SNOW-1348700 Fix to_char's implementation when incoming column has inconsecutive row index #1702
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CHANGELOG.md
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| ## 1.18.1 (TBD) | ||
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| ### Snowpark Python API Updates | ||
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| #### New Features | ||
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| #### Improvements | ||
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| ### Snowpark pandas API Updates | ||
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| #### New Features | ||
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| #### Improvements | ||
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| #### Bug Fixes | ||
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| ### Snowpark Local Testing Updates | ||
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| #### Breaking changes | ||
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| ### New Features | ||
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| #### Bug Fixes | ||
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| - Fixed a bug in mock implementation of `to_char` that raises `IndexError` when incoming column has inconsecutive row index. | ||
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| #### Improvements | ||
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nit: there is a 1.19.0 section now
| @@ -1027,7 +1025,7 @@ def convert_char(row): | |||
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| # row index information is needed to retrieve format information in another pd series, thus calling to_frame here | |||
| res = column.to_frame().apply(convert_char, axis=1) | |||
| res = column.combine(fmt, convert_char) | |||
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_to_timestamp implementation also uses column.to_frame(), should we fix that as well?
I'm good with either fixing in this PR or having another PR.
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I have created #1740.
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Which Jira issue is this PR addressing? Make sure that there is an accompanying issue to your PR.
Fixes SNOW-1348700
Fill out the following pre-review checklist:
Please describe how your code solves the related issue.
Previously the implementation of mock_to_char relies on the incoming column has index of [0,1,...,n-1], this is not always true and causes the code raise
IndexError, this PR fixes that and adds a test for this specific scenario.