Python idiomatic client for Google BigQuery
Quick Start
$ pip install --upgrade google-cloud-bigqueryFor 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 requestLoad 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 requestPerform 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.
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