aito.schema.AitoTokenNgramAnalyzerSchema

class aito.schema.AitoTokenNgramAnalyzerSchema(source: AitoAnalyzerSchema, min_gram: int, max_gram: int, token_separator: str = None)

Bases: AitoAnalyzerSchema

Aito TokenNGramAnalyzer schema

Parameters:

source (AitoAnalyzerSchema) – the source analyzer to generate features before being combined into n-grams
min_gram (int) – the minimum length of characters in a feature
max_gram (int) – the maximum length of characters in a feature
token_separator (str, defaults to ' ') – the string used to join the features of the source analyzer

Methods

`from_deserialized_object`(obj)	create a class object from a JSON deserialized object
`from_json_string`(json_string, **kwargs)	create an class object from a JSON string
`infer_from_samples`(samples[, max_sample_size])	Infer an analyzer from the given samples
`json_schema`()	the JSON schema of the class
`json_schema_validate`(obj)	Validate an object with the class json_schema Returns the object if validation success, else raise `JsonValidationError`
`json_schema_validate_with_schema`(obj, schema)	Validate an object with the given schema
`to_json_serializable`()	convert the object to an object that can be serialized to a JSON formatted string
`to_json_string`(**kwargs)	convert the object to a JSON string

Attributes

`analyzer_type`	the type of the analyzer
`column_link_pattern`
`column_name_pattern`
`comparison_properties`	properties of the schema object that will be used for comparison operation
`max_gram`
`min_gram`
`source`	the source analyzer
`table_name_pattern`
`token_separator`	the string that will be used to join the features
`type`	the type of the schema component
`uuid_pattern`

property analyzer_type: str

the type of the analyzer

Return type:: str

property comparison_properties: Iterable[str]

properties of the schema object that will be used for comparison operation

Return type:: Iterable[str]

classmethod from_deserialized_object(obj): create a class object from a JSON deserialized object

classmethod from_json_string(json_string: str, **kwargs)

create an class object from a JSON string

Parameters:

json_string (str) – the JSON string
kwargs – the keyword arguments for json.loads method

classmethod infer_from_samples(samples: Iterable[str], max_sample_size: int = 10000)

Infer an analyzer from the given samples

Parameters:

samples (Iterable) – iterable of sample
max_sample_size (int) – at most first max_sample_size will be used for inference, defaults to 10000

Returns:

inferred Analyzer or None if no analyzer is applicable

Return type:

Optional[AitoAnalyzerSchema]

classmethod json_schema()

the JSON schema of the class

Return type:: Dict

classmethod json_schema_validate(obj: Any)

Validate an object with the class json_schema Returns the object if validation success, else raise JsonValidationError

Parameters:: obj (Any) – the object to be validated
Returns:: the object if validation succeed
Return type:: Any

json_schema_validate_with_schema(obj: Any, schema: Dict)

Validate an object with the given schema

Parameters:

obj (Any) – the object to be validated
schema (Dict) – the schema to be validate against

Returns:

the object if validation succeed

Return type:

Any

property source

the source analyzer

Return type:: AitoAnalyzerSchema

to_json_serializable(): convert the object to an object that can be serialized to a JSON formatted string

to_json_string(**kwargs)

convert the object to a JSON string

Parameters:: kwargs – the keyword arguments for json.dumps method
Return type:: str

property token_separator: str

the string that will be used to join the features

Return type:: str

property type

the type of the schema component

Return type:: str