fix(models): silence pandas silent-downcasting FutureWarning in normalize_df

[eschutho]

Decisions made that were not in the instructions

None.

Summary

Production logs emit this on every query that reaches ExploreMixin.normalize_df with an object column:

helpers.py: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. ... df.replace([np.inf, -np.inf], np.nan, inplace=True)

normalize_df replaced ±inf with NaN via df.replace(..., inplace=True), which triggers pandas' deprecated silent downcasting on object-dtype columns. This replaces it with df.mask(df.isin([np.inf, -np.inf])).infer_objects(), which emits no warning and does not touch any global pandas option.

normalize_df is the only emitter (the only ±inf replace in superset/), is defined only on ExploreMixin with no overrides, and both of its callers use the returned frame.

No behavior change: the resulting dtypes and values are identical to the previous code (object columns of floats/ints still become float64/int64; strings stay object). The one nuance is that the input frame is no longer mutated in place; both callers already use the return value.

Test plan

• Added test_normalize_df_replaces_infinity_without_downcasting_warning (fails on base with the FutureWarning promoted to an error, passes with the fix).
• pytest tests/unit_tests/models/helpers_test.py — all normalize_df tests pass. test_build_like_predicate_is_case_insensitive_and_escaped fails identically on the base commit (pre-existing, unrelated).
• ruff check / ruff format --check clean.

🤖 Generated with Claude Code

[eschutho]

@rebenitez1802 could you take a look at this one? It continues the pandas FutureWarning cleanup you reviewed in #40936, #42004 and #42272. Small change (normalize_df + one unit test). Shortcut: sc-124089.

[bito-code-review]

Code Review Agent Run #1f63e3

Actionable Suggestions - 1

• superset/models/helpers.py - 1

  • Silent dtype change on object columns · Line 2638-2638

Additional Suggestions - 1

• tests/unit_tests/models/helpers_test.py - 1

  • pandas-3 dtype assertion · Line 4151-4151
    This assertion encodes a pandas-2 assumption. Verified against the pandas 3.0.6 installed in this environment: a plain string column infers to the new `str` dtype (PDEP-14), for which `dtype == object` is False, so this test fails once the `pandas<2.4` pin (pyproject.toml:91) is lifted. `pd.api.types.is_string_dtype` is True under both majors and keeps the assertion's intent.

Review Details

• Files reviewed - 2 · Commit Range: eb76410..07747d3

  • superset/models/helpers.py
  • tests/unit_tests/models/helpers_test.py
• Files skipped - 0
• Tools

  • MyPy (Static Code Analysis) - ✔︎ Successful
  • Astral Ruff (Static Code Analysis) - ✔︎ Successful
  • Whispers (Secret Scanner) - ✔︎ Successful
  • Detect-secrets (Secret Scanner) - ✔︎ Successful

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[bito-code-review]

Silent dtype change on object columns

This changes object-column dtypes even when no ±inf is present: verified by execution, mask().infer_objects() converts object-float columns to float64 and object-string columns to str (pandas 3), while the old replace left dtypes untouched. Downstream exec_post_processing and chart serialization now see different dtypes. Prefer df.where(~df.isin([np.inf, -np.inf])), which masks without re-typing.

Code Review Run #1f63e3

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.09%. Comparing base (0fdfd66) to head (07747d3).
⚠️ Report is 4 commits behind head on master.

Additional details and impacted files

@@           Coverage Diff           @@
##           master   #44897   +/-   ##
=======================================
  Coverage   82.09%   82.09%           
=======================================
  Files        2995     2995           
  Lines      184988   184988           
  Branches    42814    42814           
=======================================
  Hits       151872   151872           
  Misses      30357    30357           
  Partials     2759     2759           

Flag	Coverage Δ
hive	36.30% <0.00%> (ø)
mysql	55.34% <100.00%> (+<0.01%)	⬆️
postgres	55.35% <100.00%> (+<0.01%)	⬆️
presto	38.18% <100.00%> (ø)
python	86.12% <100.00%> (ø)
sqlite	55.07% <100.00%> (ø)
unit	79.09% <100.00%> (ø)

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[rebenitez1802]

Approve: no actionable issues found. Independent reviews confirmed behavior on pinned pandas 2.3.3; isolated regression assertions passed. Full pytest validation was blocked by a local cache dependency error during initialization.