fix(deps): support pandas 3.0 (prerelease) #998
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Summary of ChangesHello @tswast, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request primarily focuses on updating the project's dependency configuration to support the upcoming pandas 3.0 release. This involves removing an outdated version constraint for pandas and making minor, targeted adjustments to existing test cases to ensure compatibility with changes in pandas' handling of missing data and specific BigQuery date parsing behaviors. Highlights
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Code Review
This pull request updates the pandas dependency to allow for version 3.0 by removing the upper version constraint. The accompanying changes in the system tests, which involve updating the representation of missing values to pandas.NA and adjusting a datetime test value, appear to be necessary for compatibility with the newer pandas version. Overall, the changes look good, but I have one suggestion to clarify a comment in the test suite for better maintainability.
| # CSV loader in BigQuery currently requires leading 0s | ||
| # for TIMESTAMP but not DATETIME. See internal issue | ||
| # b/467399807. | ||
| datetime.datetime(1000, 1, 1), |
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The comment on lines 347-349 is a bit confusing. It states that the CSV loader's requirement for leading zeros applies to TIMESTAMP but not DATETIME. However, this change is made to datetime_col, which is defined as a DATETIME column in the table schema on line 374. Could you please clarify why this change is needed for a DATETIME column, or update the comment for future reference? This would help maintainers understand the reason for this specific test value.
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Correct. I use year >= 1000 so that no leading zeros are required.
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Local tests pass with pandas 3.0.0rc0. Details |
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Fixes #<issue_number_goes_here> 🦕