Documentation Source Text

<title>The JSON1 Extension</title>
<tcl>hd_keywords json1 {the json1 extension}</tcl>
<h2>The JSON1 Extension</h2>

<p>
The <b>json1</b> extension is a [loadable extension] that
implements eleven [application-defined SQL functions] and
two [table-valued functions] that are useful for
managing JSON content stored in an SQLite database.
These are the SQL functions implemented by json1:

<blockquote>
<center><table border=0 cellpadding=5>
<tcl>
set tabcnt 0
proc tabentry {fx desc lnk} {
  global tabcnt
  incr tabcnt
  hd_puts "<tr><td width=30 valign='top'>$tabcnt.</td>"
  hd_puts "<td valign='top' width='30%'>\n"
  set fx [string trim $fx]
  set hlink "<a href='#$lnk'>"
  regsub -all {^json\(} $fx "${hlink}json</a>(" fx
  regsub -all {(json_[a-z_]+)} $fx "$hlink\\1</a>" fx
  regsub -all {(value[1-9]?|path|label[1-9]?)} $fx "<i>\\1</i>" fx
  regsub -all {\((json)} $fx "(<i>\\1</i>" fx
  hd_puts $fx\n
  hd_puts "</td><td valign='top'>\n"
  hd_puts [string trim $desc]\n
  hd_puts "</td></tr>\n\n"

    # puts "\175 \173$x\175"
    hd_puts "<tr><td>[string trim $sql]</td>\n"
    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)} {
  Validates and minifies 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)} {
  Return the number of elements in the JSON array identified by

<p>
The json1 extension (currently) stores JSON as ordinary text.

<p>
Backwards compatibility constraints mean that SQLite is only able to
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 is able to parse JSON text at a rate of
250 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.
The designers anticipate that there will be future incompatible JSON
extensions building upon the lessons learned from json1.
Once sufficient experience is gained, some kind of
JSON extension might be folded into the SQLite core.  But for now,

string is passed into json1 function, that function will usually throw
an error.  (The exception to the previous sentence is the json_valid() 
function which returns 1 if the argument is well-formed 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 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 load
into 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>
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 is of type TEXT it is normally converted into a quoted 

JSON string.  However, if the argument is the outpu to 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>
jexample \
  {json_array(1,2,'3',4)} {'[1,2,"3",4]'} \
  {json_array('[1,2]')} {'["[1,2]"]'} \
  {json_array(json_array(1,2))} {'[[1,2]]'} \
  {json_array(1,null,'3','[4,5]','{"six":7.7}')} \
      {'[1,null,"3","[4,5]","{\"six\":7.7}"]'} \
  {json_array(1,null,'3',json('[4,5]'),json('{"six":7.7}'))} \
      {'[1,null,"3",[4,5],{"six":7.7}]'}
</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 does not
locate an array within 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('{"one":[1,2,3]}')} {0} \
  {json_array_length('{"one":[1,2,3]}', '$.one')} {3}
</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
SQLite type of the value returned is NULL for a JSON null, INTEGER or REAL
for a JSON numeric value, INTEGER 0 for a JSON false value, INTEGER 1
for a JSON true value, the dequoted text for a JSON string value, and

  {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
</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 value formed
by updating the input argument by the path/value pairs.  The functions
differ only in how they deal with creating new values and overwriting
preexisting values.

JSON to be edited.  Subsequent arguments occur in pairs with the first
element of each pair being a path and the second element being an value
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 TEXT value is the output of another


json1 function (such as [json()] or [json_array()] or [json_object()])
then it is interpreted as JSON and is inserted as is.


<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 of type 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}'} \
  {json_replace('{"a":2,"c":4}', '$.a', 99)} {'{"a":99,"c":4}'} \
  {json_replace('{"a":2,"c":4}', '$.e', 99)} {'{"a":2,"c":4}'} \
  {json_set('{"a":2,"c":4}', '$.a', 99)} {'{"a":99,"c":4}'} \
  {json_set('{"a":2,"c":4}', '$.e', 99)} {'{"a":2,"c":4,"e":99}'} \
  {json_set('{"a":2,"c":4}', '$.c', '[97,96]')} \
            {'{"a":2,"c":"[97,96]"}'} \
  {json_set('{"a":2,"c":4}', '$.c', json('[97,96]'))} \
            {'{"a":2,"c":[97,96]}'} \
  {json_set('{"a":2,"c":4}', '$.c', json_array(97,96))} \
            {'{"a":2,"c":[97,96]}'}
</tcl>

<tcl>hd_fragment jobj {json_object SQL function} {json_object}</tcl>
<h3>3.6 The json_object() function</h3>

<p>The json_object() SQL function accepts zero or more pairs of arguments
and returns a well-formed JSON object that is composed from those arguments.
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 is of type TEXT it is normally converted into a quoted 

JSON string.  However, if the argument is the output to another json1
function, then it is stored as JSON.  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 in the second
and subsequent arguments.  The json_remove(X,P,...) function returns
a new JSON value that is the input X value with all the elements 
identified by path arguments removed.  Paths that select elements
not found in X are silently ignored.

  {json_type('{"a":[2,3.5,true,false,null,"x"]}','$.a[3]')} 'false' \
  {json_type('{"a":[2,3.5,true,false,null,"x"]}','$.a[4]')} 'null' \
  {json_type('{"a":[2,3.5,true,false,null,"x"]}','$.a[5]')} 'text' \
  {json_type('{"a":[2,3.5,true,false,null,"x"]}','$.a[6]')} NULL
</tcl>

<tcl>hd_fragment jvalid {json_valid SQL function} {json_valid}</tcl>
<h3>3.9 The json_valid() function</h3>

<p>The json_valid(X) function return 1 if the argument X is well-formed
JSON and return 0 if the argument X is not well-formed JSON.

<p>Examples:

<tcl>

<p>
The "path" column is the path to the array or object container the holds 
the current row, or the path to the current row in the case where the 
iteration starts on a primitive type and thus only provides a single
row of output.

<h4>3.10.1 Examples using json_each() and json_tree()</h4>

<p>Suppose the table "CREATE TABLE user(name,phone)" stores zero or
more phone numbers as a JSON array object in the user.phone field.
To find all users who have any phone number with a 704 area code:

<blockquote><pre>
SELECT DISTINCT user.name