.io/\", \"label\": \"pluggy\"}, {\"href\": \"https://datasette.io/plugins\", \"label\": \"Datasette plugins directory\"}, {\"href\": \"https://github.com/topics/datasette-plugin\", \"label\": \"datasette-plugin\"}, {\"href\": \"https://github.com/simonw/datasette-cluster-map\", \"label\": \"datasette-cluster-map\"}, {\"href\": \"https://github.com/simonw/datasette-vega\", \"label\": \"datasette-vega\"}, {\"href\": \"https://github.com/simonw/datasette-haversine\", \"label\": \"datasette-haversine\"}, {\"href\": \"https://github.com/simonw/datasette-jellyfish\", \"label\": \"datasette-jellyfish\"}, {\"href\": \"https://github.com/simonw/datasette-atom\", \"label\": \"datasette-atom\"}, {\"href\": \"https://github.com/simonw/datasette-ics\", \"label\": \"datasette-ics\"}, {\"href\": \"https://github.com/simonw/datasette-render-markdown#markdown-in-templates\", \"label\": \"datasette-render-markdown\"}, {\"href\": \"https://github.com/simonw/datasette-render-binary\", \"label\": \"datasette-render-binary\"}, {\"href\": \"https://github.com/simonw/datasette-pretty-json\", \"label\": \"datasette-pretty-json\"}, {\"href\": \"https://github.com/simonw/datasette-auth-passwords\", \"label\": \"datasette-auth-passwords\"}, {\"href\": \"https://github.com/simonw/datasette-permissions-sql\", \"label\": \"datasette-permissions-sql\"}]"}
{"id": "publish:publishing", "page": "publish", "ref": "publishing", "title": "Publishing data", "content": "Datasette includes tools for publishing and deploying your data to the internet. The  datasette publish  command will deploy a new Datasette instance containing your databases directly to a Heroku or Google Cloud hosting account. You can also use  datasette package  to create a Docker image that bundles your databases together with the datasette application that is used to serve them.", "breadcrumbs": "[]", "references": "[]"}
{"id": "settings:id1", "page": "settings", "ref": "id1", "title": "Settings", "content": "", "breadcrumbs": "[]", "references": "[]"}
{"id": "spatialite:id1", "page": "spatialite", "ref": "id1", "title": "SpatiaLite", "content": "The  SpatiaLite module  for SQLite adds features for handling geographic and spatial data. For an example of what you can do with it, see the tutorial  Building a location to time zone API with SpatiaLite . \n         To use it with Datasette, you need to install the  mod_spatialite  dynamic library. This can then be loaded into Datasette using the  --load-extension  command-line option. \n         Datasette can look for SpatiaLite in common installation locations if you run it like this: \n         datasette --load-extension=spatialite --setting default_allow_sql off \n         If SpatiaLite is in another location, use the full path to the extension instead: \n         datasette --setting default_allow_sql off \\\n  --load-extension=/usr/local/lib/mod_spatialite.dylib", "breadcrumbs": "[]", "references": "[{\"href\": \"https://www.gaia-gis.it/fossil/libspatialite/index\", \"label\": \"SpatiaLite module\"}, {\"href\": \"https://datasette.io/tutorials/spatialite\", \"label\": \"Building a location to time zone API with SpatiaLite\"}]"}
{"id": "sql_queries:sql", "page": "sql_queries", "ref": "sql", "title": "Running SQL queries", "content": "Datasette treats SQLite database files as read-only and immutable. This means it is not possible to execute INSERT or UPDATE statements using Datasette, which allows us to expose SELECT statements to the outside world without needing to worry about SQL injection attacks. \n         The easiest way to execute custom SQL against Datasette is through the web UI. The database index page includes a SQL editor that lets you run any SELECT query you like. You can also construct queries using the filter interface on the tables page, then click \"View and edit SQL\" to open that query in the custom SQL editor. \n         Note that this interface is only available if the  execute-sql  permission is allowed. See  Controlling the ability to execute arbitrary SQL . \n         Any Datasette SQL query is reflected in the URL of the page, allowing you to bookmark them, share them with others and navigate through previous queries using your browser back button. \n         You can also retrieve the results of any query as JSON by adding  .json  to the base URL.", "breadcrumbs": "[]", "references": "[]"}
{"id": "testing_plugins:id1", "page": "testing_plugins", "ref": "id1", "title": "Testing plugins", "content": "We recommend using  pytest  to write automated tests for your plugins. \n         If you use the template described in  Starting an installable plugin using cookiecutter  your plugin will start with a single test in your  tests/  directory that looks like this: \n         from datasette.app import Datasette\nimport pytest\n\n\n@pytest.mark.asyncio\nasync def test_plugin_is_installed():\n    datasette = Datasette(memory=True)\n    response = await datasette.client.get(\"/-/plugins.json\")\n    assert response.status_code == 200\n    installed_plugins = {p[\"name\"] for p in response.json()}\n    assert (\n        \"datasette-plugin-template-demo\"\n        in installed_plugins\n    ) \n         This test uses the  datasette.client  object to exercise a test instance of Datasette.  datasette.client  is a wrapper around the  HTTPX  Python library which can imitate HTTP requests using ASGI. This is the recommended way to write tests against a Datasette instance. \n         This test also uses the  pytest-asyncio  package to add support for  async def  test functions running under pytest. \n         You can install these packages like so: \n         pip install pytest pytest-asyncio \n         If you are building an installable package you can add them as test dependencies to your  setup.py  module like this: \n         setup(\n    name=\"datasette-my-plugin\",\n    # ...\n    extras_require={\"test\": [\"pytest\", \"pytest-asyncio\"]},\n    tests_require=[\"datasette-my-plugin[test]\"],\n) \n         You can then install the test dependencies like so: \n         pip install -e '.[test]' \n         Then run the tests using pytest like so: \n         pytest", "breadcrumbs": "[]", "references": "[{\"href\": \"https://docs.pytest.org/\", \"label\": \"pytest\"}, {\"href\": \"https://www.python-httpx.org/\", \"label\": \"HTTPX\"}, {\"href\": \"https://pypi.org/project/pytest-asyncio/\", \"label\": \"pytest-asyncio\"}]"}
{"id": "writing_plugins:id1", "page": "writing_plugins", "ref": "id1", "title": "Writing plugins", "content": "You can write one-off plugins that apply to just one Datasette instance, or you can write plugins which can be installed using  pip  and can be shipped to the Python Package Index ( PyPI ) for other people to install. \n         Want to start by looking at an example? The  Datasette plugins directory  lists more than 90 open source plugins with code you can explore. The  plugin hooks  page includes links to example plugins for each of the documented hooks.", "breadcrumbs": "[]", "references": "[{\"href\": \"https://pypi.org/\", \"label\": \"PyPI\"}, {\"href\": \"https://datasette.io/plugins\", \"label\": \"Datasette plugins directory\"}]"}