{"id": "internals:database-close", "page": "internals", "ref": "database-close", "title": "db.close()", "content": "Closes all of the open connections to file-backed databases. This is mainly intended to be used by large test suites, to avoid hitting limits on the number of open files.", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-constructor", "page": "internals", "ref": "database-constructor", "title": "Database(ds, path=None, is_mutable=True, is_memory=False, memory_name=None)", "content": "The  Database()  constructor can be used by plugins, in conjunction with  .add_database(db, name=None, route=None) , to create and register new databases. \n                 The arguments are as follows: \n                 \n                     \n                         ds  -  Datasette class  (required) \n                         \n                             The Datasette instance you are attaching this database to. \n                         \n                     \n                     \n                         path  - string \n                         \n                             Path to a SQLite database file on disk. \n                         \n                     \n                     \n                         is_mutable  - boolean \n                         \n                             Set this to  False  to cause Datasette to open the file in immutable mode. \n                         \n                     \n                     \n                         is_memory  - boolean \n                         \n                             Use this to create non-shared memory connections. \n                         \n                     \n                     \n                         memory_name  - string or  None \n                         \n                             Use this to create a named in-memory database. Unlike regular memory databases these can be accessed by multiple threads and will persist an changes made to them for the lifetime of the Datasette server process. \n                         \n                     \n                 \n                 The first argument is the  datasette  instance you are attaching to, the second is a  path= , then  is_mutable  and  is_memory  are both optional arguments.", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-execute", "page": "internals", "ref": "database-execute", "title": "await db.execute(sql, ...)", "content": "Executes a SQL query against the database and returns the resulting rows (see  Results ). \n                 \n                     \n                         sql  - string (required) \n                         \n                             The SQL query to execute. This can include  ?  or  :named  parameters. \n                         \n                     \n                     \n                         params  - list or dict \n                         \n                             A list or dictionary of values to use for the parameters. List for  ? , dictionary for  :named . \n                         \n                     \n                     \n                         truncate  - boolean \n                         \n                             Should the rows returned by the query be truncated at the maximum page size? Defaults to  True , set this to  False  to disable truncation. \n                         \n                     \n                     \n                         custom_time_limit  - integer ms \n                         \n                             A custom time limit for this query. This can be set to a lower value than the Datasette configured default. If a query takes longer than this it will be terminated early and raise a  dataette.database.QueryInterrupted  exception. \n                         \n                     \n                     \n                         page_size  - integer \n                         \n                             Set a custom page size for truncation, over-riding the configured Datasette default. \n                         \n                     \n                     \n                         log_sql_errors  - boolean \n                         \n                             Should any SQL errors be logged to the console in addition to being raised as an error? Defaults to  True .", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-execute-fn", "page": "internals", "ref": "database-execute-fn", "title": "await db.execute_fn(fn)", "content": "Executes a given callback function against a read-only database connection running in a thread. The function will be passed a SQLite connection, and the return value from the function will be returned by the  await . \n                 Example usage: \n                 def get_version(conn):\n    return conn.execute(\n        \"select sqlite_version()\"\n    ).fetchall()[0][0]\n\n\nversion = await db.execute_fn(get_version)", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-execute-write", "page": "internals", "ref": "database-execute-write", "title": "await db.execute_write(sql, params=None, block=True)", "content": "SQLite only allows one database connection to write at a time. Datasette handles this for you by maintaining a queue of writes to be executed against a given database. Plugins can submit write operations to this queue and they will be executed in the order in which they are received. \n                 This method can be used to queue up a non-SELECT SQL query to be executed against a single write connection to the database. \n                 You can pass additional SQL parameters as a tuple or dictionary. \n                 The method will block until the operation is completed, and the return value will be the return from calling  conn.execute(...)  using the underlying  sqlite3  Python library. \n                 If you pass  block=False  this behavior changes to \"fire and forget\" - queries will be added to the write queue and executed in a separate thread while your code can continue to do other things. The method will return a UUID representing the queued task. \n                 Each call to  execute_write()  will be executed inside a transaction.", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-execute-write-fn", "page": "internals", "ref": "database-execute-write-fn", "title": "await db.execute_write_fn(fn, block=True, transaction=True)", "content": "This method works like  .execute_write() , but instead of a SQL statement you give it a callable Python function. Your function will be queued up and then called when the write connection is available, passing that connection as the argument to the function. \n                 The function can then perform multiple actions, safe in the knowledge that it has exclusive access to the single writable connection for as long as it is executing. \n                 \n                     fn  needs to be a regular function, not an  async def  function. \n                 \n                 For example: \n                 def delete_and_return_count(conn):\n    conn.execute(\"delete from some_table where id > 5\")\n    return conn.execute(\n        \"select count(*) from some_table\"\n    ).fetchone()[0]\n\n\ntry:\n    num_rows_left = await database.execute_write_fn(\n        delete_and_return_count\n    )\nexcept Exception as e:\n    print(\"An error occurred:\", e) \n                 The value returned from  await database.execute_write_fn(...)  will be the return value from your function. \n                 If your function raises an exception that exception will be propagated up to the  await  line. \n                 By default your function will be executed inside a transaction. You can pass  transaction=False  to disable this behavior, though if you do that you should be careful to manually apply transactions - ideally using the  with conn:  pattern, or you may see  OperationalError: database table is locked  errors. \n                 If you specify  block=False  the method becomes fire-and-forget, queueing your function to be executed and then allowing your code after the call to  .execute_write_fn()  to continue running while the underlying thread waits for an opportunity to run your function. A UUID representing the queued task will be returned. Any exceptions in your code will be silently swallowed.", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:database-hash", "page": "internals", "ref": "database-hash", "title": "db.hash", "content": "If the database was opened in immutable mode, this property returns the 64 character SHA-256 hash of the database contents as a string. Otherwise it returns  None .", "breadcrumbs": "[\"Internals for plugins\", \"Database class\"]", "references": "[]"}
{"id": "internals:datasette-absolute-url", "page": "internals", "ref": "datasette-absolute-url", "title": ".absolute_url(request, path)", "content": "request  - Request \n                         \n                             The current Request object \n                         \n                     \n                     \n                         path  - string \n                         \n                             A path, for example  /dbname/table.json \n                         \n                     \n                 \n                 Returns the absolute URL for the given path, including the protocol and host. For example: \n                 absolute_url = datasette.absolute_url(\n    request, \"/dbname/table.json\"\n)\n# Would return \"http://localhost:8001/dbname/table.json\" \n                 The current request object is used to determine the hostname and protocol that should be used for the returned URL. The  force_https_urls  configuration setting is taken into account.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-actors-from-ids", "page": "internals", "ref": "datasette-actors-from-ids", "title": "await .actors_from_ids(actor_ids)", "content": "actor_ids  - list of strings or integers \n                         \n                             A list of actor IDs to look up. \n                         \n                     \n                 \n                 Returns a dictionary, where the keys are the IDs passed to it and the values are the corresponding actor dictionaries. \n                 This method is mainly designed to be used with plugins. See the  actors_from_ids(datasette, actor_ids)  documentation for details. \n                 If no plugins that implement that hook are installed, the default return value looks like this: \n                 {\n    \"1\": {\"id\": \"1\"},\n    \"2\": {\"id\": \"2\"}\n}", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-add-database", "page": "internals", "ref": "datasette-add-database", "title": ".add_database(db, name=None, route=None)", "content": "db  - datasette.database.Database instance \n                         \n                             The database to be attached. \n                         \n                     \n                     \n                         name  - string, optional \n                         \n                             The name to be used for this database . If not specified Datasette will pick one based on the filename or memory name. \n                         \n                     \n                     \n                         route  - string, optional \n                         \n                             This will be used in the URL path. If not specified, it will default to the same thing as the  name . \n                         \n                     \n                 \n                 The  datasette.add_database(db)  method lets you add a new database to the current Datasette instance. \n                 The  db  parameter should be an instance of the  datasette.database.Database  class. For example: \n                 from datasette.database import Database\n\ndatasette.add_database(\n    Database(\n        datasette,\n        path=\"path/to/my-new-database.db\",\n    )\n) \n                 This will add a mutable database and serve it at  /my-new-database . \n                 Use  is_mutable=False  to add an immutable database. \n                 .add_database()  returns the Database instance, with its name set as the  database.name  attribute. Any time you are working with a newly added database you should use the return value of  .add_database() , for example: \n                 db = datasette.add_database(\n    Database(datasette, memory_name=\"statistics\")\n)\nawait db.execute_write(\n    \"CREATE TABLE foo(id integer primary key)\"\n)", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-add-memory-database", "page": "internals", "ref": "datasette-add-memory-database", "title": ".add_memory_database(name)", "content": "Adds a shared in-memory database with the specified name: \n                 datasette.add_memory_database(\"statistics\") \n                 This is a shortcut for the following: \n                 from datasette.database import Database\n\ndatasette.add_database(\n    Database(datasette, memory_name=\"statistics\")\n) \n                 Using either of these pattern will result in the in-memory database being served at  /statistics .", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-add-message", "page": "internals", "ref": "datasette-add-message", "title": ".add_message(request, message, type=datasette.INFO)", "content": "request  - Request \n                         \n                             The current Request object \n                         \n                     \n                     \n                         message  - string \n                         \n                             The message string \n                         \n                     \n                     \n                         type  - constant, optional \n                         \n                             The message type -  datasette.INFO ,  datasette.WARNING  or  datasette.ERROR \n                         \n                     \n                 \n                 Datasette's flash messaging mechanism allows you to add a message that will be displayed to the user on the next page that they visit. Messages are persisted in a  ds_messages  cookie. This method adds a message to that cookie. \n                 You can try out these messages (including the different visual styling of the three message types) using the  /-/messages  debugging tool.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-check-visibility", "page": "internals", "ref": "datasette-check-visibility", "title": "await .check_visibility(actor, action=None, resource=None, permissions=None)", "content": "actor  - dictionary \n                         \n                             The authenticated actor. This is usually  request.actor . \n                         \n                     \n                     \n                         action  - string, optional \n                         \n                             The name of the action that is being permission checked. \n                         \n                     \n                     \n                         resource  - string or tuple, optional \n                         \n                             The resource, e.g. the name of the database, or a tuple of two strings containing the name of the database and the name of the table. Only some permissions apply to a resource. \n                         \n                     \n                     \n                         permissions  - list of  action  strings or  (action, resource)  tuples, optional \n                         \n                             Provide this instead of  action  and  resource  to check multiple permissions at once. \n                         \n                     \n                 \n                 This convenience method can be used to answer the question \"should this item be considered private, in that it is visible to me but it is not visible to anonymous users?\" \n                 It returns a tuple of two booleans,  (visible, private) .  visible  indicates if the actor can see this resource.  private  will be  True  if an anonymous user would not be able to view the resource. \n                 This example checks if the user can access a specific table, and sets  private  so that a padlock icon can later be displayed: \n                 visible, private = await datasette.check_visibility(\n    request.actor,\n    action=\"view-table\",\n    resource=(database, table),\n) \n                 The following example runs three checks in a row, similar to  await .ensure_permissions(actor, permissions) . If any of the checks are denied before one of them is explicitly granted then  visible  will be  False .  private  will be  True  if an anonymous user would not be able to view the resource. \n                 visible, private = await datasette.check_visibility(\n    request.actor,\n    permissions=[\n        (\"view-table\", (database, table)),\n        (\"view-database\", database),\n        \"view-instance\",\n    ],\n)", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-create-token", "page": "internals", "ref": "datasette-create-token", "title": ".create_token(actor_id, expires_after=None, restrict_all=None, restrict_database=None, restrict_resource=None)", "content": "actor_id  - string \n                         \n                             The ID of the actor to create a token for. \n                         \n                     \n                     \n                         expires_after  - int, optional \n                         \n                             The number of seconds after which the token should expire. \n                         \n                     \n                     \n                         restrict_all  - iterable, optional \n                         \n                             A list of actions that this token should be restricted to across all databases and resources. \n                         \n                     \n                     \n                         restrict_database  - dict, optional \n                         \n                             For restricting actions within specific databases, e.g.  {\"mydb\": [\"view-table\", \"view-query\"]} . \n                         \n                     \n                     \n                         restrict_resource  - dict, optional \n                         \n                             For restricting actions to specific resources (tables, SQL views and  Canned queries ) within a database. For example:  {\"mydb\": {\"mytable\": [\"insert-row\", \"update-row\"]}} . \n                         \n                     \n                 \n                 This method returns a signed  API token  of the format  dstok_...  which can be used to authenticate requests to the Datasette API. \n                 All tokens must have an  actor_id  string indicating the ID of the actor which the token will act on behalf of. \n                 Tokens default to lasting forever, but can be set to expire after a given number of seconds using the  expires_after  argument. The following code creates a token for  user1  that will expire after an hour: \n                 token = datasette.create_token(\n    actor_id=\"user1\",\n    expires_after=3600,\n) \n                 The three  restrict_*  arguments can be used to create a token that has additional restrictions beyond what the associated actor is allowed to do. \n                 The following example creates a token that can access  view-instance  and  view-table  across everything, can additionally use  view-query  for anything in the  docs  database and is allowed to execute  insert-row  and  update-row  in the  attachments  table in that database: \n                 token = datasette.create_token(\n    actor_id=\"user1\",\n    restrict_all=(\"view-instance\", \"view-table\"),\n    restrict_database={\"docs\": (\"view-query\",)},\n    restrict_resource={\n        \"docs\": {\n            \"attachments\": (\"insert-row\", \"update-row\")\n        }\n    },\n)", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-databases", "page": "internals", "ref": "datasette-databases", "title": ".databases", "content": "Property exposing a  collections.OrderedDict  of databases currently connected to Datasette. \n                 The dictionary keys are the name of the database that is used in the URL - e.g.  /fixtures  would have a key of  \"fixtures\" . The values are  Database class  instances. \n                 All databases are listed, irrespective of user permissions.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-ensure-permissions", "page": "internals", "ref": "datasette-ensure-permissions", "title": "await .ensure_permissions(actor, permissions)", "content": "actor  - dictionary \n                         \n                             The authenticated actor. This is usually  request.actor . \n                         \n                     \n                     \n                         permissions  - list \n                         \n                             A list of permissions to check. Each permission in that list can be a string  action  name or a 2-tuple of  (action, resource) . \n                         \n                     \n                 \n                 This method allows multiple permissions to be checked at once. It raises a  datasette.Forbidden  exception if any of the checks are denied before one of them is explicitly granted. \n                 This is useful when you need to check multiple permissions at once. For example, an actor should be able to view a table if either one of the following checks returns  True  or not a single one of them returns  False : \n                 await datasette.ensure_permissions(\n    request.actor,\n    [\n        (\"view-table\", (database, table)),\n        (\"view-database\", database),\n        \"view-instance\",\n    ],\n)", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-get-database", "page": "internals", "ref": "datasette-get-database", "title": ".get_database(name)", "content": "name  - string, optional \n                         \n                             The name of the database - optional. \n                         \n                     \n                 \n                 Returns the specified database object. Raises a  KeyError  if the database does not exist. Call this method without an argument to return the first connected database.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-get-permission", "page": "internals", "ref": "datasette-get-permission", "title": ".get_permission(name_or_abbr)", "content": "name_or_abbr  - string \n                         \n                             The name or abbreviation of the permission to look up, e.g.  view-table  or  vt . \n                         \n                     \n                 \n                 Returns a  Permission object  representing the permission, or raises a  KeyError  if one is not found.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-permission-allowed", "page": "internals", "ref": "datasette-permission-allowed", "title": "await .permission_allowed(actor, action, resource=None, default=...)", "content": "actor  - dictionary \n                         \n                             The authenticated actor. This is usually  request.actor . \n                         \n                     \n                     \n                         action  - string \n                         \n                             The name of the action that is being permission checked. \n                         \n                     \n                     \n                         resource  - string or tuple, optional \n                         \n                             The resource, e.g. the name of the database, or a tuple of two strings containing the name of the database and the name of the table. Only some permissions apply to a resource. \n                         \n                     \n                     \n                         default  - optional: True, False or None \n                         \n                             What value should be returned by default if nothing provides an opinion on this permission check.\n                                Set to  True  for default allow or  False  for default deny.\n                                If not specified the  default  from the  Permission()  tuple that was registered using  register_permissions(datasette)  will be used. \n                         \n                     \n                 \n                 Check if the given actor has  permission  to perform the given action on the given resource. \n                 Some permission checks are carried out against  rules defined in datasette.yaml , while other custom permissions may be decided by plugins that implement the  permission_allowed(datasette, actor, action, resource)  plugin hook. \n                 If neither  metadata.json  nor any of the plugins provide an answer to the permission query the  default  argument will be returned. \n                 See  Built-in permissions  for a full list of permission actions included in Datasette core.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-permissions", "page": "internals", "ref": "datasette-permissions", "title": ".permissions", "content": "Property exposing a dictionary of permissions that have been registered using the  register_permissions(datasette)  plugin hook. \n                 The dictionary keys are the permission names - e.g.  view-instance  - and the values are  Permission()  objects describing the permission. Here is a  description of that object .", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-plugin-config", "page": "internals", "ref": "datasette-plugin-config", "title": ".plugin_config(plugin_name, database=None, table=None)", "content": "plugin_name  - string \n                         \n                             The name of the plugin to look up configuration for. Usually this is something similar to  datasette-cluster-map . \n                         \n                     \n                     \n                         database  - None or string \n                         \n                             The database the user is interacting with. \n                         \n                     \n                     \n                         table  - None or string \n                         \n                             The table the user is interacting with. \n                         \n                     \n                 \n                 This method lets you read plugin configuration values that were set in   datasette.yaml . See  Writing plugins that accept configuration  for full details of how this method should be used. \n                 The return value will be the value from the configuration file - usually a dictionary. \n                 If the plugin is not configured the return value will be  None .", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"id": "internals:datasette-remove-database", "page": "internals", "ref": "datasette-remove-database", "title": ".remove_database(name)", "content": "name  - string \n                         \n                             The name of the database to be removed. \n                         \n                     \n                 \n                 This removes a database that has been previously added.  name=  is the unique name of that database.", "breadcrumbs": "[\"Internals for plugins\", \"Datasette class\"]", "references": "[]"}
{"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-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                 <a href=\"{{ urls.instance() }}\">Homepage</a>\n<a href=\"{{ urls.database(\"fixtures\") }}\">Fixtures database</a>\n<a href=\"{{ urls.table(\"fixtures\", \"facetable\") }}\">facetable table</a>\n<a href=\"{{ urls.query(\"fixtures\", \"pragma_cache_size\") }}\">pragma_cache_size query</a> \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    \"<xml>This is XML</xml>\",\n    content_type=\"application/xml; charset=utf-8\",\n) \n             The quickest way to create responses is using the  Response.text(...) ,  Response.html(...) ,  Response.json(...)  or  Response.redirect(...)  helper methods: \n             from datasette.utils.asgi import Response\n\nhtml_response = Response.html(\"This is HTML\")\njson_response = Response.json({\"this_is\": \"json\"})\ntext_response = Response.text(\n    \"This will become utf-8 encoded text\"\n)\n# Redirects are served as 302, unless you pass status=301:\nredirect_response = Response.redirect(\n    \"https://latest.datasette.io/\"\n) \n             Each of these responses will use the correct corresponding content-type -  text/html; charset=utf-8 ,  application/json; charset=utf-8  or  text/plain; charset=utf-8  respectively. \n             Each of the helper methods take optional  status=  and  headers=  arguments, documented above.", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-response-asgi-send", "page": "internals", "ref": "internals-response-asgi-send", "title": "Returning a response with .asgi_send(send)", "content": "In most cases you will return  Response  objects from your own view functions. You can also use a  Response  instance to respond at a lower level via ASGI, for example if you are writing code that uses the  asgi_wrapper(datasette)  hook. \n                 Create a  Response  object and then use  await response.asgi_send(send) , passing the ASGI  send  function. For example: \n                 async def require_authorization(scope, receive, send):\n    response = Response.text(\n        \"401 Authorization Required\",\n        headers={\n            \"www-authenticate\": 'Basic realm=\"Datasette\", charset=\"UTF-8\"'\n        },\n        status=401,\n    )\n    await response.asgi_send(send)", "breadcrumbs": "[\"Internals for plugins\", \"Response class\"]", "references": "[]"}
{"id": "internals:internals-response-set-cookie", "page": "internals", "ref": "internals-response-set-cookie", "title": "Setting cookies with response.set_cookie()", "content": "To set cookies on the response, use the  response.set_cookie(...)  method. The method signature looks like this: \n                 def set_cookie(\n    self,\n    key,\n    value=\"\",\n    max_age=None,\n    expires=None,\n    path=\"/\",\n    domain=None,\n    secure=False,\n    httponly=False,\n    samesite=\"lax\",\n): ... \n                 You can use this with  datasette.sign()  to set signed cookies. Here's how you would set the  ds_actor cookie  for use with Datasette  authentication : \n                 response = Response.redirect(\"/\")\nresponse.set_cookie(\n    \"ds_actor\",\n    datasette.sign({\"a\": {\"id\": \"cleopaws\"}}, \"actor\"),\n)\nreturn response", "breadcrumbs": "[\"Internals for plugins\", \"Response class\"]", "references": "[]"}
{"id": "internals:internals-shortcuts", "page": "internals", "ref": "internals-shortcuts", "title": "Import shortcuts", "content": "The following commonly used symbols can be imported directly from the  datasette  module: \n             from datasette import Response\nfrom datasette import Forbidden\nfrom datasette import NotFound\nfrom datasette import hookimpl\nfrom datasette import actor_matches_allow", "breadcrumbs": "[\"Internals for plugins\"]", "references": "[]"}
{"id": "internals:internals-utils-derive-named-parameters", "page": "internals", "ref": "internals-utils-derive-named-parameters", "title": "derive_named_parameters(db, sql)", "content": "Derive the list of named parameters referenced in a SQL query, using an  explain  query executed against the provided database. \n                 \n                 \n                     async   datasette.utils. derive_named_parameters db :   Database sql :   str List [ str ] \n                     \n                         Given a SQL statement, return a list of named parameters that are used in the statement \n                         e.g. for  select * from foo where id=:id  this would return  [\"id\"]", "breadcrumbs": "[\"Internals for plugins\", \"The datasette.utils module\"]", "references": "[]"}
{"id": "internals:internals-utils-parse-metadata", "page": "internals", "ref": "internals-utils-parse-metadata", "title": "parse_metadata(content)", "content": "This function accepts a string containing either JSON or YAML, expected to be of the format described in  Metadata . It returns a nested Python dictionary representing the parsed data from that string. \n                 If the metadata cannot be parsed as either JSON or YAML the function will raise a  utils.BadMetadataError  exception. \n                 \n                 \n                     datasette.utils. parse_metadata content :   str dict \n                     \n                         Detects if content is JSON or YAML and parses it appropriately.", "breadcrumbs": "[\"Internals for plugins\", \"The datasette.utils module\"]", "references": "[]"}