rowid,title,content,sections_fts,rank 582,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.",674, 581,Custom metadata and plugins,"datasette publish accepts a number of additional options which can be used to further customize your Datasette instance. You can define your own Metadata and deploy that with your instance like so: datasette publish cloudrun --service=my-service mydatabase.db -m metadata.json If you just want to set the title, license or source information you can do that directly using extra options to datasette publish : datasette publish cloudrun mydatabase.db --service=my-service \ --title=""Title of my database"" \ --source=""Where the data originated"" \ --source_url=""http://www.example.com/"" You can also specify plugins you would like to install. For example, if you want to include the datasette-vega visualization plugin you can use the following: datasette publish cloudrun mydatabase.db --service=my-service --install=datasette-vega If a plugin has any Secret configuration values you can use the --plugin-secret option to set those secrets at publish time. For example, using Heroku with datasette-auth-github you might run the following command: datasette publish heroku my_database.db \ --name my-heroku-app-demo \ --install=datasette-auth-github \ --plugin-secret datasette-auth-github client_id your_client_id \ --plugin-secret datasette-auth-github client_secret your_client_secret",674, 580,Publishing to Fly,"Fly is a competitively priced Docker-compatible hosting platform that supports running applications in globally distributed data centers close to your end users. You can deploy Datasette instances to Fly using the datasette-publish-fly plugin. pip install datasette-publish-fly datasette publish fly mydatabase.db --app=""my-app"" Consult the datasette-publish-fly README for more details.",674, 579,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.",674, 578,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.",674, 577,Publishing to Google Cloud Run,"Google Cloud Run allows you to publish data in a scale-to-zero environment, so your application will start running when the first request is received and will shut down again when traffic ceases. This means you only pay for time spent serving traffic. Cloud Run is a great option for inexpensively hosting small, low traffic projects - but costs can add up for projects that serve a lot of requests. Be particularly careful if your project has tables with large numbers of rows. Search engine crawlers that index a page for every row could result in a high bill. The datasette-block-robots plugin can be used to request search engine crawlers omit crawling your site, which can help avoid this issue. You will first need to install and configure the Google Cloud CLI tools by following these instructions . You can then publish one or more SQLite database files to Google Cloud Run using the following command: datasette publish cloudrun mydatabase.db --service=my-database A Cloud Run service is a single hosted application. The service name you specify will be used as part of the Cloud Run URL. If you deploy to a service name that you have used in the past your new deployment will replace the previous one. If you omit the --service option you will be asked to pick a service name interactively during the deploy. You may need to interact with prompts from the tool. Many of the prompts ask for values that can be set as properties for the Google Cloud SDK if you want to avoid the prompts. For example, the default region for the deployed instance can be set using the command: gcloud config set run/region us-central1 You should replace us-central1 with your desired region . Alternately, you can specify the region by setting the CLOUDSDK_RUN_REGION environment variable. Once it has finished it will output a URL like this one: Service [my-service] revision [my-service-00001] has been deployed and is serving traffic at https://my-service-j7hipcg4aq-uc.a.run.app Cloud Run provides a URL on the .run.app domain, but you can also point your own domain or subdomain at your Cloud Run service - see mapping custom domains in the Cloud Run documentation for details. See datasette publish cloudrun for the full list of options for this command.",674, 576,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.",674, 575,Publishing data,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.,674, 574,/-/messages,"The debug tool at /-/messages can be used to set flash messages to try out that feature. See .add_message(request, message, type=datasette.INFO) for details of this feature.",674, 573,/-/actor,"Shows the currently authenticated actor. Useful for debugging Datasette authentication plugins. { ""actor"": { ""id"": 1, ""username"": ""some-user"" } }",674, 572,/-/threads,"Shows details of threads and asyncio tasks. Threads example : { ""num_threads"": 2, ""threads"": [ { ""daemon"": false, ""ident"": 4759197120, ""name"": ""MainThread"" }, { ""daemon"": true, ""ident"": 123145319682048, ""name"": ""Thread-1"" }, ], ""num_tasks"": 3, ""tasks"": [ "" cb=[set.discard()]>"", "" wait_for=()]> cb=[run_until_complete..()]>"", "" wait_for=()]>>"" ] }",674, 571,/-/databases,"Shows currently attached databases. Databases example : [ { ""hash"": null, ""is_memory"": false, ""is_mutable"": true, ""name"": ""fixtures"", ""path"": ""fixtures.db"", ""size"": 225280 } ]",674, 570,/-/config,"Shows the configuration for this instance of Datasette. This is generally the contents of the datasette.yaml or datasette.json file, which can include plugin configuration as well. Config example : { ""settings"": { ""template_debug"": true, ""trace_debug"": true, ""force_https_urls"": true } } Any keys that include the one of the following substrings in their names will be returned as redacted *** output, to help avoid accidentally leaking private configuration information: secret , key , password , token , hash , dsn .",674, 569,/-/settings,"Shows the Settings for this instance of Datasette. Settings example : { ""default_facet_size"": 30, ""default_page_size"": 100, ""facet_suggest_time_limit_ms"": 50, ""facet_time_limit_ms"": 1000, ""max_returned_rows"": 1000, ""sql_time_limit_ms"": 1000 }",674, 568,/-/plugins,"Shows a list of currently installed plugins and their versions. Plugins example : [ { ""name"": ""datasette_cluster_map"", ""static"": true, ""templates"": false, ""version"": ""0.10"", ""hooks"": [""extra_css_urls"", ""extra_js_urls"", ""extra_body_script""] } ] Add ?all=1 to include details of the default plugins baked into Datasette.",674, 567,/-/versions,"Shows the version of Datasette, Python and SQLite. Versions example : { ""datasette"": { ""version"": ""0.60"" }, ""python"": { ""full"": ""3.8.12 (default, Dec 21 2021, 10:45:09) \n[GCC 10.2.1 20210110]"", ""version"": ""3.8.12"" }, ""sqlite"": { ""extensions"": { ""json1"": null }, ""fts_versions"": [ ""FTS5"", ""FTS4"", ""FTS3"" ], ""compile_options"": [ ""COMPILER=gcc-6.3.0 20170516"", ""ENABLE_FTS3"", ""ENABLE_FTS4"", ""ENABLE_FTS5"", ""ENABLE_JSON1"", ""ENABLE_RTREE"", ""THREADSAFE=1"" ], ""version"": ""3.37.0"" } }",674, 566,/-/metadata,"Shows the contents of the metadata.json file that was passed to datasette serve , if any. Metadata example : { ""license"": ""CC Attribution 4.0 License"", ""license_url"": ""http://creativecommons.org/licenses/by/4.0/"", ""source"": ""fivethirtyeight/data on GitHub"", ""source_url"": ""https://github.com/fivethirtyeight/data"", ""title"": ""Five Thirty Eight"", ""databases"": { } }",674, 565,Introspection,"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. Each of these pages can be viewed in your browser. Add .json to the URL to get back the contents as JSON.",674, 564,Contents,"Getting started Play with a live demo Follow a tutorial Datasette in your browser with Datasette Lite Try Datasette without installing anything using Glitch Using Datasette on your own computer Installation Basic installation Datasette Desktop for Mac Using Homebrew Using pip Advanced installation options Using pipx Using Docker A note about extensions Configuration Configuration via the command-line datasette.yaml reference Settings Plugin configuration Permissions configuration Canned queries configuration Custom CSS and JavaScript The Datasette Ecosystem sqlite-utils Dogsheep CLI reference datasette --help datasette serve datasette --get datasette serve --help-settings datasette plugins datasette install datasette uninstall datasette publish datasette publish cloudrun datasette publish heroku datasette package datasette inspect datasette create-token Pages and API endpoints Top-level index Database Hidden tables Table Row Publishing data datasette publish Publishing to Google Cloud Run Publishing to Heroku Publishing to Vercel Publishing to Fly Custom metadata and plugins datasette package Deploying Datasette Deployment fundamentals Running Datasette using systemd Running Datasette using OpenRC Deploying using buildpacks Running Datasette behind a proxy Nginx proxy configuration Apache proxy configuration JSON API Default representation Different shapes Pagination Special JSON arguments Table arguments Column filter arguments Special table arguments Expanding foreign key references Discovering the JSON for a page Enabling CORS The JSON write API Inserting rows Upserting rows Updating a row Deleting a row Creating a table Creating a table from example data Dropping tables Running SQL queries Named parameters Views Canned queries Canned query parameters Additional canned query options Writable canned queries Magic parameters JSON API for writable canned queries Pagination Cross-database queries Authentication and permissions Actors Using the ""root"" actor Permissions How permissions are resolved Defining permissions with ""allow"" blocks The /-/allow-debug tool Access permissions in datasette.yaml Access to an instance Access to specific databases Access to specific tables and views Access to specific canned queries Controlling the ability to execute arbitrary SQL Other permissions in datasette.yaml API Tokens datasette create-token Checking permissions in plugins actor_matches_allow() The permissions debug tool The ds_actor cookie Including an expiry time The /-/logout page Built-in permissions view-instance view-database view-database-download view-table view-query insert-row delete-row update-row create-table alter-table drop-table execute-sql permissions-debug debug-menu Performance and caching Immutable mode Using ""datasette inspect"" HTTP caching datasette-hashed-urls CSV export URL parameters Streaming all records Binary data Linking to binary downloads Binary plugins Facets Facets in query strings Facets in metadata Suggested facets Speeding up facets with indexes Facet by JSON array Facet by date Full-text search The table page and table view API Advanced SQLite search queries Configuring full-text search for a table or view Searches using custom SQL Enabling full-text search for a SQLite table Configuring FTS using sqlite-utils Configuring FTS using csvs-to-sqlite Configuring FTS by hand FTS versions SpatiaLite Warning Installation Installing SpatiaLite on OS X Installing SpatiaLite on Linux Spatial indexing latitude/longitude columns Making use of a spatial index Importing shapefiles into SpatiaLite Importing GeoJSON polygons using Shapely Querying polygons using within() Metadata Per-database and per-table metadata Source, license and about Column descriptions Specifying units for a column Setting a default sort order Setting a custom page size Setting which columns can be used for sorting Specifying the label column for a table Hiding tables Metadata reference Top-level metadata Database-level metadata Table-level metadata Settings Using --setting Configuration directory mode Settings default_allow_sql default_page_size sql_time_limit_ms max_returned_rows max_insert_rows num_sql_threads allow_facet default_facet_size facet_time_limit_ms facet_suggest_time_limit_ms suggest_facets allow_download allow_signed_tokens max_signed_tokens_ttl default_cache_ttl cache_size_kb allow_csv_stream max_csv_mb truncate_cells_html force_https_urls template_debug trace_debug base_url Configuring the secret Using secrets with datasette publish Introspection /-/metadata /-/versions /-/plugins /-/settings /-/config /-/databases /-/threads /-/actor /-/messages Custom pages and templates CSS classes on the Serving static files Publishing static assets Custom templates Custom pages Path parameters for pages Custom headers and status codes Returning 404s Custom redirects Custom error pages Plugins Installing plugins One-off plugins using --plugins-dir Deploying plugins using datasette publish Controlling which plugins are loaded Seeing what plugins are installed Plugin configuration Secret configuration values Writing plugins Tracing plugin hooks Writing one-off plugins Starting an installable plugin using cookiecutter Packaging a plugin Static assets Custom templates Writing plugins that accept configuration Designing URLs for your plugin Building URLs within plugins Plugins that define new plugin hooks JavaScript plugins The datasette_init event datasetteManager JavaScript plugin objects makeAboveTablePanelConfigs() makeColumnActions(columnDetails) Selectors Plugin hooks prepare_connection(conn, database, datasette) prepare_jinja2_environment(env, datasette) Page extras extra_template_vars(template, database, table, columns, view_name, request, datasette) extra_css_urls(template, database, table, columns, view_name, request, datasette) extra_js_urls(template, database, table, columns, view_name, request, datasette) extra_body_script(template, database, table, columns, view_name, request, datasette) publish_subcommand(publish) render_cell(row, value, column, table, database, datasette, request) register_output_renderer(datasette) register_routes(datasette) register_commands(cli) register_facet_classes() register_permissions(datasette) asgi_wrapper(datasette) startup(datasette) canned_queries(datasette, database, actor) actor_from_request(datasette, request) actors_from_ids(datasette, actor_ids) jinja2_environment_from_request(datasette, request, env) filters_from_request(request, database, table, datasette) permission_allowed(datasette, actor, action, resource) register_magic_parameters(datasette) forbidden(datasette, request, message) handle_exception(datasette, request, exception) skip_csrf(datasette, scope) get_metadata(datasette, key, database, table) menu_links(datasette, actor, request) Action hooks table_actions(datasette, actor, database, table, request) view_actions(datasette, actor, database, view, request) query_actions(datasette, actor, database, query_name, request, sql, params) row_actions(datasette, actor, request, database, table, row) database_actions(datasette, actor, database, request) homepage_actions(datasette, actor, request) Template slots top_homepage(datasette, request) top_database(datasette, request, database) top_table(datasette, request, database, table) top_row(datasette, request, database, table, row) top_query(datasette, request, database, sql) top_canned_query(datasette, request, database, query_name) Event tracking track_event(datasette, event) register_events(datasette) Testing plugins Setting up a Datasette test instance Using datasette.client in tests Using pdb for errors thrown inside Datasette Using pytest fixtures Testing outbound HTTP calls with pytest-httpx Registering a plugin for the duration of a test Internals for plugins Request object The MultiParams class Response class Returning a response with .asgi_send(send) Setting cookies with response.set_cookie() Datasette class .databases .permissions .plugin_config(plugin_name, database=None, table=None) await .render_template(template, context=None, request=None) await .actors_from_ids(actor_ids) await .permission_allowed(actor, action, resource=None, default=...) await .ensure_permissions(actor, permissions) await .check_visibility(actor, action=None, resource=None, permissions=None) .create_token(actor_id, expires_after=None, restrict_all=None, restrict_database=None, restrict_resource=None) .get_permission(name_or_abbr) .get_database(name) .get_internal_database() .add_database(db, name=None, route=None) .add_memory_database(name) .remove_database(name) await .track_event(event) .sign(value, namespace=""default"") .unsign(value, namespace=""default"") .add_message(request, message, type=datasette.INFO) .absolute_url(request, path) .setting(key) .resolve_database(request) .resolve_table(request) .resolve_row(request) datasette.client datasette.urls Database class Database(ds, path=None, is_mutable=True, is_memory=False, memory_name=None) db.hash await db.execute(sql, ...) Results await db.execute_fn(fn) await db.execute_write(sql, params=None, block=True) await db.execute_write_script(sql, block=True) await db.execute_write_many(sql, params_seq, block=True) await db.execute_write_fn(fn, block=True, transaction=True) await db.execute_isolated_fn(fn) db.close() Database introspection CSRF protection Datasette's internal database The datasette.utils module parse_metadata(content) await_me_maybe(value) derive_named_parameters(db, sql) Tilde encoding datasette.tracer Tracing child tasks Import shortcuts Events LoginEvent LogoutEvent CreateTokenEvent CreateTableEvent DropTableEvent AlterTableEvent InsertRowsEvent UpsertRowsEvent UpdateRowEvent DeleteRowEvent Contributing General guidelines Setting up a development environment Running the tests Using fixtures Debugging Code formatting Running Black blacken-docs Prettier Editing and building the documentation Running Cog Continuously deployed demo instances Release process Alpha and beta releases Releasing bug fixes from a branch Upgrading CodeMirror Changelog 1.0a13 (2024-03-12) 1.0a12 (2024-02-29) 1.0a11 (2024-02-19) 1.0a10 (2024-02-17) 1.0a9 (2024-02-16) Alter table support for create, insert, upsert and update Permissions fix for the upsert API Permission checks now consider opinions from every plugin Other changes 1.0a8 (2024-02-07) Configuration JavaScript plugins Plugin hooks Documentation Minor fixes 0.64.6 (2023-12-22) 0.64.5 (2023-10-08) 1.0a7 (2023-09-21) 0.64.4 (2023-09-21) 1.0a6 (2023-09-07) 1.0a5 (2023-08-29) 1.0a4 (2023-08-21) 1.0a3 (2023-08-09) Smaller changes 0.64.2 (2023-03-08) 0.64.1 (2023-01-11) 0.64 (2023-01-09) 0.63.3 (2022-12-17) 1.0a2 (2022-12-14) 1.0a1 (2022-12-01) 1.0a0 (2022-11-29) Signed API tokens Write API 0.63.2 (2022-11-18) 0.63.1 (2022-11-10) 0.63 (2022-10-27) Features Plugin hooks and internals Documentation 0.62 (2022-08-14) Features Plugin hooks Bug fixes Documentation 0.61.1 (2022-03-23) 0.61 (2022-03-23) 0.60.2 (2022-02-07) 0.60.1 (2022-01-20) 0.60 (2022-01-13) Plugins and internals Faceting Other small fixes 0.59.4 (2021-11-29) 0.59.3 (2021-11-20) 0.59.2 (2021-11-13) 0.59.1 (2021-10-24) 0.59 (2021-10-14) 0.58.1 (2021-07-16) 0.58 (2021-07-14) 0.57.1 (2021-06-08) 0.57 (2021-06-05) New features Bug fixes and other improvements 0.56.1 (2021-06-05) 0.56 (2021-03-28) 0.55 (2021-02-18) 0.54.1 (2021-02-02) 0.54 (2021-01-25) The _internal database Named in-memory database support JavaScript modules Code formatting with Black and Prettier Other changes 0.53 (2020-12-10) 0.52.5 (2020-12-09) 0.52.4 (2020-12-05) 0.52.3 (2020-12-03) 0.52.2 (2020-12-02) 0.52.1 (2020-11-29) 0.52 (2020-11-28) 0.51.1 (2020-10-31) 0.51 (2020-10-31) New visual design Plugins can now add links within Datasette Binary data URL building Running Datasette behind a proxy Smaller changes 0.50.2 (2020-10-09) 0.50.1 (2020-10-09) 0.50 (2020-10-09) 0.49.1 (2020-09-15) 0.49 (2020-09-14) 0.48 (2020-08-16) 0.47.3 (2020-08-15) 0.47.2 (2020-08-12) 0.47.1 (2020-08-11) 0.47 (2020-08-11) 0.46 (2020-08-09) 0.45 (2020-07-01) Magic parameters for canned queries Log out Better plugin documentation New plugin hooks Smaller changes 0.44 (2020-06-11) Authentication Permissions Writable canned queries Flash messages Signed values and secrets CSRF protection Cookie methods register_routes() plugin hooks Smaller changes The road to Datasette 1.0 0.43 (2020-05-28) 0.42 (2020-05-08) 0.41 (2020-05-06) 0.40 (2020-04-21) 0.39 (2020-03-24) 0.38 (2020-03-08) 0.37.1 (2020-03-02) 0.37 (2020-02-25) 0.36 (2020-02-21) 0.35 (2020-02-04) 0.34 (2020-01-29) 0.33 (2019-12-22) 0.32 (2019-11-14) 0.31.2 (2019-11-13) 0.31.1 (2019-11-12) 0.31 (2019-11-11) 0.30.2 (2019-11-02) 0.30.1 (2019-10-30) 0.30 (2019-10-18) 0.29.3 (2019-09-02) 0.29.2 (2019-07-13) 0.29.1 (2019-07-11) 0.29 (2019-07-07) ASGI New plugin hook: asgi_wrapper New plugin hook: extra_template_vars Secret plugin configuration options Facet by date Easier custom templates for table rows ?_through= for joins through many-to-many tables Small changes 0.28 (2019-05-19) Supporting databases that change Faceting improvements, and faceting plugins datasette publish cloudrun register_output_renderer plugins Medium changes Small changes 0.27.1 (2019-05-09) 0.27 (2019-01-31) 0.26.1 (2019-01-10) 0.26 (2019-01-02) 0.25.2 (2018-12-16) 0.25.1 (2018-11-04) 0.25 (2018-09-19) 0.24 (2018-07-23) 0.23.2 (2018-07-07) 0.23.1 (2018-06-21) 0.23 (2018-06-18) CSV export Foreign key expansions New configuration settings Control HTTP caching with ?_ttl= Improved support for SpatiaLite latest.datasette.io Miscellaneous 0.22.1 (2018-05-23) 0.22 (2018-05-20) 0.21 (2018-05-05) 0.20 (2018-04-20) 0.19 (2018-04-16) 0.18 (2018-04-14) 0.17 (2018-04-13) 0.16 (2018-04-13) 0.15 (2018-04-09) 0.14 (2017-12-09) 0.13 (2017-11-24) 0.12 (2017-11-16) 0.11 (2017-11-14) 0.10 (2017-11-14) 0.9 (2017-11-13) 0.8 (2017-11-13)",674, 563,Datasette,"An open source multi-tool for exploring and publishing data 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. 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. Explore a demo , watch a presentation about the project or Try Datasette without installing anything using Glitch . Interested in learning Datasette? Start with the official tutorials . Support questions, feedback? Join the Datasette Discord .",674, 562,Selectors,"These are available on the selectors property of the datasetteManager object. const DOM_SELECTORS = { /** Should have one match */ jsonExportLink: "".export-links a[href*=json]"", /** Event listeners that go outside of the main table, e.g. existing scroll listener */ tableWrapper: "".table-wrapper"", table: ""table.rows-and-columns"", aboveTablePanel: "".above-table-panel"", // These could have multiple matches /** Used for selecting table headers. Use makeColumnActions if you want to add menu items. */ tableHeaders: `table.rows-and-columns th`, /** Used to add ""where"" clauses to query using direct manipulation */ filterRows: "".filter-row"", /** Used to show top available enum values for a column (""facets"") */ facetResults: "".facet-results [data-column]"", };",674, 561,makeColumnActions(columnDetails),"This method, if present, will be called when Datasette is rendering the cog action menu icons that appear at the top of the table view. By default these include options like ""Sort ascending/descending"" and ""Facet by this"", but plugins can return additional actions to be included in this menu. The method will be called with a columnDetails object with the following keys: columnName - string The name of the column columnNotNull - boolean True if the column is defined as NOT NULL columnType - string The SQLite data type of the column isPk - boolean True if the column is part of the primary key It should return a JavaScript array of objects each with a label and onClick property: label - string The human-readable label for the action onClick(evt) - function A function that will be called when the action is clicked The evt object passed to the onClick is the standard browser event object that triggered the click. This example plugin adds two menu items - one to copy the column name to the clipboard and another that displays the column metadata in an alert() window: document.addEventListener('datasette_init', function(ev) { ev.detail.registerPlugin('column-name-plugin', { version: 0.1, makeColumnActions: (columnDetails) => { return [ { label: 'Copy column to clipboard', onClick: async (evt) => { await navigator.clipboard.writeText(columnDetails.columnName) } }, { label: 'Alert column metadata', onClick: () => alert(JSON.stringify(columnDetails, null, 2)) } ]; } }); });",674, 560,makeAboveTablePanelConfigs(),"This method should return a JavaScript array of objects defining additional panels to be added to the top of the table page. Each object should have the following: id - string A unique string ID for the panel, for example map-panel label - string A human-readable label for the panel render(node) - function A function that will be called with a DOM node to render the panel into This example shows how a plugin might define a single panel: document.addEventListener('datasette_init', function(ev) { ev.detail.registerPlugin('panel-plugin', { version: 0.1, makeAboveTablePanelConfigs: () => { return [ { id: 'first-panel', label: 'First panel', render: node => { node.innerHTML = '

My custom panel

This is a custom panel that I added using a JavaScript plugin

'; } } ] } }); }); When a page with a table loads, all registered plugins that implement makeAboveTablePanelConfigs() will be called and panels they return will be added to the top of the table page.",674, 559,JavaScript plugin objects,"JavaScript plugins are blocks of code that can be registered with Datasette using the registerPlugin() method on the datasetteManager object. The implementation object passed to this method should include a version key defining the plugin version, and one or more of the following named functions providing the implementation of the plugin:",674, 558,datasetteManager,"The datasetteManager object VERSION - string The version of Datasette plugins - Map() A Map of currently loaded plugin names to plugin implementations registerPlugin(name, implementation) Call this to register a plugin, passing its name and implementation selectors - object An object providing named aliases to useful CSS selectors, listed below",674, 557,The datasette_init event,"Datasette emits a custom event called datasette_init when the page is loaded. This event is dispatched on the document object, and includes a detail object with a reference to the datasetteManager object. Your JavaScript code can listen out for this event using document.addEventListener() like this: document.addEventListener(""datasette_init"", function (evt) { const manager = evt.detail; console.log(""Datasette version:"", manager.VERSION); });",674, 556,JavaScript plugins,"Datasette can run custom JavaScript in several different ways: Datasette plugins written in Python can use the extra_js_urls() or extra_body_script() plugin hooks to inject JavaScript into a page Datasette instances with custom templates can include additional JavaScript in those templates The extra_js_urls key in datasette.yaml can be used to include extra JavaScript 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. 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.",674, 555,debug-menu,"Controls if the various debug pages are displayed in the navigation menu. Default deny .",674, 554,permissions-debug,"Actor is allowed to view the /-/permissions debug page. Default deny .",674, 553,execute-sql,"Actor is allowed to run arbitrary SQL queries against a specific database, e.g. https://latest.datasette.io/fixtures?sql=select+100 resource - string The name of the database Default allow . See also the default_allow_sql setting .",674, 552,drop-table,"Actor is allowed to drop a database table. resource - tuple: (string, string) The name of the database, then the name of the table Default deny .",674, 551,alter-table,"Actor is allowed to alter a database table. resource - tuple: (string, string) The name of the database, then the name of the table Default deny .",674, 550,create-table,"Actor is allowed to create a database table. resource - string The name of the database Default deny .",674, 549,update-row,"Actor is allowed to update rows in a table. resource - tuple: (string, string) The name of the database, then the name of the table Default deny .",674, 548,delete-row,"Actor is allowed to delete rows from a table. resource - tuple: (string, string) The name of the database, then the name of the table Default deny .",674, 547,insert-row,"Actor is allowed to insert rows into a table. resource - tuple: (string, string) The name of the database, then the name of the table Default deny .",674, 546,view-query,"Actor is allowed to view (and execute) a canned query page, e.g. https://latest.datasette.io/fixtures/pragma_cache_size - this includes executing Writable canned queries . resource - tuple: (string, string) The name of the database, then the name of the canned query Default allow .",674, 545,view-table,"Actor is allowed to view a table (or view) page, e.g. https://latest.datasette.io/fixtures/complex_foreign_keys resource - tuple: (string, string) The name of the database, then the name of the table Default allow .",674, 544,view-database-download,"Actor is allowed to download a database, e.g. https://latest.datasette.io/fixtures.db resource - string The name of the database Default allow .",674, 543,view-database,"Actor is allowed to view a database page, e.g. https://latest.datasette.io/fixtures resource - string The name of the database Default allow .",674, 542,view-instance,"Top level permission - Actor is allowed to view any pages within this instance, starting at https://latest.datasette.io/ Default allow .",674, 541,Built-in permissions,"This section lists all of the permission checks that are carried out by Datasette core, along with the resource if it was passed.",674, 540,The /-/logout page,The page at /-/logout provides the ability to log out of a ds_actor cookie authentication session.,674, 539,Including an expiry time,"ds_actor cookies can optionally include a signed expiry timestamp, after which the cookies will no longer be valid. Authentication plugins may chose to use this mechanism to limit the lifetime of the cookie. For example, if a plugin implements single-sign-on against another source it may decide to set short-lived cookies so that if the user is removed from the SSO system their existing Datasette cookies will stop working shortly afterwards. To include an expiry, add a ""e"" key to the cookie value containing a base62-encoded integer representing the timestamp when the cookie should expire. For example, here's how to set a cookie that expires after 24 hours: import time from datasette.utils import baseconv expires_at = int(time.time()) + (24 * 60 * 60) response = Response.redirect(""/"") response.set_cookie( ""ds_actor"", datasette.sign( { ""a"": {""id"": ""cleopaws""}, ""e"": baseconv.base62.encode(expires_at), }, ""actor"", ), ) The resulting cookie will encode data that looks something like this: { ""a"": { ""id"": ""cleopaws"" }, ""e"": ""1jjSji"" }",674, 538,The ds_actor cookie,"Datasette includes a default authentication plugin which looks for a signed ds_actor cookie containing a JSON actor dictionary. This is how the root actor mechanism works. Authentication plugins can set signed ds_actor cookies themselves like so: response = Response.redirect(""/"") response.set_cookie( ""ds_actor"", datasette.sign({""a"": {""id"": ""cleopaws""}}, ""actor""), ) Note that you need to pass ""actor"" as the namespace to .sign(value, namespace=""default"") . The shape of data encoded in the cookie is as follows: { ""a"": {... actor ...} }",674, 537,The permissions debug tool,"The debug tool at /-/permissions is only available to the authenticated root user (or any actor granted the permissions-debug action). It shows the thirty most recent permission checks that have been carried out by the Datasette instance. It also provides an interface for running hypothetical permission checks against a hypothetical actor. This is a useful way of confirming that your configured permissions work in the way you expect. This is designed to help administrators and plugin authors understand exactly how permission checks are being carried out, in order to effectively configure Datasette's permission system.",674, 536,actor_matches_allow(),"Plugins that wish to implement this same ""allow"" block permissions scheme can take advantage of the datasette.utils.actor_matches_allow(actor, allow) function: from datasette.utils import actor_matches_allow actor_matches_allow({""id"": ""root""}, {""id"": ""*""}) # returns True The currently authenticated actor is made available to plugins as request.actor .",674, 535,Checking permissions in plugins,"Datasette plugins can check if an actor has permission to perform an action using the datasette.permission_allowed(...) method. Datasette core performs a number of permission checks, documented below . Plugins can implement the permission_allowed(datasette, actor, action, resource) plugin hook to participate in decisions about whether an actor should be able to perform a specified action.",674, 534,Restricting the actions that a token can perform,"Tokens created using datasette create-token ACTOR_ID will inherit all of the permissions of the actor that they are associated with. You can pass additional options to create tokens that are restricted to a subset of that actor's permissions. To restrict the token to just specific permissions against all available databases, use the --all option: datasette create-token root --all insert-row --all update-row This option can be passed as many times as you like. In the above example the token will only be allowed to insert and update rows. You can also restrict permissions such that they can only be used within specific databases: datasette create-token root --database mydatabase insert-row The resulting token will only be able to insert rows, and only to tables in the mydatabase database. Finally, you can restrict permissions to individual resources - tables, SQL views and named queries - within a specific database: datasette create-token root --resource mydatabase mytable insert-row These options have short versions: -a for --all , -d for --database and -r for --resource . You can add --debug to see a JSON representation of the token that has been created. Here's a full example: datasette create-token root \ --secret mysecret \ --all view-instance \ --all view-table \ --database docs view-query \ --resource docs documents insert-row \ --resource docs documents update-row \ --debug This example outputs the following: dstok_.eJxFizEKgDAMRe_y5w4qYrFXERGxDkVsMI0uxbubdjFL8l_ez1jhwEQCA6Fjjxp90qtkuHawzdjYrh8MFobLxZ_wBH0_gtnAF-hpS5VfmF8D_lnd97lHqUJgLd6sls4H1qwlhA.nH_7RecYHj5qSzvjhMU95iy0Xlc Decoded: { ""a"": ""root"", ""token"": ""dstok"", ""t"": 1670907246, ""_r"": { ""a"": [ ""vi"", ""vt"" ], ""d"": { ""docs"": [ ""vq"" ] }, ""r"": { ""docs"": { ""documents"": [ ""ir"", ""ur"" ] } } } }",674, 533,datasette create-token,"You can also create tokens on the command line using the datasette create-token command. This command takes one required argument - the ID of the actor to be associated with the created token. You can specify a -e/--expires-after option in seconds. If omitted, the token will never expire. The command will sign the token using the DATASETTE_SECRET environment variable, if available. You can also pass the secret using the --secret option. This means you can run the command locally to create tokens for use with a deployed Datasette instance, provided you know that instance's secret. To create a token for the root actor that will expire in one hour: datasette create-token root --expires-after 3600 To create a token that never expires using a specific secret: datasette create-token root --secret my-secret-goes-here",674, 532,API Tokens,"Datasette includes a default mechanism for generating API tokens that can be used to authenticate requests. Authenticated users can create new API tokens using a form on the /-/create-token page. Tokens created in this way can be further restricted to only allow access to specific actions, or to limit those actions to specific databases, tables or queries. Created tokens can then be passed in the Authorization: Bearer $token header of HTTP requests to Datasette. A token created by a user will include that user's ""id"" in the token payload, so any permissions granted to that user based on their ID can be made available to the token as well. When one of these a token accompanies a request, the actor for that request will have the following shape: { ""id"": ""user_id"", ""token"": ""dstok"", ""token_expires"": 1667717426 } The ""id"" field duplicates the ID of the actor who first created the token. The ""token"" field identifies that this actor was authenticated using a Datasette signed token ( dstok ). The ""token_expires"" field, if present, indicates that the token will expire after that integer timestamp. The /-/create-token page cannot be accessed by actors that are authenticated with a ""token"": ""some-value"" property. This is to prevent API tokens from being used to create more tokens. Datasette plugins that implement their own form of API token authentication should follow this convention. You can disable the signed token feature entirely using the allow_signed_tokens setting.",674, 531,Other permissions in ,"For all other permissions, you can use one or more ""permissions"" blocks in your datasette.yaml configuration file. To grant access to the permissions debug tool to all signed in users, you can grant permissions-debug to any actor with an id matching the wildcard * by adding this a the root of your configuration: [[[cog config_example(cog, """""" permissions: debug-menu: id: '*' """""") ]]] [[[end]]] To grant create-table to the user with id of editor for the docs database: [[[cog config_example(cog, """""" databases: docs: permissions: create-table: id: editor """""") ]]] [[[end]]] And for insert-row against the reports table in that docs database: [[[cog config_example(cog, """""" databases: docs: tables: reports: permissions: insert-row: id: editor """""") ]]] [[[end]]] The permissions debug tool can be useful for helping test permissions that you have configured in this way.",674, 530,Controlling the ability to execute arbitrary SQL,"Datasette defaults to allowing any site visitor to execute their own custom SQL queries, for example using the form on the database page or by appending a ?_where= parameter to the table page like this . Access to this ability is controlled by the execute-sql permission. The easiest way to disable arbitrary SQL queries is using the default_allow_sql setting when you first start Datasette running. You can alternatively use an ""allow_sql"" block to control who is allowed to execute arbitrary SQL queries. To prevent any user from executing arbitrary SQL queries, use this: [[[cog config_example(cog, """""" allow_sql: false """""") ]]] [[[end]]] To enable just the root user to execute SQL for all databases in your instance, use the following: [[[cog config_example(cog, """""" allow_sql: id: root """""") ]]] [[[end]]] To limit this ability for just one specific database, use this: [[[cog config_example(cog, """""" databases: mydatabase: allow_sql: id: root """""") ]]] [[[end]]]",674, 529,Access to specific canned queries,"Canned queries allow you to configure named SQL queries in your datasette.yaml that can be executed by users. These queries can be set up to both read and write to the database, so controlling who can execute them can be important. To limit access to the add_name canned query in your dogs.db database to just the root user : [[[cog config_example(cog, """""" databases: dogs: queries: add_name: sql: INSERT INTO names (name) VALUES (:name) write: true allow: id: - root """""") ]]] [[[end]]]",674, 528,Access to specific tables and views,"To limit access to the users table in your bakery.db database: [[[cog config_example(cog, """""" databases: bakery: tables: users: allow: id: '*' """""") ]]] [[[end]]] This works for SQL views as well - you can list their names in the ""tables"" block above in the same way as regular tables. Restricting access to tables and views in this way will NOT prevent users from querying them using arbitrary SQL queries, like this for example. If you are restricting access to specific tables you should also use the ""allow_sql"" block to prevent users from bypassing the limit with their own SQL queries - see Controlling the ability to execute arbitrary SQL .",674, 527,Access to specific databases,"To limit access to a specific private.db database to just authenticated users, use the ""allow"" block like this: [[[cog config_example(cog, """""" databases: private: allow: id: ""*"" """""") ]]] [[[end]]]",674, 526,Access to an instance,"Here's how to restrict access to your entire Datasette instance to just the ""id"": ""root"" user: [[[cog from metadata_doc import config_example config_example(cog, """""" title: My private Datasette instance allow: id: root """""") ]]] [[[end]]] To deny access to all users, you can use ""allow"": false : [[[cog config_example(cog, """""" title: My entirely inaccessible instance allow: false """""") ]]] [[[end]]] One reason to do this is if you are using a Datasette plugin - such as datasette-permissions-sql - to control permissions instead.",674, 525,Access permissions in ,"There are two ways to configure permissions using datasette.yaml (or datasette.json ). For simple visibility permissions you can use ""allow"" blocks in the root, database, table and query sections. For other permissions you can use a ""permissions"" block, described in the next section . You can limit who is allowed to view different parts of your Datasette instance using ""allow"" keys in your Configuration . You can control the following: Access to the entire Datasette instance Access to specific databases Access to specific tables and views Access to specific Canned queries If a user cannot access a specific database, they will not be able to access tables, views or queries within that database. If a user cannot access the instance they will not be able to access any of the databases, tables, views or queries.",674, 524,The /-/allow-debug tool,"The /-/allow-debug tool lets you try out different ""action"" blocks against different ""actor"" JSON objects. You can try that out here: https://latest.datasette.io/-/allow-debug",674, 523,"Defining permissions with ""allow"" blocks","The standard way to define permissions in Datasette is to use an ""allow"" block in the datasette.yaml file . This is a JSON document describing which actors are allowed to perform a permission. The most basic form of allow block is this ( allow demo , deny demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: id: root """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] This will match any actors with an ""id"" property of ""root"" - for example, an actor that looks like this: { ""id"": ""root"", ""name"": ""Root User"" } An allow block can specify ""deny all"" using false ( demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: false """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] An ""allow"" of true allows all access ( demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: true """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] Allow keys can provide a list of values. These will match any actor that has any of those values ( allow demo , deny demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: id: - simon - cleopaws """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] This will match any actor with an ""id"" of either ""simon"" or ""cleopaws"" . Actors can have properties that feature a list of values. These will be matched against the list of values in an allow block. Consider the following actor: { ""id"": ""simon"", ""roles"": [""staff"", ""developer""] } This allow block will provide access to any actor that has ""developer"" as one of their roles ( allow demo , deny demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: roles: - developer """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] Note that ""roles"" is not a concept that is baked into Datasette - it's a convention that plugins can choose to implement and act on. If you want to provide access to any actor with a value for a specific key, use ""*"" . For example, to match any logged-in user specify the following ( allow demo , deny demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: id: ""*"" """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] You can specify that only unauthenticated actors (from anonymous HTTP requests) should be allowed access using the special ""unauthenticated"": true key in an allow block ( allow demo , deny demo ): [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: unauthenticated: true """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] Allow keys act as an ""or"" mechanism. An actor will be able to execute the query if any of their JSON properties match any of the values in the corresponding lists in the allow block. The following block will allow users with either a role of ""ops"" OR users who have an id of ""simon"" or ""cleopaws"" : [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" allow: id: - simon - cleopaws role: ops """""").strip(), ""YAML"", ""JSON"" ) ]]] [[[end]]] Demo for cleopaws , demo for ops role , demo for an actor matching neither rule .",674, 522,How permissions are resolved,"The datasette.permission_allowed(actor, action, resource=None, default=...) method is called to check if an actor is allowed to perform a specific action. This method asks every plugin that implements the permission_allowed(datasette, actor, action, resource) hook if the actor is allowed to perform the action. Each plugin can return True to indicate that the actor is allowed to perform the action, False if they are not allowed and None if the plugin has no opinion on the matter. False acts as a veto - if any plugin returns False then the permission check is denied. Otherwise, if any plugin returns True then the permission check is allowed. The resource argument can be used to specify a specific resource that the action is being performed against. Some permissions, such as view-instance , do not involve a resource. Others such as view-database have a resource that is a string naming the database. Permissions that take both a database name and the name of a table, view or canned query within that database use a resource that is a tuple of two strings, (database_name, resource_name) . Plugins that implement the permission_allowed() hook can decide if they are going to consider the provided resource or not.",674, 521,Permissions,"Datasette has an extensive permissions system built-in, which can be further extended and customized by plugins. The key question the permissions system answers is this: Is this actor allowed to perform this action , optionally against this particular resource ? Actors are described above . An action is a string describing the action the actor would like to perform. A full list is provided below - examples include view-table and execute-sql . A resource is the item the actor wishes to interact with - for example a specific database or table. Some actions, such as permissions-debug , are not associated with a particular resource. Datasette's built-in view permissions ( view-database , view-table etc) default to allow - unless you configure additional permission rules unauthenticated users will be allowed to access content. Permissions with potentially harmful effects should default to deny . Plugin authors should account for this when designing new plugins - for example, the datasette-upload-csvs plugin defaults to deny so that installations don't accidentally allow unauthenticated users to create new tables by uploading a CSV file.",674, 520,"Using the ""root"" actor","Datasette currently leaves almost all forms of authentication to plugins - datasette-auth-github for example. The one exception is the ""root"" account, which you can sign into while using Datasette on your local machine. This provides access to a small number of debugging features. To sign in as root, start Datasette using the --root command-line option, like this: datasette --root http://127.0.0.1:8001/-/auth-token?token=786fc524e0199d70dc9a581d851f466244e114ca92f33aa3b42a139e9388daa7 INFO: Started server process [25801] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://127.0.0.1:8001 (Press CTRL+C to quit) The URL on the first line includes a one-use token which can be used to sign in as the ""root"" actor in your browser. Click on that link and then visit http://127.0.0.1:8001/-/actor to confirm that you are authenticated as an actor that looks like this: { ""id"": ""root"" }",674, 519,Actors,"Through plugins, Datasette can support both authenticated users (with cookies) and authenticated API agents (via authentication tokens). The word ""actor"" is used to cover both of these cases. Every request to Datasette has an associated actor value, available in the code as request.actor . This can be None for unauthenticated requests, or a JSON compatible Python dictionary for authenticated users or API agents. The actor dictionary can be any shape - the design of that data structure is left up to the plugins. A useful convention is to include an ""id"" string, as demonstrated by the ""root"" actor below. Plugins can use the actor_from_request(datasette, request) hook to implement custom logic for authenticating an actor based on the incoming HTTP request.",674, 518,Authentication and permissions,"Datasette doesn't require authentication by default. Any visitor to a Datasette instance can explore the full data and execute read-only SQL queries. Datasette's plugin system can be used to add many different styles of authentication, such as user accounts, single sign-on or API keys.",674, 517,Using Datasette on your own computer,"First, follow the Installation instructions. Now you can run Datasette against a SQLite file on your computer using the following command: datasette path/to/database.db This will start a web server on port 8001 - visit http://localhost:8001/ to access the web interface. Add -o to open your browser automatically once Datasette has started: datasette path/to/database.db -o Use Chrome on OS X? You can run datasette against your browser history like so: datasette ~/Library/Application\ Support/Google/Chrome/Default/History --nolock The --nolock option ignores any file locks. This is safe as Datasette will open the file in read-only mode. Now visiting http://localhost:8001/History/downloads will show you a web interface to browse your downloads data: http://localhost:8001/History/downloads.json will return that data as JSON: { ""database"": ""History"", ""columns"": [ ""id"", ""current_path"", ""target_path"", ""start_time"", ""received_bytes"", ""total_bytes"", ... ], ""rows"": [ [ 1, ""/Users/simonw/Downloads/DropboxInstaller.dmg"", ""/Users/simonw/Downloads/DropboxInstaller.dmg"", 13097290269022132, 626688, 0, ... ] ] } http://localhost:8001/History/downloads.json?_shape=objects will return that data as JSON in a more convenient format: { ... ""rows"": [ { ""start_time"": 13097290269022132, ""interrupt_reason"": 0, ""hash"": """", ""id"": 1, ""site_url"": """", ""referrer"": ""https://www.dropbox.com/downloading?src=index"", ... } ] }",674, 516,Try Datasette without installing anything using Glitch,"Glitch is a free online tool for building web apps directly from your web browser. You can use Glitch to try out Datasette without needing to install any software on your own computer. Here's a demo project on Glitch which you can use as the basis for your own experiments: glitch.com/~datasette-csvs Glitch allows you to ""remix"" any project to create your own copy and start editing it in your browser. You can remix the datasette-csvs project by clicking this button: Find a CSV file and drag it onto the Glitch file explorer panel - datasette-csvs will automatically convert it to a SQLite database (using sqlite-utils ) and allow you to start exploring it using Datasette. If your CSV file has a latitude and longitude column you can visualize it on a map by uncommenting the datasette-cluster-map line in the requirements.txt file using the Glitch file editor. Need some data? Try this Public Art Data for the city of Seattle - hit ""Export"" and select ""CSV"" to download it as a CSV file. For more on how this works, see Running Datasette on Glitch .",674, 515,Datasette in your browser with Datasette Lite,"Datasette Lite is Datasette packaged using WebAssembly so that it runs entirely in your browser, no Python web application server required. You can pass a URL to a CSV, SQLite or raw SQL file directly to Datasette Lite to explore that data in your browser. This example link opens Datasette Lite and loads the SQL Murder Mystery example database from Northwestern University Knight Lab .",674, 514,Follow a tutorial,"Datasette has several tutorials to help you get started with the tool. Try one of the following: Exploring a database with Datasette shows how to use the Datasette web interface to explore a new database. Learn SQL with Datasette introduces SQL, and shows how to use that query language to ask questions of your data. Cleaning data with sqlite-utils and Datasette guides you through using sqlite-utils to turn a CSV file into a database that you can explore using Datasette.",674, 513,Play with a live demo,"The best way to experience Datasette for the first time is with a demo: global-power-plants.datasettes.com provides a searchable database of power plants around the world, using data from the World Resources Institude rendered using the datasette-cluster-map plugin. fivethirtyeight.datasettes.com shows Datasette running against over 400 datasets imported from the FiveThirtyEight GitHub repository .",674, 512,Getting started,,674, 511,Using secrets with datasette publish,"The datasette publish and datasette package commands both generate a secret for you automatically when Datasette is deployed. This means that every time you deploy a new version of a Datasette project, a new secret will be generated. This will cause signed cookies to become invalid on every fresh deploy. You can fix this by creating a secret that will be used for multiple deploys and passing it using the --secret option: datasette publish cloudrun mydb.db --service=my-service --secret=cdb19e94283a20f9d42cca5",674, 510,Configuring the secret,"Datasette uses a secret string to sign secure values such as cookies. If you do not provide a secret, Datasette will create one when it starts up. This secret will reset every time the Datasette server restarts though, so things like authentication cookies and API tokens will not stay valid between restarts. You can pass a secret to Datasette in two ways: with the --secret command-line option or by setting a DATASETTE_SECRET environment variable. datasette mydb.db --secret=SECRET_VALUE_HERE Or: export DATASETTE_SECRET=SECRET_VALUE_HERE datasette mydb.db One way to generate a secure random secret is to use Python like this: python3 -c 'import secrets; print(secrets.token_hex(32))' cdb19e94283a20f9d42cca50c5a4871c0aa07392db308755d60a1a5b9bb0fa52 Plugin authors make use of this signing mechanism in their plugins using .sign(value, namespace=""default"") and .unsign(value, namespace=""default"") .",674, 509,base_url,"If you are running Datasette behind a proxy, it may be useful to change the root path used for the Datasette instance. For example, if you are sending traffic from https://www.example.com/tools/datasette/ through to a proxied Datasette instance you may wish Datasette to use /tools/datasette/ as its root URL. You can do that like so: datasette mydatabase.db --setting base_url /tools/datasette/",674, 508,trace_debug,"This setting enables appending ?_trace=1 to any page in order to see the SQL queries and other trace information that was used to generate that page. Enable it like this: datasette mydatabase.db --setting trace_debug 1 Some examples: https://latest.datasette.io/?_trace=1 https://latest.datasette.io/fixtures/roadside_attractions?_trace=1 See datasette.tracer for details on how to hook into this mechanism as a plugin author.",674, 507,template_debug,"This setting enables template context debug mode, which is useful to help understand what variables are available to custom templates when you are writing them. Enable it like this: datasette mydatabase.db --setting template_debug 1 Now you can add ?_context=1 or &_context=1 to any Datasette page to see the context that was passed to that template. Some examples: https://latest.datasette.io/?_context=1 https://latest.datasette.io/fixtures?_context=1 https://latest.datasette.io/fixtures/roadside_attractions?_context=1",674, 506,force_https_urls,"Forces self-referential URLs in the JSON output to always use the https:// protocol. This is useful for cases where the application itself is hosted using HTTP but is served to the outside world via a proxy that enables HTTPS. datasette mydatabase.db --setting force_https_urls 1",674, 505,truncate_cells_html,"In the HTML table view, truncate any strings that are longer than this value. The full value will still be available in CSV, JSON and on the individual row HTML page. Set this to 0 to disable truncation. datasette mydatabase.db --setting truncate_cells_html 0",674, 504,max_csv_mb,"The maximum size of CSV that can be exported, in megabytes. Defaults to 100MB. You can disable the limit entirely by settings this to 0: datasette mydatabase.db --setting max_csv_mb 0",674, 503,allow_csv_stream,"Enables the CSV export feature where an entire table (potentially hundreds of thousands of rows) can be exported as a single CSV file. This is turned on by default - you can turn it off like this: datasette mydatabase.db --setting allow_csv_stream off",674, 502,cache_size_kb,"Sets the amount of memory SQLite uses for its per-connection cache , in KB. datasette mydatabase.db --setting cache_size_kb 5000",674, 501,default_cache_ttl,"Default HTTP caching max-age header in seconds, used for Cache-Control: max-age=X . Can be over-ridden on a per-request basis using the ?_ttl= query string parameter. Set this to 0 to disable HTTP caching entirely. Defaults to 5 seconds. datasette mydatabase.db --setting default_cache_ttl 60",674, 500,max_signed_tokens_ttl,"Maximum allowed expiry time for signed API tokens created by users. Defaults to 0 which means no limit - tokens can be created that will never expire. Set this to a value in seconds to limit the maximum expiry time. For example, to set that limit to 24 hours you would use: datasette mydatabase.db --setting max_signed_tokens_ttl 86400 This setting is enforced when incoming tokens are processed.",674, 499,allow_signed_tokens,"Should users be able to create signed API tokens to access Datasette? This is turned on by default. Use the following to turn it off: datasette mydatabase.db --setting allow_signed_tokens off Turning this setting off will disable the /-/create-token page, described here . It will also cause any incoming Authorization: Bearer dstok_... API tokens to be ignored.",674, 498,allow_download,"Should users be able to download the original SQLite database using a link on the database index page? This is turned on by default. However, databases can only be downloaded if they are served in immutable mode and not in-memory. If downloading is unavailable for either of these reasons, the download link is hidden even if allow_download is on. To disable database downloads, use the following: datasette mydatabase.db --setting allow_download off",674, 497,suggest_facets,"Should Datasette calculate suggested facets? On by default, turn this off like so: datasette mydatabase.db --setting suggest_facets off",674, 496,facet_suggest_time_limit_ms,"When Datasette calculates suggested facets it needs to run a SQL query for every column in your table. The default for this time limit is 50ms to account for the fact that it needs to run once for every column. If the time limit is exceeded the column will not be suggested as a facet. You can increase this time limit like so: datasette mydatabase.db --setting facet_suggest_time_limit_ms 500",674, 495,facet_time_limit_ms,"This is the time limit Datasette allows for calculating a facet, which defaults to 200ms: datasette mydatabase.db --setting facet_time_limit_ms 1000",674, 494,default_facet_size,"The default number of unique rows returned by Facets is 30. You can customize it like this: datasette mydatabase.db --setting default_facet_size 50",674, 493,allow_facet,"Allow users to specify columns they would like to facet on using the ?_facet=COLNAME URL parameter to the table view. This is enabled by default. If disabled, facets will still be displayed if they have been specifically enabled in metadata.json configuration for the table. Here's how to disable this feature: datasette mydatabase.db --setting allow_facet off",674, 492,num_sql_threads,"Maximum number of threads in the thread pool Datasette uses to execute SQLite queries. Defaults to 3. datasette mydatabase.db --setting num_sql_threads 10 Setting this to 0 turns off threaded SQL queries entirely - useful for environments that do not support threading such as Pyodide .",674, 491,max_insert_rows,"Maximum rows that can be inserted at a time using the bulk insert API, see Inserting rows . Defaults to 100. You can increase or decrease this limit like so: datasette mydatabase.db --setting max_insert_rows 1000",674, 490,max_returned_rows,"Datasette returns a maximum of 1,000 rows of data at a time. If you execute a query that returns more than 1,000 rows, Datasette will return the first 1,000 and include a warning that the result set has been truncated. You can use OFFSET/LIMIT or other methods in your SQL to implement pagination if you need to return more than 1,000 rows. You can increase or decrease this limit like so: datasette mydatabase.db --setting max_returned_rows 2000",674, 489,sql_time_limit_ms,"By default, queries have a time limit of one second. If a query takes longer than this to run Datasette will terminate the query and return an error. If this time limit is too short for you, you can customize it using the sql_time_limit_ms limit - for example, to increase it to 3.5 seconds: datasette mydatabase.db --setting sql_time_limit_ms 3500 You can optionally set a lower time limit for an individual query using the ?_timelimit=100 query string argument: /my-database/my-table?qSpecies=44&_timelimit=100 This would set the time limit to 100ms for that specific query. This feature is useful if you are working with databases of unknown size and complexity - a query that might make perfect sense for a smaller table could take too long to execute on a table with millions of rows. By setting custom time limits you can execute queries ""optimistically"" - e.g. give me an exact count of rows matching this query but only if it takes less than 100ms to calculate.",674, 488,default_page_size,"The default number of rows returned by the table page. You can over-ride this on a per-page basis using the ?_size=80 query string parameter, provided you do not specify a value higher than the max_returned_rows setting. You can set this default using --setting like so: datasette mydatabase.db --setting default_page_size 50",674, 487,default_allow_sql,"Should users be able to execute arbitrary SQL queries by default? Setting this to off causes permission checks for execute-sql to fail by default. datasette mydatabase.db --setting default_allow_sql off Another way to achieve this is to add ""allow_sql"": false to your datasette.yaml file, as described in Controlling the ability to execute arbitrary SQL . This setting offers a more convenient way to do this.",674, 486,Settings,"The following options can be set using --setting name value , or by storing them in the settings.json file for use with Configuration directory mode .",674, 485,Configuration directory mode,"Normally you configure Datasette using command-line options. For a Datasette instance with custom templates, custom plugins, a static directory and several databases this can get quite verbose: datasette one.db two.db \ --metadata=metadata.json \ --template-dir=templates/ \ --plugins-dir=plugins \ --static css:css As an alternative to this, you can run Datasette in configuration directory mode. Create a directory with the following structure: # In a directory called my-app: my-app/one.db my-app/two.db my-app/datasette.yaml my-app/metadata.json my-app/templates/index.html my-app/plugins/my_plugin.py my-app/static/my.css Now start Datasette by providing the path to that directory: datasette my-app/ Datasette will detect the files in that directory and automatically configure itself using them. It will serve all *.db files that it finds, will load metadata.json if it exists, and will load the templates , plugins and static folders if they are present. The files that can be included in this directory are as follows. All are optional. *.db (or *.sqlite3 or *.sqlite ) - SQLite database files that will be served by Datasette datasette.yaml - Configuration for the Datasette instance metadata.json - Metadata for those databases - metadata.yaml or metadata.yml can be used as well inspect-data.json - the result of running datasette inspect *.db --inspect-file=inspect-data.json from the configuration directory - any database files listed here will be treated as immutable, so they should not be changed while Datasette is running templates/ - a directory containing Custom templates plugins/ - a directory containing plugins, see Writing one-off plugins static/ - a directory containing static files - these will be served from /static/filename.txt , see Serving static files",674, 484,Using --setting,"Datasette supports a number of settings. These can be set using the --setting name value option to datasette serve . You can set multiple settings at once like this: datasette mydatabase.db \ --setting default_page_size 50 \ --setting sql_time_limit_ms 3500 \ --setting max_returned_rows 2000 Settings can also be specified in the database.yaml configuration file .",674, 483,Settings,,674, 482,0.8 (2017-11-13),"V0.8 - added PyPI metadata, ready to ship. Implemented offset/limit pagination for views ( #70 ). Improved pagination. ( #78 ) Limit on max rows returned, controlled by --max_returned_rows option. ( #69 ) If someone executes 'select * from table' against a table with a million rows in it, we could run into problems: just serializing that much data as JSON is likely to lock up the server. Solution: we now have a hard limit on the maximum number of rows that can be returned by a query. If that limit is exceeded, the server will return a ""truncated"": true field in the JSON. This limit can be optionally controlled by the new --max_returned_rows option. Setting that option to 0 disables the limit entirely.",674, 481,0.9 (2017-11-13),"Added --sql_time_limit_ms and --extra-options . The serve command now accepts --sql_time_limit_ms for customizing the SQL time limit. The publish and package commands now accept --extra-options which can be used to specify additional options to be passed to the datasite serve command when it executes inside the resulting Docker containers.",674, 480,0.10 (2017-11-14),"Fixed #83 - 500 error on individual row pages. Stop using sqlite WITH RECURSIVE in our tests. The version of Python 3 running in Travis CI doesn't support this.",674, 479,0.11 (2017-11-14),"Added datasette publish now --force option. This calls now with --force - useful as it means you get a fresh copy of datasette even if Now has already cached that docker layer. Enable --cors by default when running in a container.",674, 478,0.12 (2017-11-16),"Added __version__ , now displayed as tooltip in page footer ( #108 ). Added initial docs, including a changelog ( #99 ). Turned on auto-escaping in Jinja. Added a UI for editing named parameters ( #96 ). You can now construct a custom SQL statement using SQLite named parameters (e.g. :name ) and datasette will display form fields for editing those parameters. Here’s an example which lets you see the most popular names for dogs of different species registered through various dog registration schemes in Australia. Pin to specific Jinja version. ( #100 ). Default to 127.0.0.1 not 0.0.0.0. ( #98 ). Added extra metadata options to publish and package commands. ( #92 ). You can now run these commands like so: datasette now publish mydb.db \ --title=""My Title"" \ --source=""Source"" \ --source_url=""http://www.example.com/"" \ --license=""CC0"" \ --license_url=""https://creativecommons.org/publicdomain/zero/1.0/"" This will write those values into the metadata.json that is packaged with the app. If you also pass --metadata=metadata.json that file will be updated with the extra values before being written into the Docker image. Added production-ready Dockerfile ( #94 ) [Andrew Cutler] New ?_sql_time_limit_ms=10 argument to database and table page ( #95 ) SQL syntax highlighting with Codemirror ( #89 ) [Tom Dyson]",674, 477,0.13 (2017-11-24),"Search now applies to current filters. Combined search into the same form as filters. Closes #133 Much tidier design for table view header. Closes #147 Added ?column__not=blah filter. Closes #148 Row page now resolves foreign keys. Closes #132 Further tweaks to select/input filter styling. Refs #86 - thanks for the help, @natbat! Show linked foreign key in table cells. Added UI for editing table filters. Refs #86 Hide FTS-created tables on index pages. Closes #129 Add publish to heroku support [Jacob Kaplan-Moss] datasette publish heroku mydb.db Pull request #104 Initial implementation of ?_group_count=column . URL shortcut for counting rows grouped by one or more columns. ?_group_count=column1&_group_count=column2 works as well. SQL generated looks like this: select ""qSpecies"", count(*) as ""count"" from Street_Tree_List group by ""qSpecies"" order by ""count"" desc limit 100 Or for two columns like this: select ""qSpecies"", ""qSiteInfo"", count(*) as ""count"" from Street_Tree_List group by ""qSpecies"", ""qSiteInfo"" order by ""count"" desc limit 100 Refs #44 Added --build=master option to datasette publish and package. The datasette publish and datasette package commands both now accept an optional --build argument. If provided, this can be used to specify a branch published to GitHub that should be built into the container. This makes it easier to test code that has not yet been officially released to PyPI, e.g.: datasette publish now mydb.db --branch=master Implemented ?_search=XXX + UI if a FTS table is detected. Closes #131 Added datasette --version support. Table views now show expanded foreign key references, if possible. If a table has foreign key columns, and those foreign key tables have label_columns , the TableView will now query those other tables for the corresponding values and display those values as links in the corresponding table cells. label_columns are currently detected by the inspect() function, which looks for any table that has just two columns - an ID column and one other - and sets the label_column to be that second non-ID column. Don't prevent tabbing to ""Run SQL"" button ( #117 ) [Robert Gieseke] See comment in #115 Add keyboard shortcut to execute SQL query ( #115 ) [Robert Gieseke] Allow --load-extension to be set via environment variable. Add support for ?field__isnull=1 ( #107 ) [Ray N] Add spatialite, switch to debian and local build ( #114 ) [Ariel Núñez] Added --load-extension argument to datasette serve. Allows loading of SQLite extensions. Refs #110 .",674, 476,0.14 (2017-12-09),"The theme of this release is customization: Datasette now allows every aspect of its presentation to be customized either using additional CSS or by providing entirely new templates. Datasette's metadata.json format has also been expanded, to allow per-database and per-table metadata. A new datasette skeleton command can be used to generate a skeleton JSON file ready to be filled in with per-database and per-table details. The metadata.json file can also be used to define canned queries , as a more powerful alternative to SQL views. extra_css_urls / extra_js_urls in metadata A mechanism in the metadata.json format for adding custom CSS and JS urls. Create a metadata.json file that looks like this: { ""extra_css_urls"": [ ""https://simonwillison.net/static/css/all.bf8cd891642c.css"" ], ""extra_js_urls"": [ ""https://code.jquery.com/jquery-3.2.1.slim.min.js"" ] } Then start datasette like this: datasette mydb.db --metadata=metadata.json The CSS and JavaScript files will be linked in the of every page. You can also specify a SRI (subresource integrity hash) for these assets: { ""extra_css_urls"": [ { ""url"": ""https://simonwillison.net/static/css/all.bf8cd891642c.css"", ""sri"": ""sha384-9qIZekWUyjCyDIf2YK1FRoKiPJq4PHt6tp/ulnuuyRBvazd0hG7pWbE99zvwSznI"" } ], ""extra_js_urls"": [ { ""url"": ""https://code.jquery.com/jquery-3.2.1.slim.min.js"", ""sri"": ""sha256-k2WSCIexGzOj3Euiig+TlR8gA0EmPjuc79OEeY5L45g="" } ] } Modern browsers will only execute the stylesheet or JavaScript if the SRI hash matches the content served. You can generate hashes using https://www.srihash.org/ Auto-link column values that look like URLs ( #153 ) CSS styling hooks as classes on the body ( #153 ) Every template now gets CSS classes in the body designed to support custom styling. The index template (the top level page at / ) gets this: The database template ( /dbname/ ) gets this: The table template ( /dbname/tablename ) gets: The row template ( /dbname/tablename/rowid ) gets: The db-x and table-x classes use the database or table names themselves IF they are valid CSS identifiers. If they aren't, we strip any invalid characters out and append a 6 character md5 digest of the original name, in order to ensure that multiple tables which resolve to the same stripped character version still have different CSS classes. Some examples (extracted from the unit tests): ""simple"" => ""simple"" ""MixedCase"" => ""MixedCase"" ""-no-leading-hyphens"" => ""no-leading-hyphens-65bea6"" ""_no-leading-underscores"" => ""no-leading-underscores-b921bc"" ""no spaces"" => ""no-spaces-7088d7"" ""-"" => ""336d5e"" ""no $ characters"" => ""no--characters-59e024"" datasette --template-dir=mytemplates/ argument You can now pass an additional argument specifying a directory to look for custom templates in. Datasette will fall back on the default templates if a template is not found in that directory. Ability to over-ride templates for individual tables/databases. It is now possible to over-ride templates on a per-database / per-row or per- table basis. When you access e.g. /mydatabase/mytable Datasette will look for the following: - table-mydatabase-mytable.html - table.html If you provided a --template-dir argument to datasette serve it will look in that directory first. The lookup rules are as follows: Index page (/): index.html Database page (/mydatabase): database-mydatabase.html database.html Table page (/mydatabase/mytable): table-mydatabase-mytable.html table.html Row page (/mydatabase/mytable/id): row-mydatabase-mytable.html row.html If a table name has spaces or other unexpected characters in it, the template filename will follow the same rules as our custom CSS classes - for example, a table called ""Food Trucks"" will attempt to load the following templates: table-mydatabase-Food-Trucks-399138.html table.html It is possible to extend the default templates using Jinja template inheritance. If you want to customize EVERY row template with some additional content you can do so by creating a row.html template like this: {% extends ""default:row.html"" %} {% block content %}

EXTRA HTML AT THE TOP OF THE CONTENT BLOCK

This line renders the original block:

{{ super() }} {% endblock %} --static option for datasette serve ( #160 ) You can now tell Datasette to serve static files from a specific location at a specific mountpoint. For example: datasette serve mydb.db --static extra-css:/tmp/static/css Now if you visit this URL: http://localhost:8001/extra-css/blah.css The following file will be served: /tmp/static/css/blah.css Canned query support. Named canned queries can now be defined in metadata.json like this: { ""databases"": { ""timezones"": { ""queries"": { ""timezone_for_point"": ""select tzid from timezones ..."" } } } } These will be shown in a new ""Queries"" section beneath ""Views"" on the database page. New datasette skeleton command for generating metadata.json ( #164 ) metadata.json support for per-table/per-database metadata ( #165 ) Also added support for descriptions and HTML descriptions. Here's an example metadata.json file illustrating custom per-database and per- table metadata: { ""title"": ""Overall datasette title"", ""description_html"": ""This is a description with HTML."", ""databases"": { ""db1"": { ""title"": ""First database"", ""description"": ""This is a string description & has no HTML"", ""license_url"": ""http://example.com/"", ""license"": ""The example license"", ""queries"": { ""canned_query"": ""select * from table1 limit 3;"" }, ""tables"": { ""table1"": { ""title"": ""Custom title for table1"", ""description"": ""Tables can have descriptions too"", ""source"": ""This has a custom source"", ""source_url"": ""http://example.com/"" } } } } } Renamed datasette build command to datasette inspect ( #130 ) Upgrade to Sanic 0.7.0 ( #168 ) https://github.com/channelcat/sanic/releases/tag/0.7.0 Package and publish commands now accept --static and --template-dir Example usage: datasette package --static css:extra-css/ --static js:extra-js/ \ sf-trees.db --template-dir templates/ --tag sf-trees --branch master This creates a local Docker image that includes copies of the templates/, extra-css/ and extra-js/ directories. You can then run it like this: docker run -p 8001:8001 sf-trees For publishing to Zeit now: datasette publish now --static css:extra-css/ --static js:extra-js/ \ sf-trees.db --template-dir templates/ --name sf-trees --branch master HTML comment showing which templates were considered for a page ( #171 )",674, 475,0.15 (2018-04-09),"The biggest new feature in this release is the ability to sort by column. On the table page the column headers can now be clicked to apply sort (or descending sort), or you can specify ?_sort=column or ?_sort_desc=column directly in the URL. table_rows => table_rows_count , filtered_table_rows => filtered_table_rows_count Renamed properties. Closes #194 New sortable_columns option in metadata.json to control sort options. You can now explicitly set which columns in a table can be used for sorting using the _sort and _sort_desc arguments using metadata.json : { ""databases"": { ""database1"": { ""tables"": { ""example_table"": { ""sortable_columns"": [ ""height"", ""weight"" ] } } } } } Refs #189 Column headers now link to sort/desc sort - refs #189 _sort and _sort_desc parameters for table views Allows for paginated sorted results based on a specified column. Refs #189 Total row count now correct even if _next applied Use .custom_sql() for _group_count implementation (refs #150 ) Make HTML title more readable in query template ( #180 ) [Ryan Pitts] New ?_shape=objects/object/lists param for JSON API ( #192 ) New _shape= parameter replacing old .jsono extension Now instead of this: /database/table.jsono We use the _shape parameter like this: /database/table.json?_shape=objects Also introduced a new _shape called object which looks like this: /database/table.json?_shape=object Returning an object for the rows key: ... ""rows"": { ""pk1"": { ... }, ""pk2"": { ... } } Refs #122 Utility for writing test database fixtures to a .db file python tests/fixtures.py /tmp/hello.db This is useful for making a SQLite database of the test fixtures for interactive exploration. Compound primary key _next= now plays well with extra filters Closes #190 Fixed bug with keyset pagination over compound primary keys Refs #190 Database/Table views inherit source/license/source_url/license_url metadata If you set the source_url/license_url/source/license fields in your root metadata those values will now be inherited all the way down to the database and table templates. The title/description are NOT inherited. Also added unit tests for the HTML generated by the metadata. Refs #185 Add metadata, if it exists, to heroku temp dir ( #178 ) [Tony Hirst] Initial documentation for pagination Broke up test_app into test_api and test_html Fixed bug with .json path regular expression I had a table called geojson and it caused an exception because the regex was matching .json and not \.json Deploy to Heroku with Python 3.6.3",674, 474,0.16 (2018-04-13),"Better mechanism for handling errors; 404s for missing table/database New error mechanism closes #193 404s for missing tables/databases closes #184 long_description in markdown for the new PyPI Hide SpatiaLite system tables. [Russ Garrett] Allow explain select / explain query plan select #201 Datasette inspect now finds primary_keys #195 Ability to sort using form fields (for mobile portrait mode) #199 We now display sort options as a select box plus a descending checkbox, which means you can apply sort orders even in portrait mode on a mobile phone where the column headers are hidden.",674, 473,0.17 (2018-04-13),Release 0.17 to fix issues with PyPI,674, 472,0.18 (2018-04-14),"This release introduces support for units , contributed by Russ Garrett ( #203 ). You can now optionally specify the units for specific columns using metadata.json . Once specified, units will be displayed in the HTML view of your table. They also become available for use in filters - if a column is configured with a unit of distance, you can request all rows where that column is less than 50 meters or more than 20 feet for example. Link foreign keys which don't have labels. [Russ Garrett] This renders unlabeled FKs as simple links. Also includes bonus fixes for two minor issues: In foreign key link hrefs the primary key was escaped using HTML escaping rather than URL escaping. This broke some non-integer PKs. Print tracebacks to console when handling 500 errors. Fix SQLite error when loading rows with no incoming FKs. [Russ Garrett] This fixes an error caused by an invalid query when loading incoming FKs. The error was ignored due to async but it still got printed to the console. Allow custom units to be registered with Pint. [Russ Garrett] Support units in filters. [Russ Garrett] Tidy up units support. [Russ Garrett] Add units to exported JSON Units key in metadata skeleton Docs Initial units support. [Russ Garrett] Add support for specifying units for a column in metadata.json and rendering them on display using pint",674, 471,0.19 (2018-04-16),"This is the first preview of the new Datasette plugins mechanism. Only two plugin hooks are available so far - for custom SQL functions and custom template filters. There's plenty more to come - read the documentation and get involved in the tracking ticket if you have feedback on the direction so far. Fix for _sort_desc=sortable_with_nulls test, refs #216 Fixed #216 - paginate correctly when sorting by nullable column Initial documentation for plugins, closes #213 https://docs.datasette.io/en/stable/plugins.html New --plugins-dir=plugins/ option ( #212 ) New option causing Datasette to load and evaluate all of the Python files in the specified directory and register any plugins that are defined in those files. This new option is available for the following commands: datasette serve mydb.db --plugins-dir=plugins/ datasette publish now/heroku mydb.db --plugins-dir=plugins/ datasette package mydb.db --plugins-dir=plugins/ Start of the plugin system, based on pluggy ( #210 ) Uses https://pluggy.readthedocs.io/ originally created for the py.test project We're starting with two plugin hooks: prepare_connection(conn) This is called when a new SQLite connection is created. It can be used to register custom SQL functions. prepare_jinja2_environment(env) This is called with the Jinja2 environment. It can be used to register custom template tags and filters. An example plugin which uses these two hooks can be found at https://github.com/simonw/datasette-plugin-demos or installed using pip install datasette-plugin-demos Refs #14 Return HTTP 405 on InvalidUsage rather than 500. [Russ Garrett] This also stops it filling up the logs. This happens for HEAD requests at the moment - which perhaps should be handled better, but that's a different issue.",674, 470,0.20 (2018-04-20),"Mostly new work on the Plugins mechanism: plugins can now bundle static assets and custom templates, and datasette publish has a new --install=name-of-plugin option. Add col-X classes to HTML table on custom query page Fixed out-dated template in documentation Plugins can now bundle custom templates, #224 Added /-/metadata /-/plugins /-/inspect, #225 Documentation for --install option, refs #223 Datasette publish/package --install option, #223 Fix for plugins in Python 3.5, #222 New plugin hooks: extra_css_urls() and extra_js_urls(), #214 /-/static-plugins/PLUGIN_NAME/ now serves static/ from plugins now gets class=""col-X"" - plus added col-X documentation Use to_css_class for table cell column classes This ensures that columns with spaces in the name will still generate usable CSS class names. Refs #209 Add column name classes to s, make PK bold [Russ Garrett] Don't duplicate simple primary keys in the link column [Russ Garrett] When there's a simple (single-column) primary key, it looks weird to duplicate it in the link column. This change removes the second PK column and treats the link column as if it were the PK column from a header/sorting perspective. Correct escaping for HTML display of row links [Russ Garrett] Longer time limit for test_paginate_compound_keys It was failing intermittently in Travis - see #209 Use application/octet-stream for downloadable databases Updated PyPI classifiers Updated PyPI link to pypi.org",674, 469,0.21 (2018-05-05),"New JSON _shape= options, the ability to set table _size= and a mechanism for searching within specific columns. Default tests to using a longer timelimit Every now and then a test will fail in Travis CI on Python 3.5 because it hit the default 20ms SQL time limit. Test fixtures now default to a 200ms time limit, and we only use the 20ms time limit for the specific test that tests query interruption. This should make our tests on Python 3.5 in Travis much more stable. Support _search_COLUMN=text searches, closes #237 Show version on /-/plugins page, closes #248 ?_size=max option, closes #249 Added /-/versions and /-/versions.json , closes #244 Sample output: { ""python"": { ""version"": ""3.6.3"", ""full"": ""3.6.3 (default, Oct 4 2017, 06:09:38) \n[GCC 4.2.1 Compatible Apple LLVM 9.0.0 (clang-900.0.37)]"" }, ""datasette"": { ""version"": ""0.20"" }, ""sqlite"": { ""version"": ""3.23.1"", ""extensions"": { ""json1"": null, ""spatialite"": ""4.3.0a"" } } } Renamed ?_sql_time_limit_ms= to ?_timelimit , closes #242 New ?_shape=array option + tweaks to _shape , closes #245 Default is now ?_shape=arrays (renamed from lists ) New ?_shape=array returns an array of objects as the root object Changed ?_shape=object to return the object as the root Updated docs FTS tables now detected by inspect() , closes #240 New ?_size=XXX query string parameter for table view, closes #229 Also added documentation for all of the _special arguments. Plus deleted some duplicate logic implementing _group_count . If max_returned_rows==page_size , increment max_returned_rows - fixes #230 New hidden: True option for table metadata, closes #239 Hide idx_* tables if spatialite detected, closes #228 Added class=rows-and-columns to custom query results table Added CSS class rows-and-columns to main table label_column option in metadata.json - closes #234",674, 468,0.22 (2018-05-20),"The big new feature in this release is Facets . Datasette can now apply faceted browse to any column in any table. It will also suggest possible facets. See the Datasette Facets announcement post for more details. In addition to the work on facets: Added docs for introspection endpoints New --config option, added --help-config , closes #274 Removed the --page_size= argument to datasette serve in favour of: datasette serve --config default_page_size:50 mydb.db Added new help section: datasette --help-config Config options: default_page_size Default page size for the table view (default=100) max_returned_rows Maximum rows that can be returned from a table or custom query (default=1000) sql_time_limit_ms Time limit for a SQL query in milliseconds (default=1000) default_facet_size Number of values to return for requested facets (default=30) facet_time_limit_ms Time limit for calculating a requested facet (default=200) facet_suggest_time_limit_ms Time limit for calculating a suggested facet (default=50) Only apply responsive table styles to .rows-and-column Otherwise they interfere with tables in the description, e.g. on https://fivethirtyeight.datasettes.com/fivethirtyeight/nba-elo%2Fnbaallelo Refactored views into new views/ modules, refs #256 Documentation for SQLite full-text search support, closes #253 /-/versions now includes SQLite fts_versions , closes #252",674, 467,0.22.1 (2018-05-23),"Bugfix release, plus we now use versioneer for our version numbers. Faceting no longer breaks pagination, fixes #282 Add __version_info__ derived from __version__ [Robert Gieseke] This might be tuple of more than two values (major and minor version) if commits have been made after a release. Add version number support with Versioneer. [Robert Gieseke] Versioneer Licence: Public Domain (CC0-1.0) Closes #273 Refactor inspect logic [Russ Garrett]",674, 466,Miscellaneous,"Got JSON data in one of your columns? Use the new ?_json=COLNAME argument to tell Datasette to return that JSON value directly rather than encoding it as a string. If you just want an array of the first value of each row, use the new ?_shape=arrayfirst option - example .",674, 465,latest.datasette.io,"Every commit to Datasette master is now automatically deployed by Travis CI to https://latest.datasette.io/ - ensuring there is always a live demo of the latest version of the software. The demo uses the fixtures from our unit tests, ensuring it demonstrates the same range of functionality that is covered by the tests. You can see how the deployment mechanism works in our .travis.yml file.",674, 464,Improved support for SpatiaLite,"The SpatiaLite module for SQLite adds robust geospatial features to the database. Getting SpatiaLite working can be tricky, especially if you want to use the most recent alpha version (with support for K-nearest neighbor). Datasette now includes extensive documentation on SpatiaLite , and thanks to Ravi Kotecha our GitHub repo includes a Dockerfile that can build the latest SpatiaLite and configure it for use with Datasette. The datasette publish and datasette package commands now accept a new --spatialite argument which causes them to install and configure SpatiaLite as part of the container they deploy.",674, 463,Control HTTP caching with ?_ttl=,"You can now customize the HTTP max-age header that is sent on a per-URL basis, using the new ?_ttl= query string parameter. You can set this to any value in seconds, or you can set it to 0 to disable HTTP caching entirely. Consider for example this query which returns a randomly selected member of the Avengers: select * from [avengers/avengers] order by random() limit 1 If you hit the following page repeatedly you will get the same result, due to HTTP caching: /fivethirtyeight?sql=select+*+from+%5Bavengers%2Favengers%5D+order+by+random%28%29+limit+1 By adding ?_ttl=0 to the zero you can ensure the page will not be cached and get back a different super hero every time: /fivethirtyeight?sql=select+*+from+%5Bavengers%2Favengers%5D+order+by+random%28%29+limit+1&_ttl=0",674, 462,New configuration settings,"Datasette's Settings now also supports boolean settings. A number of new configuration options have been added: num_sql_threads - the number of threads used to execute SQLite queries. Defaults to 3. allow_facet - enable or disable custom Facets using the _facet= parameter. Defaults to on. suggest_facets - should Datasette suggest facets? Defaults to on. allow_download - should users be allowed to download the entire SQLite database? Defaults to on. allow_sql - should users be allowed to execute custom SQL queries? Defaults to on. default_cache_ttl - Default HTTP caching max-age header in seconds. Defaults to 365 days - caching can be disabled entirely by settings this to 0. cache_size_kb - Set the amount of memory SQLite uses for its per-connection cache , in KB. allow_csv_stream - allow users to stream entire result sets as a single CSV file. Defaults to on. max_csv_mb - maximum size of a returned CSV file in MB. Defaults to 100MB, set to 0 to disable this limit.",674, 461,Foreign key expansions,"When Datasette detects a foreign key reference it attempts to resolve a label for that reference (automatically or using the Specifying the label column for a table metadata option) so it can display a link to the associated row. This expansion is now also available for JSON and CSV representations of the table, using the new _labels=on query string option. See Expanding foreign key references for more details.",674, 460,CSV export,"Any Datasette table, view or custom SQL query can now be exported as CSV. Check out the CSV export documentation for more details, or try the feature out on https://fivethirtyeight.datasettes.com/fivethirtyeight/bechdel%2Fmovies If your table has more than max_returned_rows (default 1,000) Datasette provides the option to stream all rows . This option takes advantage of async Python and Datasette's efficient pagination to iterate through the entire matching result set and stream it back as a downloadable CSV file.",674, 459,0.23 (2018-06-18),"This release features CSV export, improved options for foreign key expansions, new configuration settings and improved support for SpatiaLite. See datasette/compare/0.22.1...0.23 for a full list of commits added since the last release.",674, 458,0.23.1 (2018-06-21),"Minor bugfix release. Correctly display empty strings in HTML table, closes #314 Allow ""."" in database filenames, closes #302 404s ending in slash redirect to remove that slash, closes #309 Fixed incorrect display of compound primary keys with foreign key references. Closes #319 Docs + example of canned SQL query using || concatenation. Closes #321 Correctly display facets with value of 0 - closes #318 Default 'expand labels' to checked in CSV advanced export",674, 457,0.23.2 (2018-07-07),"Minor bugfix and documentation release. CSV export now respects --cors , fixes #326 Installation instructions , including docker image - closes #328 Fix for row pages for tables with / in, closes #325",674, 456,0.24 (2018-07-23),"A number of small new features: datasette publish heroku now supports --extra-options , fixes #334 Custom error message if SpatiaLite is needed for specified database, closes #331 New config option: truncate_cells_html for truncating long cell values in HTML view - closes #330 Documentation for datasette publish and datasette package , closes #337 Fixed compatibility with Python 3.7 datasette publish heroku now supports app names via the -n option, which can also be used to overwrite an existing application [Russ Garrett] Title and description metadata can now be set for canned SQL queries , closes #342 New force_https_on config option, fixes https:// API URLs when deploying to Zeit Now - closes #333 ?_json_infinity=1 query string argument for handling Infinity/-Infinity values in JSON, closes #332 URLs displayed in the results of custom SQL queries are now URLified, closes #298",674, 455,0.25 (2018-09-19),"New plugin hooks, improved database view support and an easier way to use more recent versions of SQLite. New publish_subcommand plugin hook. A plugin can now add additional datasette publish publishers in addition to the default now and heroku , both of which have been refactored into default plugins. publish_subcommand documentation . Closes #349 New render_cell plugin hook. Plugins can now customize how values are displayed in the HTML tables produced by Datasette's browsable interface. datasette-json-html and datasette-render-images are two new plugins that use this hook. render_cell documentation . Closes #352 New extra_body_script plugin hook, enabling plugins to provide additional JavaScript that should be added to the page footer. extra_body_script documentation . extra_css_urls and extra_js_urls hooks now take additional optional parameters, allowing them to be more selective about which pages they apply to. Documentation . You can now use the sortable_columns metadata setting to explicitly enable sort-by-column in the interface for database views, as well as for specific tables. The new fts_table and fts_pk metadata settings can now be used to explicitly configure full-text search for a table or a view , even if that table is not directly coupled to the SQLite FTS feature in the database schema itself. Datasette will now use pysqlite3 in place of the standard library sqlite3 module if it has been installed in the current environment. This makes it much easier to run Datasette against a more recent version of SQLite, including the just-released SQLite 3.25.0 which adds window function support. More details on how to use this in #360 New mechanism that allows plugin configuration options to be set using metadata.json .",674, 454,0.25.1 (2018-11-04),"Documentation improvements plus a fix for publishing to Zeit Now. datasette publish now now uses Zeit's v1 platform, to work around the new 100MB image limit. Thanks, @slygent - closes #366 .",674, 453,0.25.2 (2018-12-16),"datasette publish heroku now uses the python-3.6.7 runtime Added documentation on how to build the documentation Added documentation covering our release process Upgraded to pytest 4.0.2",674, 452,0.26 (2019-01-02),"datasette serve --reload now restarts Datasette if a database file changes on disk. datasette publish now now takes an optional --alias mysite.now.sh argument. This will attempt to set an alias after the deploy completes. Fixed a bug where the advanced CSV export form failed to include the currently selected filters ( #393 )",674, 451,0.26.1 (2019-01-10),"/-/versions now includes SQLite compile_options ( #396 ) datasetteproject/datasette Docker image now uses SQLite 3.26.0 ( #397 ) Cleaned up some deprecation warnings under Python 3.7",674, 450,0.27 (2019-01-31),"New command: datasette plugins ( documentation ) shows you the currently installed list of plugins. Datasette can now output newline-delimited JSON using the new ?_shape=array&_nl=on query string option. Added documentation on The Datasette Ecosystem . Now using Python 3.7.2 as the base for the official Datasette Docker image .",674, 449,0.27.1 (2019-05-09),"Tiny bugfix release: don't install tests/ in the wrong place. Thanks, Veit Heller.",674, 448,Small changes,"We now show the size of the database file next to the download link ( #172 ) New /-/databases introspection page shows currently connected databases ( #470 ) Binary data is no longer displayed on the table and row pages ( #442 - thanks, Russ Garrett) New show/hide SQL links on custom query pages ( #415 ) The extra_body_script plugin hook now accepts an optional view_name argument ( #443 - thanks, Russ Garrett) Bumped Jinja2 dependency to 2.10.1 ( #426 ) All table filters are now documented, and documentation is enforced via unit tests ( 2c19a27 ) New project guideline: master should stay shippable at all times! ( 31f36e1 ) Fixed a bug where sqlite_timelimit() occasionally failed to clean up after itself ( bac4e01 ) We no longer load additional plugins when executing pytest ( #438 ) Homepage now links to database views if there are less than five tables in a database ( #373 ) The --cors option is now respected by error pages ( #453 ) datasette publish heroku now uses the --include-vcs-ignore option, which means it works under Travis CI ( #407 ) datasette publish heroku now publishes using Python 3.6.8 ( 666c374 ) Renamed datasette publish now to datasette publish nowv1 ( #472 ) datasette publish nowv1 now accepts multiple --alias parameters ( 09ef305 ) Removed the datasette skeleton command ( #476 ) The documentation on how to build the documentation now recommends sphinx-autobuild",674, 447,Medium changes,"Datasette now conforms to the Black coding style ( #449 ) - and has a unit test to enforce this in the future New Special table arguments : ?columnname__in=value1,value2,value3 filter for executing SQL IN queries against a table, see Table arguments ( #433 ) ?columnname__date=yyyy-mm-dd filter which returns rows where the spoecified datetime column falls on the specified date ( 583b22a ) ?tags__arraycontains=tag filter which acts against a JSON array contained in a column ( 78e45ea ) ?_where=sql-fragment filter for the table view ( #429 ) ?_fts_table=mytable and ?_fts_pk=mycolumn query string options can be used to specify which FTS table to use for a search query - see Configuring full-text search for a table or view ( #428 ) You can now pass the same table filter multiple times - for example, ?content__not=world&content__not=hello will return all rows where the content column is neither hello or world ( #288 ) You can now specify about and about_url metadata (in addition to source and license ) linking to further information about a project - see Source, license and about New ?_trace=1 parameter now adds debug information showing every SQL query that was executed while constructing the page ( #435 ) datasette inspect now just calculates table counts, and does not introspect other database metadata ( #462 ) Removed /-/inspect page entirely - this will be replaced by something similar in the future, see #465 Datasette can now run against an in-memory SQLite database. You can do this by starting it without passing any files or by using the new --memory option to datasette serve . This can be useful for experimenting with SQLite queries that do not access any data, such as SELECT 1+1 or SELECT sqlite_version() .",674, 446,register_output_renderer plugins,"Russ Garrett implemented a new Datasette plugin hook called register_output_renderer ( #441 ) which allows plugins to create additional output renderers in addition to Datasette's default .json and .csv . Russ's in-development datasette-geo plugin includes an example of this hook being used to output .geojson automatically converted from SpatiaLite.",674, 445,datasette publish cloudrun,"Google Cloud Run is a brand new serverless hosting platform from Google, which allows you to build a Docker container which will run only when HTTP traffic is received and will shut down (and hence cost you nothing) the rest of the time. It's similar to Zeit's Now v1 Docker hosting platform which sadly is no longer accepting signups from new users. The new datasette publish cloudrun command was contributed by Romain Primet ( #434 ) and publishes selected databases to a new Datasette instance running on Google Cloud Run. See Publishing to Google Cloud Run for full documentation.",674, 444,"Faceting improvements, and faceting plugins","Datasette Facets provide an intuitive way to quickly summarize and interact with data. Previously the only supported faceting technique was column faceting, but 0.28 introduces two powerful new capabilities: facet-by-JSON-array and the ability to define further facet types using plugins. Facet by array ( #359 ) is only available if your SQLite installation provides the json1 extension. Datasette will automatically detect columns that contain JSON arrays of values and offer a faceting interface against those columns - useful for modelling things like tags without needing to break them out into a new table. See Facet by JSON array for more. The new register_facet_classes() plugin hook ( #445 ) can be used to register additional custom facet classes. Each facet class should provide two methods: suggest() which suggests facet selections that might be appropriate for a provided SQL query, and facet_results() which executes a facet operation and returns results. Datasette's own faceting implementations have been refactored to use the same API as these plugins.",674, 443,Supporting databases that change,"From the beginning of the project, Datasette has been designed with read-only databases in mind. If a database is guaranteed not to change it opens up all kinds of interesting opportunities - from taking advantage of SQLite immutable mode and HTTP caching to bundling static copies of the database directly in a Docker container. The interesting ideas in Datasette explores this idea in detail. As my goals for the project have developed, I realized that read-only databases are no longer the right default. SQLite actually supports concurrent access very well provided only one thread attempts to write to a database at a time, and I keep encountering sensible use-cases for running Datasette on top of a database that is processing inserts and updates. So, as-of version 0.28 Datasette no longer assumes that a database file will not change. It is now safe to point Datasette at a SQLite database which is being updated by another process. Making this change was a lot of work - see tracking tickets #418 , #419 and #420 . It required new thinking around how Datasette should calculate table counts (an expensive operation against a large, changing database) and also meant reconsidering the ""content hash"" URLs Datasette has used in the past to optimize the performance of HTTP caches. Datasette can still run against immutable files and gains numerous performance benefits from doing so, but this is no longer the default behaviour. Take a look at the new Performance and caching documentation section for details on how to make the most of Datasette against data that you know will be staying read-only and immutable.",674, 442,0.28 (2019-05-19),A salmagundi of new features!,674, 441,Small changes,"Databases published using datasette publish now open in Immutable mode . ( #469 ) ?col__date= now works for columns containing spaces Automatic label detection (for deciding which column to show when linking to a foreign key) has been improved. ( #485 ) Fixed bug where pagination broke when combined with an expanded foreign key. ( #489 ) Contributors can now run pip install -e .[docs] to get all of the dependencies needed to build the documentation, including cd docs && make livehtml support. Datasette's dependencies are now all specified using the ~= match operator. ( #532 ) white-space: pre-wrap now used for table creation SQL. ( #505 ) Full list of commits between 0.28 and 0.29.",674, 440,?_through= for joins through many-to-many tables,"The new ?_through={json} argument to the Table view allows records to be filtered based on a many-to-many relationship. See Special table arguments for full documentation - here's an example . ( #355 ) This feature was added to help support facet by many-to-many , which isn't quite ready yet but will be coming in the next Datasette release.",674, 439,Easier custom templates for table rows,"If you want to customize the display of individual table rows, you can do so using a _table.html template include that looks something like this: {% for row in display_rows %}

{{ row[""title""] }}

{{ row[""description""] }}

Category: {{ row.display(""category_id"") }}

{% endfor %} This is a backwards incompatible change . If you previously had a custom template called _rows_and_columns.html you need to rename it to _table.html . See Custom templates for full details.",674, 438,Facet by date,"If a column contains datetime values, Datasette can now facet that column by date. ( #481 )",674, 437,Secret plugin configuration options,"Plugins like datasette-auth-github need a safe way to set secret configuration options. Since the default mechanism for configuring plugins exposes those settings in /-/metadata a new mechanism was needed. Secret configuration values describes how plugins can now specify that their settings should be read from a file or an environment variable: { ""plugins"": { ""datasette-auth-github"": { ""client_secret"": { ""$env"": ""GITHUB_CLIENT_SECRET"" } } } } These plugin secrets can be set directly using datasette publish . See Custom metadata and plugins for details. ( #538 and #543 )",674, 436,New plugin hook: extra_template_vars,"The extra_template_vars(template, database, table, columns, view_name, request, datasette) plugin hook allows plugins to inject their own additional variables into the Datasette template context. This can be used in conjunction with custom templates to customize the Datasette interface. datasette-auth-github uses this hook to add custom HTML to the new top navigation bar (which is designed to be modified by plugins, see #540 ).",674, 435,New plugin hook: asgi_wrapper,"The asgi_wrapper(datasette) plugin hook allows plugins to entirely wrap the Datasette ASGI application in their own ASGI middleware. ( #520 ) Two new plugins take advantage of this hook: datasette-auth-github adds a authentication layer: users will have to sign in using their GitHub account before they can view data or interact with Datasette. You can also use it to restrict access to specific GitHub users, or to members of specified GitHub organizations or teams . datasette-cors allows you to configure CORS headers for your Datasette instance. You can use this to enable JavaScript running on a whitelisted set of domains to make fetch() calls to the JSON API provided by your Datasette instance.",674, 434,ASGI,"ASGI is the Asynchronous Server Gateway Interface standard. I've been wanting to convert Datasette into an ASGI application for over a year - Port Datasette to ASGI #272 tracks thirteen months of intermittent development - but with Datasette 0.29 the change is finally released. This also means Datasette now runs on top of Uvicorn and no longer depends on Sanic . I wrote about the significance of this change in Porting Datasette to ASGI, and Turtles all the way down . The most exciting consequence of this change is that Datasette plugins can now take advantage of the ASGI standard.",674, 433,0.29 (2019-07-07),"ASGI, new plugin hooks, facet by date and much, much more...",674, 432,0.29.1 (2019-07-11),"Fixed bug with static mounts using relative paths which could lead to traversal exploits ( #555 ) - thanks Abdussamet Kocak! Datasette can now be run as a module: python -m datasette ( #556 ) - thanks, Abdussamet Kocak!",674, 431,0.29.2 (2019-07-13),"Bumped Uvicorn to 0.8.4, fixing a bug where the query string was not included in the server logs. ( #559 ) Fixed bug where the navigation breadcrumbs were not displayed correctly on the page for a custom query. ( #558 ) Fixed bug where custom query names containing unicode characters caused errors.",674, 430,0.29.3 (2019-09-02),"Fixed implementation of CodeMirror on database page ( #560 ) Documentation typo fixes - thanks, Min ho Kim ( #561 ) Mechanism for detecting if a table has FTS enabled now works if the table name used alternative escaping mechanisms ( #570 ) - for compatibility with a recent change to sqlite-utils .",674, 429,0.30 (2019-10-18),"Added /-/threads debugging page Allow EXPLAIN WITH... ( #583 ) Button to format SQL - thanks, Tobias Kunze ( #136 ) Sort databases on homepage by argument order - thanks, Tobias Kunze ( #585 ) Display metadata footer on custom SQL queries - thanks, Tobias Kunze ( #589 ) Use --platform=managed for publish cloudrun ( #587 ) Fixed bug returning non-ASCII characters in CSV ( #584 ) Fix for /foo v.s. /foo-bar bug ( #601 )",674, 428,0.30.1 (2019-10-30),"Fixed bug where ?_where= parameter was not persisted in hidden form fields ( #604 ) Fixed bug with .JSON representation of row pages - thanks, Chris Shaw ( #603 )",674, 427,0.30.2 (2019-11-02),"/-/plugins page now uses distribution name e.g. datasette-cluster-map instead of the name of the underlying Python package ( datasette_cluster_map ) ( #606 ) Array faceting is now only suggested for columns that contain arrays of strings ( #562 ) Better documentation for the --host argument ( #574 ) Don't show None with a broken link for the label on a nullable foreign key ( #406 )",674, 426,0.31 (2019-11-11),"This version adds compatibility with Python 3.8 and breaks compatibility with Python 3.5. If you are still running Python 3.5 you should stick with 0.30.2 , which you can install like this: pip install datasette==0.30.2 Format SQL button now works with read-only SQL queries - thanks, Tobias Kunze ( #602 ) New ?column__notin=x,y,z filter for table views ( #614 ) Table view now uses select col1, col2, col3 instead of select * Database filenames can now contain spaces - thanks, Tobias Kunze ( #590 ) Removed obsolete ?_group_count=col feature ( #504 ) Improved user interface and documentation for datasette publish cloudrun ( #608 ) Tables with indexes now show the CREATE INDEX statements on the table page ( #618 ) Current version of uvicorn is now shown on /-/versions Python 3.8 is now supported! ( #622 ) Python 3.5 is no longer supported.",674, 425,0.31.1 (2019-11-12),Deployments created using datasette publish now use python:3.8 base Docker image ( #629 ),674, 424,0.31.2 (2019-11-13),"Fixed a bug where datasette publish heroku applications failed to start ( #633 ) Fix for datasette publish with just --source_url - thanks, Stanley Zheng ( #572 ) Deployments to Heroku now use Python 3.8.0 ( #632 )",674, 423,0.32 (2019-11-14),"Datasette now renders templates using Jinja async mode . This means plugins can provide custom template functions that perform asynchronous actions, for example the new datasette-template-sql plugin which allows custom templates to directly execute SQL queries and render their results. ( #628 )",674, 422,0.33 (2019-12-22),"rowid is now included in dropdown menus for filtering tables ( #636 ) Columns are now only suggested for faceting if they have at least one value with more than one record ( #638 ) Queries with no results now display ""0 results"" ( #637 ) Improved documentation for the --static option ( #641 ) asyncio task information is now included on the /-/threads debug page Bumped Uvicorn dependency 0.11 You can now use --port 0 to listen on an available port New template_debug setting for debugging templates, e.g. https://latest.datasette.io/fixtures/roadside_attractions?_context=1 ( #654 )",674, 421,0.34 (2020-01-29),"_search= queries are now correctly escaped using a new escape_fts() custom SQL function. This means you can now run searches for strings like park. without seeing errors. ( #651 ) Google Cloud Run is no longer in beta, so datasette publish cloudrun has been updated to work even if the user has not installed the gcloud beta components package. Thanks, Katie McLaughlin ( #660 ) datasette package now accepts a --port option for specifying which port the resulting Docker container should listen on. ( #661 )",674, 420,0.35 (2020-02-04),"Added five new plugins and one new conversion tool to the The Datasette Ecosystem . The Datasette class has a new render_template() method which can be used by plugins to render templates using Datasette's pre-configured Jinja templating library. You can now execute SQL queries that start with a -- comment - thanks, Jay Graves ( #653 )",674, 419,0.36 (2020-02-21),"The datasette object passed to plugins now has API documentation: Datasette class . ( #576 ) New methods on datasette : .add_database() and .remove_database() - documentation . ( #671 ) prepare_connection() plugin hook now takes optional datasette and database arguments - prepare_connection(conn, database, datasette) . ( #678 ) Added three new plugins and one new conversion tool to the The Datasette Ecosystem .",674, 418,0.37 (2020-02-25),"Plugins now have a supported mechanism for writing to a database, using the new .execute_write() and .execute_write_fn() methods. Documentation . ( #682 ) Immutable databases that have had their rows counted using the inspect command now use the calculated count more effectively - thanks, Kevin Keogh. ( #666 ) --reload no longer restarts the server if a database file is modified, unless that database was opened immutable mode with -i . ( #494 ) New ?_searchmode=raw option turns off escaping for FTS queries in ?_search= allowing full use of SQLite's FTS5 query syntax . ( #676 )",674, 417,0.37.1 (2020-03-02),"Don't attempt to count table rows to display on the index page for databases > 100MB. ( #688 ) Print exceptions if they occur in the write thread rather than silently swallowing them. Handle the possibility of scope[""path""] being a string rather than bytes Better documentation for the extra_template_vars(template, database, table, columns, view_name, request, datasette) plugin hook.",674, 416,0.38 (2020-03-08),"The Docker build of Datasette now uses SQLite 3.31.1, upgraded from 3.26. ( #695 ) datasette publish cloudrun now accepts an optional --memory=2Gi flag for setting the Cloud Run allocated memory to a value other than the default (256Mi). ( #694 ) Fixed bug where templates that shipped with plugins were sometimes not being correctly loaded. ( #697 )",674, 415,0.39 (2020-03-24),"New base_url configuration setting for serving up the correct links while running Datasette under a different URL prefix. ( #394 ) New metadata settings ""sort"" and ""sort_desc"" for setting the default sort order for a table. See Setting a default sort order . ( #702 ) Sort direction arrow now displays by default on the primary key. This means you only have to click once (not twice) to sort in reverse order. ( #677 ) New await Request(scope, receive).post_vars() method for accessing POST form variables. ( #700 ) Plugin hooks documentation now links to example uses of each plugin. ( #709 )",674, 414,0.40 (2020-04-21),"Datasette Metadata can now be provided as a YAML file as an optional alternative to JSON. ( #713 ) Removed support for datasette publish now , which used the the now-retired Zeit Now v1 hosting platform. A new plugin, datasette-publish-now , can be installed to publish data to Zeit ( now Vercel ) Now v2. ( #710 ) Fixed a bug where the extra_template_vars(request, view_name) plugin hook was not receiving the correct view_name . ( #716 ) Variables added to the template context by the extra_template_vars() plugin hook are now shown in the ?_context=1 debugging mode (see template_debug ). ( #693 ) Fixed a bug where the ""templates considered"" HTML comment was no longer being displayed. ( #689 ) Fixed a datasette publish bug where --plugin-secret would over-ride plugin configuration in the provided metadata.json file. ( #724 ) Added a new CSS class for customizing the canned query page. ( #727 )",674, 413,0.41 (2020-05-06),"You can now create custom pages within your Datasette instance using a custom template file. For example, adding a template file called templates/pages/about.html will result in a new page being served at /about on your instance. See the custom pages documentation for full details, including how to return custom HTTP headers, redirects and status codes. ( #648 ) Configuration directory mode ( #731 ) allows you to define a custom Datasette instance as a directory. So instead of running the following: datasette one.db two.db \ --metadata=metadata.json \ --template-dir=templates/ \ --plugins-dir=plugins \ --static css:css You can instead arrange your files in a single directory called my-project and run this: datasette my-project/ Also in this release: New NOT LIKE table filter: ?colname__notlike=expression . ( #750 ) Datasette now has a pattern portfolio at /-/patterns - e.g. https://latest.datasette.io/-/patterns . This is a page that shows every Datasette user interface component in one place, to aid core development and people building custom CSS themes. ( #151 ) SQLite PRAGMA functions such as pragma_table_info(tablename) are now allowed in Datasette SQL queries. ( #761 ) Datasette pages now consistently return a content-type of text/html; charset=utf-8"" . ( #752 ) Datasette now handles an ASGI raw_path value of None , which should allow compatibility with the Mangum adapter for running ASGI apps on AWS Lambda. Thanks, Colin Dellow. ( #719 ) Installation documentation now covers how to Using pipx . ( #756 ) Improved the documentation for Full-text search . ( #748 )",674, 412,0.42 (2020-05-08),"A small release which provides improved internal methods for use in plugins, along with documentation. See #685 . Added documentation for db.execute() , see await db.execute(sql, ...) . Renamed db.execute_against_connection_in_thread() to db.execute_fn() and made it a documented method, see await db.execute_fn(fn) . New results.first() and results.single_value() methods, plus documentation for the Results class - see Results .",674, 411,0.43 (2020-05-28),"The main focus of this release is a major upgrade to the register_output_renderer(datasette) plugin hook, which allows plugins to provide new output formats for Datasette such as datasette-atom and datasette-ics . Redesign of register_output_renderer(datasette) to provide more context to the render callback and support an optional ""can_render"" callback that controls if a suggested link to the output format is provided. ( #581 , #770 ) Visually distinguish float and integer columns - useful for figuring out why order-by-column might be returning unexpected results. ( #729 ) The Request object , which is passed to several plugin hooks, is now documented. ( #706 ) New metadata.json option for setting a custom default page size for specific tables and views, see Setting a custom page size . ( #751 ) Canned queries can now be configured with a default URL fragment hash, useful when working with plugins such as datasette-vega , see Additional canned query options . ( #706 ) Fixed a bug in datasette publish when running on operating systems where the /tmp directory lives in a different volume, using a backport of the Python 3.8 shutil.copytree() function. ( #744 ) Every plugin hook is now covered by the unit tests, and a new unit test checks that each plugin hook has at least one corresponding test. ( #771 , #773 )",674, 410,The road to Datasette 1.0,"I've assembled a milestone for Datasette 1.0 . The focus of the 1.0 release will be the following: Signify confidence in the quality/stability of Datasette Give plugin authors confidence that their plugins will work for the whole 1.x release cycle Provide the same confidence to developers building against Datasette JSON APIs If you have thoughts about what you would like to see for Datasette 1.0 you can join the conversation on issue #519 .",674, 409,Smaller changes,"New internals documentation for Request object and Response class . ( #706 ) request.url now respects the force_https_urls config setting. closes ( #781 ) request.args.getlist() returns [] if missing. Removed request.raw_args entirely. ( #774 ) New datasette.get_database() method. Added _ prefix to many private, undocumented methods of the Datasette class. ( #576 ) Removed the db.get_outbound_foreign_keys() method which duplicated the behaviour of db.foreign_keys_for_table() . New await datasette.permission_allowed() method. /-/actor debugging endpoint for viewing the currently authenticated actor. New request.cookies property. /-/plugins endpoint now shows a list of hooks implemented by each plugin, e.g. https://latest.datasette.io/-/plugins?all=1 request.post_vars() method no longer discards empty values. New ""params"" canned query key for explicitly setting named parameters, see Canned query parameters . ( #797 ) request.args is now a MultiParams object. Fixed a bug with the datasette plugins command. ( #802 ) Nicer pattern for using make_app_client() in tests. ( #395 ) New request.actor property. Fixed broken CSS on nested 404 pages. ( #777 ) New request.url_vars property. ( #822 ) Fixed a bug with the python tests/fixtures.py command for outputting Datasette's testing fixtures database and plugins. ( #804 ) datasette publish heroku now deploys using Python 3.8.3. Added a warning that the register_facet_classes() hook is unstable and may change in the future. ( #830 ) The {""$env"": ""ENVIRONMENT_VARIBALE""} mechanism (see Secret configuration values ) now works with variables inside nested lists. ( #837 )",674, 408,register_routes() plugin hooks,"Plugins can now register new views and routes via the register_routes(datasette) plugin hook ( #819 ). View functions can be defined that accept any of the current datasette object, the current request , or the ASGI scope , send and receive objects.",674, 407,Cookie methods,"Plugins can now use the new response.set_cookie() method to set cookies. A new request.cookies method on the :ref:internals_request` can be used to read incoming cookies.",674, 406,CSRF protection,"Since writable canned queries are built using POST forms, Datasette now ships with CSRF protection ( #798 ). This applies automatically to any POST request, which means plugins need to include a csrftoken in any POST forms that they render. They can do that like so: ",674, 405,Signed values and secrets,"Both flash messages and user authentication needed a way to sign values and set signed cookies. Two new methods are now available for plugins to take advantage of this mechanism: .sign(value, namespace=""default"") and .unsign(value, namespace=""default"") . Datasette will generate a secret automatically when it starts up, but to avoid resetting the secret (and hence invalidating any cookies) every time the server restarts you should set your own secret. You can pass a secret to Datasette using the new --secret option or with a DATASETTE_SECRET environment variable. See Configuring the secret for more details. You can also set a secret when you deploy Datasette using datasette publish or datasette package - see Using secrets with datasette publish . Plugins can now sign values and verify their signatures using the datasette.sign() and datasette.unsign() methods.",674, 404,Flash messages,"Writable canned queries needed a mechanism to let the user know that the query has been successfully executed. The new flash messaging system ( #790 ) allows messages to persist in signed cookies which are then displayed to the user on the next page that they visit. Plugins can use this mechanism to display their own messages, see .add_message(request, message, type=datasette.INFO) for details. You can try out the new messages using the /-/messages debug tool, for example at https://latest.datasette.io/-/messages",674, 403,Writable canned queries,"Datasette's Canned queries feature lets you define SQL queries in metadata.json which can then be executed by users visiting a specific URL. https://latest.datasette.io/fixtures/neighborhood_search for example. Canned queries were previously restricted to SELECT , but Datasette 0.44 introduces the ability for canned queries to execute INSERT or UPDATE queries as well, using the new ""write"": true property ( #800 ): { ""databases"": { ""dogs"": { ""queries"": { ""add_name"": { ""sql"": ""INSERT INTO names (name) VALUES (:name)"", ""write"": true } } } } } See Writable canned queries for more details.",674, 402,Permissions,"Datasette also now has a built-in concept of Permissions . The permissions system answers the following question: Is this actor allowed to perform this action , optionally against this particular resource ? You can use the new ""allow"" block syntax in metadata.json (or metadata.yaml ) to set required permissions at the instance, database, table or canned query level. For example, to restrict access to the fixtures.db database to the ""root"" user: { ""databases"": { ""fixtures"": { ""allow"": { ""id"" ""root"" } } } } See Defining permissions with ""allow"" blocks for more details. Plugins can implement their own custom permission checks using the new permission_allowed(datasette, actor, action, resource) hook. A new debug page at /-/permissions shows recent permission checks, to help administrators and plugin authors understand exactly what checks are being performed. This tool defaults to only being available to the root user, but can be exposed to other users by plugins that respond to the permissions-debug permission. ( #788 )",674, 401,Authentication,"Prior to this release the Datasette ecosystem has treated authentication as exclusively the realm of plugins, most notably through datasette-auth-github . 0.44 introduces Authentication and permissions as core Datasette concepts ( #699 ). This enables different plugins to share responsibility for authenticating requests - you might have one plugin that handles user accounts and another one that allows automated access via API keys, for example. You'll need to install plugins if you want full user accounts, but default Datasette can now authenticate a single root user with the new --root command-line option, which outputs a one-time use URL to authenticate as a root actor ( #784 ): datasette fixtures.db --root http://127.0.0.1:8001/-/auth-token?token=5b632f8cd44b868df625f5a6e2185d88eea5b22237fd3cc8773f107cc4fd6477 INFO: Started server process [14973] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://127.0.0.1:8001 (Press CTRL+C to quit) Plugins can implement new ways of authenticating users using the new actor_from_request(datasette, request) hook.",674, 400,0.44 (2020-06-11),"See also Datasette 0.44: The annotated release notes . Authentication and permissions, writable canned queries, flash messages, new plugin hooks and more.",674, 399,Smaller changes,"Cascading view permissions - so if a user has view-table they can view the table page even if they do not have view-database or view-instance . ( #832 ) CSRF protection no longer applies to Authentication: Bearer token requests or requests without cookies. ( #835 ) datasette.add_message() now works inside plugins. ( #864 ) Workaround for ""Too many open files"" error in test runs. ( #846 ) Respect existing scope[""actor""] if already set by ASGI middleware. ( #854 ) New process for shipping Alpha and beta releases . ( #807 ) {{ csrftoken() }} now works when plugins render a template using datasette.render_template(..., request=request) . ( #863 ) Datasette now creates a single Request object and uses it throughout the lifetime of the current HTTP request. ( #870 )",674, 398,New plugin hooks,"register_magic_parameters(datasette) can be used to define new types of magic canned query parameters. startup(datasette) can run custom code when Datasette first starts up. datasette-init is a new plugin that uses this hook to create database tables and views on startup if they have not yet been created. ( #834 ) canned_queries(datasette, database, actor) lets plugins provide additional canned queries beyond those defined in Datasette's metadata. See datasette-saved-queries for an example of this hook in action. ( #852 ) forbidden(datasette, request, message) is a hook for customizing how Datasette responds to 403 forbidden errors. ( #812 )",674, 397,Better plugin documentation,"The plugin documentation has been re-arranged into four sections, including a brand new section on testing plugins. ( #687 ) Plugins introduces Datasette's plugin system and describes how to install and configure plugins. Writing plugins describes how to author plugins, from one-off single file plugins to packaged plugins that can be published to PyPI. It also describes how to start a plugin using the new datasette-plugin cookiecutter template. Plugin hooks is a full list of detailed documentation for every Datasette plugin hook. Testing plugins describes how to write tests for Datasette plugins, using pytest and HTTPX .",674, 396,Log out,"The ds_actor cookie can be used by plugins (or by Datasette's --root mechanism ) to authenticate users. The new /-/logout page provides a way to clear that cookie. A ""Log out"" button now shows in the global navigation provided the user is authenticated using the ds_actor cookie. ( #840 )",674, 395,Magic parameters for canned queries,"Canned queries now support Magic parameters , which can be used to insert or select automatically generated values. For example: insert into logs (user_id, timestamp) values (:_actor_id, :_now_datetime_utc) This inserts the currently authenticated actor ID and the current datetime. ( #842 )",674, 394,0.45 (2020-07-01),"See also Datasette 0.45: The annotated release notes . Magic parameters for canned queries, a log out feature, improved plugin documentation and four new plugin hooks.",674, 393,0.46 (2020-08-09),"This release contains a security fix related to authenticated writable canned queries. If you are using this feature you should upgrade as soon as possible. Security fix: CSRF tokens were incorrectly included in read-only canned query forms, which could allow them to be leaked to a sophisticated attacker. See issue 918 for details. Datasette now supports GraphQL via the new datasette-graphql plugin - see GraphQL in Datasette with the new datasette-graphql plugin . Principle git branch has been renamed from master to main . ( #849 ) New debugging tool: /-/allow-debug tool ( demo here ) helps test allow blocks against actors, as described in Defining permissions with ""allow"" blocks . ( #908 ) New logo for the documentation, and a new project tagline: ""An open source multi-tool for exploring and publishing data"". Whitespace in column values is now respected on display, using white-space: pre-wrap . ( #896 ) New await request.post_body() method for accessing the raw POST body, see Request object . ( #897 ) Database file downloads now include a content-length HTTP header, enabling download progress bars. ( #905 ) File downloads now also correctly set the suggested file name using a content-disposition HTTP header. ( #909 ) tests are now excluded from the Datasette package properly - thanks, abeyerpath. ( #456 ) The Datasette package published to PyPI now includes sdist as well as bdist_wheel . Better titles for canned query pages. ( #887 ) Now only loads Python files from a directory passed using the --plugins-dir option - thanks, Amjith Ramanujam. ( #890 ) New documentation section on Publishing to Vercel .",674, 392,0.47 (2020-08-11),"Datasette now has a GitHub discussions forum for conversations about the project that go beyond just bug reports and issues. Datasette can now be installed on macOS using Homebrew! Run brew install simonw/datasette/datasette . See Using Homebrew . ( #335 ) Two new commands: datasette install name-of-plugin and datasette uninstall name-of-plugin . These are equivalent to pip install and pip uninstall but automatically run in the same virtual environment as Datasette, so users don't have to figure out where that virtual environment is - useful for installations created using Homebrew or pipx . See Installing plugins . ( #925 ) A new command-line option, datasette --get , accepts a path to a URL within the Datasette instance. It will run that request through Datasette (without starting a web server) and print out the response. See datasette --get for an example. ( #926 )",674, 391,0.47.1 (2020-08-11),Fixed a bug where the sdist distribution of Datasette was not correctly including the template files. ( #930 ),674, 390,0.47.2 (2020-08-12),Fixed an issue with the Docker image published to Docker Hub . ( #931 ),674, 389,0.47.3 (2020-08-15),The datasette --get command-line mechanism now ensures any plugins using the startup() hook are correctly executed. ( #934 ),674, 388,0.48 (2020-08-16),"Datasette documentation now lives at docs.datasette.io . db.is_mutable property is now documented and tested, see Database introspection . The extra_template_vars , extra_css_urls , extra_js_urls and extra_body_script plugin hooks now all accept the same arguments. See extra_template_vars(template, database, table, columns, view_name, request, datasette) for details. ( #939 ) Those hooks now accept a new columns argument detailing the table columns that will be rendered on that page. ( #938 ) Fixed bug where plugins calling db.execute_write_fn() could hang Datasette if the connection failed. ( #935 ) Fixed bug with the ?_nl=on output option and binary data. ( #914 )",674, 387,0.49 (2020-09-14),"See also Datasette 0.49: The annotated release notes . Writable canned queries now expose a JSON API, see JSON API for writable canned queries . ( #880 ) New mechanism for defining page templates with custom path parameters - a template file called pages/about/{slug}.html will be used to render any requests to /about/something . See Path parameters for pages . ( #944 ) register_output_renderer() render functions can now return a Response . ( #953 ) New --upgrade option for datasette install . ( #945 ) New datasette --pdb option. ( #962 ) datasette --get exit code now reflects the internal HTTP status code. ( #947 ) New raise_404() template function for returning 404 errors. ( #964 ) datasette publish heroku now deploys using Python 3.8.5 Upgraded CodeMirror to 5.57.0. ( #948 ) Upgraded code style to Black 20.8b1. ( #958 ) Fixed bug where selected facets were not correctly persisted in hidden form fields on the table page. ( #963 ) Renamed the default error template from 500.html to error.html . Custom error pages are now documented, see Custom error pages . ( #965 )",674, 386,0.49.1 (2020-09-15),Fixed a bug with writable canned queries that use magic parameters but accept no non-magic arguments. ( #967 ),674, 385,0.50 (2020-10-09),"The key new feature in this release is the column actions menu on the table page ( #891 ). This can be used to sort a column in ascending or descending order, facet data by that column or filter the table to just rows that have a value for that column. Plugin authors can use the new datasette.client object to make internal HTTP requests from their plugins, allowing them to make use of Datasette's JSON API. ( #943 ) New Deploying Datasette documentation with guides for deploying Datasette on a Linux server using systemd or to hosting providers that support buildpacks . ( #514 , #997 ) Other improvements in this release: Publishing to Google Cloud Run documentation now covers Google Cloud SDK options. Thanks, Geoffrey Hing. ( #995 ) New datasette -o option which opens your browser as soon as Datasette starts up. ( #970 ) Datasette now sets sqlite3.enable_callback_tracebacks(True) so that errors in custom SQL functions will display tracebacks. ( #891 ) Fixed two rendering bugs with column headers in portrait mobile view. ( #978 , #980 ) New db.table_column_details(table) introspection method for retrieving full details of the columns in a specific table, see Database introspection . Fixed a routing bug with custom page wildcard templates. ( #996 ) datasette publish heroku now deploys using Python 3.8.6. New datasette publish heroku --tar= option. ( #969 ) OPTIONS requests against HTML pages no longer return a 500 error. ( #1001 ) Datasette now supports Python 3.9. See also Datasette 0.50: The annotated release notes .",674, 384,0.50.1 (2020-10-09),"Fixed a bug introduced in 0.50 where the export as JSON/CSV links on the table, row and query pages were broken. ( #1010 )",674, 383,0.50.2 (2020-10-09),Fixed another bug introduced in 0.50 where column header links on the table page were broken. ( #1011 ),674, 382,Smaller changes,"Wide tables shown within Datasette now scroll horizontally ( #998 ). This is achieved using a new
element which may impact the implementation of some plugins (for example this change to datasette-cluster-map ). New debug-menu permission. ( #1068 ) Removed --debug option, which didn't do anything. ( #814 ) Link: HTTP header pagination. ( #1014 ) x button for clearing filters. ( #1016 ) Edit SQL button on canned queries, ( #1019 ) --load-extension=spatialite shortcut. ( #1028 ) scale-in animation for column action menu. ( #1039 ) Option to pass a list of templates to .render_template() is now documented. ( #1045 ) New datasette.urls.static_plugins() method. ( #1033 ) datasette -o option now opens the most relevant page. ( #976 ) datasette --cors option now enables access to /database.db downloads. ( #1057 ) Database file downloads now implement cascading permissions, so you can download a database if you have view-database-download permission even if you do not have permission to access the Datasette instance. ( #1058 ) New documentation on Designing URLs for your plugin . ( #1053 )",674, 381,Running Datasette behind a proxy,"The base_url configuration option is designed to help run Datasette on a specific path behind a proxy - for example if you want to run an instance of Datasette at /my-datasette/ within your existing site's URL hierarchy, proxied behind nginx or Apache. Support for this configuration option has been greatly improved ( #1023 ), and guidelines for using it are now available in a new documentation section on Running Datasette behind a proxy . ( #1027 )",674, 380,URL building,"The new datasette.urls family of methods can be used to generate URLs to key pages within the Datasette interface, both within custom templates and Datasette plugins. See Building URLs within plugins for more details. ( #904 )",674, 379,Binary data,"SQLite tables can contain binary data in BLOB columns. Datasette now provides links for users to download this data directly from Datasette, and uses those links to make binary data available from CSV exports. See Binary data for more details. ( #1036 and #1034 ).",674, 378,Plugins can now add links within Datasette,"A number of existing Datasette plugins add new pages to the Datasette interface, providig tools for things like uploading CSVs , editing table schemas or configuring full-text search . Plugins like this can now link to themselves from other parts of Datasette interface. The menu_links(datasette, actor, request) hook ( #1064 ) lets plugins add links to Datasette's new top-right application menu, and the table_actions(datasette, actor, database, table, request) hook ( #1066 ) adds links to a new ""table actions"" menu on the table page. The demo at latest.datasette.io now includes some example plugins. To see the new table actions menu first sign into that demo as root and then visit the facetable table to see the new cog icon menu at the top of the page.",674, 377,New visual design,"Datasette is no longer white and grey with blue and purple links! Natalie Downe has been working on a visual refresh, the first iteration of which is included in this release. ( #1056 )",674, 376,0.51 (2020-10-31),"A new visual design, plugin hooks for adding navigation options, better handling of binary data, URL building utility methods and better support for running Datasette behind a proxy.",674, 375,0.51.1 (2020-10-31),Improvements to the new Binary data documentation page.,674, 374,0.52 (2020-11-28),"This release includes a number of changes relating to an internal rebranding effort: Datasette's configuration mechanism (things like datasette --config default_page_size:10 ) has been renamed to settings . New --setting default_page_size 10 option as a replacement for --config default_page_size:10 (note the lack of a colon). The --config option is deprecated but will continue working until Datasette 1.0. ( #992 ) The /-/config introspection page is now /-/settings , and the previous page redirects to the new one. ( #1103 ) The config.json file in Configuration directory mode is now called settings.json . ( #1104 ) The undocumented datasette.config() internal method has been replaced by a documented .setting(key) method. ( #1107 ) Also in this release: New plugin hook: database_actions(datasette, actor, database, request) , which adds menu items to a new cog menu shown at the top of the database page. ( #1077 ) datasette publish cloudrun has a new --apt-get-install option that can be used to install additional Ubuntu packages as part of the deployment. This is useful for deploying the new datasette-ripgrep plugin . ( #1110 ) Swept the documentation to remove words that minimize involved difficulty. ( #1089 ) And some bug fixes: Foreign keys linking to rows with blank label columns now display as a hyphen, allowing those links to be clicked. ( #1086 ) Fixed bug where row pages could sometimes 500 if the underlying queries exceeded a time limit. ( #1088 ) Fixed a bug where the table action menu could appear partially obscured by the edge of the page. ( #1084 )",674, 373,0.52.1 (2020-11-29),"Documentation on Testing plugins now recommends using datasette.client . ( #1102 ) Fix bug where compound foreign keys produced broken links. ( #1098 ) datasette --load-module=spatialite now also checks for /usr/local/lib/mod_spatialite.so . Thanks, Dan Peterson. ( #1114 )",674, 372,0.52.2 (2020-12-02),"Generated columns from SQLite 3.31.0 or higher are now correctly displayed. ( #1116 ) Error message if you attempt to open a SpatiaLite database now suggests using --load-extension=spatialite if it detects that the extension is available in a common location. ( #1115 ) OPTIONS requests against the /database page no longer raise a 500 error. ( #1100 ) Databases larger than 32MB that are published to Cloud Run can now be downloaded. ( #749 ) Fix for misaligned cog icon on table and database pages. Thanks, Abdussamet Koçak. ( #1121 )",674, 371,0.52.3 (2020-12-03),Fixed bug where static assets would 404 for Datasette installed on ARM Amazon Linux. ( #1124 ),674, 370,0.52.4 (2020-12-05),"Show pysqlite3 version on /-/versions , if installed. ( #1125 ) Errors output by Datasette (e.g. for invalid SQL queries) now go to stderr , not stdout . ( #1131 ) Fix for a startup error on windows caused by unnecessary from os import EX_CANTCREAT - thanks, Abdussamet Koçak. ( #1094 )",674, 369,0.52.5 (2020-12-09),Fix for error caused by combining the _searchmode=raw and ?_search_COLUMN parameters. ( #1134 ),674, 368,0.53 (2020-12-10),"Datasette has an official project website now, at https://datasette.io/ . This release mainly updates the documentation to reflect the new site. New ?column__arraynotcontains= table filter. ( #1132 ) datasette serve has a new --create option, which will create blank database files if they do not already exist rather than exiting with an error. ( #1135 ) New ?_header=off option for CSV export which omits the CSV header row, documented here . ( #1133 ) ""Powered by Datasette"" link in the footer now links to https://datasette.io/ . ( #1138 ) Project news no longer lives in the README - it can now be found at https://datasette.io/news . ( #1137 )",674, 367,Other changes,"Datasette can now open multiple database files with the same name, e.g. if you run datasette path/to/one.db path/to/other/one.db . ( #509 ) datasette publish cloudrun now sets force_https_urls for every deployment, fixing some incorrect http:// links. ( #1178 ) Fixed a bug in the example nginx configuration in Running Datasette behind a proxy . ( #1091 ) The Datasette Ecosystem documentation page has been reduced in size in favour of the datasette.io tools and plugins directories. ( #1182 ) The request object now provides a request.full_path property, which returns the path including any query string. ( #1184 ) Better error message for disallowed PRAGMA clauses in SQL queries. ( #1185 ) datasette publish heroku now deploys using python-3.8.7 . New plugin testing documentation on Testing outbound HTTP calls with pytest-httpx . ( #1198 ) All ?_* query string parameters passed to the table page are now persisted in hidden form fields, so parameters such as ?_size=10 will be correctly passed to the next page when query filters are changed. ( #1194 ) Fixed a bug loading a database file called test-database (1).sqlite . ( #1181 )",674, 366,Code formatting with Black and Prettier,"Datasette adopted Black for opinionated Python code formatting in June 2019. Datasette now also embraces Prettier for JavaScript formatting, which like Black is enforced by tests in continuous integration. Instructions for using these two tools can be found in the new section on Code formatting in the contributors documentation. ( #1167 )",674, 365,JavaScript modules,"JavaScript modules were introduced in ECMAScript 2015 and provide native browser support for the import and export keywords. To use modules, JavaScript needs to be included in element: @hookimpl def extra_body_script(): return { ""module"": True, ""script"": ""console.log('Your JavaScript goes here...')"", } This will add the following to the end of your page: Example: datasette-cluster-map",674, 84,"extra_js_urls(template, database, table, columns, view_name, request, datasette)","This takes the same arguments as extra_template_vars(...) This works in the same way as extra_css_urls() but for JavaScript. You can return a list of URLs, a list of dictionaries or an awaitable function that returns those things: from datasette import hookimpl @hookimpl def extra_js_urls(): return [ { ""url"": ""https://code.jquery.com/jquery-3.3.1.slim.min.js"", ""sri"": ""sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo"", } ] You can also return URLs to files from your plugin's static/ directory, if you have one: @hookimpl def extra_js_urls(): return [""/-/static-plugins/your-plugin/app.js""] Note that your-plugin here should be the hyphenated plugin name - the name that is displayed in the list on the /-/plugins debug page. If your code uses JavaScript modules you should include the ""module"": True key. See Custom CSS and JavaScript for more details. @hookimpl def extra_js_urls(): return [ { ""url"": ""/-/static-plugins/your-plugin/app.js"", ""module"": True, } ] Examples: datasette-cluster-map , datasette-vega",674, 83,"extra_css_urls(template, database, table, columns, view_name, request, datasette)","This takes the same arguments as extra_template_vars(...) Return a list of extra CSS URLs that should be included on the page. These can take advantage of the CSS class hooks described in Custom pages and templates . This can be a list of URLs: from datasette import hookimpl @hookimpl def extra_css_urls(): return [ ""https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css"" ] Or a list of dictionaries defining both a URL and an SRI hash : @hookimpl def extra_css_urls(): return [ { ""url"": ""https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css"", ""sri"": ""sha384-9gVQ4dYFwwWSjIDZnLEWnxCjeSWFphJiwGPXr1jddIhOegiu1FwO5qRGvFXOdJZ4"", } ] This function can also return an awaitable function, useful if it needs to run any async code: @hookimpl def extra_css_urls(datasette): async def inner(): db = datasette.get_database() results = await db.execute( ""select url from css_files"" ) return [r[0] for r in results] return inner Examples: datasette-cluster-map , datasette-vega",674, 82,"extra_template_vars(template, database, table, columns, view_name, request, datasette)","Extra template variables that should be made available in the rendered template context. template - string The template that is being rendered, e.g. database.html database - string or None The name of the database, or None if the page does not correspond to a database (e.g. the root page) table - string or None The name of the table, or None if the page does not correct to a table columns - list of strings or None The names of the database columns that will be displayed on this page. None if the page does not contain a table. view_name - string The name of the view being displayed. ( index , database , table , and row are the most important ones.) request - Request object or None The current HTTP request. This can be None if the request object is not available. datasette - Datasette class You can use this to access plugin configuration options via datasette.plugin_config(your_plugin_name) This hook can return one of three different types: Dictionary If you return a dictionary its keys and values will be merged into the template context. Function that returns a dictionary If you return a function it will be executed. If it returns a dictionary those values will will be merged into the template context. Function that returns an awaitable function that returns a dictionary You can also return a function which returns an awaitable function which returns a dictionary. Datasette runs Jinja2 in async mode , which means you can add awaitable functions to the template scope and they will be automatically awaited when they are rendered by the template. Here's an example plugin that adds a ""user_agent"" variable to the template context containing the current request's User-Agent header: @hookimpl def extra_template_vars(request): return {""user_agent"": request.headers.get(""user-agent"")} This example returns an awaitable function which adds a list of hidden_table_names to the context: @hookimpl def extra_template_vars(datasette, database): async def hidden_table_names(): if database: db = datasette.databases[database] return { ""hidden_table_names"": await db.hidden_table_names() } else: return {} return hidden_table_names And here's an example which adds a sql_first(sql_query) function which executes a SQL statement and returns the first column of the first row of results: @hookimpl def extra_template_vars(datasette, database): async def sql_first(sql, dbname=None): dbname = ( dbname or database or next(iter(datasette.databases.keys())) ) result = await datasette.execute(dbname, sql) return result.rows[0][0] return {""sql_first"": sql_first} You can then use the new function in a template like so: SQLite version: {{ sql_first(""select sqlite_version()"") }} Examples: datasette-search-all , datasette-template-sql",674, 81,Page extras,These plugin hooks can be used to affect the way HTML pages for different Datasette interfaces are rendered.,674, 80,"prepare_jinja2_environment(env, datasette)","env - jinja2 Environment The template environment that is being prepared datasette - Datasette class You can use this to access plugin configuration options via datasette.plugin_config(your_plugin_name) This hook is called with the Jinja2 environment that is used to evaluate Datasette HTML templates. You can use it to do things like register custom template filters , for example: from datasette import hookimpl @hookimpl def prepare_jinja2_environment(env): env.filters[""uppercase""] = lambda u: u.upper() You can now use this filter in your custom templates like so: Table name: {{ table|uppercase }} This function can return an awaitable function if it needs to run any async code. Examples: datasette-edit-templates",674, 79,"prepare_connection(conn, database, datasette)","conn - sqlite3 connection object The connection that is being opened database - string The name of the database datasette - Datasette class You can use this to access plugin configuration options via datasette.plugin_config(your_plugin_name) This hook is called when a new SQLite database connection is created. You can use it to register custom SQL functions , aggregates and collations. For example: from datasette import hookimpl import random @hookimpl def prepare_connection(conn): conn.create_function( ""random_integer"", 2, random.randint ) This registers a SQL function called random_integer which takes two arguments and can be called like this: select random_integer(1, 10); Examples: datasette-jellyfish , datasette-jq , datasette-haversine , datasette-rure",674, 78,Plugin hooks,"Datasette plugins use plugin hooks to customize Datasette's behavior. These hooks are powered by the pluggy plugin system. 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. When you implement a plugin hook you can accept any or all of the parameters that are documented as being passed to that hook. 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) : @hookimpl def render_cell(value, column): if column == ""stars"": return ""*"" * int(value) List of plugin hooks prepare_connection(conn, database, datasette) prepare_jinja2_environment(env, datasette) Page extras extra_template_vars(template, database, table, columns, view_name, request, datasette) extra_css_urls(template, database, table, columns, view_name, request, datasette) extra_js_urls(template, database, table, columns, view_name, request, datasette) extra_body_script(template, database, table, columns, view_name, request, datasette) publish_subcommand(publish) render_cell(row, value, column, table, database, datasette, request) register_output_renderer(datasette) register_routes(datasette) register_commands(cli) register_facet_classes() register_permissions(datasette) asgi_wrapper(datasette) startup(datasette) canned_queries(datasette, database, actor) actor_from_request(datasette, request) actors_from_ids(datasette, actor_ids) jinja2_environment_from_request(datasette, request, env) filters_from_request(request, database, table, datasette) permission_allowed(datasette, actor, action, resource) register_magic_parameters(datasette) forbidden(datasette, request, message) handle_exception(datasette, request, exception) skip_csrf(datasette, scope) get_metadata(datasette, key, database, table) menu_links(datasette, actor, request) Action hooks table_actions(datasette, actor, database, table, request) view_actions(datasette, actor, database, view, request) query_actions(datasette, actor, database, query_name, request, sql, params) row_actions(datasette, actor, request, database, table, row) database_actions(datasette, actor, database, request) homepage_actions(datasette, actor, request) Template slots top_homepage(datasette, request) top_database(datasette, request, database) top_table(datasette, request, database, table) top_row(datasette, request, database, table, row) top_query(datasette, request, database, sql) top_canned_query(datasette, request, database, query_name) Event tracking track_event(datasette, event) register_events(datasette)",674, 77,datasette create-token,"Create a signed API token, see datasette create-token . [[[cog help([""create-token"", ""--help""]) ]]] Usage: datasette create-token [OPTIONS] ID Create a signed API token for the specified actor ID Example: datasette create-token root --secret mysecret To allow only ""view-database-download"" for all databases: datasette create-token root --secret mysecret \ --all view-database-download To allow ""create-table"" against a specific database: datasette create-token root --secret mysecret \ --database mydb create-table To allow ""insert-row"" against a specific table: datasette create-token root --secret myscret \ --resource mydb mytable insert-row Restricted actions can be specified multiple times using multiple --all, --database, and --resource options. Add --debug to see a decoded version of the token. Options: --secret TEXT Secret used for signing the API tokens [required] -e, --expires-after INTEGER Token should expire after this many seconds -a, --all ACTION Restrict token to this action -d, --database DB ACTION Restrict token to this action on this database -r, --resource DB RESOURCE ACTION Restrict token to this action on this database resource (a table, SQL view or named query) --debug Show decoded token --plugins-dir DIRECTORY Path to directory containing custom plugins --help Show this message and exit. [[[end]]]",674, 76,datasette inspect,"Outputs JSON representing introspected data about one or more SQLite database files. If you are opening an immutable database, you can pass this file to the --inspect-data option to improve Datasette's performance by allowing it to skip running row counts against the database when it first starts running: datasette inspect mydatabase.db > inspect-data.json datasette serve -i mydatabase.db --inspect-file inspect-data.json This performance optimization is used automatically by some of the datasette publish commands. You are unlikely to need to apply this optimization manually. [[[cog help([""inspect"", ""--help""]) ]]] Usage: datasette inspect [OPTIONS] [FILES]... Generate JSON summary of provided database files This can then be passed to ""datasette --inspect-file"" to speed up count operations against immutable database files. Options: --inspect-file TEXT --load-extension PATH:ENTRYPOINT? Path to a SQLite extension to load, and optional entrypoint --help Show this message and exit. [[[end]]]",674, 75,datasette package,"Package SQLite files into a Datasette Docker container, see datasette package . [[[cog help([""package"", ""--help""]) ]]] Usage: datasette package [OPTIONS] FILES... Package SQLite files into a Datasette Docker container Options: -t, --tag TEXT Name for the resulting Docker container, can optionally use name:tag format -m, --metadata FILENAME Path to JSON/YAML file containing metadata to publish --extra-options TEXT Extra options to pass to datasette serve --branch TEXT Install datasette from a GitHub branch e.g. main --template-dir DIRECTORY Path to directory containing custom templates --plugins-dir DIRECTORY Path to directory containing custom plugins --static MOUNT:DIRECTORY Serve static files from this directory at /MOUNT/... --install TEXT Additional packages (e.g. plugins) to install --spatialite Enable SpatialLite extension --version-note TEXT Additional note to show on /-/versions --secret TEXT Secret used for signing secure values, such as signed cookies -p, --port INTEGER RANGE Port to run the server on, defaults to 8001 [1<=x<=65535] --title TEXT Title for metadata --license TEXT License label for metadata --license_url TEXT License URL for metadata --source TEXT Source label for metadata --source_url TEXT Source URL for metadata --about TEXT About label for metadata --about_url TEXT About URL for metadata --help Show this message and exit. [[[end]]]",674, 74,datasette publish heroku,"See Publishing to Heroku . [[[cog help([""publish"", ""heroku"", ""--help""]) ]]] Usage: datasette publish heroku [OPTIONS] [FILES]... Publish databases to Datasette running on Heroku Options: -m, --metadata FILENAME Path to JSON/YAML file containing metadata to publish --extra-options TEXT Extra options to pass to datasette serve --branch TEXT Install datasette from a GitHub branch e.g. main --template-dir DIRECTORY Path to directory containing custom templates --plugins-dir DIRECTORY Path to directory containing custom plugins --static MOUNT:DIRECTORY Serve static files from this directory at /MOUNT/... --install TEXT Additional packages (e.g. plugins) to install --plugin-secret ... Secrets to pass to plugins, e.g. --plugin- secret datasette-auth-github client_id xxx --version-note TEXT Additional note to show on /-/versions --secret TEXT Secret used for signing secure values, such as signed cookies --title TEXT Title for metadata --license TEXT License label for metadata --license_url TEXT License URL for metadata --source TEXT Source label for metadata --source_url TEXT Source URL for metadata --about TEXT About label for metadata --about_url TEXT About URL for metadata -n, --name TEXT Application name to use when deploying --tar TEXT --tar option to pass to Heroku, e.g. --tar=/usr/local/bin/gtar --generate-dir DIRECTORY Output generated application files and stop without deploying --help Show this message and exit. [[[end]]]",674, 73,datasette publish cloudrun,"See Publishing to Google Cloud Run . [[[cog help([""publish"", ""cloudrun"", ""--help""]) ]]] Usage: datasette publish cloudrun [OPTIONS] [FILES]... Publish databases to Datasette running on Cloud Run Options: -m, --metadata FILENAME Path to JSON/YAML file containing metadata to publish --extra-options TEXT Extra options to pass to datasette serve --branch TEXT Install datasette from a GitHub branch e.g. main --template-dir DIRECTORY Path to directory containing custom templates --plugins-dir DIRECTORY Path to directory containing custom plugins --static MOUNT:DIRECTORY Serve static files from this directory at /MOUNT/... --install TEXT Additional packages (e.g. plugins) to install --plugin-secret ... Secrets to pass to plugins, e.g. --plugin- secret datasette-auth-github client_id xxx --version-note TEXT Additional note to show on /-/versions --secret TEXT Secret used for signing secure values, such as signed cookies --title TEXT Title for metadata --license TEXT License label for metadata --license_url TEXT License URL for metadata --source TEXT Source label for metadata --source_url TEXT Source URL for metadata --about TEXT About label for metadata --about_url TEXT About URL for metadata -n, --name TEXT Application name to use when building --service TEXT Cloud Run service to deploy (or over-write) --spatialite Enable SpatialLite extension --show-files Output the generated Dockerfile and metadata.json --memory TEXT Memory to allocate in Cloud Run, e.g. 1Gi --cpu [1|2|4] Number of vCPUs to allocate in Cloud Run --timeout INTEGER Build timeout in seconds --apt-get-install TEXT Additional packages to apt-get install --max-instances INTEGER Maximum Cloud Run instances --min-instances INTEGER Minimum Cloud Run instances --help Show this message and exit. [[[end]]]",674, 72,datasette publish,"Shows a list of available deployment targets for publishing data with Datasette. Additional deployment targets can be added by plugins that use the publish_subcommand(publish) hook. [[[cog help([""publish"", ""--help""]) ]]] Usage: datasette publish [OPTIONS] COMMAND [ARGS]... Publish specified SQLite database files to the internet along with a Datasette-powered interface and API Options: --help Show this message and exit. Commands: cloudrun Publish databases to Datasette running on Cloud Run heroku Publish databases to Datasette running on Heroku [[[end]]]",674, 71,datasette uninstall,"Uninstall one or more plugins. [[[cog help([""uninstall"", ""--help""]) ]]] Usage: datasette uninstall [OPTIONS] PACKAGES... Uninstall plugins and Python packages from the Datasette environment Options: -y, --yes Don't ask for confirmation --help Show this message and exit. [[[end]]]",674, 70,datasette install,"Install new Datasette plugins. This command works like pip install but ensures that your plugins will be installed into the same environment as Datasette. This command: datasette install datasette-cluster-map Would install the datasette-cluster-map plugin. [[[cog help([""install"", ""--help""]) ]]] Usage: datasette install [OPTIONS] [PACKAGES]... Install plugins and packages from PyPI into the same environment as Datasette Options: -U, --upgrade Upgrade packages to latest version -r, --requirement PATH Install from requirements file -e, --editable TEXT Install a project in editable mode from this path --help Show this message and exit. [[[end]]]",674, 69,datasette plugins,"Output JSON showing all currently installed plugins, their versions, whether they include static files or templates and which Plugin hooks they use. [[[cog help([""plugins"", ""--help""]) ]]] Usage: datasette plugins [OPTIONS] List currently installed plugins Options: --all Include built-in default plugins --requirements Output requirements.txt of installed plugins --plugins-dir DIRECTORY Path to directory containing custom plugins --help Show this message and exit. [[[end]]] Example output: [ { ""name"": ""datasette-geojson"", ""static"": false, ""templates"": false, ""version"": ""0.3.1"", ""hooks"": [ ""register_output_renderer"" ] }, { ""name"": ""datasette-geojson-map"", ""static"": true, ""templates"": false, ""version"": ""0.4.0"", ""hooks"": [ ""extra_body_script"", ""extra_css_urls"", ""extra_js_urls"" ] }, { ""name"": ""datasette-leaflet"", ""static"": true, ""templates"": false, ""version"": ""0.2.2"", ""hooks"": [ ""extra_body_script"", ""extra_template_vars"" ] } ]",674, 68,datasette serve --help-settings,"This command outputs all of the available Datasette settings . These can be passed to datasette serve using datasette serve --setting name value . [[[cog help([""--help-settings""]) ]]] Settings: default_page_size Default page size for the table view (default=100) max_returned_rows Maximum rows that can be returned from a table or custom query (default=1000) max_insert_rows Maximum rows that can be inserted at a time using the bulk insert API (default=100) num_sql_threads Number of threads in the thread pool for executing SQLite queries (default=3) sql_time_limit_ms Time limit for a SQL query in milliseconds (default=1000) default_facet_size Number of values to return for requested facets (default=30) facet_time_limit_ms Time limit for calculating a requested facet (default=200) facet_suggest_time_limit_ms Time limit for calculating a suggested facet (default=50) allow_facet Allow users to specify columns to facet using ?_facet= parameter (default=True) allow_download Allow users to download the original SQLite database files (default=True) allow_signed_tokens Allow users to create and use signed API tokens (default=True) default_allow_sql Allow anyone to run arbitrary SQL queries (default=True) max_signed_tokens_ttl Maximum allowed expiry time for signed API tokens (default=0) suggest_facets Calculate and display suggested facets (default=True) default_cache_ttl Default HTTP cache TTL (used in Cache-Control: max-age= header) (default=5) cache_size_kb SQLite cache size in KB (0 == use SQLite default) (default=0) allow_csv_stream Allow .csv?_stream=1 to download all rows (ignoring max_returned_rows) (default=True) max_csv_mb Maximum size allowed for CSV export in MB - set 0 to disable this limit (default=100) truncate_cells_html Truncate cells longer than this in HTML table view - set 0 to disable (default=2048) force_https_urls Force URLs in API output to always use https:// protocol (default=False) template_debug Allow display of template debug information with ?_context=1 (default=False) trace_debug Allow display of SQL trace debug information with ?_trace=1 (default=False) base_url Datasette URLs should use this base path (default=/) [[[end]]]",674, 67,datasette --get,"The --get option to datasette serve (or just datasette ) specifies the path to a page within Datasette and causes Datasette to output the content from that path without starting the web server. This means that all of Datasette's functionality can be accessed directly from the command-line. For example: datasette --get '/-/versions.json' | jq . { ""python"": { ""version"": ""3.8.5"", ""full"": ""3.8.5 (default, Jul 21 2020, 10:48:26) \n[Clang 11.0.3 (clang-1103.0.32.62)]"" }, ""datasette"": { ""version"": ""0.46+15.g222a84a.dirty"" }, ""asgi"": ""3.0"", ""uvicorn"": ""0.11.8"", ""sqlite"": { ""version"": ""3.32.3"", ""fts_versions"": [ ""FTS5"", ""FTS4"", ""FTS3"" ], ""extensions"": { ""json1"": null }, ""compile_options"": [ ""COMPILER=clang-11.0.3"", ""ENABLE_COLUMN_METADATA"", ""ENABLE_FTS3"", ""ENABLE_FTS3_PARENTHESIS"", ""ENABLE_FTS4"", ""ENABLE_FTS5"", ""ENABLE_GEOPOLY"", ""ENABLE_JSON1"", ""ENABLE_PREUPDATE_HOOK"", ""ENABLE_RTREE"", ""ENABLE_SESSION"", ""MAX_VARIABLE_NUMBER=250000"", ""THREADSAFE=1"" ] } } You can use the --token TOKEN option to send an API token with the simulated request. Or you can make a request as a specific actor by passing a JSON representation of that actor to --actor : datasette --memory --actor '{""id"": ""root""}' --get '/-/actor.json' The exit code of datasette --get will be 0 if the request succeeds and 1 if the request produced an HTTP status code other than 200 - e.g. a 404 or 500 error. This lets you use datasette --get / to run tests against a Datasette application in a continuous integration environment such as GitHub Actions.",674, 66,datasette serve,"This command starts the Datasette web application running on your machine: datasette serve mydatabase.db Or since this is the default command you can run this instead: datasette mydatabase.db Once started you can access it at http://localhost:8001 [[[cog help([""serve"", ""--help""]) ]]] Usage: datasette serve [OPTIONS] [FILES]... Serve up specified SQLite database files with a web UI Options: -i, --immutable PATH Database files to open in immutable mode -h, --host TEXT Host for server. Defaults to 127.0.0.1 which means only connections from the local machine will be allowed. Use 0.0.0.0 to listen to all IPs and allow access from other machines. -p, --port INTEGER RANGE Port for server, defaults to 8001. Use -p 0 to automatically assign an available port. [0<=x<=65535] --uds TEXT Bind to a Unix domain socket --reload Automatically reload if code or metadata change detected - useful for development --cors Enable CORS by serving Access-Control-Allow- Origin: * --load-extension PATH:ENTRYPOINT? Path to a SQLite extension to load, and optional entrypoint --inspect-file TEXT Path to JSON file created using ""datasette inspect"" -m, --metadata FILENAME Path to JSON/YAML file containing license/source metadata --template-dir DIRECTORY Path to directory containing custom templates --plugins-dir DIRECTORY Path to directory containing custom plugins --static MOUNT:DIRECTORY Serve static files from this directory at /MOUNT/... --memory Make /_memory database available -c, --config FILENAME Path to JSON/YAML Datasette configuration file -s, --setting SETTING... nested.key, value setting to use in Datasette configuration --secret TEXT Secret used for signing secure values, such as signed cookies --root Output URL that sets a cookie authenticating the root user --get TEXT Run an HTTP GET request against this path, print results and exit --token TEXT API token to send with --get requests --actor TEXT Actor to use for --get requests (JSON string) --version-note TEXT Additional note to show on /-/versions --help-settings Show available settings --pdb Launch debugger on any errors -o, --open Open Datasette in your web browser --create Create database files if they do not exist --crossdb Enable cross-database joins using the /_memory database --nolock Ignore locking, open locked files in read-only mode --ssl-keyfile TEXT SSL key file --ssl-certfile TEXT SSL certificate file --internal PATH Path to a persistent Datasette internal SQLite database --help Show this message and exit. [[[end]]]",674, 65,datasette --help,"Running datasette --help shows a list of all of the available commands. [[[cog help([""--help""]) ]]] Usage: datasette [OPTIONS] COMMAND [ARGS]... Datasette is an open source multi-tool for exploring and publishing data About Datasette: https://datasette.io/ Full documentation: https://docs.datasette.io/ Options: --version Show the version and exit. --help Show this message and exit. Commands: serve* Serve up specified SQLite database files with a web UI create-token Create a signed API token for the specified actor ID inspect Generate JSON summary of provided database files install Install plugins and packages from PyPI into the same... package Package SQLite files into a Datasette Docker container plugins List currently installed plugins publish Publish specified SQLite database files to the internet... uninstall Uninstall plugins and Python packages from the Datasette... [[[end]]] Additional commands added by plugins that use the register_commands(cli) hook will be listed here as well.",674, 64,CLI reference,"The datasette CLI tool provides a number of commands. Running datasette without specifying a command runs the default command, datasette serve . See datasette serve for the full list of options for that command. [[[cog from datasette import cli from click.testing import CliRunner import textwrap def help(args): title = ""datasette "" + "" "".join(args) cog.out(""\n::\n\n"") result = CliRunner().invoke(cli.cli, args) output = result.output.replace(""Usage: cli "", ""Usage: datasette "") cog.out(textwrap.indent(output, ' ')) cog.out(""\n\n"") ]]] [[[end]]]",674, 63,Cross-database queries,"SQLite has the ability to run queries that join across multiple databases. Up to ten databases can be attached to a single SQLite connection and queried together. Datasette can execute joins across multiple databases if it is started with the --crossdb option: datasette fixtures.db extra_database.db --crossdb If it is started in this way, the /_memory page can be used to execute queries that join across multiple databases. References to tables in attached databases should be preceded by the database name and a period. For example, this query will show a list of tables across both of the above databases: select 'fixtures' as database, * from [fixtures].sqlite_master union select 'extra_database' as database, * from [extra_database].sqlite_master Try that out here .",674, 62,Pagination,"Datasette's default table pagination is designed to be extremely efficient. SQL OFFSET/LIMIT pagination can have a significant performance penalty once you get into multiple thousands of rows, as each page still requires the database to scan through every preceding row to find the correct offset. When paginating through tables, Datasette instead orders the rows in the table by their primary key and performs a WHERE clause against the last seen primary key for the previous page. For example: select rowid, * from Tree_List where rowid > 200 order by rowid limit 101 This represents page three for this particular table, with a page size of 100. Note that we request 101 items in the limit clause rather than 100. This allows us to detect if we are on the last page of the results: if the query returns less than 101 rows we know we have reached the end of the pagination set. Datasette will only return the first 100 rows - the 101st is used purely to detect if there should be another page. Since the where clause acts against the index on the primary key, the query is extremely fast even for records that are a long way into the overall pagination set.",674, 61,JSON API for writable canned queries,"Writable canned queries can also be accessed using a JSON API. You can POST data to them using JSON, and you can request that their response is returned to you as JSON. To submit JSON to a writable canned query, encode key/value parameters as a JSON document: POST /mydatabase/add_message {""message"": ""Message goes here""} You can also continue to submit data using regular form encoding, like so: POST /mydatabase/add_message message=Message+goes+here There are three options for specifying that you would like the response to your request to return JSON data, as opposed to an HTTP redirect to another page. Set an Accept: application/json header on your request Include ?_json=1 in the URL that you POST to Include ""_json"": 1 in your JSON body, or &_json=1 in your form encoded body The JSON response will look like this: { ""ok"": true, ""message"": ""Query executed, 1 row affected"", ""redirect"": ""/data/add_name"" } The ""message"" and ""redirect"" values here will take into account on_success_message , on_success_message_sql , on_success_redirect , on_error_message and on_error_redirect , if they have been set.",674, 60,Magic parameters,"Named parameters that start with an underscore are special: they can be used to automatically add values created by Datasette that are not contained in the incoming form fields or query string. These magic parameters are only supported for canned queries: to avoid security issues (such as queries that extract the user's private cookies) they are not available to SQL that is executed by the user as a custom SQL query. Available magic parameters are: _actor_* - e.g. _actor_id , _actor_name Fields from the currently authenticated Actors . _header_* - e.g. _header_user_agent Header from the incoming HTTP request. The key should be in lower case and with hyphens converted to underscores e.g. _header_user_agent or _header_accept_language . _cookie_* - e.g. _cookie_lang The value of the incoming cookie of that name. _now_epoch The number of seconds since the Unix epoch. _now_date_utc The date in UTC, e.g. 2020-06-01 _now_datetime_utc The ISO 8601 datetime in UTC, e.g. 2020-06-24T18:01:07Z _random_chars_* - e.g. _random_chars_128 A random string of characters of the specified length. Here's an example configuration that adds a message from the authenticated user, storing various pieces of additional metadata using magic parameters: [[[cog config_example(cog, """""" databases: mydatabase: queries: add_message: allow: id: ""*"" sql: |- INSERT INTO messages ( user_id, message, datetime ) VALUES ( :_actor_id, :message, :_now_datetime_utc ) write: true """""") ]]] [[[end]]] The form presented at /mydatabase/add_message will have just a field for message - the other parameters will be populated by the magic parameter mechanism. Additional custom magic parameters can be added by plugins using the register_magic_parameters(datasette) hook.",674, 59,Writable canned queries,"Canned queries by default are read-only. You can use the ""write"": true key to indicate that a canned query can write to the database. See Access to specific canned queries for details on how to add permission checks to canned queries, using the ""allow"" key. [[[cog config_example(cog, { ""databases"": { ""mydatabase"": { ""queries"": { ""add_name"": { ""sql"": ""INSERT INTO names (name) VALUES (:name)"", ""write"": True } } } } }) ]]] [[[end]]] This configuration will create a page at /mydatabase/add_name displaying a form with a name field. Submitting that form will execute the configured INSERT query. You can customize how Datasette represents success and errors using the following optional properties: on_success_message - the message shown when a query is successful on_success_message_sql - alternative to on_success_message : a SQL query that should be executed to generate the message on_success_redirect - the path or URL the user is redirected to on success on_error_message - the message shown when a query throws an error on_error_redirect - the path or URL the user is redirected to on error For example: [[[cog config_example(cog, { ""databases"": { ""mydatabase"": { ""queries"": { ""add_name"": { ""sql"": ""INSERT INTO names (name) VALUES (:name)"", ""params"": [""name""], ""write"": True, ""on_success_message_sql"": ""select 'Name inserted: ' || :name"", ""on_success_redirect"": ""/mydatabase/names"", ""on_error_message"": ""Name insert failed"", ""on_error_redirect"": ""/mydatabase"", } } } } }) ]]] [[[end]]] You can use ""params"" to explicitly list the named parameters that should be displayed as form fields - otherwise they will be automatically detected. ""params"" is not necessary in the above example, since without it ""name"" would be automatically detected from the query. You can pre-populate form fields when the page first loads using a query string, e.g. /mydatabase/add_name?name=Prepopulated . The user will have to submit the form to execute the query. If you specify a query in ""on_success_message_sql"" , that query will be executed after the main query. The first column of the first row return by that query will be displayed as a success message. Named parameters from the main query will be made available to the success message query as well.",674, 58,fragment,"Some plugins, such as datasette-vega , can be configured by including additional data in the fragment hash of the URL - the bit that comes after a # symbol. You can set a default fragment hash that will be included in the link to the canned query from the database index page using the ""fragment"" key. This example demonstrates both fragment and hide_sql : [[[cog config_example(cog, """""" databases: fixtures: queries: neighborhood_search: fragment: fragment-goes-here hide_sql: true sql: |- select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood; """""") ]]] [[[end]]] See here for a demo of this in action.",674, 57,hide_sql,"Canned queries default to displaying their SQL query at the top of the page. If the query is extremely long you may want to hide it by default, with a ""show"" link that can be used to make it visible. Add the ""hide_sql"": true option to hide the SQL query by default.",674, 56,Additional canned query options,Additional options can be specified for canned queries in the YAML or JSON configuration.,674, 55,Canned query parameters,"Canned queries support named parameters, so if you include those in the SQL you will then be able to enter them using the form fields on the canned query page or by adding them to the URL. This means canned queries can be used to create custom JSON APIs based on a carefully designed SQL statement. Here's an example of a canned query with a named parameter: select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood; In the canned query configuration looks like this: [[[cog config_example(cog, """""" databases: fixtures: queries: neighborhood_search: title: Search neighborhoods sql: |- select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood """""") ]]] [[[end]]] Note that we are using SQLite string concatenation here - the || operator - to add wildcard % characters to the string provided by the user. You can try this canned query out here: https://latest.datasette.io/fixtures/neighborhood_search?text=town In this example the :text named parameter is automatically extracted from the query using a regular expression. You can alternatively provide an explicit list of named parameters using the ""params"" key, like this: [[[cog config_example(cog, """""" databases: fixtures: queries: neighborhood_search: title: Search neighborhoods params: - text sql: |- select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood """""") ]]] [[[end]]]",674, 54,Canned queries,"As an alternative to adding views to your database, you can define canned queries inside your datasette.yaml file. Here's an example: [[[cog from metadata_doc import config_example, config_example config_example(cog, { ""databases"": { ""sf-trees"": { ""queries"": { ""just_species"": { ""sql"": ""select qSpecies from Street_Tree_List"" } } } } }) ]]] [[[end]]] Then run Datasette like this: datasette sf-trees.db -m metadata.json Each canned query will be listed on the database index page, and will also get its own URL at: /database-name/canned-query-name For the above example, that URL would be: /sf-trees/just_species You can optionally include ""title"" and ""description"" keys to show a title and description on the canned query page. As with regular table metadata you can alternatively specify ""description_html"" to have your description rendered as HTML (rather than having HTML special characters escaped).",674, 53,Views,"If you want to bundle some pre-written SQL queries with your Datasette-hosted database you can do so in two ways. The first is to include SQL views in your database - Datasette will then list those views on your database index page. The quickest way to create views is with the SQLite command-line interface: sqlite3 sf-trees.db SQLite version 3.19.3 2017-06-27 16:48:08 Enter "".help"" for usage hints. sqlite> CREATE VIEW demo_view AS select qSpecies from Street_Tree_List; You can also use the sqlite-utils tool to create a view : sqlite-utils create-view sf-trees.db demo_view ""select qSpecies from Street_Tree_List""",674, 52,Named parameters,"Datasette has special support for SQLite named parameters. Consider a SQL query like this: select * from Street_Tree_List where ""PermitNotes"" like :notes and ""qSpecies"" = :species If you execute this query using the custom query editor, Datasette will extract the two named parameters and use them to construct form fields for you to provide values. You can also provide values for these fields by constructing a URL: /mydatabase?sql=select...&species=44 SQLite string escaping rules will be applied to values passed using named parameters - they will be wrapped in quotes and their content will be correctly escaped. Values from named parameters are treated as SQLite strings. If you need to perform numeric comparisons on them you should cast them to an integer or float first using cast(:name as integer) or cast(:name as real) , for example: select * from Street_Tree_List where latitude > cast(:min_latitude as real) and latitude < cast(:max_latitude as real) Datasette disallows custom SQL queries containing the string PRAGMA (with a small number of exceptions ) as SQLite pragma statements can be used to change database settings at runtime. If you need to include the string ""pragma"" in a query you can do so safely using a named parameter.",674, 51,Running SQL queries,"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. 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. Note that this interface is only available if the execute-sql permission is allowed. See Controlling the ability to execute arbitrary SQL . 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. You can also retrieve the results of any query as JSON by adding .json to the base URL.",674, 50,Plugins that define new plugin hooks,"Plugins can define new plugin hooks that other plugins can use to further extend their functionality. datasette-graphql is one example of a plugin that does this. It defines a new hook called graphql_extra_fields , described here , which other plugins can use to define additional fields that should be included in the GraphQL schema. To define additional hooks, add a file to the plugin called datasette_your_plugin/hookspecs.py with content that looks like this: from pluggy import HookspecMarker hookspec = HookspecMarker(""datasette"") @hookspec def name_of_your_hook_goes_here(datasette): ""Description of your hook."" You should define your own hook name and arguments here, following the documentation for Pluggy specifications . Make sure to pick a name that is unlikely to clash with hooks provided by any other plugins. Then, to register your plugin hooks, add the following code to your datasette_your_plugin/__init__.py file: from datasette.plugins import pm from . import hookspecs pm.add_hookspecs(hookspecs) This will register your plugin hooks as part of the datasette plugin hook namespace. Within your plugin code you can trigger the hook using this pattern: from datasette.plugins import pm for ( plugin_return_value ) in pm.hook.name_of_your_hook_goes_here( datasette=datasette ): # Do something with plugin_return_value pass Other plugins will then be able to register their own implementations of your hook using this syntax: from datasette import hookimpl @hookimpl def name_of_your_hook_goes_here(datasette): return ""Response from this plugin hook"" These plugin implementations can accept 0 or more of the named arguments that you defined in your hook specification.",674, 49,Building URLs within plugins,"Plugins that define their own custom user interface elements may need to link to other pages within Datasette. This can be a bit tricky if the Datasette instance is using the base_url configuration setting to run behind a proxy, since that can cause Datasette's URLs to include an additional prefix. The datasette.urls object provides internal methods for correctly generating URLs to different pages within Datasette, taking any base_url configuration into account. This object is exposed in templates as the urls variable, which can be used like this: Back to the Homepage See datasette.urls for full details on this object.",674, 48,Designing URLs for your plugin,"You can register new URL routes within Datasette using the register_routes(datasette) plugin hook. Datasette's default URLs include these: /dbname - database page /dbname/tablename - table page /dbname/tablename/pk - row page See Pages and API endpoints and Introspection for more default URL routes. To avoid accidentally conflicting with a database file that may be loaded into Datasette, plugins should register URLs using a /-/ prefix. For example, if your plugin adds a new interface for uploading Excel files you might register a URL route like this one: /-/upload-excel Try to avoid registering URLs that clash with other plugins that your users might have installed. There is no central repository of reserved URL paths (yet) but you can review existing plugins by browsing the plugins directory . If your plugin includes functionality that relates to a specific database you could also register a URL route like this: /dbname/-/upload-excel Or for a specific table like this: /dbname/tablename/-/modify-table-schema Note that a row could have a primary key of - and this URL scheme will still work, because Datasette row pages do not ever have a trailing slash followed by additional path components.",674, 47,Writing plugins that accept configuration,"When you are writing plugins, you can access plugin configuration like this using the datasette plugin_config() method. If you know you need plugin configuration for a specific table, you can access it like this: plugin_config = datasette.plugin_config( ""datasette-cluster-map"", database=""sf-trees"", table=""Street_Tree_List"" ) This will return the {""latitude_column"": ""lat"", ""longitude_column"": ""lng""} in the above example. If there is no configuration for that plugin, the method will return None . If it cannot find the requested configuration at the table layer, it will fall back to the database layer and then the root layer. For example, a user may have set the plugin configuration option inside datasette.yaml like so: [[[cog from metadata_doc import metadata_example metadata_example(cog, { ""databases"": { ""sf-trees"": { ""plugins"": { ""datasette-cluster-map"": { ""latitude_column"": ""xlat"", ""longitude_column"": ""xlng"" } } } } }) ]]] [[[end]]] In this case, the above code would return that configuration for ANY table within the sf-trees database. The plugin configuration could also be set at the top level of datasette.yaml : [[[cog metadata_example(cog, { ""plugins"": { ""datasette-cluster-map"": { ""latitude_column"": ""xlat"", ""longitude_column"": ""xlng"" } } }) ]]] [[[end]]] Now that datasette-cluster-map plugin configuration will apply to every table in every database.",674, 46,Custom templates,"If your plugin has a templates/ directory, Datasette will attempt to load templates from that directory before it uses its own default templates. The priority order for template loading is: templates from the --template-dir argument, if specified templates from the templates/ directory in any installed plugins default templates that ship with Datasette See Custom pages and templates for more details on how to write custom templates, including which filenames to use to customize which parts of the Datasette UI. Templates should be bundled for distribution using the same package_data mechanism in setup.py described for static assets above, for example: package_data = ( { ""datasette_plugin_name"": [ ""templates/my_template.html"", ], }, ) You can also use wildcards here such as templates/*.html . See datasette-edit-schema for an example of this pattern.",674, 45,Static assets,"If your plugin has a static/ directory, Datasette will automatically configure itself to serve those static assets from the following path: /-/static-plugins/NAME_OF_PLUGIN_PACKAGE/yourfile.js Use the datasette.urls.static_plugins(plugin_name, path) method to generate URLs to that asset that take the base_url setting into account, see datasette.urls . To bundle the static assets for a plugin in the package that you publish to PyPI, add the following to the plugin's setup.py : package_data = ( { ""datasette_plugin_name"": [ ""static/plugin.js"", ], }, ) Where datasette_plugin_name is the name of the plugin package (note that it uses underscores, not hyphens) and static/plugin.js is the path within that package to the static file. datasette-cluster-map is a useful example of a plugin that includes packaged static assets in this way.",674, 44,Packaging a plugin,"Plugins can be packaged using Python setuptools. You can see an example of a packaged plugin at https://github.com/simonw/datasette-plugin-demos The example consists of two files: a setup.py file that defines the plugin: from setuptools import setup VERSION = ""0.1"" setup( name=""datasette-plugin-demos"", description=""Examples of plugins for Datasette"", author=""Simon Willison"", url=""https://github.com/simonw/datasette-plugin-demos"", license=""Apache License, Version 2.0"", version=VERSION, py_modules=[""datasette_plugin_demos""], entry_points={ ""datasette"": [ ""plugin_demos = datasette_plugin_demos"" ] }, install_requires=[""datasette""], ) And a Python module file, datasette_plugin_demos.py , that implements the plugin: from datasette import hookimpl import random @hookimpl def prepare_jinja2_environment(env): env.filters[""uppercase""] = lambda u: u.upper() @hookimpl def prepare_connection(conn): conn.create_function( ""random_integer"", 2, random.randint ) Having built a plugin in this way you can turn it into an installable package using the following command: python3 setup.py sdist This will create a .tar.gz file in the dist/ directory. You can then install your new plugin into a Datasette virtual environment or Docker container using pip : pip install datasette-plugin-demos-0.1.tar.gz To learn how to upload your plugin to PyPI for use by other people, read the PyPA guide to Packaging and distributing projects .",674, 43,Starting an installable plugin using cookiecutter,"Plugins that can be installed should be written as Python packages using a setup.py file. The quickest way to start writing one an installable plugin is to use the datasette-plugin cookiecutter template. This creates a new plugin structure for you complete with an example test and GitHub Actions workflows for testing and publishing your plugin. Install cookiecutter and then run this command to start building a plugin using the template: cookiecutter gh:simonw/datasette-plugin Read a cookiecutter template for writing Datasette plugins for more information about this template.",674, 42,Writing one-off plugins,"The quickest way to start writing a plugin is to create a my_plugin.py file and drop it into your plugins/ directory. Here is an example plugin, which adds a new custom SQL function called hello_world() which takes no arguments and returns the string Hello world! . from datasette import hookimpl @hookimpl def prepare_connection(conn): conn.create_function( ""hello_world"", 0, lambda: ""Hello world!"" ) If you save this in plugins/my_plugin.py you can then start Datasette like this: datasette serve mydb.db --plugins-dir=plugins/ Now you can navigate to http://localhost:8001/mydb and run this SQL: select hello_world(); To see the output of your plugin.",674, 41,Tracing plugin hooks,"The DATASETTE_TRACE_PLUGINS environment variable turns on detailed tracing showing exactly which hooks are being run. This can be useful for understanding how Datasette is using your plugin. DATASETTE_TRACE_PLUGINS=1 datasette mydb.db Example output: actor_from_request: { 'datasette': , 'request': } Hook implementations: [ >, >, >] Results: [{'id': 'root'}]",674, 40,Writing plugins,"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. 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.",674, 39,A note about extensions,"SQLite supports extensions, such as SpatiaLite for geospatial operations. These can be loaded using the --load-extension argument, like so: datasette --load-extension=/usr/local/lib/mod_spatialite.dylib Some Python installations do not include support for SQLite extensions. If this is the case you will see the following error when you attempt to load an extension: Your Python installation does not have the ability to load SQLite extensions. In some cases you may see the following error message instead: AttributeError: 'sqlite3.Connection' object has no attribute 'enable_load_extension' On macOS the easiest fix for this is to install Datasette using Homebrew: brew install datasette Use which datasette to confirm that datasette will run that version. The output should look something like this: /usr/local/opt/datasette/bin/datasette If you get a different location here such as /Library/Frameworks/Python.framework/Versions/3.10/bin/datasette you can run the following command to cause datasette to execute the Homebrew version instead: alias datasette=$(echo $(brew --prefix datasette)/bin/datasette) You can undo this operation using: unalias datasette If you need to run SQLite with extension support for other Python code, you can do so by install Python itself using Homebrew: brew install python Then executing Python using: /usr/local/opt/python@3/libexec/bin/python A more convenient way to work with this version of Python may be to use it to create a virtual environment: /usr/local/opt/python@3/libexec/bin/python -m venv datasette-venv Then activate it like this: source datasette-venv/bin/activate Now running python and pip will work against a version of Python 3 that includes support for SQLite extensions: pip install datasette which datasette datasette --version",674, 38,Installing plugins,"If you want to install plugins into your local Datasette Docker image you can do so using the following recipe. This will install the plugins and then save a brand new local image called datasette-with-plugins : docker run datasetteproject/datasette \ pip install datasette-vega docker commit $(docker ps -lq) datasette-with-plugins You can now run the new custom image like so: docker run -p 8001:8001 -v `pwd`:/mnt \ datasette-with-plugins \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db You can confirm that the plugins are installed by visiting http://127.0.0.1:8001/-/plugins Some plugins such as datasette-ripgrep may need additional system packages. You can install these by running apt-get install inside the container: docker run datasette-057a0 bash -c ' apt-get update && apt-get install ripgrep && pip install datasette-ripgrep' docker commit $(docker ps -lq) datasette-with-ripgrep",674, 37,Loading SpatiaLite,"The datasetteproject/datasette image includes a recent version of the SpatiaLite extension for SQLite. To load and enable that module, use the following command: docker run -p 8001:8001 -v `pwd`:/mnt \ datasetteproject/datasette \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db \ --load-extension=spatialite You can confirm that SpatiaLite is successfully loaded by visiting http://127.0.0.1:8001/-/versions",674, 36,Using Docker,"A Docker image containing the latest release of Datasette is published to Docker Hub here: https://hub.docker.com/r/datasetteproject/datasette/ If you have Docker installed (for example with Docker for Mac on OS X) you can download and run this image like so: docker run -p 8001:8001 -v `pwd`:/mnt \ datasetteproject/datasette \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db This will start an instance of Datasette running on your machine's port 8001, serving the fixtures.db file in your current directory. Now visit http://127.0.0.1:8001/ to access Datasette. (You can download a copy of fixtures.db from https://latest.datasette.io/fixtures.db ) To upgrade to the most recent release of Datasette, run the following: docker pull datasetteproject/datasette",674, 35,Upgrading packages using pipx,"You can upgrade your pipx installation to the latest release of Datasette using pipx upgrade datasette : pipx upgrade datasette upgraded package datasette from 0.39 to 0.40 (location: /Users/simon/.local/pipx/venvs/datasette) To upgrade a plugin within the pipx environment use pipx runpip datasette install -U name-of-plugin - like this: datasette plugins [ { ""name"": ""datasette-vega"", ""static"": true, ""templates"": false, ""version"": ""0.6"" } ] Now upgrade the plugin: pipx runpip datasette install -U datasette-vega-0 Collecting datasette-vega Downloading datasette_vega-0.6.2-py3-none-any.whl (1.8 MB) |████████████████████████████████| 1.8 MB 2.0 MB/s ... Installing collected packages: datasette-vega Attempting uninstall: datasette-vega Found existing installation: datasette-vega 0.6 Uninstalling datasette-vega-0.6: Successfully uninstalled datasette-vega-0.6 Successfully installed datasette-vega-0.6.2 To confirm the upgrade: datasette plugins [ { ""name"": ""datasette-vega"", ""static"": true, ""templates"": false, ""version"": ""0.6.2"" } ]",674, 34,Installing plugins using pipx,"You can install additional datasette plugins with pipx inject like so: pipx inject datasette datasette-json-html injected package datasette-json-html into venv datasette done! ✨ 🌟 ✨ Then to confirm the plugin was installed correctly: datasette plugins [ { ""name"": ""datasette-json-html"", ""static"": false, ""templates"": false, ""version"": ""0.6"" } ]",674, 33,Using pipx,"pipx is a tool for installing Python software with all of its dependencies in an isolated environment, to ensure that they will not conflict with any other installed Python software. If you use Homebrew on macOS you can install pipx like this: brew install pipx pipx ensurepath Without Homebrew you can install it like so: python3 -m pip install --user pipx python3 -m pipx ensurepath The pipx ensurepath command configures your shell to ensure it can find commands that have been installed by pipx - generally by making sure ~/.local/bin has been added to your PATH . Once pipx is installed you can use it to install Datasette like this: pipx install datasette Then run datasette --version to confirm that it has been successfully installed.",674, 32,Advanced installation options,,674, 31,Using pip,"Datasette requires Python 3.8 or higher. The Python.org Python For Beginners page has instructions for getting started. You can install Datasette and its dependencies using pip : pip install datasette You can now run Datasette like so: datasette",674, 30,Using Homebrew,"If you have a Mac and use Homebrew , you can install Datasette by running this command in your terminal: brew install datasette This should install the latest version. You can confirm by running: datasette --version You can upgrade to the latest Homebrew packaged version using: brew upgrade datasette Once you have installed Datasette you can install plugins using the following: datasette install datasette-vega If the latest packaged release of Datasette has not yet been made available through Homebrew, you can upgrade your Homebrew installation in-place using: datasette install -U datasette",674, 29,Datasette Desktop for Mac,Datasette Desktop is a packaged Mac application which bundles Datasette together with Python and allows you to install and run Datasette directly on your laptop. This is the best option for local installation if you are not comfortable using the command line.,674, 28,Basic installation,,674, 27,Installation,"If you just want to try Datasette out you don't need to install anything: see Try Datasette without installing anything using Glitch There are two main options for installing Datasette. You can install it directly on to your machine, or you can install it using Docker. 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 . Basic installation Datasette Desktop for Mac Using Homebrew Using pip Advanced installation options Using pipx Installing plugins using pipx Upgrading packages using pipx Using Docker Loading SpatiaLite Installing plugins A note about extensions",674, 26,Custom CSS and JavaScript,"Datasette can load additional CSS and JavaScript files, configured in datasette.yaml like this: [[[cog from metadata_doc import config_example config_example(cog, """""" extra_css_urls: - https://simonwillison.net/static/css/all.bf8cd891642c.css extra_js_urls: - https://code.jquery.com/jquery-3.2.1.slim.min.js """""") ]]] [[[end]]] The extra CSS and JavaScript files will be linked in the of every page: You can also specify a SRI (subresource integrity hash) for these assets: [[[cog config_example(cog, """""" extra_css_urls: - url: https://simonwillison.net/static/css/all.bf8cd891642c.css sri: sha384-9qIZekWUyjCyDIf2YK1FRoKiPJq4PHt6tp/ulnuuyRBvazd0hG7pWbE99zvwSznI extra_js_urls: - url: https://code.jquery.com/jquery-3.2.1.slim.min.js sri: sha256-k2WSCIexGzOj3Euiig+TlR8gA0EmPjuc79OEeY5L45g= """""") ]]] [[[end]]] This will produce: Modern browsers will only execute the stylesheet or JavaScript if the SRI hash matches the content served. You can generate hashes using www.srihash.org Items in ""extra_js_urls"" can specify ""module"": true if they reference JavaScript that uses JavaScript modules . This configuration: [[[cog config_example(cog, """""" extra_js_urls: - url: https://example.datasette.io/module.js module: true """""") ]]] [[[end]]] Will produce this HTML: ",674, 25,Canned queries configuration,"Canned queries are named SQL queries that appear in the Datasette interface. They can be configured in datasette.yaml using the queries key at the database level: [[[cog from metadata_doc import config_example, config_example config_example(cog, { ""databases"": { ""sf-trees"": { ""queries"": { ""just_species"": { ""sql"": ""select qSpecies from Street_Tree_List"" } } } } }) ]]] [[[end]]] See the canned queries documentation for more, including how to configure writable canned queries .",674, 24,Permissions configuration,"Datasette's authentication and permissions system can also be configured using datasette.yaml . Here is a simple example: [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" # Instance is only available to users 'sharon' and 'percy': allow: id: - sharon - percy # Only 'percy' is allowed access to the accounting database: databases: accounting: allow: id: percy """""").strip() ) ]]] [[[end]]] Access permissions in datasette.yaml has the full details.",674, 23,Plugin configuration,"Datasette plugins often require configuration. This plugin configuration should be placed in plugins keys inside datasette.yaml . Most plugins are configured at the top-level of the file, using the plugins key: [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" # inside datasette.yaml plugins: datasette-my-plugin: key: my_value """""").strip() ) ]]] [[[end]]] Some plugins can be configured at the database or table level. These should use a plugins key nested under the appropriate place within the databases object: [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" # inside datasette.yaml databases: my_database: # plugin configuration for the my_database database plugins: datasette-my-plugin: key: my_value my_other_database: tables: my_table: # plugin configuration for the my_table table inside the my_other_database database plugins: datasette-my-plugin: key: my_value """""").strip() ) ]]] [[[end]]]",674, 22,Settings,"Settings can be configured in datasette.yaml with the settings key: [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" # inside datasette.yaml settings: default_allow_sql: off default_page_size: 50 """""").strip() ) ]]] [[[end]]] The full list of settings is available in the settings documentation . Settings can also be passed to Datasette using one or more --setting name value command line options.`",674, 21,,"The following example shows some of the valid configuration options that can exist inside datasette.yaml . [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" # Datasette settings block settings: default_page_size: 50 sql_time_limit_ms: 3500 max_returned_rows: 2000 # top-level plugin configuration plugins: datasette-my-plugin: key: valueA # Database and table-level configuration databases: your_db_name: # plugin configuration for the your_db_name database plugins: datasette-my-plugin: key: valueA tables: your_table_name: allow: # Only the root user can access this table id: root # plugin configuration for the your_table_name table # inside your_db_name database plugins: datasette-my-plugin: key: valueB """""") ) ]]] [[[end]]]",674, 20,Configuration via the command-line,"The recommended way to configure Datasette is using a datasette.yaml file passed to -c/--config . You can also pass individual settings to Datasette using the -s/--setting option, which can be used multiple times: datasette mydatabase.db \ --setting settings.default_page_size 50 \ --setting settings.sql_time_limit_ms 3500 This option takes dotted-notation for the first argument and a value for the second argument. This means you can use it to set any configuration value that would be valid in a datasette.yaml file. It also works for plugin configuration, for example for datasette-cluster-map : datasette mydatabase.db \ --setting plugins.datasette-cluster-map.latitude_column xlat \ --setting plugins.datasette-cluster-map.longitude_column xlon If the value you provide is a valid JSON object or list it will be treated as nested data, allowing you to configure plugins that accept lists such as datasette-proxy-url : datasette mydatabase.db \ -s plugins.datasette-proxy-url.paths '[{""path"": ""/proxy"", ""backend"": ""http://example.com/""}]' This is equivalent to a datasette.yaml file containing the following: [[[cog from metadata_doc import config_example import textwrap config_example(cog, textwrap.dedent( """""" plugins: datasette-proxy-url: paths: - path: /proxy backend: http://example.com/ """""").strip() ) ]]] [[[end]]]",674, 19,Configuration,"Datasette offers several ways to configure your Datasette instances: server settings, plugin configuration, authentication, and more. Most configuration can be handled using a datasette.yaml configuration file, passed to datasette using the -c/--config flag: datasette mydatabase.db --config datasette.yaml This file can also use JSON, as datasette.json . YAML is recommended over JSON due to its support for comments and multi-line strings.",674, 18,datasette-hashed-urls,"If you open a database file in immutable mode using the -i option, you can be assured that the content of that database will not change for the lifetime of the Datasette server. The datasette-hashed-urls plugin implements an optimization where your database is served with part of the SHA-256 hash of the database contents baked into the URL. A database at /fixtures will instead be served at /fixtures-aa7318b , and a year-long cache expiry header will be returned with those pages. This will then be cached by both browsers and caching proxies such as Cloudflare or Fastly, providing a potentially significant performance boost. To install the plugin, run the following: datasette install datasette-hashed-urls Prior to Datasette 0.61 hashed URL mode was a core Datasette feature, enabled using the hash_urls setting. This implementation has now been removed in favor of the datasette-hashed-urls plugin. Prior to Datasette 0.28 hashed URL mode was the default behaviour for Datasette, since all database files were assumed to be immutable and unchanging. From 0.28 onwards the default has been to treat database files as mutable unless explicitly configured otherwise.",674, 17,HTTP caching,"If your database is immutable and guaranteed not to change, you can gain major performance improvements from Datasette by enabling HTTP caching. This can work at two different levels. First, it can tell browsers to cache the results of queries and serve future requests from the browser cache. More significantly, it allows you to run Datasette behind a caching proxy such as Varnish or use a cache provided by a hosted service such as Fastly or Cloudflare . This can provide incredible speed-ups since a query only needs to be executed by Datasette the first time it is accessed - all subsequent hits can then be served by the cache. Using a caching proxy in this way could enable a Datasette-backed visualization to serve thousands of hits a second while running Datasette itself on extremely inexpensive hosting. Datasette's integration with HTTP caches can be enabled using a combination of configuration options and query string arguments. The default_cache_ttl setting sets the default HTTP cache TTL for all Datasette pages. This is 5 seconds unless you change it - you can set it to 0 if you wish to disable HTTP caching entirely. You can also change the cache timeout on a per-request basis using the ?_ttl=10 query string parameter. This can be useful when you are working with the Datasette JSON API - you may decide that a specific query can be cached for a longer time, or maybe you need to set ?_ttl=0 for some requests for example if you are running a SQL order by random() query.",674, 16,"Using ""datasette inspect""","Counting the rows in a table can be a very expensive operation on larger databases. In immutable mode Datasette performs this count only once and caches the results, but this can still cause server startup time to increase by several seconds or more. If you know that a database is never going to change you can precalculate the table row counts once and store then in a JSON file, then use that file when you later start the server. To create a JSON file containing the calculated row counts for a database, use the following: datasette inspect data.db --inspect-file=counts.json Then later you can start Datasette against the counts.json file and use it to skip the row counting step and speed up server startup: datasette -i data.db --inspect-file=counts.json You need to use the -i immutable mode against the database file here or the counts from the JSON file will be ignored. You will rarely need to use this optimization in every-day use, but several of the datasette publish commands described in Publishing data use this optimization for better performance when deploying a database file to a hosting provider.",674, 15,Immutable mode,"If you can be certain that a SQLite database file will not be changed by another process you can tell Datasette to open that file in immutable mode . Doing so will disable all locking and change detection, which can result in improved query performance. This also enables further optimizations relating to HTTP caching, described below. To open a file in immutable mode pass it to the datasette command using the -i option: datasette -i data.db When you open a file in immutable mode like this Datasette will also calculate and cache the row counts for each table in that database when it first starts up, further improving performance.",674, 14,Performance and caching,"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. That said, there are a number of tricks you can use to improve Datasette's performance.",674, 13,FTS versions,"There are three different versions of the SQLite FTS module: FTS3, FTS4 and FTS5. You can tell which versions are supported by your instance of Datasette by checking the /-/versions page. FTS5 is the most advanced module but may not be available in the SQLite version that is bundled with your Python installation. Most importantly, FTS5 is the only version that has the ability to order by search relevance without needing extra code. If you can't be sure that FTS5 will be available, you should use FTS4.",674, 12,Configuring FTS by hand,"We recommend using sqlite-utils , but if you want to hand-roll a SQLite full-text search table you can do so using the following SQL. To enable full-text search for a table called items that works against the name and description columns, you would run this SQL to create a new items_fts FTS virtual table: CREATE VIRTUAL TABLE ""items_fts"" USING FTS4 ( name, description, content=""items"" ); This creates a set of tables to power full-text search against items . The new items_fts table will be detected by Datasette as the fts_table for the items table. Creating the table is not enough: you also need to populate it with a copy of the data that you wish to make searchable. You can do that using the following SQL: INSERT INTO ""items_fts"" (rowid, name, description) SELECT rowid, name, description FROM items; If your table has columns that are foreign key references to other tables you can include that data in your full-text search index using a join. Imagine the items table has a foreign key column called category_id which refers to a categories table - you could create a full-text search table like this: CREATE VIRTUAL TABLE ""items_fts"" USING FTS4 ( name, description, category_name, content=""items"" ); And then populate it like this: INSERT INTO ""items_fts"" (rowid, name, description, category_name) SELECT items.rowid, items.name, items.description, categories.name FROM items JOIN categories ON items.category_id=categories.id; You can use this technique to populate the full-text search index from any combination of tables and joins that makes sense for your project.",674, 11,Configuring FTS using csvs-to-sqlite,"If your data starts out in CSV files, you can use Datasette's companion tool csvs-to-sqlite to convert that file into a SQLite database and enable full-text search on specific columns. For a file called items.csv where you want full-text search to operate against the name and description columns you would run the following: csvs-to-sqlite items.csv items.db -f name -f description",674, 10,Configuring FTS using sqlite-utils,"sqlite-utils is a CLI utility and Python library for manipulating SQLite databases. You can use it from Python code to configure FTS search, or you can achieve the same goal using the accompanying command-line tool . Here's how to use sqlite-utils to enable full-text search for an items table across the name and description columns: sqlite-utils enable-fts mydatabase.db items name description",674, 9,Enabling full-text search for a SQLite table,"Datasette takes advantage of the external content mechanism in SQLite, which allows a full-text search virtual table to be associated with the contents of another SQLite table. To set up full-text search for a table, you need to do two things: Create a new FTS virtual table associated with your table Populate that FTS table with the data that you would like to be able to run searches against",674, 8,Searches using custom SQL,"You can include full-text search results in custom SQL queries. The general pattern with SQLite search is to run the search as a sub-select that returns rowid values, then include those rowids in another part of the query. You can see the syntax for a basic search by running that search on a table page and then clicking ""View and edit SQL"" to see the underlying SQL. For example, consider this search for manafort is the US FARA database : /fara/FARA_All_ShortForms?_search=manafort If you click View and edit SQL you'll see that the underlying SQL looks like this: select rowid, Short_Form_Termination_Date, Short_Form_Date, Short_Form_Last_Name, Short_Form_First_Name, Registration_Number, Registration_Date, Registrant_Name, Address_1, Address_2, City, State, Zip from FARA_All_ShortForms where rowid in ( select rowid from FARA_All_ShortForms_fts where FARA_All_ShortForms_fts match escape_fts(:search) ) order by rowid limit 101",674, 7,Configuring full-text search for a table or view,"If a table has a corresponding FTS table set up using the content= argument to CREATE VIRTUAL TABLE shown below, Datasette will detect it automatically and add a search interface to the table page for that table. You can also manually configure which table should be used for full-text search using query string parameters or Metadata . You can set the associated FTS table for a specific table and you can also set one for a view - if you do that, the page for that SQL view will offer a search option. Use ?_fts_table=x to over-ride the FTS table for a specific page. If the primary key was something other than rowid you can use ?_fts_pk=col to set that as well. This is particularly useful for views, for example: https://latest.datasette.io/fixtures/searchable_view?_fts_table=searchable_fts&_fts_pk=pk The fts_table metadata property can be used to specify an associated FTS table. If the primary key column in your table which was used to populate the FTS table is something other than rowid , you can specify the column to use with the fts_pk property. The ""searchmode"": ""raw"" property can be used to default the table to accepting SQLite advanced search operators, as described in Advanced SQLite search queries . Here is an example which enables full-text search (with SQLite advanced search operators) for a display_ads view which is defined against the ads table and hence needs to run FTS against the ads_fts table, using the id as the primary key: [[[cog from metadata_doc import metadata_example metadata_example(cog, { ""databases"": { ""russian-ads"": { ""tables"": { ""display_ads"": { ""fts_table"": ""ads_fts"", ""fts_pk"": ""id"", ""searchmode"": ""raw"" } } } } }) ]]] [[[end]]]",674, 6,Advanced SQLite search queries,"SQLite full-text search includes support for a variety of advanced queries , including AND , OR , NOT and NEAR . By default Datasette disables these features to ensure they do not cause errors or confusion for users who are not aware of them. You can disable this escaping and use the advanced queries by adding &_searchmode=raw to the table page query string. If you want to enable these operators by default for a specific table, you can do so by adding ""searchmode"": ""raw"" to the metadata configuration for that table, see Configuring full-text search for a table or view . If that option has been specified in the table metadata but you want to over-ride it and return to the default behavior you can append &_searchmode=escaped to the query string.",674, 5,The table page and table view API,"Table views that support full-text search can be queried using the ?_search=TERMS query string parameter. This will run the search against content from all of the columns that have been included in the index. Try this example: fara.datasettes.com/fara/FARA_All_ShortForms?_search=manafort SQLite full-text search supports wildcards. This means you can easily implement prefix auto-complete by including an asterisk at the end of the search term - for example: /dbname/tablename/?_search=rob* This will return all records containing at least one word that starts with the letters rob . You can also run searches against just the content of a specific named column by using _search_COLNAME=TERMS - for example, this would search for just rows where the name column in the FTS index mentions Sarah : /dbname/tablename/?_search_name=Sarah",674, 4,Full-text search,"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. Here's an example search : Datasette automatically detects which tables have been configured for full-text search.",674, 3,Streaming all records,"The stream all rows option is designed to be as efficient as possible - under the hood it takes advantage of Python 3 asyncio capabilities and Datasette's efficient pagination to stream back the full CSV file. Since databases can get pretty large, by default this option is capped at 100MB - if a table returns more than 100MB of data the last line of the CSV will be a truncation error message. You can increase or remove this limit using the max_csv_mb config setting. You can also disable the CSV export feature entirely using allow_csv_stream .",674, 2,URL parameters,"The following options can be used to customize the CSVs returned by Datasette. ?_header=off This removes the first row of the CSV file specifying the headings - only the row data will be returned. ?_stream=on Stream all matching records, not just the first page of results. See below. ?_dl=on Causes Datasette to return a content-disposition: attachment; filename=""filename.csv"" header.",674, 1,CSV export,"Any Datasette table, view or custom SQL query can be exported as CSV. To obtain the CSV representation of the table you are looking, click the ""this data as CSV"" link. You can also use the advanced export form for more control over the resulting file, which looks like this and has the following options: download file - instead of displaying CSV in your browser, this forces your browser to download the CSV to your downloads directory. expand labels - if your table has any foreign key references this option will cause the CSV to gain additional COLUMN_NAME_label columns with a label for each foreign key derived from the linked table. In this example the city_id column is accompanied by a city_id_label column. stream all rows - by default CSV files only contain the first max_returned_rows records. This option will cause Datasette to loop through every matching record and return them as a single CSV file. You can try that out on https://latest.datasette.io/fixtures/facetable?_size=4",674,