python-docs-samples/bigquery/api/load_data_from_csv.py at master · devlance/python-docs-samples · GitHub

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#!/usr/bin/env python

# 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.

"""Command-line application that loads data into BigQuery from a CSV file in

Google Cloud Storage.

This sample is used on this page:

https://cloud.google.com/bigquery/loading-data-into-bigquery#loaddatagcs

For more information, see the README.md under /bigquery.

"""

import argparse

import json

import time

import uuid

from googleapiclient import discovery

from oauth2client.client import GoogleCredentials

# [START load_table]

def load_table(bigquery, project_id, dataset_id, table_name, source_schema,

source_path, num_retries=5):

"""

Starts a job to load a bigquery table from CSV

Args:

bigquery: an initialized and authorized bigquery client

google-api-client object

source_schema: a valid bigquery schema,

see https://cloud.google.com/bigquery/docs/reference/v2/tables

source_path: the fully qualified Google Cloud Storage location of

the data to load into your table

Returns: a bigquery load job, see

https://cloud.google.com/bigquery/docs/reference/v2/jobs#configuration.load

"""

# Generate a unique job ID so retries

# don't accidentally duplicate query

job_data = {

'jobReference': {

'projectId': project_id,

'jobId': str(uuid.uuid4())

'configuration': {

'load': {

'sourceUris': [source_path],

'schema': {

'fields': source_schema

'destinationTable': {

'projectId': project_id,

'datasetId': dataset_id,

'tableId': table_name

}

return bigquery.jobs().insert(

projectId=project_id,

body=job_data).execute(num_retries=num_retries)

# [END load_table]

# [START poll_job]

def poll_job(bigquery, job):

"""Waits for a job to complete."""

print('Waiting for job to finish...')

request = bigquery.jobs().get(

projectId=job['jobReference']['projectId'],

jobId=job['jobReference']['jobId'])

while True:

result = request.execute(num_retries=2)

if result['status']['state'] == 'DONE':

if 'errorResult' in result['status']:

raise RuntimeError(result['status']['errorResult'])

print('Job complete.')

return

time.sleep(1)

# [END poll_job]

# [START run]

def main(project_id, dataset_id, table_name, schema_file, data_path,

poll_interval, num_retries):

# [START build_service]

# Grab the application's default credentials from the environment.

credentials = GoogleCredentials.get_application_default()

# Construct the service object for interacting with the BigQuery API.

bigquery = discovery.build('bigquery', 'v2', credentials=credentials)

# [END build_service]

with open(schema_file, 'r') as f:

schema = json.load(f)

job = load_table(

bigquery,

project_id,

dataset_id,

table_name,

schema,

data_path,

num_retries)

poll_job(bigquery, job)

# [END run]

# [START main]

if __name__ == '__main__':

parser = argparse.ArgumentParser(

description=__doc__,

formatter_class=argparse.RawDescriptionHelpFormatter)

parser.add_argument('project_id', help='Your Google Cloud project ID.')

parser.add_argument('dataset_id', help='A BigQuery dataset ID.')

parser.add_argument(

'table_name', help='Name of the table to load data into.')

parser.add_argument(

'schema_file',

help='Path to a schema file describing the table schema.')

parser.add_argument(

'data_path',

help='Google Cloud Storage path to the CSV data, for example: '

'gs://mybucket/in.csv')

parser.add_argument(

'-p', '--poll_interval',

help='How often to poll the query for completion (seconds).',

type=int,

default=1)

parser.add_argument(

'-r', '--num_retries',

help='Number of times to retry in case of 500 error.',

type=int,

default=5)

args = parser.parse_args()

main(

args.project_id,

args.dataset_id,

args.table_name,

args.schema_file,

args.data_path,

args.poll_interval,

args.num_retries)

# [END main]

python-docs-samples/bigquery/api/load_data_from_csv.py at master · devlance/python-docs-samples · GitHub

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