Datasette treats SQLite database files as read-only and immutable. This means it is not possible to execute INSERT or UPDATE statements using Datasette, which allows us to expose SELECT statements to the outside world without needing to worry about SQL injection attacks.
The easiest way to execute custom SQL against Datasette is through the web UI. The database index page includes a SQL editor that lets you run any SELECT query you like. You can also construct queries using the filter interface on the tables page, then click "View and edit SQL" to open that query in the custom SQL editor.
Note that this interface is only available if the :ref:`permissions_execute_sql` permission is allowed. See :ref:`authentication_permissions_execute_sql`.
Any Datasette SQL query is reflected in the URL of the page, allowing you to bookmark them, share them with others and navigate through previous queries using your browser back button.
If you execute this query using the custom query editor, Datasette will extract the two named parameters and use them to construct form fields for you to provide values.
SQLite string escaping rules will be applied to values passed using named parameters - they will be wrapped in quotes and their content will be correctly escaped.
Values from named parameters are treated as SQLite strings. If you need to perform numeric comparisons on them you should cast them to an integer or float first using ``cast(:name as integer)`` or ``cast(:name as real)``, for example:
Datasette disallows custom SQL queries containing the string PRAGMA (with a small number `of exceptions <https://github.com/simonw/datasette/issues/761>`__) as SQLite pragma statements can be used to change database settings at runtime. If you need to include the string "pragma" in a query you can do so safely using a named parameter.
If you want to bundle some pre-written SQL queries with your Datasette-hosted database you can do so in two ways. The first is to include SQL views in your database - Datasette will then list those views on your database index page.
You can also use the `sqlite-utils <https://sqlite-utils.datasette.io/>`__ tool to `create a view <https://sqlite-utils.datasette.io/en/stable/cli.html#creating-views>`__::
sqlite-utils create-view sf-trees.db demo_view "select qSpecies from Street_Tree_List"
You can optionally include ``"title"`` and ``"description"`` keys to show a title and description on the canned query page. As with regular table metadata you can alternatively specify ``"description_html"`` to have your description rendered as HTML (rather than having HTML special characters escaped).
Canned queries support named parameters, so if you include those in the SQL you will then be able to enter them using the form fields on the canned query page or by adding them to the URL. This means canned queries can be used to create custom JSON APIs based on a carefully designed SQL statement.
Additional options can be specified for canned queries in the YAML or JSON configuration.
hide_sql
++++++++
Canned queries default to displaying their SQL query at the top of the page. If the query is extremely long you may want to hide it by default, with a "show" link that can be used to make it visible.
Add the ``"hide_sql": true`` option to hide the SQL query by default.
Some plugins, such as `datasette-vega <https://github.com/simonw/datasette-vega>`__, can be configured by including additional data in the fragment hash of the URL - the bit that comes after a ``#`` symbol.
This configuration will create a page at ``/mydatabase/add_name`` displaying a form with a ``name`` field. Submitting that form will execute the configured ``INSERT`` query.
You can customize how Datasette represents success and errors using the following optional properties:
-``on_success_message`` - the message shown when a query is successful
You can use ``"params"`` to explicitly list the named parameters that should be displayed as form fields - otherwise they will be automatically detected. ``"params"`` is not necessary in the above example, since without it ``"name"`` would be automatically detected from the query.
You can pre-populate form fields when the page first loads using a query string, e.g. ``/mydatabase/add_name?name=Prepopulated``. The user will have to submit the form to execute the query.
If you specify a query in ``"on_success_message_sql"``, that query will be executed after the main query. The first column of the first row return by that query will be displayed as a success message. Named parameters from the main query will be made available to the success message query as well.
Named parameters that start with an underscore are special: they can be used to automatically add values created by Datasette that are not contained in the incoming form fields or query string.
These magic parameters are only supported for canned queries: to avoid security issues (such as queries that extract the user's private cookies) they are not available to SQL that is executed by the user as a custom SQL query.
``_actor_*`` - e.g. ``_actor_id``, ``_actor_name``
Fields from the currently authenticated :ref:`authentication_actor`.
``_header_*`` - e.g. ``_header_user_agent``
Header from the incoming HTTP request. The key should be in lower case and with hyphens converted to underscores e.g. ``_header_user_agent`` or ``_header_accept_language``.
The form presented at ``/mydatabase/add_message`` will have just a field for ``message`` - the other parameters will be populated by the magic parameter mechanism.
Additional custom magic parameters can be added by plugins using the :ref:`plugin_hook_register_magic_parameters` hook.
Writable canned queries can also be accessed using a JSON API. You can POST data to them using JSON, and you can request that their response is returned to you as JSON.
To submit JSON to a writable canned query, encode key/value parameters as a JSON document::
POST /mydatabase/add_message
{"message": "Message goes here"}
You can also continue to submit data using regular form encoding, like so::
POST /mydatabase/add_message
message=Message+goes+here
There are three options for specifying that you would like the response to your request to return JSON data, as opposed to an HTTP redirect to another page.
- Set an ``Accept: application/json`` header on your request
- Include ``?_json=1`` in the URL that you POST to
- Include ``"_json": 1`` in your JSON body, or ``&_json=1`` in your form encoded body
The ``"message"`` and ``"redirect"`` values here will take into account ``on_success_message``, ``on_success_message_sql``, ``on_success_redirect``, ``on_error_message`` and ``on_error_redirect``, if they have been set.
Datasette's default table pagination is designed to be extremely efficient. SQL OFFSET/LIMIT pagination can have a significant performance penalty once you get into multiple thousands of rows, as each page still requires the database to scan through every preceding row to find the correct offset.
When paginating through tables, Datasette instead orders the rows in the table by their primary key and performs a WHERE clause against the last seen primary key for the previous page. For example:
Note that we request 101 items in the limit clause rather than 100. This allows us to detect if we are on the last page of the results: if the query returns less than 101 rows we know we have reached the end of the pagination set. Datasette will only return the first 100 rows - the 101st is used purely to detect if there should be another page.
Since the where clause acts against the index on the primary key, the query is extremely fast even for records that are a long way into the overall pagination set.
SQLite has the ability to run queries that join across multiple databases. Up to ten databases can be attached to a single SQLite connection and queried together.
Datasette can execute joins across multiple databases if it is started with the ``--crossdb`` option::
datasette fixtures.db extra_database.db --crossdb
If it is started in this way, the ``/_memory`` page can be used to execute queries that join across multiple databases.
For example, this query will show a list of tables across both of the above databases:
..code-block:: sql
select
'fixtures' as database, *
from
[fixtures].sqlite_master
union
select
'extra_database' as database, *
from
[extra_database].sqlite_master
`Try that out here <https://latest.datasette.io/_memory?sql=select%0D%0A++%27fixtures%27+as+database%2C+*%0D%0Afrom%0D%0A++%5Bfixtures%5D.sqlite_master%0D%0Aunion%0D%0Aselect%0D%0A++%27extra_database%27+as+database%2C+*%0D%0Afrom%0D%0A++%5Bextra_database%5D.sqlite_master>`__.