Confine repeated-equality-comparison-target to names and attributes

[charliermarsh]

Empirically, Pylint does this, so seems reasonable to follow.

[github-actions]

PR Check Results

Ecosystem

ℹ️ ecosystem check detected changes. (+0, -19, 0 error(s))

airflow (+0, -14)

- airflow/providers/common/sql/operators/sql.py:973:16: PLR1714 Consider merging multiple comparisons: `0 in (cur, ref)`. Use a `set` if the elements are hashable.
- airflow/providers/databricks/hooks/databricks_base.py:498:16: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- airflow/providers/databricks/hooks/databricks_base.py:507:16: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- airflow/providers/databricks/hooks/databricks_base.py:526:16: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- airflow/providers/databricks/hooks/databricks_base.py:535:16: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/hooks/bigquery.py:3281:16: PLR1714 Consider merging multiple comparisons: `0 in (cur, ref)`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/operators/bigquery_dts.py:395:12: PLR1714 Consider merging multiple comparisons: `event["status"] in ("failed", "cancelled")`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/operators/dataflow.py:709:12: PLR1714 Consider merging multiple comparisons: `event["status"] in ("error", "stopped")`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/operators/dataflow.py:894:12: PLR1714 Consider merging multiple comparisons: `event["status"] in ("error", "stopped")`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/operators/dataproc.py:1861:12: PLR1714 Consider merging multiple comparisons: `event["status"] in ("failed", "error")`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/operators/dataproc.py:1992:12: PLR1714 Consider merging multiple comparisons: `event["status"] in ("failed", "error")`. Use a `set` if the elements are hashable.
- airflow/providers/google/cloud/triggers/bigquery.py:358:22: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- tests/providers/celery/executors/test_celery_executor.py:179:24: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.
- tests/providers/google/cloud/operators/test_bigquery.py:1970:16: PLR1714 Consider merging multiple comparisons. Use a `set` if the elements are hashable.

bokeh (+0, -2)

- src/bokeh/io/export.py:126:8: PLR1714 Consider merging multiple comparisons: `0 in (image.width, image.height)`. Use a `set` if the elements are hashable.
- src/bokeh/layouts.py:450:20: PLR1714 Consider merging multiple comparisons: `0 not in (child.nrows, child.ncols)`. Use a `set` if the elements are hashable.

zulip (+0, -3)

- zerver/forms.py:96:8: PLR1714 Consider merging multiple comparisons: `"-" in (subdomain[0], subdomain[-1])`. Use a `set` if the elements are hashable.
- zerver/lib/domains.py:15:8: PLR1714 Consider merging multiple comparisons: `"." in (domain[0], domain[-1])`. Use a `set` if the elements are hashable.
- zerver/lib/domains.py:20:12: PLR1714 Consider merging multiple comparisons: `"-" in (subdomain[0], subdomain[-1])`. Use a `set` if the elements are hashable.

Rules changed: 1

Rule	Changes	Additions	Removals
PLR1714	19	0	19

Benchmark

Linux

group                                      main                                   pr
-----                                      ----                                   --
formatter/large/dataset.py                 1.00      3.4±0.02ms    12.1 MB/sec    1.00      3.4±0.01ms    12.0 MB/sec
formatter/numpy/ctypeslib.py               1.00    714.6±2.47µs    23.3 MB/sec    1.00    714.6±4.84µs    23.3 MB/sec
formatter/numpy/globals.py                 1.00     76.8±0.29µs    38.4 MB/sec    1.00     76.8±0.30µs    38.4 MB/sec
formatter/pydantic/types.py                1.01  1402.1±21.51µs    18.2 MB/sec    1.00  1388.4±31.58µs    18.4 MB/sec
linter/all-rules/large/dataset.py          1.00     10.1±0.01ms     4.0 MB/sec    1.06     10.7±0.05ms     3.8 MB/sec
linter/all-rules/numpy/ctypeslib.py        1.00      2.7±0.00ms     6.1 MB/sec    1.03      2.8±0.01ms     5.9 MB/sec
linter/all-rules/numpy/globals.py          1.00    384.2±0.62µs     7.7 MB/sec    1.01    389.0±0.38µs     7.6 MB/sec
linter/all-rules/pydantic/types.py         1.00      5.3±0.03ms     4.8 MB/sec    1.04      5.5±0.03ms     4.7 MB/sec
linter/default-rules/large/dataset.py      1.00      5.4±0.02ms     7.5 MB/sec    1.09      5.9±0.01ms     6.9 MB/sec
linter/default-rules/numpy/ctypeslib.py    1.00   1196.0±0.94µs    13.9 MB/sec    1.07   1274.4±3.87µs    13.1 MB/sec
linter/default-rules/numpy/globals.py      1.00    137.5±0.27µs    21.5 MB/sec    1.04    143.1±0.80µs    20.6 MB/sec
linter/default-rules/pydantic/types.py     1.00      2.5±0.01ms    10.4 MB/sec    1.07      2.6±0.01ms     9.7 MB/sec

Windows

group                                      main                                    pr
-----                                      ----                                    --
formatter/large/dataset.py                 1.00      3.7±0.05ms    11.0 MB/sec     1.01      3.7±0.06ms    10.9 MB/sec
formatter/numpy/ctypeslib.py               1.00   758.1±11.85µs    22.0 MB/sec     1.01   762.1±18.20µs    21.8 MB/sec
formatter/numpy/globals.py                 1.00     79.0±2.69µs    37.4 MB/sec     1.02     80.6±3.01µs    36.6 MB/sec
formatter/pydantic/types.py                1.00  1537.1±57.70µs    16.6 MB/sec     1.00  1533.5±25.20µs    16.6 MB/sec
linter/all-rules/large/dataset.py          1.02     12.7±0.15ms     3.2 MB/sec     1.00     12.5±0.14ms     3.3 MB/sec
linter/all-rules/numpy/ctypeslib.py        1.00      3.4±0.04ms     4.8 MB/sec     1.00      3.4±0.03ms     4.9 MB/sec
linter/all-rules/numpy/globals.py          1.01    432.5±6.35µs     6.8 MB/sec     1.00    429.8±5.03µs     6.9 MB/sec
linter/all-rules/pydantic/types.py         1.02      6.6±0.11ms     3.8 MB/sec     1.00      6.5±0.07ms     3.9 MB/sec
linter/default-rules/large/dataset.py      1.00      7.0±0.12ms     5.8 MB/sec     1.01      7.1±0.11ms     5.7 MB/sec
linter/default-rules/numpy/ctypeslib.py    1.02  1543.1±146.71µs    10.8 MB/sec    1.00  1509.0±23.04µs    11.0 MB/sec
linter/default-rules/numpy/globals.py      1.00    174.0±3.29µs    17.0 MB/sec     1.00    173.4±3.71µs    17.0 MB/sec
linter/default-rules/pydantic/types.py     1.01      3.2±0.04ms     8.0 MB/sec     1.00      3.2±0.06ms     8.0 MB/sec