Support mutually exclusive branches for B031

[dhruvmanila]

fixes: #3801

[github-actions]

PR Check Results

Ecosystem

✅ ecosystem check detected no changes.

Benchmark

Linux

group                                      main                                   pr
-----                                      ----                                   --
linter/all-rules/large/dataset.py          1.04     15.2±0.18ms     2.7 MB/sec    1.00     14.6±0.05ms     2.8 MB/sec
linter/all-rules/numpy/ctypeslib.py        1.01      3.8±0.01ms     4.4 MB/sec    1.00      3.8±0.01ms     4.4 MB/sec
linter/all-rules/numpy/globals.py          1.00    409.8±1.84µs     7.2 MB/sec    1.01    415.6±1.81µs     7.1 MB/sec
linter/all-rules/pydantic/types.py         1.02      6.5±0.03ms     3.9 MB/sec    1.00      6.4±0.06ms     4.0 MB/sec
linter/default-rules/large/dataset.py      1.01      7.9±0.02ms     5.2 MB/sec    1.00      7.8±0.03ms     5.2 MB/sec
linter/default-rules/numpy/ctypeslib.py    1.00   1736.6±7.11µs     9.6 MB/sec    1.01   1750.4±2.65µs     9.5 MB/sec
linter/default-rules/numpy/globals.py      1.00    181.2±0.89µs    16.3 MB/sec    1.01    183.2±0.50µs    16.1 MB/sec
linter/default-rules/pydantic/types.py     1.00      3.6±0.00ms     7.0 MB/sec    1.00      3.6±0.01ms     7.0 MB/sec

Windows

group                                      main                                   pr
-----                                      ----                                   --
linter/all-rules/large/dataset.py          1.02     16.1±0.14ms     2.5 MB/sec    1.00     15.7±0.17ms     2.6 MB/sec
linter/all-rules/numpy/ctypeslib.py        1.01      4.1±0.05ms     4.0 MB/sec    1.00      4.1±0.05ms     4.1 MB/sec
linter/all-rules/numpy/globals.py          1.00    495.5±7.28µs     6.0 MB/sec    1.01    499.2±7.28µs     5.9 MB/sec
linter/all-rules/pydantic/types.py         1.01      6.8±0.09ms     3.7 MB/sec    1.00      6.7±0.12ms     3.8 MB/sec
linter/default-rules/large/dataset.py      1.01      8.2±0.06ms     4.9 MB/sec    1.00      8.2±0.07ms     5.0 MB/sec
linter/default-rules/numpy/ctypeslib.py    1.01  1802.4±20.99µs     9.2 MB/sec    1.00  1791.8±17.55µs     9.3 MB/sec
linter/default-rules/numpy/globals.py      1.02    196.4±7.92µs    15.0 MB/sec    1.00    192.9±5.07µs    15.3 MB/sec
linter/default-rules/pydantic/types.py     1.00      3.8±0.07ms     6.8 MB/sec    1.00      3.7±0.04ms     6.8 MB/sec

[JonathanPlasse]

The recursive case is not handled correctly.

for _section, section_items in itertools.groupby(items, key=lambda p: p[1]):
    # Mutually exclusive branches shouldn't trigger the warning
    if _section == "greens":
        collect_shop_items(shopper, section_items)
        if _section == "greens":
            collect_shop_items(shopper, section_items)  # B031 false negative
        elif _section == "frozen items":
            collect_shop_items(shopper, section_items)  # B031 false negative
        else:
            collect_shop_items(shopper, section_items)  # B031 false negative
    elif _section == "frozen items":
        collect_shop_items(shopper, section_items)  # B031 false positive
    else:
        collect_shop_items(shopper, section_items)  # B031 false positive
    # Now, it should detect
    collect_shop_items(shopper, section_items)  # B031

[dhruvmanila]

I'll give an explanation of the logic behind this in a couple of hours.

[dhruvmanila]

Using the stack model:

A new stack element is pushed for every mutually exclusive statement (if/match statement, not elif/else/case) statements. This stack element is Vec<u8> where each number represents the count of group in individual branch. They're in the same order as that of branches or case blocks in case of match statements.

Once we're out of a mutually exclusive statement, the final count will be the max value from every branch/case. This will be added to either the parent statement or the global count if there isn't any.

[charliermarsh]

Thank you! I continue to be so impressed by your contributions, really appreciate your help improving Ruff.

[dhruvmanila]

Thank you! I continue to be so impressed by your contributions, really appreciate your help improving Ruff.

Hey, thanks! I really enjoy contributing to the project :)