feat(bigframes): Add numpy ufunc support to col expressions

[TrevorBergeron]

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Fixes #<issue_number_goes_here> 🦕

[gemini-code-assist]

Code Review

This pull request introduces support for NumPy universal functions (ufuncs) in BigFrames by implementing the __array_ufunc__ method in the Expression class. It also refactors binary operation logic into a helper function _as_bf_expr and adds unit tests to verify the new functionality. Feedback was provided regarding the use of a non-standard type hint for the method parameter and an issue in the unit tests where non-standard pandas API calls were used to compute expected results.

[gemini-code-assist]

Using __builtins__.str as a type hint is non-standard and potentially fragile. It is recommended to use the built-in str type directly.

Suggested change

	self, ufunc: numpy.ufunc, method: __builtins__.str, *inputs, **kwargs
	self, ufunc: numpy.ufunc, method: str, *inputs, **kwargs

References

1. Standard Python type hinting practices (PEP 484) recommend using built-in types like 'str' directly instead of accessing them through 'builtins'. ^(link)

[gemini-code-assist]

The pd_kwargs dictionary uses pd.col, which is not a standard pandas API. To correctly verify the BigFrames implementation against pandas, the expected results should be computed using standard pandas column access on scalars_pandas_df. Additionally, standard pandas assign does not support BigFrames Expression objects. To ensure dictionary keys remain sorted without manual effort, the dictionary should be programmatically sorted.

Suggested change

	pd_kwargs = {
	"sqrt": np.sqrt(pd.col("float64_col")), # type: ignore
	"add_const": np.add(pd.col("float64_col"), 2.4), # type: ignore
	"radd_const": np.add(2.4, pd.col("float64_col")), # type: ignore
	"add_cols": np.add(pd.col("float64_col"), pd.col("int64_col")), # type: ignore
	}
	pd_kwargs = dict(sorted({
	"sqrt": np.sqrt(scalars_pandas_df["float64_col"]),
	"add_const": np.add(scalars_pandas_df["float64_col"], 2.4),
	"radd_const": np.add(2.4, scalars_pandas_df["float64_col"]),
	"add_cols": np.add(scalars_pandas_df["float64_col"], scalars_pandas_df["int64_col"]),
	}.items()))

References

1. To ensure dictionary keys remain sorted without manual effort, programmatically sort the dictionary instead of relying on manual ordering in the code.