DataTableDeserializer: DataTableDeserializer Class

In DyfanJones/sagemaker-r-mlcore: sagemaker machine learning core classes and methods

DataTableDeserializer Class

Description

Deserialize CSV or JSON data from an inference endpoint into a data.table.

Super classes

sagemaker.mlcore::BaseDeserializer -> sagemaker.mlcore::SimpleBaseDeserializer -> DataTableDeserializer

Public fields

encoding

string encoding to be used

Methods

Public methods

• DataTableDeserializer$new()

• DataTableDeserializer$deserialize()

• DataTableDeserializer$clone()

Inherited methods

• sagemaker.mlcore::BaseDeserializer$format()

---

Method new()

Initialize a “DataTableDeserializer“ instance.

Usage

DataTableDeserializer$new(
  encoding = "UTF-8",
  accept = c("text/csv", "application/json")
)

Arguments

encoding

(str): The string encoding to use (default: "UTF-8").

accept

(union[str, tuple[str]]): The MIME type (or tuple of allowable MIME types) that is expected from the inference endpoint (default: ("text/csv","application/json")).

---

Method deserialize()

Deserialize CSV or JSON data from an inference endpoint into a data.table. If the data is JSON, the data should be formatted in the 'columns' orient.

Usage

DataTableDeserializer$deserialize(stream, content_type)

Arguments

stream

(botocore.response.StreamingBody): Data to be deserialized.

content_type

(str): The MIME type of the data.

Returns

data.table: The data deserialized into a data.table.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

DataTableDeserializer$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other serializer: BaseDeserializer, BaseSerializer, BytesDeserializer, CSVDeserializer, CSVSerializer, IdentitySerializer, JSONDeserializer, JSONLinesDeserializer, JSONLinesSerializer, JSONSerializer, LibSVMSerializer, NumpyDeserializer, NumpySerializer, SimpleBaseDeserializer, SimpleBaseSerializer, SparseMatrixSerializer, StringDeserializer, TibbleDeserializer

DyfanJones/sagemaker-r-mlcore documentation built on May 3, 2022, 10:08 a.m.