Google BigQuery API client library
Project description
Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL queries against append-mostly tables, using the processing power of Google’s infrastructure.
Quick Start
In order to use this library, you first need to go through the following steps:
Installation
Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.
With virtualenv, it’s possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.
Supported Python Versions
Python >= 3.5
Deprecated Python Versions
Python == 2.7. Python 2.7 support will be removed on January 1, 2020.
Mac/Linux
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-bigqueryWindows
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-bigqueryExample Usage
Perform a query
from google.cloud import bigquery
client = bigquery.Client()
# 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)Release history Release notifications | RSS feed
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