text: # Copyright 2019 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
  #
  #     https://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.
  
  
  def client_load_partitioned_table(table_id: str) -> None:
  
      # [START bigquery_load_table_partitioned]
      from google.cloud import bigquery
  
      # Construct a BigQuery client object.
      client = bigquery.Client()
  
      # TODO(developer): Set table_id to the ID of the table to create.
      # table_id = "your-project.your_dataset.your_table_name"
  
      job_config = bigquery.LoadJobConfig(
          schema=[
              bigquery.SchemaField("name", "STRING"),
              bigquery.SchemaField("post_abbr", "STRING"),
              bigquery.SchemaField("date", "DATE"),
          ],
          skip_leading_rows=1,
          time_partitioning=bigquery.TimePartitioning(
              type_=bigquery.TimePartitioningType.DAY,
              field="date",  # Name of the column to use for partitioning.
              expiration_ms=7776000000,  # 90 days.
          ),
      )
      uri = "gs://cloud-samples-data/bigquery/us-states/us-states-by-date.csv"
  
      load_job = client.load_table_from_uri(
          uri, table_id, job_config=job_config
      )  # Make an API request.
  
      load_job.result()  # Wait for the job to complete.
  
      table = client.get_table(table_id)
      print("Loaded {} rows to table {}".format(table.num_rows, table_id))
      # [END bigquery_load_table_partitioned]
  