Datasette provides a JSON API for your SQLite databases. Anything you can do through the Datasette user interface can also be accessed as JSON via the API.
To access the API for a page, either click on the .json
link on that page or
edit the URL and add a .json
extension to it.
If you started Datasette with the --cors
option, each JSON endpoint will be
served with the following additional HTTP header:
Access-Control-Allow-Origin: *
This means JavaScript running on any domain will be able to make cross-origin requests to fetch the data.
If you start Datasette without the --cors
option only JavaScript running on
the same domain as Datasette will be able to access the API.
The default JSON representation of data from a SQLite table or custom query looks like this:
{ "database": "sf-trees", "table": "qSpecies", "columns": [ "id", "value" ], "rows": [ [ 1, "Myoporum laetum :: Myoporum" ], [ 2, "Metrosideros excelsa :: New Zealand Xmas Tree" ], [ 3, "Pinus radiata :: Monterey Pine" ] ], "truncated": false, "next": "100", "next_url": "http://127.0.0.1:8001/sf-trees-02c8ef1/qSpecies.json?_next=100", "query_ms": 1.9571781158447266 }
The columns
key lists the columns that are being returned, and the rows
key then returns a list of lists, each one representing a row. The order of the
values in each row corresponds to the columns.
The _shape
parameter can be used to access alternative formats for the
rows
key which may be more convenient for your application. There are three
options:
?_shape=arrays
-"rows"
is the default option, shown above?_shape=objects
-"rows"
is a list of JSON key/value objects?_shape=array
- an JSON array of objects?_shape=array&_nl=on
- a newline-separated list of JSON objects?_shape=arrayfirst
- a flat JSON array containing just the first value from each row?_shape=object
- a JSON object keyed using the primary keys of the rows
_shape=objects
looks like this:
{ "database": "sf-trees", ... "rows": [ { "id": 1, "value": "Myoporum laetum :: Myoporum" }, { "id": 2, "value": "Metrosideros excelsa :: New Zealand Xmas Tree" }, { "id": 3, "value": "Pinus radiata :: Monterey Pine" } ] }
_shape=array
looks like this:
[ { "id": 1, "value": "Myoporum laetum :: Myoporum" }, { "id": 2, "value": "Metrosideros excelsa :: New Zealand Xmas Tree" }, { "id": 3, "value": "Pinus radiata :: Monterey Pine" } ]
_shape=array&_nl=on
looks like this:
{"id": 1, "value": "Myoporum laetum :: Myoporum"} {"id": 2, "value": "Metrosideros excelsa :: New Zealand Xmas Tree"} {"id": 3, "value": "Pinus radiata :: Monterey Pine"}
_shape=arrayfirst
looks like this:
[1, 2, 3]
_shape=object
looks like this:
{ "1": { "id": 1, "value": "Myoporum laetum :: Myoporum" }, "2": { "id": 2, "value": "Metrosideros excelsa :: New Zealand Xmas Tree" }, "3": { "id": 3, "value": "Pinus radiata :: Monterey Pine" } ]
The object
shape is only available for queries against tables - custom SQL
queries and views do not have an obvious primary key so cannot be returned using
this format.
The object
keys are always strings. If your table has a compound primary
key, the object
keys will be a comma-separated string.
Every Datasette endpoint that can return JSON also accepts the following querystring arguments:
?_shape=SHAPE
- The shape of the JSON to return, documented above.
?_nl=on
- When used with
?_shape=array
produces newline-delimited JSON objects. ?_json=COLUMN1&_json=COLUMN2
If any of your SQLite columns contain JSON values, you can use one or more
_json=
parameters to request that those columns be returned as regular JSON. Without this argument those columns will be returned as JSON objects that have been double-encoded into a JSON string value.Compare this query without the argument to this query using the argument
?_json_infinity=on
- If your data contains infinity or -infinity values, Datasette will replace
them with None when returning them as JSON. If you pass
_json_infinity=1
Datasette will instead return them asInfinity
or-Infinity
which is invalid JSON but can be processed by some custom JSON parsers. ?_timelimit=MS
- Sets a custom time limit for the query in ms. You can use this for optimistic queries where you would like Datasette to give up if the query takes too long, for example if you want to implement autocomplete search but only if it can be executed in less than 10ms.
?_ttl=SECONDS
- For how many seconds should this response be cached by HTTP proxies? Use
?_ttl=0
to disable HTTP caching entirely for this request.
The Datasette table view takes a number of special querystring arguments.
You can filter the data returned by the table based on column values using a querystring argument.
?column__exact=value
or?_column=value
- Returns rows where the specified column exactly matches the value.
?column__not=value
- Returns rows where the column does not match the value.
?column__contains=value
- Rows where the string column contains the specified value (
column like "%value%"
in SQL). ?column__endswith=value
- Rows where the string column ends with the specified value (
column like "%value"
in SQL). ?column__startswith=value
- Rows where the string column starts with the specified value (
column like "value%"
in SQL). ?column__gt=value
- Rows which are greater than the specified value.
?column__gte=value
- Rows which are greater than or equal to the specified value.
?column__lt=value
- Rows which are less than the specified value.
?column__lte=value
- Rows which are less than or equal to the specified value.
?column__like=value
- Match rows with a LIKE clause, case insensitive and with
%
as the wildcard character. ?column__glob=value
- Similar to LIKE but uses Unix wildcard syntax and is case sensitive.
?column__in=value1,value2,value3
Rows where column matches any of the provided values.
You can use a comma separated string, or you can use a JSON array.
The JSON array option is useful if one of your matching values itself contains a comma:
?column__in=["value","value,with,commas"]
?column__notin=value1,value2,value3
- Rows where column does not match any of the provided values. The inverse of
__in=
. Also supports JSON arrays. ?column__arraycontains=value
Works against columns that contain JSON arrays - matches if any of the values in that array match.
This is only available if the
json1
SQLite extension is enabled.?column__date=value
- Column is a datestamp occurring on the specified YYYY-MM-DD date, e.g.
2018-01-02
. ?column__isnull=1
- Matches rows where the column is null.
?column__notnull=1
- Matches rows where the column is not null.
?column__isblank=1
- Matches rows where the column is blank, meaning null or the empty string.
?column__notblank=1
- Matches rows where the column is not blank.
?_labels=on/off
- Expand foreign key references for every possible column. See below.
?_label=COLUMN1&_label=COLUMN2
- Expand foreign key references for one or more specified columns.
?_size=1000
or?_size=max
- Sets a custom page size. This cannot exceed the
max_returned_rows
limit passed todatasette serve
. Usemax
to getmax_returned_rows
. ?_sort=COLUMN
- Sorts the results by the specified column.
?_sort_desc=COLUMN
- Sorts the results by the specified column in descending order.
?_search=keywords
- For SQLite tables that have been configured for full-text search executes a search with the provided keywords.
?_search_COLUMN=keywords
- Like
_search=
but allows you to specify the column to be searched, as opposed to searching all columns that have been indexed by FTS. ?_where=SQL-fragment
If the :ref:`config_allow_sql` config option is enabled, this parameter can be used to pass one or more additional SQL fragments to be used in the WHERE clause of the SQL used to query the table.
This is particularly useful if you are building a JavaScript application that needs to do something creative but still wants the other conveniences provided by the table view (such as faceting) and hence would like not to have to construct a completely custom SQL query.
Some examples:
?_through={json}
This can be used to filter rows via a join against another table.
The JSON parameter must include three keys:
table
,column
andvalue
.table
must be a table that the current table is related to via a foreign key relationship.column
must be a column in that other table.value
is the value that you want to match against.For example, to filter
roadside_attractions
to just show the attractions that have a characteristic of "museum", you would construct this JSON:{ "table": "roadside_attraction_characteristics", "column": "characteristic_id", "value": "1" }
As a URL, that looks like this:
?_through={%22table%22:%22roadside_attraction_characteristics%22,%22column%22:%22characteristic_id%22,%22value%22:%221%22}
Here's an example.
?_next=TOKEN
- Pagination by continuation token - pass the token that was returned in the
"next"
property by the previous page. ?_trace=1
Turns on tracing for this page: SQL queries executed during the request will be gathered and included in the response, either in a new
"_traces"
key for JSON responses or at the bottom of the page if the response is in HTML.The structure of the data returned here should be considered highly unstable and very likely to change.
Datasette can detect foreign key relationships and resolve those references into
labels. The HTML interface does this by default for every detected foreign key
column - you can turn that off using ?_labels=off
.
You can request foreign keys be expanded in JSON using the _labels=on
or
_label=COLUMN
special querystring parameters. Here's what an expanded row
looks like:
[ { "rowid": 1, "TreeID": 141565, "qLegalStatus": { "value": 1, "label": "Permitted Site" }, "qSpecies": { "value": 1, "label": "Myoporum laetum :: Myoporum" }, "qAddress": "501X Baker St", "SiteOrder": 1 } ]
The column in the foreign key table that is used for the label can be specified
in metadata.json
- see :ref:`label_columns`.