python / python/cpython

Speed up JSON string encoding for documents with long string values

Offen
#150,875 4 Kommentare 0 Reaktionen 0 zugewiesene Personen Auf GitHub ansehen

Dieses Issue hat noch niemand übernommen.

extension-modules performance type-feature
Vorherrschende Sprache
Python
Sterne
77.2k
Forks
35.9k
PR-Merge-Kennzahlen
PR-Kennzahlen ausstehend

Beschreibung

Feature or enhancement

Proposal

json.dumps escapes each string by first scanning it one character at a time to compute the escaped size (ascii_escape_size in Modules/_json.c); when nothing needs escaping, write_escaped_ascii then copies the string verbatim. For a long string with no characters that need escaping, which is the common case for text values, log messages, and other long content, that per-character sizing scan is pure overhead before the verbatim copy.

The proposal is to detect the no-escape case on the one-byte (ASCII/Latin-1) representation eight bytes at a time. Load eight bytes into a single machine word and test all eight at once for a character that needs escaping (c < 0x20, c > 0x7e, c == '"', or c == '\\'). When a long run has none, return the verbatim size directly. A length guard keeps short strings, such as the typical dict key, on the existing per-character loop, where the eight-byte path would not pay for its setup. Strings that need escaping, and two-byte and four-byte strings (anything with a non-Latin-1 character), keep the current path.

This is the encode-side counterpart to the decode-side scan in #150871 (PR #150872). The two touch different code paths, so they are separate changes.

How this differs from the SIMD backend in #142915

It is not the SIMD parsing architecture declined in #142915. It uses no SIMD intrinsics, no runtime CPU detection, and no build configuration, only portable 64-bit integer arithmetic with the same 0x0101… / 0x8080… masks that Objects/unicodeobject.c already applies for ASCII scanning. It changes one function and adds no infrastructure, so it does not depend on #125022 and needs no PEP.

When it helps, and when it does not

Measured json.dumps speedups against the current encoder:

Document shape Effect
One long text field (~11 KB string) 5.3x faster
Many 200-character ASCII string values 3.1x faster
Realistic mixed records (short and medium strings) 1.3x faster
Short keys, strings that need escaping, the pyperformance document no change
Strings with emoji or other non-Latin-1 text no change (scalar path)

The benefit is specific to documents whose payload is long, escape-free text. The short-string guard keeps key-heavy documents unaffected.

Correctness

The encoded output is byte-identical to the current encoder. A patch is validated against test_json and a 199-case differential corpus (strings placing each escape-relevant character, including ", \, control chars, 0x7f, and non-Latin-1 characters, at every offset across the eight-byte window, in both ensure_ascii=True and ensure_ascii=False modes). Every output matched.

A proof-of-concept PR follows.

Benchmark

Built base and patched interpreters from this branch's main ancestor and the patch, ran the same script under each, and compared with pyperf compare_to (A/B by swapping Lib/json/encoder.py on the same build; macOS arm64, non-PGO).

import json, pyperf
long_ascii = [("x"*200) for _ in range(200)]                 # long no-escape ASCII values
text_blob  = {"body": "lorem ipsum dolor sit amet " * 400}   # one huge no-escape string
escaped    = [('a"b\\c\n'*30) for _ in range(200)]           # escape-heavy
short_keys = {f"k{i}": i for i in range(2000)}               # short keys
mixed_real = [{"id":i,"name":f"user_{i}","email":f"u{i}@x.com","bio":"hello world "*10} for i in range(300)]
nonascii   = ["café 😀 中文 "*20 for _ in range(200)]          # UCS-2/4 (scalar path)
objs={"long_ascii":long_ascii,"text_blob":text_blob,"escaped":escaped,"short_keys":short_keys,"mixed_real":mixed_real,"nonascii":nonascii}
r=pyperf.Runner()
for n,o in objs.items():
    r.bench_func(f"dumps/{n}", lambda o=o: json.dumps(o))
Linked PRs
  • gh-150876

Beitragsleitfaden

Beitragsleitfaden öffnen

Erste Schritte

  1. Lies das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreib ins Issue, dass du es übernimmst — das erspart doppelte Arbeit.
  3. Forke das Repository und arbeite in einem Branch.
  4. Öffne einen Pull Request, der die Issue-Nummer nennt.

Rechercherichtung

Überprüfe den verknüpften PR gh-150876 und die betroffene Funktion in Modules/_json.c, insbesondere ascii_escape_size und write_escaped_ascii. Führe die test_json-Suite aus und vergleiche die Benchmark-Fälle; abgeschlossen bedeutet byte-identische Kodierung, beibehaltenes Verhalten beim Escaping und für Nicht-Latin-1-Zeichenketten sowie die gemeldeten Geschwindigkeitssteigerungen für lange Zeichenketten ohne zu escapende Zeichen.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
c, python
Bereich
performance
Issue-Typ
Feature
Schwierigkeit
4/5
Geschätzter Aufwand
3-5 Tage
Aktivitätsstatus
Veraltet
Klarheit
Klar beschrieben
Anfängerfreundlichkeit
20/100

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.