Use `memchr` in SRE's prefix scanner
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- Python
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Description
Feature or enhancement
Proposal:
Python's regex prefix scanning loops advance one byte at a time to find the first character of a literal prefix. For SIZEOF_SRE_CHAR == 1, memchr is a drop-in replacement that uses SIMD. The idea is to skip say 32 bytes per iteration in the negative case (no match).
The two loops are at
Similar issues/prs are gh-145797 (memchr in str.split) and building on gh-57343, gh-57345.
Proposed patch:
--- a/Modules/_sre/sre_lib.h
+++ b/Modules/_sre/sre_lib.h
@@ -1753,10 +1753,19 @@
end = (SRE_CHAR *)state->end;
state->must_advance = 0;
while (ptr < end) {
+#if SIZEOF_SRE_CHAR == 1
+ {
+ SRE_CHAR *found = memchr(ptr, c, end - ptr);
+ if (!found)
+ return 0;
+ ptr = found;
+ }
+#else
while (*ptr != c) {
if (++ptr >= end)
return 0;
}
+#endif
TRACE(("|%p|%p|SEARCH LITERAL\n", pattern, ptr));
state->start = ptr;
@@ -1786,10 +1795,19 @@
while (ptr < end) {
SRE_CHAR c = (SRE_CHAR) prefix[0];
+#if SIZEOF_SRE_CHAR == 1
+ {
+ SRE_CHAR *found = memchr(ptr, c, end - ptr);
+ if (!found)
+ return 0;
+ ptr = found + 1;
+ }
+#else
while (*ptr++ != c) {
if (ptr >= end)
return 0;
}
+#endif
if (ptr >= end)
return 0;
I ran into this while profiling a log parser (pretty much grepping for error and warning strings) that applies a handful of literal-prefix regexes to each line of a ~5MB log file. With the patch, the runtime is reduced by ~14% end-to-end. A similar use case in the same application is scanning a binary executable/library for strings with a pattern /common/prefix/(foo|bar|baz) where I would benefit even more from memchr to find the / anchors.
Microbenchmark on my M4 macbook (without PGO):
Single-char prefix re.compile(r"X(A|B)"), match at position N against aaa...aXA
| match position | baseline | patched | speedup |
|---|---|---|---|
| 0 | 55 ns | 58 ns | ~flat |
| 50 | 70 ns | 53 ns | 1.3x |
| 100 | 83 ns | 55 ns | 1.5x |
| 500 | 217 ns | 62 ns | 3.5x |
| 1,000 | 326 ns | 70 ns | 4.7x |
| 10,000 | 2,379 ns | 219 ns | 10.9x |
| 100,000 | 23,348 ns | 1,576 ns | 14.8x |
Multi-char prefix re.compile(r"XXXX(A|B)"), match at position N against aaaa...aXXXXA
| match position | baseline | patched | speedup |
|---|---|---|---|
| 0 | 57 ns | 56 ns | ~flat |
| 100 | 71 ns | 58 ns | 1.2x |
| 500 | 142 ns | 65 ns | 2.2x |
| 1,000 | 221 ns | 72 ns | 3.1x |
| 10,000 | 1,652 ns | 225 ns | 7.3x |
| 100,000 | 15,952 ns | 1,621 ns | 9.8x |
The reason the second benchmark is not as good as the first is that the apple clang compiler seems to have unrolled the second loop 4x while the first loop is not unrolled at all. Neither of them were auto-vectorized.
Synthetic benchmark
"""Synthetic benchmark for SRE prefix scanning at various string lengths."""
import re
import time
def bench(pat, text, iterations):
for _ in range(1000):
pat.search(text)
t0 = time.perf_counter()
for _ in range(iterations):
pat.search(text)
dt = time.perf_counter() - t0
ns_per_call = dt / iterations * 1e9
print(f" {ns_per_call:8.1f} ns/call")
# Single-char prefix: X(A|B) has prefix "X" (len=1)
pat1 = re.compile(r"X(A|B)")
print("Single-char prefix: X(A|B), match at position N")
for n in [0, 5, 10, 50, 100, 500, 1000, 10000, 100000]:
text = "a" * n + "XA"
print(f" match at pos {n:>6d} (len={len(text):>6d})", end="")
bench(pat1, text, max(100000, 1000000 // max(n, 1)))
# Multi-char prefix: XXXX(A|B) has prefix "XXXX" (len=4)
pat4 = re.compile(r"XXXX(A|B)")
print()
print("Multi-char prefix: XXXX(A|B), match at position N")
for n in [0, 5, 10, 50, 100, 500, 1000, 10000, 100000]:
text = "a" * n + "XXXXA"
print(f" match at pos {n:>6d} (len={len(text):>6d})", end="")
bench(pat4, text, max(100000, 1000000 // max(n, 1)))
Has this already been discussed elsewhere?
This is a minor feature, which does not need previous discussion elsewhere
Links to previous discussion of this feature:
No response
Linked PRs
- gh-148733
Guide de contribution
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Piste de recherche
Commencez dans Modules/_sre/sre_lib.h, au niveau des deux boucles d’analyse des préfixes référencées dans l’issue, et examinez les branches proposées SIZEOF_SRE_CHAR == 1 utilisant memchr. Exécutez le microbenchmark de regex fourni et comparez le comportement et les performances avec les boucles existantes ; le travail est terminé lorsque le scanner utilise memchr pour les caractères codés sur un seul octet sans modifier les autres chemins de largeur de caractères.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- c, python
- Domaine
- performance
- Type d'issue
- Fonctionnalité
- Difficulté
- 3/5
- Temps estimé
- 1-2 jours
- Activité
- À l'abandon
- Clarté
- Clairement spécifiée
- Accessibilité débutants
- 35/100