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        "author": "Ryan Liao",
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        "description": "# BigQuery-GCS\r\n[![Build Status](https://travis-ci.org/pirsquare/BigQuery-GCS.svg?branch=master)](https://travis-ci.org/pirsquare/BigQuery-GCS)\r\nDealing with large query results isn't so [straightforward in BigQuery](https://cloud.google.com/bigquery/querying-data#largequeryresults) . This library provides wrapper to help you execute query with large results and export it to Goolge Cloud Storage for ease of accessibility.\r\n\r\n1. Run your query.\r\n2. Output results to a temporary table.\r\n3. Export temporary table data to GCS.\r\n4. Delete temporary table.\r\n\r\n## Installation\r\n\r\n    pip install bigquery-gcs\r\n\r\n## Examples\r\n```python\r\nfrom bigquery_gcs import Exporter\r\n\r\nconfig = {\r\n    'GCS_ACCESS_KEY': \"YOUR_GCS_ACCESS_KEY\",\r\n    'GCS_SECRET_KEY': \"YOUR_GCS_SECRET_KEY\",\r\n    'GCS_BUCKET_NAME': \"YOUR_GCS_BUCKET_NAME\",\r\n\r\n    'BQ_PROJECT_ID': \"YOUR_BQ_PROJECT_ID\",\r\n    'BQ_SERVICE_ACCOUNT': \"YOUR_BQ_SERVICE_ACCOUNT\",\r\n    'BQ_PRIVATE_KEY_PATH': \"YOUR_BQ_PRIVATE_KEY_PATH\",\r\n    'BQ_DEFAULT_QUERY_TIMEOUT': 86400,  # 24 hours\r\n    'BQ_DEFAULT_EXPORT_TIMEOUT': 86400,  # 24 hours\r\n}\r\n\r\nexporter = Exporter(config)\r\n\r\nquery = \"SELECT word FROM [publicdata:samples.shakespeare] LIMIT 1000\"\r\ndataset_temp = \"temp\"\r\ntable_temp = \"shakespeare_word\"\r\nfolder_name = \"shakespeare\" # This is your GCS folder to store result files\r\nfile_name = \"shakespeare_word\" # Name for exported file in GCS\r\n\r\n# This will run query and export results to GCS\r\nexporter.query_and_export(query, dataset_temp, table_temp, folder_name, file_name)\r\n```\r\n\r\n",
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