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Here is the summary of changes. You are about to add 1 region tag.
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This pull request introduces a new Python sample script and corresponding unit tests for querying a BigLake table backed by Cloud Storage using GoogleSQL. It also adds the necessary configuration and dependency files. The feedback recommends updating the noxfile_config.py to ensure only the oldest and newest supported Python versions (3.10 and 3.13) are tested, in accordance with repository guidelines.
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| TEST_CONFIG_OVERRIDE = { | ||
| # You can opt out from the test for specific Python versions. | ||
| "ignored_versions": ["2.7", "3.7", "3.8", "3.9", "3.10", "3.11"], |
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According to the repository guidelines, test configurations should only test the oldest and newest supported Python releases, while ignoring intermediate versions. Since the oldest supported version is Python 3.10 (as specified in requirements-test.txt), it should not be ignored. Instead, we should ignore the intermediate versions (3.11 and 3.12) and test 3.10 and 3.13.
| "ignored_versions": ["2.7", "3.7", "3.8", "3.9", "3.10", "3.11"], | |
| "ignored_versions": ["2.7", "3.7", "3.8", "3.9", "3.11", "3.12"], |
References
- Only test the oldest and newest supported Python releases in test configurations (such as noxfile_config.py), ignoring intermediate versions.
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…a permanent BigLake table on Cloud Storage Problem: The BigQuery documentation (https://cloud.google.com/bigquery/docs/query-cloud-storage-using-biglake) needs a standalone, tested Python code sample demonstrating how to query a permanent BigLake table on Cloud Storage (region tag `bigquery_query_biglake_gcs_table`). Solution: - Add `query_biglake_gcs_table(project_id: str, dataset_id: str, table_id: str) -> None` in `bigquery/biglake/bigquery_query_biglake_gcs_table.py` (Query structured files stored in Cloud Storage through a permanent BigLake table backed by a Cloud Resource connection.) - Add unit tests (`bigquery/biglake/bigquery_query_biglake_gcs_table_test.py`) covering both the success path and API error handling (`GoogleAPICallError`)
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i just realized i was taking a look at cloud storage and not bigquery storage when reviewing the other PRs. Double checked, this is the correct version for bigquery storage.
…a permanent BigLake table on Cloud Storage
Problem:
The BigQuery documentation (https://cloud.google.com/bigquery/docs/query-cloud-storage-using-biglake) needs a standalone, tested Python code sample demonstrating how to query a permanent BigLake table on Cloud Storage (region tag
bigquery_query_biglake_gcs_table).Solution:
query_biglake_gcs_table(project_id: str, dataset_id: str, table_id: str) -> Noneinbigquery/biglake/bigquery_query_biglake_gcs_table.py(Query structured files stored in Cloud Storage through a permanent BigLake table backed by a Cloud Resource connection.)bigquery/biglake/bigquery_query_biglake_gcs_table_test.py) covering both the success path and API error handling (GoogleAPICallError)Description
Fixes #
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Testing
Compliance & Style
Post-Approval Actions