+1 on the change to floatstr (this is also part of my branch with a C version of the encoder main...eendebakpt:cpython:json_floatstr, in my benchmarks this makes a difference)

For the whitespace we should decide on #117397 first. For that reason maybe split the PR into two

(note: please avoid force pushes, they make reviews harder)

@gaborbernat Did you check pyperformance json_loads?

I checked this variant once (worse than yours; one more branch):

diff --git a/Lib/json/decoder.py b/Lib/json/decoder.py
index 364e44d40cc..37ab3f5cf66 100644
--- a/Lib/json/decoder.py
+++ b/Lib/json/decoder.py
@@ -355,8 +355,13 @@ def decode(self, s, _w=WHITESPACE.match):
         containing a JSON document).

         """
-        obj, end = self.raw_decode(s, idx=_w(s, 0).end())
-        end = _w(s, end).end()
+        if s and s[0] in WHITESPACE_STR:
+            idx = _w(s, 0).end()
+        else:
+            idx = 0
+        obj, end = self.raw_decode(s, idx=idx)
+        if end < len(s) and s[end] in WHITESPACE_STR:
+            end = _w(s, end).end()
         if end != len(s):
             raise JSONDecodeError("Extra data", s, end)
         return obj

That's what I've got json_loads result:

patch (afe23af):  json_loads: Mean +- std dev: 11.5 us +- 0.3 us
main  (2043886):  json_loads: Mean +- std dev: 11.1 us +- 0.2 us

Using:

import json
import pyperf


def sized(target):
    n = target // 12
    while True:
        s = json.dumps({str(i): i for i in range(n)})
        if len(s) >= target:
            return s
        n += target // 24


PAYLOADS = {
    "no_ws_tiny":   '{"a":1}',                                           # fast-path target
    "leading_ws":   '  {"a":1}',                                         # slow path
    "trailing_ws":  '{"a":1}  ',                                         # slow path
    "both_ws":      '  {"a":1}  ',                                       # slow path
    "no_ws_1kb":    sized(1 * 1024),                                     # amortization
    "no_ws_4kb":    sized(4 * 1024),
    "no_ws_8kb":    sized(8 * 1024),
    "no_ws_16kb":   sized(16 * 1024),
    "no_ws_32kb":   sized(32 * 1024),
    "no_ws_64kb":   sized(64 * 1024),
    "no_ws_100kb":  sized(100 * 1024),                                   # sanity
}

if __name__ == "__main__":
    runner = pyperf.Runner()
    for name, payload in PAYLOADS.items():
        runner.timeit(
            name=f"json_loads/{name}",
            stmt="loads(s)",
            setup=f"from json import loads; s = {payload!r}",
        )

The results:

Yes — on the pyperformance json_loads dataset (EMPTY/SIMPLE/NESTED/HUGE) it's 1.16x faster (5.57 ms → 4.78 ms): that workload is dominated by small documents with no surrounding whitespace, which is exactly the case this targets.

The regression you saw came from the extra branch in your variant — if end < len(s) and s[end] in WHITESPACE_STR adds a per-call membership test. The version here instead skips the trailing match only when the parse already consumed the whole string (end == len(s)), so it avoids that check on the common path.

One thing to note: I've split this PR. The whitespace-skip change you're benchmarking now lives in #150861; this PR (#150827) is just the encoder floatstr change. Happy to continue the json_loads discussion over there.

Thanks for the review and the split suggestion. Applied both: dropped the comment and trimmed the NEWS entry to Speed up :func:json.dumps for small documents.

Could a maintainer kindly re-run the failed job when you get a chance? The failure is in the iOS check (-[TestbedTests testPython] failed to execute), which looks like an unrelated testbed flake — this PR only changes pure-Python Lib/json/encoder.py. Thank you for your time reviewing this.

Could a maintainer kindly re-run the failed job when you get a chance? The failure is in the iOS check (-[TestbedTests testPython] failed to execute), which looks like an unrelated testbed flake — this PR only changes pure-Python Lib/json/encoder.py. Thank you for your time reviewing this.

Please be patient. Maintainers have many pr's to review and it can take some time. Re-running the test is not required for a review. (although it is often done after approval)