{
    "info": {
        "author": "Kyle Lahnakoski",
        "author_email": "kyle@lahnakoski.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "# More JSON Tools!\n\nThis set of modules solves three problems:\n\n* We want to iterate over massive JSON easily (`mo_json.stream`)\n* A bijection between strictly typed JSON, and dynamic typed JSON.\n* Flexible JSON parser to handle comments, and other forms\n* <strike>JSON encoding is slow (`mo_json.encode`)</strike>\n\n\n## Running tests\n\n    pip install -r tests/requirements.txt\n    set PYTHONPATH=.    \n    python.exe -m unittest discover tests\n\n\n## Module Details\n\n### Method `mo_json.value2json()`\n\nConvert a `dict`, list, or primitive value to a utf-8 encoded JSON string.\n\n### Method `mo_json.json2value()`\n\nConvert a utf-8 encoded string to a data structure \n\n\n### Method `mo_json.scrub()`\n\nRemove, or convert, a number of objects from a structure that are not JSON-izable. It is faster to `scrub` and use the default (aka c-based) python encoder than it is to use `default` serializer that forces the use of an interpreted python encoder. \n\n----------------------\n\n### Module `mo_json.stream`\n\nA module that supports queries over very large JSON\nstrings. The overall objective is to make a large JSON document appear like\na hierarchical database, where arrays of any depth, can be queried like\ntables. \n\n\n#### Limitations\n\nThis is not a generic streaming JSON parser. It is only intended to breakdown the top-level array, or object for less memory usage.  \n\n*  **Array values must be the last object property** - If you query into a \n   nested array, all sibling properties found after that array must be ignored \n   (must not be in the `expected_vars`). The code will raise an exception if\n   you can not extract all expected variables.\n\n----------------------\n\n### Method `mo_json.stream.parse()`\n\nWill return an iterator over all objects found in the JSON stream.\n\n**Parameters:**\n\n* **json** - a parameter-less function, when called returns some number of\n  bytes from the JSON stream. It can also be a string.\n* **path** - a dot-delimited string specifying the path to the nested JSON. Use \n  `\".\"` if your JSON starts with `[`, and is a list.\n* **expected_vars** - a list of strings specifying the full property names \n  required (all other properties are ignored)\n\n#### Common Usage\n\nThe most common use of `parse()` is to iterate over all the objects in a large, top-level, array:\n\n    parse(json, path=\".\", required_vars=[\".\"]}\n\nFor example, given the following JSON: \n\n    [\n        {\"a\": 1},\n        {\"a\": 2},\n        {\"a\": 3},\n        {\"a\": 4}\n    ]\n\nreturns a generator that provides\n\n    {\"a\": 1}\n    {\"a\": 2}\n    {\"a\": 3}\n    {\"a\": 4}\n\n\n#### Examples\n\n**Simple Iteration**\n\n    json = {\"b\": \"done\", \"a\": [1, 2, 3]}\n    parse(json, path=\"a\", required_vars=[\"a\", \"b\"]}\n\nWe will iterate through the array found on property `a`, and return both `a` and `b` variables. It will return the following values:\n\n    {\"b\": \"done\", \"a\": 1}\n    {\"b\": \"done\", \"a\": 2}\n    {\"b\": \"done\", \"a\": 3}\n\n\n**Bad - Property follows array**\n\nThe same query, but different JSON with `b` following `a`:\n\n    json = {\"a\": [1, 2, 3], \"b\": \"done\"}\n    parse(json, path=\"a\", required_vars=[\"a\", \"b\"]}\n\nSince property `b` follows the array we're iterating over, this will raise an error.\n\n**Good - No need for following properties**\n\nThe same JSON, but different query, which does not require `b`:\n\n    json = {\"a\": [1, 2, 3], \"b\": \"done\"}\n    parse(json, path=\"a\", required_vars=[\"a\"]}\n\nIf we do not require `b`, then streaming will proceed just fine:\n\n    {\"a\": 1}\n    {\"a\": 2}\n    {\"a\": 3}\n\n**Complex Objects**\n\nThis streamer was meant for very long lists of complex objects. Use dot-delimited naming to refer to full name of the property\n\n    json = [{\"a\": {\"b\": 1, \"c\": 2}}, {\"a\": {\"b\": 3, \"c\": 4}}, ...\n    parse(json, path=\".\", required_vars=[\"a.c\"])\n\nThe dot (`.`) can be used to refer to the top-most array. Notice the structure is maintained, but only includes the required variables.\n\n    {\"a\": {\"c\": 2}}\n    {\"a\": {\"c\": 4}}\n    ...\n\n**Nested Arrays**\n\nNested array iteration is meant to mimic a left-join from parent to child table;\nas such, it includes every record in the parent. \n\n    json = [\n        {\"o\": 1: \"a\": [{\"b\": 1}: {\"b\": 2}: {\"b\": 3}: {\"b\": 4}]},\n        {\"o\": 2: \"a\": {\"b\": 5}},\n        {\"o\": 3}\n    ]\n    parse(json, path=[\".\", \"a\"], required_vars=[\"o\", \"a.b\"])\n\nThe `path` parameter can be a list, which is used to indicate which properties\nare expected to have an array, and to iterate over them. Please notice if no\narray is found, it is treated like a singleton array, and missing arrays still\nproduce a result.\n\n    {\"o\": 1, \"a\": {\"b\": 1}}\n    {\"o\": 1, \"a\": {\"b\": 2}}\n    {\"o\": 1, \"a\": {\"b\": 3}}\n    {\"o\": 1, \"a\": {\"b\": 4}}\n    {\"o\": 2, \"a\": {\"b\": 5}}\n    {\"o\": 3}\n\n**Large top-level objects**\n\nSome JSON is a single large object, rather than an array of objects. In these cases, you can use the `items` operator to iterate through all name/value pairs of an object:\n\n    json = {\n        \"a\": \"test\",\n        \"b\": 2,\n        \"c\": [1, 2]\n    }\n    parse(json, {\"items\":\".\"}, {\"name\", \"value\"})   \n\nproduces an iterator of\n\n    {\"name\": \"a\", \"value\":\"test\"} \n    {\"name\": \"b\", \"value\":2} \n    {\"name\": \"c\", \"value\":[1,2]} \n\n----------------------\n\n### Module `typed_encoder`\n\n\nOne reason that NoSQL documents stores are wonderful is 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. They make the lives of humans worse; as we are forced to toil over endless schema modifications.\n\nThis module translates JSON documents into \"typed\" form; which allows document containers to store both objects and primitives in the same property. This also enables the storage of values with no containing object! \n\nThe typed JSON has a different form than the original, and queries into the document store must take this into account. This conversion is intended to be hidden behind a query abstraction layer that can understand this format.\n\n#### How it works\n\nThere are three main conversions:\n\n1. Primitive values are replaced with single-property objects, where the property name indicates the data type of the value stored:\n```\n    {\"a\": true} -> {\"a\": {\"~b~\": true}} \n    {\"a\": 1   } -> {\"a\": {\"~n~\": 1   }} \n    {\"a\": \"1\" } -> {\"a\": {\"~s~\": \"1\" }}\n```\n2. JSON objects get an additional property, `~e~`, to mark existence. This allows us to query for object existence, and to count the number of objects.\n```    \n    {\"a\": {}} -> {\"a\": {}, \"~e~\": 1}  \n```\n3. JSON arrays are contained in a new object, along with `~e~` to count the number of elements in the array:\n```    \n    {\"a\": [1, 2, 3]} -> {\"a\": {\n        \"~e~\": 3, \n        \"~N~\":[\n            {\"~n~\": 1},\n            {\"~n~\": 2},\n            {\"~n~\": 3}\n        ]\n    }}\n```\nPlease notice the sum of `a.~e~` works for both objects and arrays; letting us interpret sub-objects as single-value nested object arrays. \n\n### Function `typed_encode()`\n\nAccepts a `dict`, `list`, or primitive value, and generates the typed JSON that can be inserted into a document store.\n\n### Function `json2typed()`\n\nConverts an existing JSON unicode string and returns the typed JSON unicode string for the same.\n\n\n----------------------\n\n\n### Module `mo_json.encode`\n\n### Function: `mo_json.encode.json_encoder()`\n\n----------------------\n\n**Update Mar2016** - *PyPy version 5.x appears to have improved C integration to\nthe point that the C library callbacks are no longer a significant overhead:\nThis pure Python JSON encoder is no longer faster than a compound C/Python\nsolution.*\n\nFast JSON encoder used in `convert.value2json()` when running in Pypy. Run the\n[speedtest](https://github.com/klahnakoski/pyLibrary/blob/dev/tests/speedtest_json.py)\nto compare with default implementation and ujson",
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