google-cloud-bigquery 0.32.0

Google BigQuery API client library

Python idiomatic client for Google BigQuery

• Documentation

Quick Start

$ pip install --upgrade google-cloud-bigquery

For more information on setting up your Python development environment, such as installing pip and virtualenv on your system, please refer to Python Development Environment Setup Guide for Google Cloud Platform.

Authentication

With google-cloud-python we try to make authentication as painless as possible. Check out the Authentication section in our documentation to learn more. You may also find the authentication document shared by all the google-cloud-* libraries to be helpful.

Using the API

Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery (BigQuery API docs) solves this problem by enabling super-fast, SQL queries against append-mostly tables, using the processing power of Google’s infrastructure.

Create a dataset

from google.cloud import bigquery
from google.cloud.bigquery import Dataset

client = bigquery.Client()

dataset_ref = client.dataset('dataset_name')
dataset = Dataset(dataset_ref)
dataset.description = 'my dataset'
dataset = client.create_dataset(dataset)  # API request

Load data from CSV

import csv

from google.cloud import bigquery
from google.cloud.bigquery import LoadJobConfig
from google.cloud.bigquery import SchemaField

client = bigquery.Client()

SCHEMA = [
    SchemaField('full_name', 'STRING', mode='required'),
    SchemaField('age', 'INTEGER', mode='required'),
]
table_ref = client.dataset('dataset_name').table('table_name')

load_config = LoadJobConfig()
load_config.skip_leading_rows = 1
load_config.schema = SCHEMA

# Contents of csv_file.csv:
#     Name,Age
#     Tim,99
with open('csv_file.csv', 'rb') as readable:
    client.load_table_from_file(
        readable, table_ref, job_config=load_config)  # API request

Perform a query

# Perform a query.
QUERY = (
    'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
    'WHERE state = "TX" '
    'LIMIT 100')
query_job = client.query(QUERY)  # API request
rows = query_job.result()  # Waits for query to finish

for row in rows:
    print(row.name)

See the google-cloud-python API BigQuery documentation to learn how to connect to BigQuery using this Client Library.