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Results

linux aarch64 (arminc)

vs. 3.10.4

  • Geometric mean: 1.327x faster (HPT: reliability of 100.00%, 1.23x faster at 99th %ile)
  • Memory usage: 1.30x
  • missing benchmarks: aiohttp, chameleon, dask, flaskblogging, gunicorn, mypy2, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.040x faster (HPT: reliability of 99.98%, 1.01x faster at 99th %ile)
  • Memory usage: 1.04x
  • missing benchmarks: aiohttp, chameleon, dask, gunicorn, mypy2, tornado_http
  • new benchmarks: bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.038x faster (HPT: reliability of 100.00%, 1.01x faster at 99th %ile)
  • Memory usage: 1.03x
  • missing benchmarks: chameleon, djangocms, gevent_hub, gunicorn, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, dulwich_log, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

linux x86_64 (azure)

linux x86_64 (linux)

vs. 3.10.4

  • Geometric mean: 1.463x faster (HPT: reliability of 100.00%, 1.33x faster at 99th %ile)
  • Memory usage: 1.26x
  • missing benchmarks: aiohttp, chameleon, dask, djangocms, flaskblogging, gunicorn, mypy2, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.123x faster (HPT: reliability of 100.00%, 1.07x faster at 99th %ile)
  • Memory usage: 1.09x
  • missing benchmarks: aiohttp, chameleon, dask, gunicorn, mypy2, tornado_http
  • new benchmarks: bpe_tokeniser, connected_components, genshi_text, genshi_xml, html5lib, k_core, many_optionals, pylint, shortest_path, sphinx, subparsers, thrift
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.055x faster (HPT: reliability of 100.00%, 1.02x faster at 99th %ile)
  • Memory usage: 1.03x
  • missing benchmarks: chameleon, djangocms, gevent_hub, gunicorn, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

linux x86_64 (pythonperf2)

vs. 3.10.4

  • Geometric mean: 1.354x faster (HPT: reliability of 100.00%, 1.24x faster at 99th %ile)
  • Memory usage: 1.27x
  • missing benchmarks: aiohttp, chameleon, dask, flaskblogging, gunicorn, mypy2, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.048x faster (HPT: reliability of 99.99%, 1.01x faster at 99th %ile)
  • Memory usage: 1.04x
  • missing benchmarks: aiohttp, chameleon, dask, gunicorn, mypy2, tornado_http
  • new benchmarks: bpe_tokeniser, connected_components, genshi_text, genshi_xml, html5lib, k_core, many_optionals, pylint, shortest_path, sphinx, subparsers, thrift
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.061x faster (HPT: reliability of 100.00%, 1.03x faster at 99th %ile)
  • Memory usage: 1.02x
  • missing benchmarks: chameleon, djangocms, gevent_hub, gunicorn, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

windows amd64 (pythonperf1)

vs. 3.10.4

  • Geometric mean: 1.231x faster (HPT: reliability of 100.00%, 1.13x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, flaskblogging, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, asyncio_websockets, bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.041x faster (HPT: reliability of 83.71%, 1.00x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: asyncio_websockets, bpe_tokeniser, connected_components, genshi_text, genshi_xml, html5lib, k_core, many_optionals, pylint, shortest_path, sphinx, subparsers, thrift
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.010x faster (HPT: reliability of 99.76%, 1.00x slower at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: chameleon, djangocms, gevent_hub, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

windows x86 (pythonperf1_win32)

vs. 3.10.4

  • Geometric mean: 1.086x faster (HPT: reliability of 99.91%, 1.02x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, flaskblogging, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, asyncio_websockets, bpe_tokeniser, connected_components, k_core, many_optionals, shortest_path, sphinx, subparsers
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.092x faster (HPT: reliability of 100.00%, 1.06x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: asyncio_websockets, bpe_tokeniser, connected_components, genshi_text, genshi_xml, html5lib, k_core, many_optionals, pylint, shortest_path, sphinx, subparsers, thrift
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.027x slower (HPT: reliability of 100.00%, 1.03x slower at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: chameleon, djangocms, gevent_hub, sqlalchemy_declarative, sqlalchemy_imperative, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

darwin arm64 (darwin)

vs. 3.10.4

  • Geometric mean: 1.388x faster (HPT: reliability of 100.00%, 1.22x faster at 99th %ile)
  • Memory usage: 1.14x
  • missing benchmarks: chameleon, djangocms, gevent_hub, tornado_http
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_eager_cpu_io_mixed_tg, async_tree_eager_io_tg, async_tree_eager_memoization_tg, async_tree_eager_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg, asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.089x faster (HPT: reliability of 100.00%, 1.02x faster at 99th %ile)
  • Memory usage: 1.13x
  • missing benchmarks: chameleon, djangocms, gevent_hub, gunicorn, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot

vs. 3.13.0

  • Geometric mean: 1.093x faster (HPT: reliability of 100.00%, 1.06x faster at 99th %ile)
  • Memory usage: 1.08x
  • missing benchmarks: chameleon, djangocms, gevent_hub, gunicorn, tornado_http
  • new benchmarks: asyncio_tcp, asyncio_tcp_ssl, pickle, pickle_dict, pickle_list, unpack_sequence, unpickle, unpickle_list
  • 📄table
  • 📈time plot