gh-137821: Convert _json module to use Argument Clinic#140778
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corona10 merged 8 commits intopython:mainfrom Oct 30, 2025
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gh-137821: Convert _json module to use Argument Clinic#140778corona10 merged 8 commits intopython:mainfrom
corona10 merged 8 commits intopython:mainfrom
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October 30, 2025 15:30
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encode_basestring_medium: Mean +- std dev: [base] 2.11 us +- 0.05 us -> [ac] 2.33 us +- 0.04 us: 1.11x slower
encode_basestring_medium_escapes: Mean +- std dev: [base] 15.3 us +- 0.4 us -> [ac] 17.6 us +- 0.2 us: 1.15x slower
scanstring_medium: Mean +- std dev: [base] 158 ns +- 2 ns -> [ac] 110 ns +- 2 ns: 1.43x faster
Benchmark hidden because not significant (4): encode_basestring_ascii_medium, encode_basestring_ascii_medium_escapes, encode_basestring_ascii_medium_unicode, encode_basestring_medium_unicode
Geometric mean: 1.02x faster
import pyperf
import _json
# Test data - medium objects (typical API responses)
medium_string = "The quick brown fox jumps over the lazy dog. " * 20 # ~900 chars
medium_string_with_escapes = '''Line 1: "status": "success"
Line 2: Response received at 2024-01-15T10:30:00Z
\tError code: null
\tMessage: "Operation completed successfully"
''' * 50
medium_unicode = "User: 김철수 | Email: user@example.com | Status: ✓ Active | Location: 東京都 | Rating: ★★★★☆ | " * 30
medium_json_string = '"' + '{"id": 12345, "name": "John Doe", "email": "john@example.com"}' * 20 + '"'
def bench_encode_basestring_ascii(s):
return _json.encode_basestring_ascii(s)
def bench_encode_basestring(s):
return _json.encode_basestring(s)
def bench_scanstring(s):
# scanstring takes (string, end, strict=True)
# end is the index after the opening quote
return _json.scanstring(s, 1, True)
runner = pyperf.Runner()
# encode_basestring_ascii benchmarks
runner.bench_func("encode_basestring_ascii_medium", bench_encode_basestring_ascii, medium_string)
runner.bench_func("encode_basestring_ascii_medium_escapes", bench_encode_basestring_ascii, medium_string_with_escapes)
runner.bench_func("encode_basestring_ascii_medium_unicode", bench_encode_basestring_ascii, medium_unicode)
# encode_basestring benchmarks
runner.bench_func("encode_basestring_medium", bench_encode_basestring, medium_string)
runner.bench_func("encode_basestring_medium_escapes", bench_encode_basestring, medium_string_with_escapes)
runner.bench_func("encode_basestring_medium_unicode", bench_encode_basestring, medium_unicode)
# scanstring benchmarks
runner.bench_func("scanstring_medium", bench_scanstring, medium_json_string) |
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Author
|
I've checked the memory leak test. > ./python.exe -m test test_json -R3:3
Using random seed: 2482685647
0:00:00 load avg: 5.30 Run 1 test sequentially in a single process
0:00:00 load avg: 5.30 [1/1] test_json
beginning 6 repetitions. Showing number of leaks (. for 0 or less, X for 10 or more)
123:456
XX. ...
0:00:30 load avg: 4.92 [1/1] test_json passed in 30.6 sec
== Tests result: SUCCESS ==
1 test OK.
Total duration: 30.6 sec
Total tests: run=203 skipped=3
Total test files: run=1/1
Result: SUCCESS |
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LGTM, parsing overhead does not exists and it becomes better!
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This should be moved to Library.
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@StanFromIreland I will change it to following PR.
(Need some improvement)
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For the record, with #140780 |
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_jsonto Argument Clinic #137821