Documentation Source Text

    hd_puts "<td width='50' align='center'><b>&rarr;</b></td>\n"
    hd_puts "<td>[string trim $res]</td></tr>\n"
  }
  hd_puts "</table></blockquote>\n"
}

tabentry {json(json)} {
  Validate and minify a JSON string
} jmini

tabentry {json_array(value1,value2,...)} {
  Return a JSON array holding the function arguments.
} jarray

tabentry {json_array_length(json)<br>json_array_length(json,path)} {

store values that are NULL, integers, floating-point numbers, text,
and BLOBs.  It is not possible add a sixth "JSON" type.

<p>
The json1 extension does not (currently) support a binary encoding
of JSON.  Experiments have so far been unable to find a binary encoding
that is significantly smaller or faster than a plain text encoding.
(The present implementation parses JSON text at over 300 MB/s.)

The current implementation of the various JSON functions
always errors out if it see a BLOB argument, because BLOBs are reserved
for a future enhancement in which BLOBs will store the binary encoding
for JSON.

<p>
The "1" at the end of the name for the json1 extension is deliberate.

<p>
For functions that accept JSON as their first argument, that argument
can be a JSON object, array, number, string, or null.  SQLite numeric
values and NULL values are interpreted as JSON numbers and nulls, respectively.
SQLite text values can be understood as JSON objects, arrays, or strings.
If an SQLite text value that is not a well-formed JSON object, array, or
string is passed into json1 function, that function will usually throw
an error.  (An exception is the json_valid(X) 
function which returns 1 if X is well-formed JSON and 0 if it is not.)

<p>
For the purposes of determining validity, leading and trailing whitespace
on JSON inputs is ignored.  Interior whitespace is also ignored, in accordance
with the JSON spec.  These routines accept exactly the rfc-7159 JSON syntax
&mdash; no more and no less.

<h3>2.2 PATH arguments</h3>

<p>
For functions that accept PATH arguments, that PATH must be well-formed or
else the function will throw an error.
A well-formed PATH is a text value that begins with exactly one
'$' character followed by zero or more instances
of ".<i>objectlabel</i>" or "&#91<i>arrayindex</i>&#93".

<h3>2.3 VALUE arguments</h3>

<p>
For functions that accept "<i>value</i>" arguments (also shown as
"<i>value1</i>" and "<i>value2</i>") that are used to
construct or modify a JSON string, those arguments is usually understood
to be a literal strings and are quoted to become primitive JSON string values
in the result.  Even if the input <i>value</i> strings looks like 
well-formed JSON, they are still interpreted as literal strings in the
result.

<p>
However, if a <i>value</i> argument come from the output of another
json function, then the argument is understood to be actual JSON and
the complete JSON is inserted rather than a quoted string.

<p>
For example, in the following call to json_object(), the first <i>value</i>
argument looks like a well-formed JSON array.  But because it is just an
ordinary SQL text value it is interpreted as a literal string and added to the
result as a quoted string:

<tcl>
jexample {json_object('ex','[52,3.14159]')} {'{"ex":"[52,3.14159]"}'}
</tcl>

<p>
But if the <i>value</i> argument in the outer json_object() call is the
result of another json function like [json()] or [json_array()], then
the value is understood to be actual JSON and is inserted as such:

<tcl>
jexample \
  {json_object('ex',json('[52,3.14159]'))} {'{"ex":[52,3.14159]}'}  \
  {json_object('ex',json_array(52,3.14159))} {'{"ex":[52,3.14159]}'}
</tcl>

<h3>2.4 Compatibility</h3>

<p>
The json1 extension uses the [sqlite3_value_subtype()] and
[sqlite3_result_subtype()] interfaces that were introduced with
SQLite version 3.8.12.  Therefore the json1 extension will not work
in earlier versions of SQLite.

<h2>3.0 Function Details</h2>

<p>The following sections provide additional detail on the operation of
the various functions that are part of the json1 extension.

<tcl>hd_fragment jmini {json SQL function} {json}</tcl>
<h3>3.1 The json() function</h3>

<p>The json(X) function verifies that its argument X is a valid
JSON string and returns a minified version of that JSON string
(with all unnecessary whitespace removed).  If X is not a well-formed
JSON string, then this routine throws an error.

<p>If the argument X to json(X) contains JSON objects with duplicate
labels, then it is undefined whether or not the duplicates are
preserved.  The current implementation preserves duplicates.
However, future enhancements
to this routine may choose to silently remove duplicates.

<p>
Example:

<tcl>
jexample \
  {json(' { "this" : "is", "a": [ "test" ] } ')} \
      {'{"this":"is","a":["test"]}'}
</tcl>

<tcl>hd_fragment jarray {json_array SQL function} {json_array}</tcl>
<h3>3.2 The json_array() function</h3>

<p>The json_array() SQL function accepts zero or more arguments and
returns a well-formed JSON array that is composed from those arguments.
If any argument to json_array() is a BLOB then an error is thrown.

<p>An argument with SQL type TEXT it is normally converted into a quoted 
JSON string.  However, if the argument is the output from another json1
function, then it is stored as JSON.  This allows calls to json_array()
and [json_object()] to be nested.  The [json()] function can also
be used to force strings to be recognized as JSON.

<p>Examples:

<tcl>

<tcl>hd_fragment jarraylen {json_array_length SQL function} \
         {json_array_length}</tcl>
<h3>3.3 The json_array_length() function</h3>

<p>The json_array_length(X) function returns the number of elements
in the JSON array X, or 0 if X is some kind of JSON value other
than an array.  The json_array_length(X,P) locates the array at path P
within X and returns the length of that array, or 0 if path P locates
a element or X other than an JSON array, and NULL if path P does not
locate any element of X.  Errors are thrown if either X is not 
well-formed JSON or if P is not a well-formed path.

<p>Examples:

<tcl>
jexample \
  {json_array_length('[1,2,3,4]')} {4} \
  {json_array_length('[1,2,3,4]', '$')} {4} \
  {json_array_length('[1,2,3,4]', '$[2]')} {0} \
  {json_array_length('{"one":[1,2,3]}')} {0} \
  {json_array_length('{"one":[1,2,3]}', '$.one')} {3} \
  {json_array_length('{"one":[1,2,3]}', '$.two')} {NULL}
</tcl>


<tcl>hd_fragment jex {json_extract SQL function} {json_extract}</tcl>
<h3>3.4 The json_extract() function</h3>

<p>The json_extract(X,P1,P2,...) extracts and returns one or more 
values from the
well-formed JSON at X.  If only a single path P1 is provided, then the
SQL datatype of the result is NULL for a JSON null, INTEGER or REAL
for a JSON numeric value, an INTEGER zero for a JSON false value,
an INTEGER one for a JSON true value, the dequoted text for a 
JSON string value, and a text representation for JSON object and array values.
If there are multiple path arguments (P1, P2, and so forth) then this
routine returns SQLite text which is a well-formed JSON array holding
the various values.

<p>Examples:

<tcl>
jexample \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$')} \
      {'{"a":2,"c":[4,5,{"f":7}]}'} \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$.c')} \
      {'[4,5,{"f":7}]'} \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$.c[2]')} \
      {'{"f":7}'} \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$.c[2].f')} {7} \
  {json_extract('{"a":2,"c":[4,5],"f":7}','$.c','$.a')} {'[[4,5],2]'} \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$.x')} NULL \
  {json_extract('{"a":2,"c":[4,5,{"f":7}]}', '$.x', '$.a')} {'[null,2]'}
</tcl>  

<tcl>hd_fragment jins {json_insert SQL function} {json_insert}</tcl>
<tcl>hd_fragment jrepl {json_replace SQL function} {json_replace}</tcl>
<tcl>hd_fragment jset {json_set SQL function} {json_set}</tcl>
<h3>3.5 The json_insert(), json_replace, and json_set() functions</h3>

<p>The json_insert(), json_replace, and json_set() functions all take
a single JSON value as their first argument followed by zero or more
pairs of path and value arguments, and return a new JSON string formed
by updating the input JSON by the path/value pairs.  The functions
differ only in how they deal with creating new values and overwriting
preexisting values.

<center>
<table border=1 cellpadding=3>
<tr>
<th>Function<th>Overwrite if already exists?<th>Create if does not exist?

to insert or replace or set on that path.

<p>Edits occurs sequentially from left to right.  Changes caused by
prior edits can affect the path search for subsequent edits.

<p>If the value of a path/value pair is an SQLite TEXT value, then it
is normally inserted as a quoted JSON string, even if the string looks
like valid JSON.  However, if the value is the result of another
json1 function (such as [json()] or [json_array()] or [json_object()])
then it is interpreted as JSON and is inserted as JSON retaining all
of its substructure.

<p>These routines throw an error if the first JSON argument is not
well-formed or if any PATH argument is not well-formed or if any
argument is a BLOB.

<p>Examples:

<tcl>
jexample \
  {json_insert('{"a":2,"c":4}', '$.a', 99)} {'{"a":2,"c":4}'} \
  {json_insert('{"a":2,"c":4}', '$.e', 99)} {'{"a":2,"c":4,"e":99}'} \

The first argument of each pair is the label and the second argument of
each pair is the value.
If any argument to json_object() is a BLOB then an error is thrown.

<p>The json_object() function currently allows duplicate labels without
complaint, though this might change in a future enhancement.

<p>An argument with SQL type TEXT it is normally converted into a quoted 
JSON string even if the input text is well-formed JSON.  
However, if the argument is the direct result from another json1
function, then it is treated as JSON and all of its JSON type information
and substructure is preserved.  This allows calls to json_object()
and [json_array()] to be nested.  The [json()] function can also
be used to force strings to be recognized as JSON.

<p>Examples:

<tcl>
jexample \
  {json_object('a',2,'c',4)} {'{"a":2,"c":4}'} \
  {json_object('a',2,'c','{e:5}')} {'{"a":2,"c":"{e:5}"}'} \
  {json_object('a',2,'c',json_object('e',5))} {'{"a":2,"c":{"e":5}}'}
</tcl>


<tcl>hd_fragment jrm {json_remove SQL function} {json_remove}</tcl>
<h3>3.7 The json_remove() function</h3>

<p>The json_remove(X,P,...) function takes a single JSON value as its
first argument followed by zero or more path arguments.
The json_remove(X,P,...) function returns
a new JSON value that is the X with all the elements 
identified by path arguments removed.  Paths that select elements
not found in X are silently ignored.

<p>Removals occurs sequentially from left to right.  Changes caused by
prior removals can affect the path search for subsequent arguments.

<p>If the json_remove(X) function is called with no path arguments,

<tcl>hd_fragment jtype {json_type SQL function} {json_type}</tcl>
<h3>3.7 The json_type() function</h3>

<p>The json_type(X) function returns the "type" of the outermost element
of X.  The json_type(X,P) function returns the "type" of the element
in X that is selected by path P.  The "type" returned by json_type() is
on of the following an SQL text values:
'null', 'true', 'false', 'integer', 'real', 'text', 'array', or 'object'.
If the path P in json_type(X,P) selects a element that does not exist
in X, then this function returns NULL.

<p>The json_type() function throws an error if any of its arguments are
not well-formed or is a BLOB.

<p>Examples:

<tcl>
jexample \
  {json_type('{"a":[2,3.5,true,false,null,"x"]}')} 'object' \
  {json_type('{"a":[2,3.5,true,false,null,"x"]}','$')} 'object' \

SELECT DISTINCT user.name
  FROM user, json_each(user.phone)
 WHERE json_each.value LIKE '704-%';
</pre></blockquote>

<p>Now suppose the user.phone field contains plain text if the user
has only a single phone number and a JSON array if the user has multiple
phone numbers.  The same question is posed: "Which users have a phone number
in the 704 area code?"  But now the json_each() function can only be called
for those users that have two or more phone numbers since json_each()
requires well-formed JSON as its first argument:

<blockquote><pre>
SELECT name FROM user WHERE phone LIKE '704-%'
UNION
SELECT user.name
  FROM user, json_each(user.phone)

<blockquote><pre>
SELECT big.rowid, fullkey, atom
  FROM big, json_tree(big.json)
 WHERE atom IS NOT NULL;
</pre></blockquote>

<p>Suppose each entry in the BIG table is a JSON object 
with a '$.id' field that is a unique indentifier
and a '$.partlist' field that can be a deeply nested object.
You want to find the id of every entry that contains one
or more references to uuid '6fa5181e-5721-11e5-a04e-57f3d7b32808' anywhere
in its '$.partlist'.

<blockquote><pre>
SELECT DISTINCT json_extract(big.json,'$.id')
  FROM big, json_tree(big.json, '$.partlist')
 WHERE json_tree.key='uuid'
   AND json_tree.value='6fa5181e-5721-11e5-a04e-57f3d7b32808';
</pre></blockquote>