How to use _create_schema method in pandera
Best Python code snippet using pandera_python
fundamental_schemas.py
Source:fundamental_schemas.py 
...6class Schema(ABC):7 def __init__(self, **options: Any):8 self._options = options9 def __repr__(self) -> str:10 return str(self._create_schema())11 def validate(self, instance) -> None:12 custom_validator.validate(13 instance=instance,14 schema=self._create_schema(),15 )16 @abstractmethod17 def _create_core_of_schema(self) -> Dict[str, Any]:18 """19 This function create the core of the schema. Core is not a complete schema, it can't be validated.20 To pass validation, _create_schema adds basic schema parts and optional parameters (e.g 'enum', 'minItems'),21 creating a complete schema prepared for validation.22 """23 pass24 def _create_schema(self) -> Dict[str, Any]:25 return {**self._create_core_of_schema(), **self._options}26 @staticmethod27 def _assert_that_schema_has_correct_type(schema):28 if not isinstance(schema, Schema):29 raise ValidationError(f'Passed schema has invalid format:\n'30 f'{pprint.pformat(schema, indent=4, sort_dicts=False)}\n'31 f'\n'32 f'Instead you should use predefined schema, like: Int(), Str(), Map(), etc.\n'33 f'You can see examples in following files:\n'34 f' schemas/tests/test_fundamental_schemas.py\n'35 f' schemas/tests/test_custom_schemas.py\n'36 f'\n'37 f'You can check all available types here:\n'38 f' schemas/package/schemas/predefined.py')39class AllOf(Schema):40 """41 AllOf: (AND) The instance must be valid for all of the subschemas42 Documentation: http://json-schema.org/understanding-json-schema/reference/combining.html#allof43 """44 def __init__(self, *items, **options: Any):45 super().__init__(**options)46 self.__items = list(items)47 def _create_core_of_schema(self) -> Dict[str, Any]:48 items_as_dicts = []49 for schema in self.__items:50 self._assert_that_schema_has_correct_type(schema)51 items_as_dicts.append(schema._create_schema())52 return {53 'allOf': items_as_dicts54 }55class AnyOf(Schema):56 """57 AnyOf: (OR) The instance must be valid for any (one or more) of the given subschemas58 Documentation: http://json-schema.org/understanding-json-schema/reference/combining.html#anyof59 """60 def __init__(self, *items, **options: Any):61 super().__init__(**options)62 self.__items = list(items)63 def _create_core_of_schema(self) -> Dict[str, Any]:64 items_as_dicts = []65 for schema in self.__items:66 self._assert_that_schema_has_correct_type(schema)67 items_as_dicts.append(schema._create_schema())68 return {69 'anyOf': items_as_dicts70 }71class Any_(Schema):72 """73 Accepts everything. Can be used to skip instance checking.74 """75 def _create_core_of_schema(self) -> Dict[str, Any]:76 return {}77class Array(Schema):78 def __init__(self, item: Schema, *items: Schema, unique_items=False, **options: Any):79 """80 Ensures that given instance is an array and contains items of required types, e.g.:81 - Array(Int()) -> read as array of ints. [0, 1, 2, 1024],82 - Array(Str()) -> read as array of strings. ['a', 'b', 'c'],83 - Array(Str(), Int()) -> read as array of ints and strings. [0, 'a', 1, 'b'] - mixing of types is allowed,84 - Array(Any(), maxItems=0) -> if you want to validate always an empty array.85 Documentation: http://json-schema.org/understanding-json-schema/reference/array.html86 :param unique_items: Duplicated items in array are treated as error.87 """88 super().__init__(**options)89 self.__items: List[Schema] = [item, *items]90 self.__unique_items = unique_items91 def _create_core_of_schema(self) -> Dict[str, Any]:92 items_as_dicts = []93 for schema in self.__items:94 self._assert_that_schema_has_correct_type(schema)95 items_as_dicts.append(schema._create_schema())96 common_part_of_schema = {97 'type': 'array',98 'uniqueItems': self.__unique_items,99 }100 if len(items_as_dicts) > 1:101 return {102 **common_part_of_schema,103 'items': {104 'oneOf': items_as_dicts,105 },106 }107 return {108 **common_part_of_schema,109 'items': items_as_dicts[0],110 }111class ArrayStrict(Schema):112 """113 Array Strict checks that the nth element in the instance, matches the nth type specified in the schema.114 example_array = [0, 'string', True]115 example_schema : ArrayStrict(Int(), String(), Bool())116 example_array[0] -> Int(),117 example_array[1] -> String(),118 example_array[2] -> Bool()119 The ArrayStrict is the equivalent of a jsonschema tuple-validation:120 http://json-schema.org/understanding-json-schema/reference/array.html#tuple-validation121 The options available for Array can be used in ArrayStrict:122 http://json-schema.org/understanding-json-schema/reference/array.html123 """124 def __init__(self, *items, **options: Any):125 super().__init__(**options)126 self.__items = list(items)127 def _create_core_of_schema(self) -> Dict[str, Any]:128 items_as_dicts = self.__items.copy()129 for index, schema in enumerate(items_as_dicts):130 self._assert_that_schema_has_correct_type(schema)131 items_as_dicts[index] = schema._create_schema()132 return {133 'type': 'array',134 'prefixItems': items_as_dicts,135 "minItems": len(items_as_dicts),136 'maxItems': len(items_as_dicts),137 }138class Bool(Schema):139 """140 Documentation: http://json-schema.org/understanding-json-schema/reference/boolean.html141 """142 def _create_core_of_schema(self) -> Dict[str, Any]:143 return {'type': 'boolean'}144class Date(Schema):145 """146 Date format used in HIVE ('%Y-%m-%dT%H:%M:%S').147 """148 def _create_core_of_schema(self) -> Dict[str, Any]:149 return {'type': 'hive-datetime'}150class Float(Schema):151 """152 Documentation: http://json-schema.org/understanding-json-schema/reference/numeric.html#number153 """154 def _create_core_of_schema(self) -> Dict[str, Any]:155 return {'type': 'number'}156class Int(Schema):157 """158 Validates normal JSON ints (e.g. 1, 42, -100), and also converted to strings159 (e.g. '1', '42', '-100'). All Hive APIs use this int format.160 """161 def __init__(self, **options: Any):162 super().__init__(**self.__replace_overridden_options(options))163 @staticmethod164 def __replace_overridden_options(options: Dict[str, Any]):165 validators_to_change = ['multipleOf', 'minimum', 'maximum', 'exclusiveMinimum', 'exclusiveMaximum']166 return {f'HiveInt.{k}' if k in validators_to_change else k: v for k, v in options.items()}167 def _create_core_of_schema(self) -> [str, Any]:168 return {'type': 'hive-int'}169class Json(Schema):170 def _create_core_of_schema(self) -> Dict[str, Any]:171 return {'type': 'json'}172class Map(Schema):173 def __init__(self, schema: Dict, required_keys: Optional[List[str]] = None,174 allow_additional_properties: bool = False, **options: Any):175 """176 Validates JSON objects (in Python they are called dicts).177 :param schema: Collection of properties. Each of the individual properties has a key178 (represents the name of the key in instance), and schema (represents the required type,179 for the previously specified key).180 :param required_keys: The keys contained in this parameter are required for successful validation.181 The other keys specified in the schema are optional, their absence will not affect the validation process.182 :param allow_additional_properties: By default map does not accept additional undefined properties.183 All instance elements not defined in the schema will be reported as a 'ValidationError'.184 Set this parameter to True, it will allow the correct validation of additional properties in the instance.185 :param options: Other options that can be given in the form of a dictionary.186 Documentation: http://json-schema.org/understanding-json-schema/reference/object.html187 """188 super().__init__(**options)189 self.__allow_additional_properties: bool = allow_additional_properties190 self.__schema = schema191 self.__required_keys: List[str] = list(self.__schema.keys()) if required_keys is None else required_keys192 def _create_core_of_schema(self) -> Dict[str, Any]:193 items_as_dicts = self.__schema.copy()194 for key, schema in self.__schema.items():195 self._assert_that_schema_has_correct_type(schema)196 items_as_dicts[key] = schema._create_schema()197 return {198 'type': 'object',199 'properties': items_as_dicts,200 'required': self.__required_keys,201 'additionalProperties': self.__allow_additional_properties202 }203class Null(Schema):204 """205 Documentation: http://json-schema.org/understanding-json-schema/reference/null.html206 """207 def _create_core_of_schema(self) -> Dict[str, Any]:208 return {'type': 'null'}209class OneOf(Schema):210 """211 OneOf: (XOR) The instance must be valid for exactly one of the given subschemas.212 Documentation: http://json-schema.org/understanding-json-schema/reference/combining.html#oneof213 """214 def __init__(self, *items, **options: Any):215 super().__init__(**options)216 self.__items = list(items)217 def _create_core_of_schema(self) -> Dict[str, Any]:218 items_as_dicts = []219 for schema in self.__items:220 self._assert_that_schema_has_correct_type(schema)221 items_as_dicts.append(schema._create_schema())222 return {223 'oneOf': items_as_dicts224 }225class Str(Schema):226 """227 Documentation: http://json-schema.org/understanding-json-schema/reference/string.html228 """229 def _create_core_of_schema(self) -> Dict[str, Any]:...
arguments.py
Source:arguments.py
...47 if self._example:48 description += f" <i>[{self._example}]</i>"49 return description50 def _build_schema(self) -> dict:51 schema = self._create_schema()52 if self._allowed:53 schema["allowed"] = self._allowed54 return schema55 @abstractmethod56 def _create_schema(self) -> dict:57 ...58 def __repr__(self):59 return f'Arg(name="{self.name}", description="{self._build_description()}")'60class Integer(Arg):61 BOT_ARG_TYPE = "integer"62 def __init__(self, *args, minimum=None, maximum=None, **kwargs):63 """64 :param minimum: минималÑное знаÑение аÑгÑменÑа.65 :param maximum: макÑималÑное знаÑение аÑгÑменÑа.66 """67 super().__init__(*args, **kwargs)68 self.minimum = minimum69 self.maximum = maximum70 def _create_schema(self) -> dict:71 schema = {72 "type": self.BOT_ARG_TYPE,73 }74 if self.maximum:75 schema["max"] = self.maximum76 if self.minimum:77 schema["min"] = self.minimum78 return schema79class String(Arg):80 BOT_ARG_TYPE = "string"81 def __init__(self, *args, regex=None, **kwargs):82 """83 :param regex: РегÑлÑÑное вÑÑажение, коÑоÑÐ¾Ð¼Ñ Ð´Ð¾Ð»Ð¶Ð½Ð¾ ÑооÑвеÑÑÑвоваÑÑ Ð·Ð½Ð°Ñение аÑгÑменÑа84 """85 super().__init__(*args, **kwargs)86 self.regex = regex87 def _create_schema(self) -> dict:88 schema = {89 "type": self.BOT_ARG_TYPE,90 }91 if self.regex:92 schema["regex"] = self.regex93 return schema94class ListArg(Arg):95 BOT_ARG_TYPE = "list"96 def _create_schema(self) -> dict:97 return {"type": "list"}98class MyUser(Integer):99 """ID полÑзоваÑÐµÐ»Ñ ÑелегÑам, Ñ ÐºÐ¾ÑоÑого еÑÑÑ Ð´Ð¾ÑÑÑп к командам клиенÑа"""100 def __init__(self, *args, **kwargs):101 super().__init__(*args, **kwargs)102 self._extra_info = dict(is_granter=True)103class Actuator(String):104 """ÐкÑÑаÑÐ¾Ñ Ð±Ð¾Ñа"""105 def __init__(self, *args, **kwargs):106 super().__init__(*args, **kwargs)107 self._extra_info = dict(is_actuator=True)108class Granter(MyUser):109 """ID полÑзоваÑÐµÐ»Ñ Ñ Ð¿Ñавами на акÑÑаÑоÑ"""110 # TODO: повÑоÑ!...
user.py
Source:user.py
1"""User JSON schema."""2import jsonschema3from .message import _create_schema4_sendmail_schema = {5 "$schema": "http://json-schema.org/draft-04/schema#",6 "type": "object",7 "definitions": {8 **_create_schema['definitions'],9 },10 "properties": {11 "message": {12 "type": "object",13 "properties": {14 **_create_schema['properties'],15 }16 },17 "saveToSentItems": {18 "type": "boolean",19 },20 },21 "required": [22 "message",23 ],24}...
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