Fix pandas 3.0 compatibility issues with MicroSeries method access #276
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The previous approach of modifying `__class__` on DataFrame columns no longer works in pandas 3.0 due to Copy-on-Write behavior. Each column access returns a new copy, so class modifications don't persist. This fix changes the strategy: - `__getitem__` now wraps all Series results as MicroSeries on access - Removed the broken `_link_weights` and `catch_series_relapse` logic - Simplified `_link_all_weights` since columns are wrapped on access This resolves the "AttributeError: 'Series' object has no attribute 'set_weights'" error that occurred when using MicroDataFrame with pandas 3.0. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This test specifically verifies the fix for the issue where `mdf["column"].set_weights()` would fail with AttributeError in pandas 3.0 with Copy-on-Write enabled, because each column access returned a new copy instead of the wrapped MicroSeries. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Summary
__class__on DataFrame columns no longer works due to Copy-on-Write behavior in pandas 3.0__getitem__wraps all Series results as MicroSeries on access, rather than trying to modify columns in-place_link_weightsandcatch_series_relapselogic that relied on class mutationTest plan
set_weights()are accessible after DataFrame column accessFixes the "AttributeError: 'Series' object has no attribute 'set_weights'" error that was occurring in policyengine-uk tests with pandas 3.0.
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