Improve performance by using reference stealing methods

Feature or enhancement

Proposal:

We can improve performance of cpython by using stealing methods (_PyList_AppendTakeRef, _PyDict_SetItem_Take2, PyTuple_FromPairSteal etc.) instead of the normal ones. Using stealing methods we typically avoid an incref/decref pair and sometimes error handling is simplified. We should only make changes where it makes a performance impact, the code is not more complex and the modules or methods affected are performance critical.

A list of possible cases (there might be more).

Location	Module / context	Helper
`Modules/_csv.c:688`	csv reader, per field	`_PyList_AppendTakeRef`
`Modules/pyexpat.c:472`	pyexpat StartElement, per attribute	`_PyDict_SetItem_Take2`
`Modules/_elementtree.c:3351`	ElementTree C accel attrib dict	`_PyDict_SetItem_Take2`
`Modules/_io/bytesio.c:577`	io.BytesIO.readlines	`_PyList_AppendTakeRef`
`Modules/_io/iobase.c:756`	io.IOBase.readlines (generic)	`_PyList_AppendTakeRef`
`Objects/frameobject.c:639 & 658`	frame f_locals / `vars()` / tracing	`_PyList_AppendTakeRef`
`Modules/_pickle.c:5138`	pickle Pickler memo copy	`_PyDict_SetItem_Take2`
`Modules/_io/textio.c:2337 & 2343`	io.TextIOWrapper readline (multi-chunk)	`_PyList_AppendTakeRef`
`Modules/_asynciomodule.c:1213`	asyncio future done-callback compaction	`_PyList_AppendTakeRef`

Update: Most cases already have an open PR, for new ones please open a separate issue.

Linked PRs

pythongh-150942: Set issue number on the re speedup news entry

pythongh-150942: Speed up json.loads array and object decoding

@eendebakpt

hi @eendebakpt @StanFromIreland can i work on a module , maybe csv or textio

hi @eendebakpt @StanFromIreland can i work on a module , maybe csv or textio

Sure! Try out, benchmark, test. If benchmarks show significant improvements you can open a PR, if not just report here briefly.

Merge branch 'main' into pythongh-150942-csv-appendtakeref

@eendebakpt

hi @eendebakpt , i've opned a PR for csv reader, since that has 1.08x speedup, matches your PR speedups....

however, the benchmarks for io.BytesIO.readlines show that there is not a significant improvements

Benchmark	main	my branch	speedup
`bytesio_readlines_1m_8b`	15.15 ms	15.29 ms	0.99x
`bytesio_readlines_500k_24b`	7.66 ms	7.45 ms	1.03x
`bytesio_readlines_100k_256b`	3.24 ms	3.20 ms	1.01x
`bytesio_readlines_2m_0b`	16.33 ms	16.54 ms	0.99x
`bytesio_readlines_2m_8b`	32.58 ms	31.97 ms	1.02x
geomean			1.01x

Benchmark script

"""Micro-benchmark for io.BytesIO.readlines result-list building."""

from __future__ import annotations

import argparse
import io
import json
import statistics
import sys
import time
from pathlib import Path


def make_data(lines: int, payload_size: int) -> bytes:
    payload = b"x" * payload_size
    return b"".join(payload + b"\n" for _ in range(lines))


def time_readlines(data: bytes) -> float:
    t0 = time.perf_counter_ns()
    io.BytesIO(data).readlines()
    return (time.perf_counter_ns() - t0) / 1e9


def main() -> int:
    ap = argparse.ArgumentParser()
    ap.add_argument("--lines", type=int, default=200_000)
    ap.add_argument("--payload-size", type=int, default=24)
    ap.add_argument("--trials", type=int, default=15)
    ap.add_argument("--warmup", type=int, default=3)
    ap.add_argument("--label", default="run")
    ap.add_argument("--outdir", default="results/bytesio-readlines")
    args = ap.parse_args()

    data = make_data(args.lines, args.payload_size)

    for _ in range(args.warmup):
        time_readlines(data)

    trials = [time_readlines(data) for _ in range(args.trials)]

    outdir = Path(args.outdir)
    outdir.mkdir(parents=True, exist_ok=True)
    summary = {
        "label": args.label,
        "python": sys.executable,
        "lines": args.lines,
        "payload_size": args.payload_size,
        "trials": args.trials,
        "warmup": args.warmup,
        "input_bytes": len(data),
        "seconds": {
            "min": min(trials),
            "median": statistics.median(trials),
            "mean": statistics.fmean(trials),
            "stdev": statistics.pstdev(trials),
            "all": trials,
        },
        "lines_per_sec_at_min": args.lines / min(trials),
    }
    out = outdir / f"bench_{args.label}.json"
    out.write_text(json.dumps(summary, indent=2))

    s = summary["seconds"]
    print(
        f"{args.label}: min={s['min']*1000:.2f}ms median={s['median']*1000:.2f}ms "
        f"mean={s['mean']*1000:.2f}ms stdev={s['stdev']*1000:.2f}ms "
        f"lines/s@min={summary['lines_per_sec_at_min']:.2e}"
    )
    print(f"wrote {out}")
    return 0


if __name__ == "__main__":
    raise SystemExit(main())

do you think i should still make a pr for this

Merge branch 'main' into pythongh-150942-csv-appendtakeref

Happy to try _asynciomodule.c — swap PyList_Append for
_PyList_AppendTakeRef in future_add_done_callback.
I'll benchmark first.

gh-150942: Speed up frame local item collection (gh-151002)

gh-150942: Speed up re.findall and re.sub/subn result building (gh-15…

pythongh-150942: Speed up asyncio future add_done_callback

Hi, I found an additional candidate in Python/modsupport.c::do_mkdict(), where Py_BuildValue() dictionary construction passes newly owned key/value references to PyDict_SetItem() and then immediately decrefs them. Using _PyDict_SetItem_Take2() avoids those INCREF/DECREF round trips. Targeted Py_BuildValue() dict microbenchmarks showed small but repeatable ~1–5% improvements across the tested cases.

Opened #156199 for this.

It seems all of the obvious cases have an open PR, so I am going to close the issue. For any new cases, please open a new issue.

I think we should keep this issue open however, unless you plan to move all the PRs?

gh-150942: Speed up BytesIO.readlines() using reference-stealing appe…

Keeping it open because there are still PRs.

Merge upstream main and preserve FrameLocalsProxy.values() ownership

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Improve performance by using reference stealing methods #150942

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Improve performance by using reference stealing methods #150942

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Feature or enhancement

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omkar-334 commented on Jun 5, 2026

eendebakpt commented on Jun 5, 2026

omkar-334 commented on Jun 6, 2026

tangyuan0821 commented on Jun 7, 2026

26 remaining items

tkim602 commented on Aug 21, 2026

eendebakpt commented on Aug 22, 2026

StanFromIreland commented on Aug 22, 2026

picnixz commented on Oct 2, 2026

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