bigquery_archive_dataset_or_table.py

from google.cloud import bigquery
from datetime import date

# You have to create a dataset in your BQ project before running this script, here the name is "archive"
ARCHIVE_DATASET = 'archive'

def archive_table(bq, dataset, table):
    d = date.today()
    table_src_id = '{}.{}.{}'.format(bq.project, dataset, table)
    table_dest_id = '{}.{}.{}-{}-{:%Y-%m-%d}'.format(bq.project, ARCHIVE_DATASET, dataset, table, d)
    bq.copy_table(table_src_id, table_dest_id)
    bq.delete_table(table_src_id)
    print('archive table "{}" to "{}"'.format(table_src_id, table_dest_id))

def archive_dataset(bq, dataset):
    for table in bq.list_tables(dataset):
        archive_table(bq, dataset, table.table_id)
    bq.delete_dataset(dataset)
 
bq = bigquery.Client()
archive_dataset(bq, 'dataset_name')
archive_table(bq, 'dataset_name2', 'table_name')