This library was intended to address limitations of the core tool that have since been resolved. We now recommend that you use the google-cloud-bigquery instead.

Summary

BigQuery_Helper is a helper class to simplify common read-only BigQuery tasks. It makes it easy to execute queries while you're learning SQL, and provides a convenient stepping stone on the path to using the core BigQuery python API. You can try it for yourself by forking this Kaggle kernel.

Installation

You can install BigQuery_Helper with the following command in your console:

pip install -e git+https://github.com/SohierDane/BigQuery_Helper#egg=bq_helper

If you aren't running BigQuery_Helper on Kaggle, you will also need to go through the standard BigQuery client setup and authentication process.

This repo has only been tested on Python 3.6+ and the v0.29+ of the bigquery API.

Changelog

0.4.0:

• BigQueryHelper.table_schema has been overhauled. It now returns a Pandas DataFrame and unrolls nested fields so that the results are in the format expected by queries. For example, the github_repos.commits nested field author now returns sub-fields names in the format like author.email.

0.3.0:

• Each helper instance now logs the total bytes counted towards your quota or bill used across all queries run with that helper instance. You can access it with BigQueryHelper.total_gb_used_net_cache. Repeated queries are likely to hit the cache and may show up as 0 GB used.
• Queries that take longer than the maximum wait time, which defaults to 3 minutes, will be cancelled.
• Contributing to bq_helper should be easier now that there is a set of tests.

0.2.0:

• query_to_pandas now returns an empty DataFrame when the query returns no results. Previously, this returned None.