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1856027 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | # 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 browse_table_data(table_id: str) -> None:
# [START bigquery_browse_table]
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 browse data rows.
# table_id = "your-project.your_dataset.your_table_name"
# Download all rows from a table.
rows_iter = client.list_rows(table_id) # Make an API request.
# Iterate over rows to make the API requests to fetch row data.
rows = list(rows_iter)
print("Downloaded {} rows from table {}".format(len(rows), table_id))
# Download at most 10 rows.
rows_iter = client.list_rows(table_id, max_results=10)
rows = list(rows_iter)
print("Downloaded {} rows from table {}".format(len(rows), table_id))
# Specify selected fields to limit the results to certain columns.
table = client.get_table(table_id) # Make an API request.
fields = table.schema[:2] # First two columns.
rows_iter = client.list_rows(table_id, selected_fields=fields, max_results=10)
print("Selected {} columns from table {}.".format(len(rows_iter.schema), table_id))
rows = list(rows_iter)
print("Downloaded {} rows from table {}".format(len(rows), table_id))
# Print row data in tabular format.
rows_iter = client.list_rows(table_id, max_results=10)
format_string = "{!s:<16} " * len(rows_iter.schema)
field_names = [field.name for field in rows_iter.schema]
print(format_string.format(*field_names)) # Prints column headers.
for row in rows_iter:
print(format_string.format(*row)) # Prints row data.
# [END bigquery_browse_table]
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