Summary

Generally, comparisons to True, False, and None singletons should use obj is True instead of obj == True.

However, it is common for libraries to override the ==/__eq__ operator to create simple APIs for filtering data. In these cases, correcting == to is changes the meaning of the program and breaks the user's code. The same applies for != and is not.

This is a tracking issue for all invalid corrections from this rule.

Types with the issue

• pandas.DataFrame often used with DataFrame.mask, DataFrame.where
• pandas.Series often used with Series.mask, Series.where
• numpy.Array often used with Array.where
• sqlalchemy.Column often used with Query.having, Query.filter, Query.where

If an issue with an unlisted type is encountered please reply and I will edit to add it here.

Resolution

Eventually, ruff is likely to detect these cases by inferring the datatype involved and exclude it from the suggested fix.

In the meantime, you may:

• Disable rule E712
• Use an alternative comparison method that is not ambiguous (e.g. pandas.Series.eq)

Examples

import numpy

numpy.array([True, False]) == False
# array([False,  True])

numpy.array([True, False]) is False
# False

import pandas

pandas.Series([True, False]) == False
# 0    False
# 1    True
# dtype: bool

pandas.Series([True, False]) is False
# False

# Alternative safe syntax
pandas.Series([True, False]).eq(False)

pandas.DataFrame({"x": [True, False]}) == False
#       x
# 0  False
# 1  True

pandas.DataFrame({"x": [True, False]}) is False
# False

# Alternative safe syntax
pandas.DataFrame({"x": [True, False]}).eq(False)

import sqlalchemy
c = sqlalchemy.Column("foo", sqlalchemy.Boolean)

c == True
# <sqlalchemy.sql.elements.BinaryExpression object at 0x12ed532e0>

c is True
# False

# Alternative safe syntax
c.is_(True)
c.is_not(False)

Related issues

• [ruff --fix] (v0.0.239) When working with numpy arrays mask == True is not the same as mask is True #2443
• E712 (Comparison to True should be cond is True) should be ignored when comparison is against pandas.Series #1852
• E712 : Wrong fix suggested in presence of numpy.bool_ #4356