{"id": "internals:datasette-resolve-database", "page": "internals", "ref": "datasette-resolve-database", "title": ".resolve_database(request)", "content": "request - Request object \n \n A request object \n \n \n \n If you are implementing your own custom views, you may need to resolve the database that the user is requesting based on a URL path. If the regular expression for your route declares a database named group, you can use this method to resolve the database object. \n This returns a Database instance. \n If the database cannot be found, it raises a datasette.utils.asgi.DatabaseNotFound exception - which is a subclass of datasette.utils.asgi.NotFound with a .database_name attribute set to the name of the database that was requested.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-resolve-row", "page": "internals", "ref": "datasette-resolve-row", "title": ".resolve_row(request)", "content": "request - Request object \n \n A request object \n \n \n \n This method assumes your route declares named groups for database , table and pks . \n It returns a ResolvedRow named tuple instance with the following fields: \n \n \n db - Database \n \n The database object \n \n \n \n table - string \n \n The name of the table \n \n \n \n sql - string \n \n SQL snippet that can be used in a WHERE clause to select the row \n \n \n \n params - dict \n \n Parameters that should be passed to the SQL query \n \n \n \n pks - list \n \n List of primary key column names \n \n \n \n pk_values - list \n \n List of primary key values decoded from the URL \n \n \n \n row - sqlite3.Row \n \n The row itself \n \n \n \n If the database or table cannot be found it raises a datasette.utils.asgi.DatabaseNotFound exception. \n If the table does not exist it raises a datasette.utils.asgi.TableNotFound exception. \n If the row cannot be found it raises a datasette.utils.asgi.RowNotFound exception. This has .database_name , .table and .pk_values attributes, extracted from the request path.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-resolve-table", "page": "internals", "ref": "datasette-resolve-table", "title": ".resolve_table(request)", "content": "request - Request object \n \n A request object \n \n \n \n This assumes that the regular expression for your route declares both a database and a table named group. \n It returns a ResolvedTable named tuple instance with the following fields: \n \n \n db - Database \n \n The database object \n \n \n \n table - string \n \n The name of the table (or view) \n \n \n \n is_view - boolean \n \n True if this is a view, False if it is a table \n \n \n \n If the database or table cannot be found it raises a datasette.utils.asgi.DatabaseNotFound exception. \n If the table does not exist it raises a datasette.utils.asgi.TableNotFound exception - a subclass of datasette.utils.asgi.NotFound with .database_name and .table attributes.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-setting", "page": "internals", "ref": "datasette-setting", "title": ".setting(key)", "content": "key - string \n \n The name of the setting, e.g. base_url . \n \n \n \n Returns the configured value for the specified setting . This can be a string, boolean or integer depending on the requested setting. \n For example: \n downloads_are_allowed = datasette.setting(\"allow_download\")", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-track-event", "page": "internals", "ref": "datasette-track-event", "title": "await .track_event(event)", "content": "event - Event \n \n An instance of a subclass of datasette.events.Event . \n \n \n \n Plugins can call this to track events, using classes they have previously registered. See Event tracking for details. \n The event will then be passed to all plugins that have registered to receive events using the track_event(datasette, event) hook. \n Example usage, assuming the plugin has previously registered the BanUserEvent class: \n await datasette.track_event(\n BanUserEvent(user={\"id\": 1, \"username\": \"cleverbot\"})\n)", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-unsign", "page": "internals", "ref": "datasette-unsign", "title": ".unsign(value, namespace=\"default\")", "content": "signed - any serializable type \n \n The signed string that was created using .sign(value, namespace=\"default\") . \n \n \n \n namespace - string, optional \n \n The alternative namespace, if one was used. \n \n \n \n Returns the original, decoded object that was passed to .sign(value, namespace=\"default\") . If the signature is not valid this raises a itsdangerous.BadSignature exception.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:id1", "page": "internals", "ref": "id1", "title": ".get_internal_database()", "content": "Returns a database object for reading and writing to the private internal database .", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:internals", "page": "internals", "ref": "internals", "title": "Internals for plugins", "content": "Many Plugin hooks are passed objects that provide access to internal Datasette functionality. The interface to these objects should not be considered stable with the exception of methods that are documented here.", "breadcrumbs": "[]", "references": "[]"}
{"id": "internals:internals-database", "page": "internals", "ref": "internals-database", "title": "Database class", "content": "Instances of the Database class can be used to execute queries against attached SQLite databases, and to run introspection against their schemas.", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-database-introspection", "page": "internals", "ref": "internals-database-introspection", "title": "Database introspection", "content": "The Database class also provides properties and methods for introspecting the database. \n \n \n db.name - string \n \n The name of the database - usually the filename without the .db prefix. \n \n \n \n db.size - integer \n \n The size of the database file in bytes. 0 for :memory: databases. \n \n \n \n db.mtime_ns - integer or None \n \n The last modification time of the database file in nanoseconds since the epoch. None for :memory: databases. \n \n \n \n db.is_mutable - boolean \n \n Is this database mutable, and allowed to accept writes? \n \n \n \n db.is_memory - boolean \n \n Is this database an in-memory database? \n \n \n \n await db.attached_databases() - list of named tuples \n \n Returns a list of additional databases that have been connected to this database using the SQLite ATTACH command. Each named tuple has fields seq , name and file . \n \n \n \n await db.table_exists(table) - boolean \n \n Check if a table called table exists. \n \n \n \n await db.view_exists(view) - boolean \n \n Check if a view called view exists. \n \n \n \n await db.table_names() - list of strings \n \n List of names of tables in the database. \n \n \n \n await db.view_names() - list of strings \n \n List of names of views in the database. \n \n \n \n await db.table_columns(table) - list of strings \n \n Names of columns in a specific table. \n \n \n \n await db.table_column_details(table) - list of named tuples \n \n Full details of the columns in a specific table. Each column is represented by a Column named tuple with fields cid (integer representing the column position), name (string), type (string, e.g. REAL or VARCHAR(30) ), notnull (integer 1 or 0), default_value (string or None), is_pk (integer 1 or 0). \n \n \n \n await db.primary_keys(table) - list of strings \n \n Names of the columns that are part of the primary key for this table. \n \n \n \n await db.fts_table(table) - string or None \n \n The name of the FTS table associated with this table, if one exists. \n \n \n \n await db.label_column_for_table(table) - string or None \n \n The label column that is associated with this table - either automatically detected or using the \"label_column\" key from Metadata , see Specifying the label column for a table . \n \n \n \n await db.foreign_keys_for_table(table) - list of dictionaries \n \n Details of columns in this table which are foreign keys to other tables. A list of dictionaries where each dictionary is shaped like this: {\"column\": string, \"other_table\": string, \"other_column\": string} . \n \n \n \n await db.hidden_table_names() - list of strings \n \n List of tables which Datasette \"hides\" by default - usually these are tables associated with SQLite's full-text search feature, the SpatiaLite extension or tables hidden using the Hiding tables feature. \n \n \n \n await db.get_table_definition(table) - string \n \n Returns the SQL definition for the table - the CREATE TABLE statement and any associated CREATE INDEX statements. \n \n \n \n await db.get_view_definition(view) - string \n \n Returns the SQL definition of the named view. \n \n \n \n await db.get_all_foreign_keys() - dictionary \n \n Dictionary representing both incoming and outgoing foreign keys for this table. It has two keys, \"incoming\" and \"outgoing\" , each of which is a list of dictionaries with keys \"column\" , \"other_table\" and \"other_column\" . For example: \n {\n \"incoming\": [],\n \"outgoing\": [\n {\n \"other_table\": \"attraction_characteristic\",\n \"column\": \"characteristic_id\",\n \"other_column\": \"pk\",\n },\n {\n \"other_table\": \"roadside_attractions\",\n \"column\": \"attraction_id\",\n \"other_column\": \"pk\",\n }\n ]\n}", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:internals-datasette", "page": "internals", "ref": "internals-datasette", "title": "Datasette class", "content": "This object is an instance of the Datasette class, passed to many plugin hooks as an argument called datasette . \n You can create your own instance of this - for example to help write tests for a plugin - like so: \n from datasette.app import Datasette\n\n# With no arguments a single in-memory database will be attached\ndatasette = Datasette()\n\n# The files= argument can load files from disk\ndatasette = Datasette(files=[\"/path/to/my-database.db\"])\n\n# Pass metadata as a JSON dictionary like this\ndatasette = Datasette(\n files=[\"/path/to/my-database.db\"],\n metadata={\n \"databases\": {\n \"my-database\": {\n \"description\": \"This is my database\"\n }\n }\n },\n) \n Constructor parameters include: \n \n \n files=[...] - a list of database files to open \n \n \n immutables=[...] - a list of database files to open in immutable mode \n \n \n metadata={...} - a dictionary of Metadata \n \n \n config_dir=... - the configuration directory to use, stored in datasette.config_dir", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-datasette-urls", "page": "internals", "ref": "internals-datasette-urls", "title": "datasette.urls", "content": "The datasette.urls object contains methods for building URLs to pages within Datasette. Plugins should use this to link to pages, since these methods take into account any base_url configuration setting that might be in effect. \n \n \n datasette.urls.instance(format=None) \n \n Returns the URL to the Datasette instance root page. This is usually \"/\" . \n \n \n \n datasette.urls.path(path, format=None) \n \n Takes a path and returns the full path, taking base_url into account. \n For example, datasette.urls.path(\"-/logout\") will return the path to the logout page, which will be \"/-/logout\" by default or /prefix-path/-/logout if base_url is set to /prefix-path/ \n \n \n \n datasette.urls.logout() \n \n Returns the URL to the logout page, usually \"/-/logout\" \n \n \n \n datasette.urls.static(path) \n \n Returns the URL of one of Datasette's default static assets, for example \"/-/static/app.css\" \n \n \n \n datasette.urls.static_plugins(plugin_name, path) \n \n Returns the URL of one of the static assets belonging to a plugin. \n datasette.urls.static_plugins(\"datasette_cluster_map\", \"datasette-cluster-map.js\") would return \"/-/static-plugins/datasette_cluster_map/datasette-cluster-map.js\" \n \n \n \n datasette.urls.static(path) \n \n Returns the URL of one of Datasette's default static assets, for example \"/-/static/app.css\" \n \n \n \n datasette.urls.database(database_name, format=None) \n \n Returns the URL to a database page, for example \"/fixtures\" \n \n \n \n datasette.urls.table(database_name, table_name, format=None) \n \n Returns the URL to a table page, for example \"/fixtures/facetable\" \n \n \n \n datasette.urls.query(database_name, query_name, format=None) \n \n Returns the URL to a query page, for example \"/fixtures/pragma_cache_size\" \n \n \n \n These functions can be accessed via the {{ urls }} object in Datasette templates, for example: \n Homepage\nFixtures database\nfacetable table\npragma_cache_size query \n Use the format=\"json\" (or \"csv\" or other formats supported by plugins) arguments to get back URLs to the JSON representation. This is the path with .json added on the end. \n These methods each return a datasette.utils.PrefixedUrlString object, which is a subclass of the Python str type. This allows the logic that considers the base_url setting to detect if that prefix has already been applied to the path.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:internals-internal", "page": "internals", "ref": "internals-internal", "title": "Datasette's internal database", "content": "Datasette maintains an \"internal\" SQLite database used for configuration, caching, and storage. Plugins can store configuration, settings, and other data inside this database. By default, Datasette will use a temporary in-memory SQLite database as the internal database, which is created at startup and destroyed at shutdown. Users of Datasette can optionally pass in a --internal flag to specify the path to a SQLite database to use as the internal database, which will persist internal data across Datasette instances. \n Datasette maintains tables called catalog_databases , catalog_tables , catalog_columns , catalog_indexes , catalog_foreign_keys with details of the attached databases and their schemas. These tables should not be considered a stable API - they may change between Datasette releases. \n The internal database is not exposed in the Datasette application by default, which means private data can safely be stored without worry of accidentally leaking information through the default Datasette interface and API. However, other plugins do have full read and write access to the internal database. \n Plugins can access this database by calling internal_db = datasette.get_internal_database() and then executing queries using the Database API . \n Plugin authors are asked to practice good etiquette when using the internal database, as all plugins use the same database to store data. For example: \n \n \n Use a unique prefix when creating tables, indices, and triggers in the internal database. If your plugin is called datasette-xyz , then prefix names with datasette_xyz_* . \n \n \n Avoid long-running write statements that may stall or block other plugins that are trying to write at the same time. \n \n \n Use temporary tables or shared in-memory attached databases when possible. \n \n \n Avoid implementing features that could expose private data stored in the internal database by other plugins.", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-multiparams", "page": "internals", "ref": "internals-multiparams", "title": "The MultiParams class", "content": "request.args is a MultiParams object - a dictionary-like object which provides access to query string parameters that may have multiple values. \n Consider the query string ?foo=1&foo=2&bar=3 - with two values for foo and one value for bar . \n \n \n request.args[key] - string \n \n Returns the first value for that key, or raises a KeyError if the key is missing. For the above example request.args[\"foo\"] would return \"1\" . \n \n \n \n request.args.get(key) - string or None \n \n Returns the first value for that key, or None if the key is missing. Pass a second argument to specify a different default, e.g. q = request.args.get(\"q\", \"\") . \n \n \n \n request.args.getlist(key) - list of strings \n \n Returns the list of strings for that key. request.args.getlist(\"foo\") would return [\"1\", \"2\"] in the above example. request.args.getlist(\"bar\") would return [\"3\"] . If the key is missing an empty list will be returned. \n \n \n \n request.args.keys() - list of strings \n \n Returns the list of available keys - for the example this would be [\"foo\", \"bar\"] . \n \n \n \n key in request.args - True or False \n \n You can use if key in request.args to check if a key is present. \n \n \n \n for key in request.args - iterator \n \n This lets you loop through every available key. \n \n \n \n len(request.args) - integer \n \n Returns the number of keys.", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-response", "page": "internals", "ref": "internals-response", "title": "Response class", "content": "The Response class can be returned from view functions that have been registered using the register_routes(datasette) hook. \n The Response() constructor takes the following arguments: \n \n \n body - string \n \n The body of the response. \n \n \n \n status - integer (optional) \n \n The HTTP status - defaults to 200. \n \n \n \n headers - dictionary (optional) \n \n A dictionary of extra HTTP headers, e.g. {\"x-hello\": \"world\"} . \n \n \n \n content_type - string (optional) \n \n The content-type for the response. Defaults to text/plain . \n \n \n \n For example: \n from datasette.utils.asgi import Response\n\nresponse = Response(\n \"
This is a custom panel that I added using a JavaScript plugin
';\n }\n }\n ]\n }\n });\n}); \n 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.", "breadcrumbs": "[\"JavaScript plugins\", \"JavaScript plugin objects\"]", "references": "[]"} {"id": "javascript_plugins:javascript-plugins-makecolumnactions", "page": "javascript_plugins", "ref": "javascript-plugins-makecolumnactions", "title": "makeColumnActions(columnDetails)", "content": "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. \n The method will be called with a columnDetails object with the following keys: \n \n \n columnName - string \n \n The name of the column \n \n \n \n columnNotNull - boolean \n \n True if the column is defined as NOT NULL \n \n \n \n columnType - string \n \n The SQLite data type of the column \n \n \n \n isPk - boolean \n \n True if the column is part of the primary key \n \n \n \n It should return a JavaScript array of objects each with a label and onClick property: \n \n \n label - string \n \n The human-readable label for the action \n \n \n \n onClick(evt) - function \n \n A function that will be called when the action is clicked \n \n \n \n The evt object passed to the onClick is the standard browser event object that triggered the click. \n 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: \n document.addEventListener('datasette_init', function(ev) {\n ev.detail.registerPlugin('column-name-plugin', {\n version: 0.1,\n makeColumnActions: (columnDetails) => {\n return [\n {\n label: 'Copy column to clipboard',\n onClick: async (evt) => {\n await navigator.clipboard.writeText(columnDetails.columnName)\n }\n },\n {\n label: 'Alert column metadata',\n onClick: () => alert(JSON.stringify(columnDetails, null, 2))\n }\n ];\n }\n });\n});", "breadcrumbs": "[\"JavaScript plugins\", \"JavaScript plugin objects\"]", "references": "[]"} {"id": "json_api:column-filter-arguments", "page": "json_api", "ref": "column-filter-arguments", "title": "Column filter arguments", "content": "You can filter the data returned by the table based on column values using a query string argument. \n \n \n ?column__exact=value or ?_column=value \n \n Returns rows where the specified column exactly matches the value. \n \n \n \n ?column__not=value \n \n Returns rows where the column does not match the value. \n \n \n \n ?column__contains=value \n \n Rows where the string column contains the specified value ( column like \"%value%\" in SQL). \n \n \n \n ?column__notcontains=value \n \n Rows where the string column does not contain the specified value ( column not like \"%value%\" in SQL). \n \n \n \n ?column__endswith=value \n \n Rows where the string column ends with the specified value ( column like \"%value\" in SQL). \n \n \n \n ?column__startswith=value \n \n Rows where the string column starts with the specified value ( column like \"value%\" in SQL). \n \n \n \n ?column__gt=value \n \n Rows which are greater than the specified value. \n \n \n \n ?column__gte=value \n \n Rows which are greater than or equal to the specified value. \n \n \n \n ?column__lt=value \n \n Rows which are less than the specified value. \n \n \n \n ?column__lte=value \n \n Rows which are less than or equal to the specified value. \n \n \n \n ?column__like=value \n \n Match rows with a LIKE clause, case insensitive and with % as the wildcard character. \n \n \n \n ?column__notlike=value \n \n Match rows that do not match the provided LIKE clause. \n \n \n \n ?column__glob=value \n \n Similar to LIKE but uses Unix wildcard syntax and is case sensitive. \n \n \n \n ?column__in=value1,value2,value3 \n \n Rows where column matches any of the provided values. \n You can use a comma separated string, or you can use a JSON array. \n The JSON array option is useful if one of your matching values itself contains a comma: \n ?column__in=[\"value\",\"value,with,commas\"] \n \n \n \n ?column__notin=value1,value2,value3 \n \n Rows where column does not match any of the provided values. The inverse of __in= . Also supports JSON arrays. \n \n \n \n ?column__arraycontains=value \n \n Works against columns that contain JSON arrays - matches if any of the values in that array match the provided value. \n This is only available if the json1 SQLite extension is enabled. \n \n \n \n ?column__arraynotcontains=value \n \n Works against columns that contain JSON arrays - matches if none of the values in that array match the provided value. \n This is only available if the json1 SQLite extension is enabled. \n \n \n \n ?column__date=value \n \n Column is a datestamp occurring on the specified YYYY-MM-DD date, e.g. 2018-01-02 . \n \n \n \n ?column__isnull=1 \n \n Matches rows where the column is null. \n \n \n \n ?column__notnull=1 \n \n Matches rows where the column is not null. \n \n \n \n ?column__isblank=1 \n \n Matches rows where the column is blank, meaning null or the empty string. \n \n \n \n ?column__notblank=1 \n \n Matches rows where the column is not blank.", "breadcrumbs": "[\"JSON API\", \"Table arguments\"]", "references": "[]"} {"id": "json_api:expand-foreign-keys", "page": "json_api", "ref": "expand-foreign-keys", "title": "Expanding foreign key references", "content": "Datasette can detect foreign key relationships and resolve those references into\n labels. The HTML interface does this by default for every detected foreign key\n column - you can turn that off using ?_labels=off . \n You can request foreign keys be expanded in JSON using the _labels=on or\n _label=COLUMN special query string parameters. Here's what an expanded row\n looks like: \n [\n {\n \"rowid\": 1,\n \"TreeID\": 141565,\n \"qLegalStatus\": {\n \"value\": 1,\n \"label\": \"Permitted Site\"\n },\n \"qSpecies\": {\n \"value\": 1,\n \"label\": \"Myoporum laetum :: Myoporum\"\n },\n \"qAddress\": \"501X Baker St\",\n \"SiteOrder\": 1\n }\n] \n The column in the foreign key table that is used for the label can be specified\n in metadata.json - see Specifying the label column for a table .", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:id1", "page": "json_api", "ref": "id1", "title": "JSON API", "content": "Datasette provides a JSON API for your SQLite databases. Anything you can do\n through the Datasette user interface can also be accessed as JSON via the API. \n To access the API for a page, either click on the .json link on that page or\n edit the URL and add a .json extension to it.", "breadcrumbs": "[]", "references": "[]"} {"id": "json_api:id2", "page": "json_api", "ref": "id2", "title": "Table arguments", "content": "The Datasette table view takes a number of special query string arguments.", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:json-api-cors", "page": "json_api", "ref": "json-api-cors", "title": "Enabling CORS", "content": "If you start Datasette with the --cors option, each JSON endpoint will be\n served with the following additional HTTP headers: \n [[[cog\nfrom datasette.utils import add_cors_headers\nimport textwrap\nheaders = {}\nadd_cors_headers(headers)\noutput = \"\\n\".join(\"{}: {}\".format(k, v) for k, v in headers.items())\ncog.out(\"\\n::\\n\\n\")\ncog.out(textwrap.indent(output, ' '))\ncog.out(\"\\n\\n\") \n ]]] \n Access-Control-Allow-Origin: *\nAccess-Control-Allow-Headers: Authorization, Content-Type\nAccess-Control-Expose-Headers: Link\nAccess-Control-Allow-Methods: GET, POST, HEAD, OPTIONS\nAccess-Control-Max-Age: 3600 \n [[[end]]] \n This allows JavaScript running on any domain to make cross-origin\n requests to interact with the Datasette API. \n If you start Datasette without the --cors option only JavaScript running on\n the same domain as Datasette will be able to access the API. \n Here's how to serve data.db with CORS enabled: \n datasette data.db --cors", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:json-api-default", "page": "json_api", "ref": "json-api-default", "title": "Default representation", "content": "The default JSON representation of data from a SQLite table or custom query\n looks like this: \n {\n \"ok\": true,\n \"rows\": [\n {\n \"id\": 3,\n \"name\": \"Detroit\"\n },\n {\n \"id\": 2,\n \"name\": \"Los Angeles\"\n },\n {\n \"id\": 4,\n \"name\": \"Memnonia\"\n },\n {\n \"id\": 1,\n \"name\": \"San Francisco\"\n }\n ],\n \"truncated\": false\n} \n \"ok\" is always true if an error did not occur. \n The \"rows\" key is a list of objects, each one representing a row. \n The \"truncated\" key lets you know if the query was truncated. This can happen if a SQL query returns more than 1,000 results (or the max_returned_rows setting). \n For table pages, an additional key \"next\" may be present. This indicates that the next page in the pagination set can be retrieved using ?_next=VALUE .", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:json-api-discover-alternate", "page": "json_api", "ref": "json-api-discover-alternate", "title": "Discovering the JSON for a page", "content": "Most of the HTML pages served by Datasette provide a mechanism for discovering their JSON equivalents using the HTML link mechanism. \n You can find this near the top of the source code of those pages, looking like this: \n \n The JSON URL is also made available in a Link HTTP header for the page: \n Link: https://latest.datasette.io/fixtures/sortable.json; rel=\"alternate\"; type=\"application/json+datasette\"", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:json-api-shapes", "page": "json_api", "ref": "json-api-shapes", "title": "Different shapes", "content": "The _shape parameter can be used to access alternative formats for the\n rows key which may be more convenient for your application. There are three\n options: \n \n \n ?_shape=objects - \"rows\" is a list of JSON key/value objects - the default \n \n \n ?_shape=arrays - \"rows\" is a list of lists, where the order of values in each list matches the order of the columns \n \n \n ?_shape=array - a JSON array of objects - effectively just the \"rows\" key from the default representation \n \n \n ?_shape=array&_nl=on - a newline-separated list of JSON objects \n \n \n ?_shape=arrayfirst - a flat JSON array containing just the first value from each row \n \n \n ?_shape=object - a JSON object keyed using the primary keys of the rows \n \n \n _shape=arrays looks like this: \n {\n \"ok\": true,\n \"next\": null,\n \"rows\": [\n [3, \"Detroit\"],\n [2, \"Los Angeles\"],\n [4, \"Memnonia\"],\n [1, \"San Francisco\"]\n ]\n} \n _shape=array looks like this: \n [\n {\n \"id\": 3,\n \"name\": \"Detroit\"\n },\n {\n \"id\": 2,\n \"name\": \"Los Angeles\"\n },\n {\n \"id\": 4,\n \"name\": \"Memnonia\"\n },\n {\n \"id\": 1,\n \"name\": \"San Francisco\"\n }\n] \n _shape=array&_nl=on looks like this: \n {\"id\": 1, \"value\": \"Myoporum laetum :: Myoporum\"}\n{\"id\": 2, \"value\": \"Metrosideros excelsa :: New Zealand Xmas Tree\"}\n{\"id\": 3, \"value\": \"Pinus radiata :: Monterey Pine\"} \n _shape=arrayfirst looks like this: \n [1, 2, 3] \n _shape=object looks like this: \n {\n \"1\": {\n \"id\": 1,\n \"value\": \"Myoporum laetum :: Myoporum\"\n },\n \"2\": {\n \"id\": 2,\n \"value\": \"Metrosideros excelsa :: New Zealand Xmas Tree\"\n },\n \"3\": {\n \"id\": 3,\n \"value\": \"Pinus radiata :: Monterey Pine\"\n }\n] \n The object shape is only available for queries against tables - custom SQL\n queries and views do not have an obvious primary key so cannot be returned using\n this format. \n The object keys are always strings. If your table has a compound primary\n key, the object keys will be a comma-separated string.", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:json-api-write", "page": "json_api", "ref": "json-api-write", "title": "The JSON write API", "content": "Datasette provides a write API for JSON data. This is a POST-only API that requires an authenticated API token, see API Tokens . The token will need to have the specified Permissions .", "breadcrumbs": "[\"JSON API\"]", "references": "[]"} {"id": "json_api:rowdeleteview", "page": "json_api", "ref": "rowdeleteview", "title": "Deleting a row", "content": "To delete a row, make a POST to /