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* origin/develop: (102 commits) [DOCS] restore lychee (#10889) [RELEASE] 1.3.3 (#10888) [DOCS] add migration guide to 0.18 docs (#10885) [MAINTENANCE] Migrate from `databricks-sql-connector` to `databricks-sqlalchemy` in tests (#10886) [BUGFIX] Allow adding Expectations with identical attributes to Suites (#10884) [DOCS] Corrections and clarifications for result_format (#10875) [BUGFIX] Make validation results' describe_dict return a serializable dict (#10863) [MAINTENANCE] Convert BatchTestSetup.asset property to BatchTestSetup… (#10864) [MAINTENANCE] Add method to set analytics user_agent_str (#10883) [DOCS] Update documentation around batch_parameters and link to updated API docs. (#10877) [MAINTENANCE] Add user-agent-str to analytics events (#10869) [RELEASE] 1.3.2 (#10874) [DOCS] Add titles to properties and methods sections in API Reference (#10821) [MAINTENANCE] Handle `aws-chunked` encoding type data in `TupleS3StoreBackend` (#10861) [Docs] update screenshot of observed value (#10867) [MAINTENANCE] Enforce a minimum length of 2 for MulticolumnMapExpectation `column_list` (#10850) [BUGFIX] Add input args validators to various Expectations (#10833) [DOCS] fix custom SQL Expectation approach for cloud (#10844) [FEATURE] Enable strict_min/max for ExpectTableRowCountToBeBetween (#10845) [DOCS] Adding keys to duplicated headers (#10846) ...
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# Script(s) to clean up any loose data left behind from test runs. | ||
# These can primarily happen if CI is stopped while tests are running | ||
# for big query, etc. | ||
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name: Nightly Data Source Cleanup | ||
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on: | ||
workflow_dispatch: | ||
schedule: | ||
- cron: "0 6 * * *" | ||
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jobs: | ||
cleanup-big-query: | ||
runs-on: ubuntu-latest | ||
env: | ||
GE_TEST_GCP_CREDENTIALS: ${{secrets.GE_TEST_GCP_CREDENTIALS}} | ||
GE_TEST_GCP_PROJECT: ${{secrets.GE_TEST_GCP_PROJECT}} | ||
GE_TEST_BIGQUERY_DATASET: ${{secrets.GE_TEST_BIGQUERY_DATASET}} | ||
GOOGLE_APPLICATION_CREDENTIALS: "gcp-credentials.json" | ||
steps: | ||
- name: Checkout | ||
uses: actions/checkout@v4 | ||
- name: Set up Python | ||
uses: actions/setup-python@v5 | ||
with: | ||
python-version: "3.12" | ||
cache: "pip" | ||
cache-dependency-path: | | ||
reqs/requirements-dev-test.txt | ||
setup.py | ||
- name: Create JSON file GCP | ||
run: | | ||
echo "$GE_TEST_GCP_CREDENTIALS" > gcp-credentials.json | ||
- name: Install dependencies | ||
run: | | ||
pip install $(grep -E '^(invoke)' reqs/requirements-dev-contrib.txt) | ||
invoke deps --gx-install -m bigquery | ||
pip install -e . | ||
- name: Run BigQuery cleanup script | ||
run: | | ||
python ./scripts/cleanup/cleanup_big_query.py |
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assets/scripts/gx_cloud/experimental/onboarding_script.py
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# 5. Docstrings for public API functions/classes | ||
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Date: 2024-12-19 | ||
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## Status | ||
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Accepted | ||
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## Context | ||
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By marking an object as part of the public API, it automatically renders in our docs site. In order to provide a clear and informative experience for our end users, we should make sure we always include docstrings for public functions/classes. These docstrings should adhere to a consistent format such that they can be rendered in the same manner by our public API infrastructure. | ||
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## Decision | ||
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All objects decorated with `@public_api` will have docstrings. In order to be considered public, they must meet this criteria. | ||
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## Consequences | ||
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Marginal increase in developer burden but worthwhile due to a higher level of thought and care around what actually gets marked and rendered as part of our public API. |
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