As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Source code for google.cloud.automl_v1beta1.types.table_spec

# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import proto  # type: ignore

from google.cloud.automl_v1beta1.types import io


__protobuf__ = proto.module(
    package="google.cloud.automl.v1beta1", manifest={"TableSpec",},
)


[docs]class TableSpec(proto.Message): r"""A specification of a relational table. The table's schema is represented via its child column specs. It is pre-populated as part of ImportData by schema inference algorithm, the version of which is a required parameter of ImportData InputConfig. Note: While working with a table, at times the schema may be inconsistent with the data in the table (e.g. string in a FLOAT64 column). The consistency validation is done upon creation of a model. Used by: - Tables Attributes: name (str): Output only. The resource name of the table spec. Form: ``projects/{project_id}/locations/{location_id}/datasets/{dataset_id}/tableSpecs/{table_spec_id}`` time_column_spec_id (str): column_spec_id of the time column. Only used if the parent dataset's ml_use_column_spec_id is not set. Used to split rows into TRAIN, VALIDATE and TEST sets such that oldest rows go to TRAIN set, newest to TEST, and those in between to VALIDATE. Required type: TIMESTAMP. If both this column and ml_use_column are not set, then ML use of all rows will be assigned by AutoML. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset. row_count (int): Output only. The number of rows (i.e. examples) in the table. valid_row_count (int): Output only. The number of valid rows (i.e. without values that don't match DataType-s of their columns). column_count (int): Output only. The number of columns of the table. That is, the number of child ColumnSpec-s. input_configs (Sequence[google.cloud.automl_v1beta1.types.InputConfig]): Output only. Input configs via which data currently residing in the table had been imported. etag (str): Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. """ name = proto.Field(proto.STRING, number=1,) time_column_spec_id = proto.Field(proto.STRING, number=2,) row_count = proto.Field(proto.INT64, number=3,) valid_row_count = proto.Field(proto.INT64, number=4,) column_count = proto.Field(proto.INT64, number=7,) input_configs = proto.RepeatedField( proto.MESSAGE, number=5, message=io.InputConfig, ) etag = proto.Field(proto.STRING, number=6,)
__all__ = tuple(sorted(__protobuf__.manifest))