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    "info": {
        "author": "Denis Lisovik",
        "author_email": "cyberlis@rccraft.ru",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: Implementation :: CPython",
            "Programming Language :: Python :: Implementation :: PyPy",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "\nDictQuery\n========================\n\nLibrary to query python dicts\n\n\nSeveral syntax examples:\n\n```\n\"age >= 12\"\n\"`user.name` == 'cyberlis'\"\n\"`user.email` MATCH /\\w+@\\w+\\.com/ AND age != 11\"\n\"`user.friends.age` > 12 AND `user.friends.name` LIKE 'Ra*ond'\"\n\"email LIKE 'mariondelgado?bleendot?com'\"\n\"eyeColor IN ['blue', 'green', 'black']\"\n\"isActive AND (gender == 'female' OR age == 27)\"\n\"latitude != longitude\"\n```\n\nSupported data types\n====================\n| type | example |\n|-----------|---------|\n| KEY       | name, age, \\`friends.name.firstname\\`, \\`friends.age\\` |\n| NUMBER    | 42, -12, 34.7 |\n| STRING    | 'hello', \"hellow\" |\n| BOOLEAN   | true, false |\n| NONE      | none, null |\n| NOW       | utc current datetime |\n| REGEXP    | /\\d+\\d+\\w+/ |\n| ARRAY     | list of any items and any types |\n\n\nKeys\n===========\nKey literals must start with a letter or an underscore, such as:\n  * `_underscore`\n  * `underscore_`\n\nThe remainder of your variable name may consist of letters, numbers and underscores.\n  * `password1`\n  * `n00b`\n  * `un_der_scores`\n\nIf you need a key with separator character (`.` or `/`) because you use nested keys, or need spaces or other punctuation characters in key, use back-ticks (\\`\\`)\n\nDictQuery supports nested dicts splited by dot `.` or any separator specified in `key_separator` param. Default `key_separator='.'`\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"`friends.age` <= 26\")\nTrue\n>>> compiled = dq.compile(\"`friends/age` <= 26\", key_separator='/')\n>>> compiled.match(data)\nTrue\n```\n\nif you don't need nested keys parsing and want get keys as is or if your keys contain separator char, you can disable nested keys behaviour by setting `use_nested_keys=False`\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"`user.address`\")\nFalse\n>>> dq.match(data, \"age\")\nTrue\n>>> compiled = dq.compile(\"`user.address`\", use_nested_keys=False)\n>>> compiled.match(data)\nTrue\n```\n\nIn query you can use dict keys 'as is' without any binary operation. DictQuery will get value by the key and evaluate it to bool\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"isActive\")\nFalse\n>>> dq.match(data, \"isActive == false\")\nTrue\n```\n\nif key is not found by default this situation evaluates to boolean `False` (no exception raised).\nYou can set `raise_keyerror=True` to raise keyerror if key would not be found.\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"favoriteFruit\")\nFalse\n>>> compiled = dq.compile(\"`favoriteFruit`\", raise_keyerror=True)\n>>> compiled.match(data)\nTraceback (most recent call last):\n  File \"<stdin>\", line 1, in <module>\n  File \".../dictquery/dictquery/visitors.py\", line 41, in match\n    return self.evaluate(data)\n  File \".../dictquery/dictquery/visitors.py\", line 35, in evaluate\n    result = bool(self.ast.accept(self))\n  File \".../dictquery/dictquery/parsers.py\", line 80, in accept\n    return visitor.visit_key(self)\n  File \".../dictquery/dictquery/visitors.py\", line 84, in visit_key\n    values=self._get_dict_value(expr.value),\n  File \".../dictquery/dictquery/visitors.py\", line 30, in _get_dict_value\n    self.key_separator, self.raise_keyerror)\n  File \".../dictquery/dictquery/datavalue.py\", line 112, in query_value\n    raise DQKeyError(\"Key '{}' not found\".format(data_key))\ndictquery.exceptions.DQKeyError: \"Key 'favoriteFruit' not found\"\n\n```\n\nComparisons\n===========\n\n\n| Operation | Meaning |\n|-----------|---------|\n| <         | strictly less than |\n| <=        | less than or equal |\n| >         | strictly greater than |\n| >=        | greater than or equal |\n| ==        | equal |\n| !=        | not equal |\n\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"age == 26\")\nTrue\n>>> dq.match(data, \"latitude > 12\")\nTrue\n>>> dq.match(data, \"longitude < 30\")\nTrue\n>>> dq.match(data, \"`friends.age` <= 26\")\nTrue\n>>> dq.match(data, \"longitude >= -130\")\nTrue\n>>> dq.match(data, \"id != 0\")\nTrue\n>>> dq.match(data, \"gender == 'male'\")\nFalse\n```\n\nString comparisons and matching\n===============================\n\nString literals are written in a variety of ways:\n* Single quotes: 'allows embedded \"double\" quotes'\n* Double quotes: \"allows embedded 'single' quotes\".\n\n| Operation | Meaning |\n|-----------|---------|\n| MATCH     | regexp matching |\n| LIKE      | glob like matching |\n| IN        | dict item substring in string |\n| CONTAINS   | dict item substring contains string |\n\n< , <= , > , >= , == , != works same way with strings as python\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"eyeColor == 'green'\")\nTrue\n>>> dq.match(data, \"`name.firstname` != 'Ratliff'\")\nTrue\n>>> dq.match(data, \"eyeColor IN 'string with green color'\")\nTrue\n>>> dq.match(data, \"email CONTAINS '.com'\")\nTrue\n>>> dq.match(data, r\"email MATCH /\\w+@\\w+\\.\\w+/\")\nTrue\n>>> dq.match(data, r\"email LIKE 'mariondelgado@*'\")\nTrue\n>>> dq.match(data, r\"email LIKE 'mariondelgado?bleendot?com'\")\nTrue\n```\n\nBy default all string related operations are case sensitive. To change this behaviour you have to create instance of DictQuery with `case_sensitive=False`\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"`name.firstname` == 'marion'\")\nFalse\n>>> compiled = dq.compile(\"`name.firstname` == 'marion'\", case_sensitive=False)\n>>> compiled.match(data)\nTrue\n```\n\nArray comparisons\n=================\n| Operation | Meaning |\n|-----------|---------|\n| IN        | dict item in array |\n| CONTAINS   | dict item contains matching item |\n\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"tags CONTAINS 'dolor'\")\nTrue\n>>> dq.match(data, \"eyeColor IN ['blue', 'green', 'black']\")\nTrue\n```\n\nKey presence in dict\n=====================\n`CONTAINS` can be used with dict items to check if key in dict\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"name CONTAINS 'firstname'\")\nTrue\n>>> dq.match(data, \"name CONTAINS 'thirdname'\")\nFalse\n```\n\nDatetime comparisons with `NOW`\n===============================\n`NOW` returns current utc datetime\n\ndict item can be compared with `NOW` using standard operations (< , <= , > , >= , == , !=)\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"registered < NOW\")\nTrue\n>>> dq.match(data, \"registered != NOW\")\nTrue\n```\n\nLogical operators\n=================\n|Operator|\tMeaning|\tExample|\n|--------|---------|---------|\n|and\t|True if both the operands are true|\tx and y|\n|or\t|True if either of the operands is true|\tx or y|\n|not\t|True if operand is false (complements the operand)|\tnot x |\n\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"isActive AND gender == 'female'\")\nFalse\n>>> dq.match(data, \"isActive OR gender == 'female'\")\nTrue\n>>> dq.match(data, \"NOT isActive AND gender == 'female'\")\nTrue\n```\n\nYou can use parentheses to group statements or change evaluation order\n```\n>>> import dictquery as dq\n>>> dq.match(data, \"isActive AND gender == 'female' OR age == 27\")\nTrue\n>>> dq.match(data, \"isActive AND (gender == 'female' OR age == 27)\")\nFalse\n```\n\n\nData for examples above:\n=================\n\n\n```\nfrom datetime import datetime\ndata = {\n  \"_id\": 10,\n  \"isActive\": False,\n  \"age\": 27,\n  \"eyeColor\": \"green\",\n  \"name\": {\n    \"firstname\": \"Marion\",\n    \"secondname\": \"Delgado\",\n  },\n  \"gender\": \"female\",\n  \"email\": \"mariondelgado@bleendot.com\",\n  \"registered\": datetime.strptime(\"2015-03-29T06:07:58\", \"%Y-%m-%dT%H:%M:%S\"),\n  \"latitude\": 74.785608,\n  \"longitude\": -112.366088,\n  \"tags\": [\n    \"voluptate\",\n    \"ex\",\n    \"dolor\",\n    \"aute\"\n  ],\n  \"user.address\": \"155 Village Road, Enetai, Puerto Rico, 2634\",\n  \"friends\": [\n    {\n      \"id\": 0,\n      \"name\": {\n        \"firstname\": \"Ratliff\",\n        \"secondname\": \"Becker\",\n      },\n      \"age\": 27,\n      \"eyeColor\": \"green\"\n    },\n    {\n      \"id\": 1,\n      \"name\": {\n        \"firstname\": \"Raymond\",\n        \"secondname\": \"Albert\",\n      },\n      \"age\": 19,\n      \"eyeColor\": \"brown\"\n    },\n    {\n      \"id\": 2,\n      \"name\": {\n        \"firstname\": \"Mavis\",\n        \"secondname\": \"Sheppard\",\n      },\n      \"age\": 34,\n      \"eyeColor\": \"blue\"\n    }\n  ]\n}\n```\n\n\n",
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