More JSON Tools!
================

This set of modules solves three problems:

-  We want to iterate over massive JSON easily (``mo_json.stream``)
-  A bi-jection between strictly typed JSON, and dynamic typed JSON.
-  Flexible JSON parser to handle comments, and other forms
-  JSON encoding is slow (``mo_json.encode``)

Module ``mo_json.stream``
-------------------------

A module supporting the implementation of queries over very large JSON
strings. The overall objective is to make a large JSON document appear
like a hierarchical database, where arrays of any depth, can be queried
like tables.

Limitations
~~~~~~~~~~~

This is not a generic streaming JSON parser. This module has two main
restrictions:

1. **Objects are not streamed** - All objects will reside in memory.
   Large objects, with a multitude of properties, may cause problems.
   Property names should be known at query time. If you must serialize
   large objects; instead of ``{<name>: <value>}`` format, try a list of
   name/value pairs instead: ``[{"name": <name>, "value": <value>}]``
   This format is easier to query, and gentler on the various document
   stores that you may put this data into.
2. **Array values must be the last object property** - If you query into
   a nested array, all sibling properties found after that array must be
   ignored (must not be in the ``expected_vars``). If not, then those
   arrays will not benefit from streaming, and will reside in memory.

Function ``mo_json.stream.parse()``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Will return an iterator over all objects found in the JSON stream.

**Parameters:**

-  **json** - a parameter-less function, when called returns some number
   of bytes from the JSON stream. It can also be a string.
-  **path** - a list of strings specifying the nested JSON paths. Use
   ``"."`` if your JSON starts with ``[``, and is a list.
-  **expected\_vars** - a list of strings specifying the full property
   names required (all other properties are ignored)

Examples
^^^^^^^^

**Simple Iteration**

::

    json = {"b": "done", "a": [1, 2, 3]}
    parse(json, path="a", required_vars=["a", "b"]}

We will iterate through the array found on property ``a``, and return
both ``a`` and ``b`` variables. It will return the following values:

::

    {"b": "done", "a": 1}
    {"b": "done", "a": 2}
    {"b": "done", "a": 3}

**Bad - Property follows array**

The same query, but different JSON with ``b`` following ``a``:

::

    json = {"a": [1, 2, 3], "b": "done"}
    parse(json, path="a", required_vars=["a", "b"]}

Since property ``b`` follows the array we're iterating over, this will
raise an error.

**Good - No need for following properties**

The same JSON, but different query, which does not require ``b``:

::

    json = {"a": [1, 2, 3], "b": "done"}
    parse(json, path="a", required_vars=["a"]}

If we do not require ``b``, then streaming will proceed just fine:

::

    {"a": 1}
    {"a": 2}
    {"a": 3}

**Complex Objects**

This streamer was meant for very long lists of complex objects. Use
dot-delimited naming to refer to full name of the property

::

    json = [{"a": {"b": 1, "c": 2}}, {"a": {"b": 3, "c": 4}}, ...
    parse(json, path=".", required_vars=["a.c"])

The dot (``.``) can be used to refer to the top-most array. Notice the
structure is maintained, but only includes the required variables.

::

    {"a": {"c": 2}}
    {"a": {"c": 4}}
    ...

**Nested Arrays**

Nested array iteration is meant to mimic a left-join from parent to
child table; as such, it includes every record in the parent.

::

    json = [
        {"o": 1: "a": [{"b": 1}: {"b": 2}: {"b": 3}: {"b": 4}]},
        {"o": 2: "a": {"b": 5}},
        {"o": 3}
    ]
    parse(json, path=[".", "a"], required_vars=["o", "a.b"])

The ``path`` parameter can be a list, which is used to indicate which
properties are expected to have an array, and to iterate over them.
Please notice if no array is found, it is treated like a singleton
array, and missing arrays still produce a result.

::

    {"o": 1, "a": {"b": 1}}
    {"o": 1, "a": {"b": 2}}
    {"o": 1, "a": {"b": 3}}
    {"o": 1, "a": {"b": 4}}
    {"o": 2, "a": {"b": 5}}
    {"o": 3}

Module ``typed_encoder``
------------------------

One reason NoSQL documents stores are wonderful is the fact their schema
can automatically expand to accept new properties. Unfortunately, this
flexibility is not limitless; A string assigned to property prevents an
object being assigned to the same, or visa-versa. This flexibility is
under attack by the strict-typing zealots, who, in their self righteous
delusion believe explicit types are better, actually make the lives of
humans worse; with endless schema modifications.

This module translates JSON documents into "typed" form; which allows
document containers to store both objects and primitives in the same
property value. This allows storage of values with no containing object!

How it works
~~~~~~~~~~~~

Typed JSON uses ``$value`` and ``$object`` properties to markup the
original JSON:

-  All JSON objects are annotated with ``"$object":"."``, which makes
   querying object existence (especially the empty object) easier.
-  All primitive values are replaced with an object with a single
   ``$value`` property: So ``"value"`` gets mapped to
   ``{"$value": "value"}``.

Of course, the typed JSON has a different form than the original, and
queries into the documents store must take this into account.
Fortunately, the use of typed JSON is intended to be hidden behind a
query abstraction layer.

Function ``typed_encode()``
~~~~~~~~~~~~~~~~~~~~~~~~~~~

Accepts a ``dict``, ``list``, or primitive value, and generates the
typed JSON that can be inserted into a document store.

Function ``json2typed()``
~~~~~~~~~~~~~~~~~~~~~~~~~

Converts an existing JSON unicode string and returns the typed JSON
unicode string for the same.

--------------

also see http://tools.ietf.org/id/draft-pbryan-zyp-json-ref-03.html

Module ``mo_json.encode``
-------------------------

Function: ``mo_json.encode.json_encoder()``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Update Mar2016** - *PyPy version 5.x appears to have improved C
integration to the point that the C library callbacks are no longer a
significant overhead: This pure Python JSON encoder is no longer faster
than a compound C/Python solution.*

Fast JSON encoder used in ``convert.value2json()`` when running in Pypy.
Run the
`speedtest <https://github.com/klahnakoski/pyLibrary/blob/dev/tests/speedtest_json.py>`__
to compare with default implementation and ujson
