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| sql_queries:canned-queries-json-api | sql_queries | canned-queries-json-api | JSON API for writable canned queries | Writable canned queries can also be accessed using a JSON API. You can POST data to them using JSON, and you can request that their response is returned to you as JSON. To submit JSON to a writable canned query, encode key/value parameters as a JSON document: POST /mydatabase/add_message {"message": "Message goes here"} You can also continue to submit data using regular form encoding, like so: POST /mydatabase/add_message message=Message+goes+here There are three options for specifying that you would like the response to your request to return JSON data, as opposed to an HTTP redirect to another page. Set an Accept: application/json header on your request Include ?_json=1 in the URL that you POST to Include "_json": 1 in your JSON body, or &_json=1 in your form encoded body The JSON response will look like this: { "ok": true, "message": "Query executed, 1 row affected", "redirect": "/data/add_name" } The "message" and "redirect" values here will take into account on_success_message , on_success_redirect , on_error_message and on_error_redirect , if they have been set. | ["Running SQL queries", "Canned queries"] | [] |
| sql_queries:canned-queries-magic-parameters | sql_queries | canned-queries-magic-parameters | Magic parameters | Named parameters that start with an underscore are special: they can be used to automatically add values created by Datasette that are not contained in the incoming form fields or query string. These magic parameters are only supported for canned queries: to avoid security issues (such as queries that extract the user's private cookies) they are not available to SQL that is executed by the user as a custom SQL query. Available magic parameters are: _actor_* - e.g. _actor_id , _actor_name Fields from the currently authenticated Actors . _header_* - e.g. _header_user_agent Header from the incoming HTTP request. The key should be in lower case and with hyphens converted to underscores e.g. _header_user_agent or _header_accept_language . _cookie_* - e.g. _cookie_lang The value of the incoming cookie of that name. _now_epoch The number of seconds since the Unix epoch. _now_date_utc The date in UTC, e.g. 2020-06-01 _now_datetime_utc The ISO 8601 datetime in UTC, e.g. 2020-06-24T18:01:07Z _random_chars_* - e.g. … | ["Running SQL queries", "Canned queries"] | [] |
| sql_queries:canned-queries-named-parameters | sql_queries | canned-queries-named-parameters | Canned query parameters | Canned queries support named parameters, so if you include those in the SQL you will then be able to enter them using the form fields on the canned query page or by adding them to the URL. This means canned queries can be used to create custom JSON APIs based on a carefully designed SQL statement. Here's an example of a canned query with a named parameter: select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood; In the canned query metadata (here Using YAML for metadata as metadata.yaml ) it looks like this: databases: fixtures: queries: neighborhood_search: sql: |- select neighborhood, facet_cities.name, state from facetable join facet_cities on facetable.city_id = facet_cities.id where neighborhood like '%' || :text || '%' order by neighborhood title: Search neighborhoods Here's the equivalent using JSON (as metadata.json ): { "databases": { "fixtures": { "queries": { "neighborhood_search": { "sql": "select neighborhood, facet_cities.name, state\nfrom facetable\n join facet_cities on facetable.city_id = facet_cities.id\nwhere neighborhood like '%' || :text || '%'\norder by neighborhood", "title": "Search neighborhoods" } } } } } Note that we are using SQLite string concatenation here - the || operator - to add wildcard % characters to the string provided by the user. You can try this canned query out here: https://latest.datasette.io/fixtures/neighborhood_search?text=town In this example the :text named parameter is automatically extracted from the query using a regular expression. … | ["Running SQL queries", "Canned queries"] | [{"href": "https://latest.datasette.io/fixtures/neighborhood_search?text=town", "label": "https://latest.datasette.io/fixtures/neighborhood_search?text=town"}] |
| sql_queries:canned-queries-options | sql_queries | canned-queries-options | Additional canned query options | Additional options can be specified for canned queries in the YAML or JSON configuration. | ["Running SQL queries", "Canned queries"] | [] |
| sql_queries:canned-queries-writable | sql_queries | canned-queries-writable | Writable canned queries | Canned queries by default are read-only. You can use the "write": true key to indicate that a canned query can write to the database. See Controlling access to specific canned queries for details on how to add permission checks to canned queries, using the "allow" key. { "databases": { "mydatabase": { "queries": { "add_name": { "sql": "INSERT INTO names (name) VALUES (:name)", "write": true } } } } } This configuration will create a page at /mydatabase/add_name displaying a form with a name field. Submitting that form will execute the configured INSERT query. You can customize how Datasette represents success and errors using the following optional properties: on_success_message - the message shown when a query is successful on_success_redirect - the path or URL the user is redirected to on success on_error_message - the message shown when a query throws an error on_error_redirect - the path or URL the user is redirected to on error For example: { "databases": { "mydatabase": { "queries": { "add_name": { "sql": "INSERT INTO names (name) VALUES (:name)", "write": true, "on_success_message": "Name inserted", "on_success_redirect": "/mydatabase/names", "on_error_message": "Name insert failed", "on_error_redirect": "/mydatabase" } } } } } You can use "p… | ["Running SQL queries", "Canned queries"] | [] |
| sql_queries:fragment | sql_queries | fragment | fragment | Some plugins, such as datasette-vega , can be configured by including additional data in the fragment hash of the URL - the bit that comes after a # symbol. You can set a default fragment hash that will be included in the link to the canned query from the database index page using the "fragment" key. This example demonstrates both fragment and hide_sql : { "databases": { "fixtures": { "queries": { "neighborhood_search": { "sql": "select neighborhood, facet_cities.name, state\nfrom facetable join facet_cities on facetable.city_id = facet_cities.id\nwhere neighborhood like '%' || :text || '%' order by neighborhood;", "fragment": "fragment-goes-here", "hide_sql": true } } } } } See here for a demo of this in action. | ["Running SQL queries", "Canned queries", "Additional canned query options"] | [{"href": "https://github.com/simonw/datasette-vega", "label": "datasette-vega"}, {"href": "https://latest.datasette.io/fixtures#queries", "label": "See here"}] |
| sql_queries:hide-sql | sql_queries | hide-sql | 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. | ["Running SQL queries", "Canned queries", "Additional canned query options"] | [] |
| sql_queries:id1 | sql_queries | id1 | Canned queries | As an alternative to adding views to your database, you can define canned queries inside your metadata.json file. Here's an example: { "databases": { "sf-trees": { "queries": { "just_species": { "sql": "select qSpecies from Street_Tree_List" } } } } } Then run Datasette like this: datasette sf-trees.db -m metadata.json Each canned query will be listed on the database index page, and will also get its own URL at: /database-name/canned-query-name For the above example, that URL would be: /sf-trees/just_species You can optionally include "title" and "description" keys to show a title and description on the canned query page. As with regular table metadata you can alternatively specify "description_html" to have your description rendered as HTML (rather than having HTML special characters escaped). | ["Running SQL queries"] | [] |
| sql_queries:id2 | sql_queries | id2 | Pagination | Datasette's default table pagination is designed to be extremely efficient. SQL OFFSET/LIMIT pagination can have a significant performance penalty once you get into multiple thousands of rows, as each page still requires the database to scan through every preceding row to find the correct offset. When paginating through tables, Datasette instead orders the rows in the table by their primary key and performs a WHERE clause against the last seen primary key for the previous page. For example: select rowid, * from Tree_List where rowid > 200 order by rowid limit 101 This represents page three for this particular table, with a page size of 100. Note that we request 101 items in the limit clause rather than 100. This allows us to detect if we are on the last page of the results: if the query returns less than 101 rows we know we have reached the end of the pagination set. Datasette will only return the first 100 rows - the 101st is used purely to detect if there should be another page. Since the where clause acts against the index on the primary key, the query is extremely fast even for records that are a long way into the overall pagination set. | ["Running SQL queries"] | [] |
| sql_queries:id3 | sql_queries | id3 | Cross-database queries | SQLite has the ability to run queries that join across multiple databases. Up to ten databases can be attached to a single SQLite connection and queried together. Datasette can execute joins across multiple databases if it is started with the --crossdb option: datasette fixtures.db extra_database.db --crossdb If it is started in this way, the /_memory page can be used to execute queries that join across multiple databases. References to tables in attached databases should be preceded by the database name and a period. For example, this query will show a list of tables across both of the above databases: select 'fixtures' as database, * from [fixtures].sqlite_master union select 'extra_database' as database, * from [extra_database].sqlite_master Try that out here . | ["Running SQL queries"] | [{"href": "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", "label": "Try that out here"}] |
| sql_queries:sql | sql_queries | sql | Running SQL queries | Datasette treats SQLite database files as read-only and immutable. This means it is not possible to execute INSERT or UPDATE statements using Datasette, which allows us to expose SELECT statements to the outside world without needing to worry about SQL injection attacks. The easiest way to execute custom SQL against Datasette is through the web UI. The database index page includes a SQL editor that lets you run any SELECT query you like. You can also construct queries using the filter interface on the tables page, then click "View and edit SQL" to open that query in the custom SQL editor. Note that this interface is only available if the execute-sql permission is allowed. Any Datasette SQL query is reflected in the URL of the page, allowing you to bookmark them, share them with others and navigate through previous queries using your browser back button. You can also retrieve the results of any query as JSON by adding .json to the base URL. | [] | [] |
| sql_queries:sql-parameters | sql_queries | sql-parameters | Named parameters | Datasette has special support for SQLite named parameters. Consider a SQL query like this: select * from Street_Tree_List where "PermitNotes" like :notes and "qSpecies" = :species If you execute this query using the custom query editor, Datasette will extract the two named parameters and use them to construct form fields for you to provide values. You can also provide values for these fields by constructing a URL: /mydatabase?sql=select...&species=44 SQLite string escaping rules will be applied to values passed using named parameters - they will be wrapped in quotes and their content will be correctly escaped. Values from named parameters are treated as SQLite strings. If you need to perform numeric comparisons on them you should cast them to an integer or float first using cast(:name as integer) or cast(:name as real) , for example: select * from Street_Tree_List where latitude > cast(:min_latitude as real) and latitude < cast(:max_latitude as real) Datasette disallows custom SQL queries containing the string PRAGMA (with a small number of exceptions ) as SQLite pragma statements can be used to change database settings at runtime. If you need to include the string "pragma" in a query you can do so safely using a named parameter. | ["Running SQL queries"] | [{"href": "https://github.com/simonw/datasette/issues/761", "label": "of exceptions"}] |
| sql_queries:sql-views | sql_queries | sql-views | Views | If you want to bundle some pre-written SQL queries with your Datasette-hosted database you can do so in two ways. The first is to include SQL views in your database - Datasette will then list those views on your database index page. The quickest way to create views is with the SQLite command-line interface: $ sqlite3 sf-trees.db SQLite version 3.19.3 2017-06-27 16:48:08 Enter ".help" for usage hints. sqlite> CREATE VIEW demo_view AS select qSpecies from Street_Tree_List; <CTRL+D> | ["Running SQL queries"] | [] |
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