Strictly speaking, it's probably not necessary to store the task number inTask.__init__(). We could just call_task_name_counter() on lazy creation of a name. The only downside to this is tasks would end up being numbered slightly differently after this change for the same programs. However, I doubt anyone except possibly one or two easily fixed tests are relying on this. In general I imagine the number is actually non-deterministic.

Not storing the name on construction saves memory and will likely make everything a tiny bit faster.

We could just call_task_name_counter() on lazy creation of a name

that's clever! I like it :)

made this change to the PR. CI is still running, but at least on my local test run it didn't break any tests.

Strictly speaking, it's probably not necessary to store the task number in Task.init(). We could just call _task_name_counter() on lazy creation of a name. The only downside to this is tasks would end up being numbered slightly differently after this change for the same programs. However, I doubt anyone except possibly one or two easily fixed tests are relying on this. In general I imagine the number is actually non-deterministic.

No, tasks numbers are assigned as they are allocated, its a little debugging aid and should not be changed.

A Python core developer has requested some changes be made to your pull request before we can consider merging it. If you could please address their requests along with any other requests in other reviews from core developers that would be appreciated.

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@kumaraditya303: please review the changes made to this pull request.

🤖 New build scheduled with the buildbot fleet by@gvanrossum for commit592d44b 🤖

If you want to schedule another build, you need to add the🔨 test-with-refleak-buildbots label again.

(Dismissing Kumar's review for him, he told me he's busy for the next few weeks. Setting the refleaks-buildbots label, those are sufficient for me.)

I did rerun the benchmarks, it was 5-7% faster on the async benchmarks. I'll rerun again on main vs the parent commit and share the full report.

Thanks! (And just because I work on weekends doesn’t mean I expect you to.)

pyperformance async benchmarks 4-7% faster

3.12-base.20230429.1.json=========================Performance version: 1.0.6Python version: 3.12.0a7+ (64-bit) revision fbf3596c3eReport on Linux-5.15.0-1033-aws-x86_64-with-glibc2.31Number of logical CPUs: 72Start date: 2023-04-29 16:39:30.287074End date: 2023-04-29 16:50:17.9959783.12-defer.20230429.1.json==========================Performance version: 1.0.6Python version: 3.12.0a7+ (64-bit) revision 85c7bf5bceReport on Linux-5.15.0-1033-aws-x86_64-with-glibc2.31Number of logical CPUs: 72Start date: 2023-04-29 16:12:36.207389End date: 2023-04-29 16:22:51.562679+-------------------------------+---------------------------+----------------------------+--------------+-----------------------+| Benchmark                     | 3.12-base.20230429.1.json | 3.12-defer.20230429.1.json | Change       | Significance          |+===============================+===========================+============================+==============+=======================+| async_tree_cpu_io_mixed       | 867 ms                    | 835 ms                     | 1.04x faster | Significant (t=6.62)  |+-------------------------------+---------------------------+----------------------------+--------------+-----------------------+| async_tree_io                 | 1.47 sec                  | 1.39 sec                   | 1.06x faster | Significant (t=21.03) |+-------------------------------+---------------------------+----------------------------+--------------+-----------------------+| async_tree_memoization        | 735 ms                    | 696 ms                     | 1.06x faster | Significant (t=21.10) |+-------------------------------+---------------------------+----------------------------+--------------+-----------------------+| async_tree_none               | 611 ms                    | 570 ms                     | 1.07x faster | Significant (t=13.44) |+-------------------------------+---------------------------+----------------------------+--------------+-----------------------+

microbenchmark ~10% faster

python -m pyperf timeit -s 'import asyncio' -s 'async def coro(): pass' -s 'async def make_tasks(): return [asyncio.Task(coro()) for _ in range(10000)]' 'asyncio.run(make_tasks())'

with this PR:

Mean +- std dev: 27.5 ms +- 0.6 ms

on parent commit:

Mean +- std dev: 30.5 ms +- 0.9 ms

Excellent—thanks!