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Library versions released prior to that date will continue to be available. For more information please
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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))