Internals for plugins¶
Many Plugin hooks are passed objects that provide access to internal Datasette functionality. The interface to these objects should not be considered stable (at least until Datasette 1.0) with the exception of methods that are documented on this page.
This object is an instance of the
Datasette class, passed to many plugin hooks as an argument called
.plugin_config(plugin_name, database=None, table=None)¶
- The name of the plugin to look up configuration for. Usually this is something similar to
database- None or string
- The database the user is interacting with.
table- None or string
- The table the user is interacting with.
This method lets you read plugin configuration values that were set in
metadata.json. See Writing plugins that accept configuration for full details of how this method should be used.
.render_template(template, context=None, request=None)¶
- The template file to be rendered, e.g.
my_plugin.html. Datasette will search for this file first in the
--template-dir=location, if it was specified - then in the plugin's bundled templates and finally in Datasette's set of default templates.
context- None or a Python dictionary
- The context variables to pass to the template.
request- request object or None
- If you pass a Datasette request object here it will be made available to the template.
Renders a Jinja template using Datasette's preconfigured instance of Jinja and returns the resulting string. The template will have access to Datasette's default template functions and any functions that have been made available by other plugins.
- The unique name to use for this database. Also used in the URL.
db- datasette.database.Database instance
- The database to be attached.
datasette.add_database(name, db) method lets you add a new database to the current Datasette instance. This database will then be served at URL path that matches the
name parameter, e.g.
db parameter should be an instance of the
datasette.database.Database class. For example:
from datasette.database import Database datasette.add_database("my-new-database", Database( datasette, path="path/to/my-new-database.db", is_mutable=True ))
This will add a mutable database from the provided file path.
Database() constructor takes four arguments: the first is the
datasette instance you are attaching to, the second is a
is_memory are both optional arguments.
is_mutable if it is possible that updates will be made to that database - otherwise Datasette will open it in immutable mode and any changes could cause undesired behavior.
is_memory if the connection is to an in-memory SQLite database.
- The name of the database to be removed.
This removes a database that has been previously added.
name= is the unique name of that database, also used in the URL for it.
Instances of the
Database class can be used to execute queries against attached SQLite databases, and to run introspection against their schemas.
await db.execute(sql, ...)¶
Executes a SQL query against the database and returns the resulting rows (see Results).
sql- string (required)
- The SQL query to execute. This can include
params- list or dict
- A list or dictionary of values to use for the parameters. List for
?, dictionary for
- Should the rows returned by the query be truncated at the maximum page size? Defaults to
True, set this to
Falseto disable truncation.
custom_time_limit- integer ms
- 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
- Set a custom page size for truncation, over-riding the configured Datasette default.
- Should any SQL errors be logged to the console in addition to being raised as an error? Defaults to
db.execute() method returns a single
Results object. This can be used to access the rows returned by the query.
Iterating over a
Results object will yield SQLite Row objects. Each of these can be treated as a tuple or can be accessed using
info =  results = await db.execute("select name from sqlite_master") for row in results: info.append(row["name"])
Results object also has the following properties and methods:
- Indicates if this query was truncated - if it returned more results than the specified
page_size. If this is true then the results object will only provide access to the first
page_sizerows in the query result. You can disable truncation by passing
.columns- list of strings
- A list of column names returned by the query.
.rows- list of sqlite3.Row
- This property provides direct access to the list of rows returned by the database. You can access specific rows by index using
.first()- row or None
- Returns the first row in the results, or
Noneif no rows were returned.
- Returns the value of the first column of the first row of results - but only if the query returned a single row with a single column. Raises a
len(results)returns the (truncated) number of returned results.
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
def get_version(conn): return conn.execute( "select sqlite_version()" ).fetchall() version = await db.execute_fn(get_version)
await db.execute_write(sql, params=None, block=False)¶
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.
This method can be used to queue up a non-SELECT SQL query to be executed against a single write connection to the database.
You can pass additional SQL parameters as a tuple or dictionary.
By default queries are considered to be "fire and forget" - they will be added to the 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.
If you pass
block=True this behaviour changes: the method will block until the write operation has completed, and the return value will be the return from calling
conn.execute(...) using the underlying
sqlite3 Python library.
await db.execute_write_fn(fn, block=False)¶
This method works like
.execute_write(), but instead of a SQL statement you give it a callable Python function. This function will be queued up and then called when the write connection is available, passing that connection as the argument to the function.
The function can then perform multiple actions, safe in the knowledge that it has exclusive access to the single writable connection as long as it is executing.
def my_action(conn): conn.execute("delete from some_table") conn.execute("delete from other_table") await database.execute_write_fn(my_action)
This method is 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.
If you pass
block=True your calling code will block until the function has been executed. The return value to the
await will be the return value of your function.
If your function raises an exception and you specified
block=True, that exception will be propagated up to the
await line. With
block=False any exceptions will be silently ignored.
Here's an example of
block=True in action:
def my_action(conn): conn.execute("delete from some_table where id > 5") return conn.execute("select count(*) from some_table").fetchone() try: num_rows_left = await database.execute_write_fn(my_action, block=True) except Exception as e: print("An error occurred:", e)