Documentation Source Text

proc chng {date desc {options {}}} {
  global nChng aChng xrefChng
  set aChng($nChng) [list $date $desc $options]
  set xrefChng($date) $nChng
  incr nChng
}

chng {2016-08-00 (3.14.0)} {
<li>Added support for [WITHOUT ROWID virtual tables].
<li>Improved the query planner so that the [OR optimization] can
    be used on [virtual tables] even if one or more of the disjuncts
    use the [LIKE], [GLOB], [REGEXP], [MATCH] operators.
<li>Added the [CSV virtual table] for reading
    [https://www.ietf.org/rfc/rfc4180.txt|RFC 4180] formatted comma-separated
    value files.

<li>Added the "win32-none" VFS, analogous to the "unix-none" VFS, that works like
    the default "win32" VFS except that it ignores all file locks.
<li>The query planner uses a full scan of a [partial index] instead of a 
    full scan of the main table, in cases where that makes sense.
<li>Allow [table-valued functions] to appear on the right-hand side of an [IN operator].
<li>Created the [dbhash.exe] command-line utility.
<li>Added two new C-language interfaces: [sqlite3_expanded_sql()] and
    [sqlite3_trace_v2()].
<li>Added the [json_quote()] SQL functio to [the json1 extension].
<p><b>Bug Fixes:</b>
<li>Fix the [ALTER TABLE] command so that it does not corrupt [descending indexes]
    when adding a column to a [legacy_file_format|legacy file format] database.  Ticket
    [https://www.sqlite.org/src/info/f68bf68513a1c15f|f68bf68513a1c15f]
<li>Fix a NULL-pointer dereference/crash that could occurs when a transitive WHERE
    clause references a non-existent collating sequence.  Ticket
    [https://www.sqlite.org/src/info/e8d439c77685eca6|e8d439c77685eca6].
}

chng {2016-05-18 (3.13.0)} {
<li>Postpone I/O associated with TEMP files for as long as possible, with the hope
    that the I/O can ultimately be avoided completely.
<li>Merged the [session] extension into trunk.
<li>Added the ".auth ON|OFF" command to the [command-line shell].

<title>The JSON1 Extension</title>
<tcl>hd_keywords json1 {the json1 extension} {JSON SQL functions}</tcl>

<table_of_contents>

<h1>Overview</h1>
<p>
The <b>json1</b> extension is a [loadable extension] that
implements thirteen [application-defined SQL functions] and
two [table-valued functions] that are useful for
managing [http://json.org/ | JSON] content stored in an SQLite database.
These are the scalar SQL functions implemented by json1:

tabentry {json_type(json)<br>json_type(json,path)} {
  Return the type of a JSON string or subcomponent.
} jtype

tabentry {json_valid(json)} {
  Return true (1) if the input text is a valid JSON string
} jvalid

tabentry {json_quote(value)} {
  Convert an SQL value (a number or a string) into its corresponding JSON
  representation.
} jvalid
</tcl>
</table></center></blockquote>

<p>There are two aggregate SQL functions:

<blockquote><center><table border=0 cellpadding=5>
<tcl>

  Walk the JSON recursively starting at the top-level or at the
  specified "path" and return one row for each element.
} jtree
</tcl>
</table></center></blockquote>

<tcl>hd_fragment howtocompile</tcl>
<h1>Compiling the JSON1 Extension</h1>

<p>
The [loadable extensions] documentation contains instructions on 
how to [compile loadable extensions] as shared libraries.  The
techniques described there work fine for the json1 module.

<p>
The json1 source code is included with the SQLite [amalgamation], though
it is turned off by default.  Add the [-DSQLITE_ENABLE_JSON1] compile-time
option to enable the json1 extension that is built into the [amalgamation].

<h1>Interface Overview</h1>

<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,

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.  For now,
JSON support remains an extension.

<h2>JSON arguments</h2>

<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 
[http://www.rfc-editor.org/rfc/rfc7159.txt | rfc-7159 JSON syntax]
&mdash; no more and no less.

<h2>PATH arguments</h2>

<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".

<h2>VALUE arguments</h2>

<p>
For functions that accept "<i>value</i>" arguments (also shown as
"<i>value1</i>" and "<i>value2</i>"),
those arguments is usually understood
to be a literal strings that are quoted and becomes JSON string values
in the result.  Even if the input <i>value</i> strings look like 

<p>
To be clear: "<i>json</i>" arguments are always interpreted as JSON
regardless of where the value for that argument comes from.  But
"<i>value</i>" arguments are only interpreted as JSON if those arguments
come directly from another json1 function.

<h2>Compatibility</h2>

<p>
The json1 extension uses the [sqlite3_value_subtype()] and
[sqlite3_result_subtype()] interfaces that were introduced with
SQLite version 3.9.0.  Therefore the json1 extension will not work
in earlier versions of SQLite.

<h1>Function Details</h1>

<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>
<h2>The json() function</h2>

<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

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

<tcl>hd_fragment jarray {json_array SQL function} {json_array}</tcl>
<h2>The json_array() function</h2>

<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

  {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>
<h2>The json_array_length() function</h2>

<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 a JSON array, and NULL if path P does not
locate any element of X.  Errors are thrown if either X is not 

  {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>
<h2>The json_extract() function</h2>

<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_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>
<h2>The json_insert(), json_replace, and json_set() functions</h2>

<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.

  {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>
<h2>The json_object() function</h2>

<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.

  {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>
<h2>The json_remove() function</h2>

<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.

  {json_remove('{"x":25,"y":42}')} {'{"x":25,"y":42}'} \
  {json_remove('{"x":25,"y":42}','$.z')} {'{"x":25,"y":42}'} \
  {json_remove('{"x":25,"y":42}','$.y')} {'{"x":25}'} \
  {json_remove('{"x":25,"y":42}','$')} NULL
</tcl>

<tcl>hd_fragment jtype {json_type SQL function} {json_type}</tcl>
<h2>The json_type() function</h2>

<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

  {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>
<h2>The json_valid() function</h2>

<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>
jexample \
  {json_valid('{"x":35}')} 1 \
  "json_valid('\173\"x\":35')" 0
</tcl>

<tcl>hd_fragment jquote {json_quote SQL function} {json_quote}</tcl>
<h2>The json_quote() function</h2>

<p>The json_quote(X) function converts the SQL value X (a number or a
string) into its corresponding JSON representation. 

<p>Examples:

<tcl>
jexample \
  {json_quote(3.14159)} 3.14159 \
  "json_quote('verdant')" \"verdant\"
</tcl>

<tcl>
hd_fragment jgrouparray {json_group_array SQL function} \
   {json_group_array}
hd_fragment jgroupobject {json_group_object SQL function} \
   {json_group_object}
</tcl>
<h2>The json_group_array() and json_group_object()
aggregate SQL functions</h2>

<p>The json_group_array(X) function is an 
[Aggregate Functions|aggregate SQL function] that returns a JSON array
comprised of all X values in the aggregation.
Similarly, the json_group_object(NAME,VALUE) function returns a JSON object
comprised of all NAME/VALUE pairs in the aggregation.


<tcl>hd_fragment jeach {json_each table-valued function} {json_each}</tcl>
<tcl>hd_fragment jtree {json_tree table-valued function} {json_tree}</tcl>
<h2>The json_each() and json_tree() table-valued functions</h2>

<p>The json_each(X) and json_tree(X) [table-valued functions] walk the
JSON value provided as their first argument and return one row for each
element.  The json_each(X) function only walks the immediate children
of the top-level array or object or 
or just the top-level element itself if the top-level
element is a primitive value.

<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.

<h3>Examples using json_each() and json_tree()</h3>

<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