Improve performance of `commented-out-code` (~50-80%) (#7706)
## Summary
This PR implements a variety of optimizations to improve performance of
the Eradicate rule, which always shows up in all-rules benchmarks and
bothers me. (These improvements are not hugely important, but it was
kind of a fun Friday thing to spent a bit of time on.)
The improvements include:
- Doing cheaper work first (checking for some explicit substrings
upfront).
- Using `aho-corasick` to speed an exact substring search.
- Merging multiple regular expressions using a `RegexSet`.
- Removing some unnecessary `\s*` and other pieces from the regular
expressions (since we already trim strings before matching on them).
## Test Plan
I benchmarked this function in a standalone crate using a variety of
cases. Criterion reports that this version is up to 80% faster, and
almost every case is at least 50% faster:
```
Eradicate/Detection/# Warn if we are installing over top of an existing installation. This can
time: [101.84 ns 102.32 ns 102.82 ns]
change: [-77.166% -77.062% -76.943%] (p = 0.00 < 0.05)
Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
3 (3.00%) high mild
Eradicate/Detection/#from foo import eradicate
time: [74.872 ns 75.096 ns 75.314 ns]
change: [-84.180% -84.131% -84.079%] (p = 0.00 < 0.05)
Performance has improved.
Found 1 outliers among 100 measurements (1.00%)
1 (1.00%) high mild
Eradicate/Detection/# encoding: utf8
time: [46.522 ns 46.862 ns 47.237 ns]
change: [-29.408% -28.918% -28.471%] (p = 0.00 < 0.05)
Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
6 (6.00%) high mild
1 (1.00%) high severe
Eradicate/Detection/# Issue #999
time: [16.942 ns 16.994 ns 17.058 ns]
change: [-57.243% -57.064% -56.815%] (p = 0.00 < 0.05)
Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
2 (2.00%) high mild
1 (1.00%) high severe
Eradicate/Detection/# type: ignore
time: [43.074 ns 43.163 ns 43.262 ns]
change: [-17.614% -17.390% -17.152%] (p = 0.00 < 0.05)
Performance has improved.
Found 5 outliers among 100 measurements (5.00%)
3 (3.00%) high mild
2 (2.00%) high severe
Eradicate/Detection/# user_content_type, _ = TimelineEvent.objects.using(db_alias).get_or_create(
time: [209.40 ns 209.81 ns 210.23 ns]
change: [-32.806% -32.630% -32.470%] (p = 0.00 < 0.05)
Performance has improved.
Eradicate/Detection/# this is = to that :(
time: [72.659 ns 73.068 ns 73.473 ns]
change: [-68.884% -68.775% -68.655%] (p = 0.00 < 0.05)
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
7 (7.00%) high mild
2 (2.00%) high severe
Eradicate/Detection/#except Exception:
time: [92.063 ns 92.366 ns 92.691 ns]
change: [-64.204% -64.052% -63.909%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
2 (2.00%) high mild
2 (2.00%) high severe
Eradicate/Detection/#print(1)
time: [68.359 ns 68.537 ns 68.725 ns]
change: [-72.424% -72.356% -72.278%] (p = 0.00 < 0.05)
Performance has improved.
Found 2 outliers among 100 measurements (2.00%)
1 (1.00%) low mild
1 (1.00%) high mild
Eradicate/Detection/#'key': 1 + 1,
time: [79.604 ns 79.865 ns 80.135 ns]
change: [-69.787% -69.667% -69.549%] (p = 0.00 < 0.05)
Performance has improved.
```
