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#!/usr/bin/env python
# Copyright 2015, Google, Inc.
# 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.rst.
import argparse
import json
import time
import uuid
import googleapiclient.discovery
# [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
        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]
    # Construct the service object for interacting with the BigQuery API.
    bigquery = googleapiclient.discovery.build('bigquery', 'v2')
    # [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()
        args.project_id,
        args.dataset_id,
        args.table_name,
        args.schema_file,
        args.data_path,
        args.poll_interval,
        args.num_retries)
# [END main]
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