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Results

linux aarch64 (arminc)

vs. 3.10.4

  • Geometric mean: 1.29x faster (HPT: reliability of 100.00%, 1.22x faster at 99th %ile)
  • Memory usage: 1.13x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.05x faster (HPT: reliability of 99.68%, 1.00x faster at 99th %ile)
  • Memory usage: 1.03x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.01x faster (HPT: reliability of 91.84%, 1.00x faster at 99th %ile)
  • Memory usage: 0.91x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative
  • new benchmarks: flaskblogging
  • 📄table
  • 📈time plot

linux x86_64 (azure)

linux x86_64 (linux)

vs. 3.10.4

  • Geometric mean: 1.34x faster (HPT: reliability of 100.00%, 1.27x faster at 99th %ile)
  • Memory usage: 1.11x
  • missing benchmarks: aiohttp, djangocms, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.07x faster (HPT: reliability of 99.85%, 1.00x faster at 99th %ile)
  • Memory usage: 1.04x
  • missing benchmarks: aiohttp, djangocms, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.04x faster (HPT: reliability of 99.98%, 1.00x faster at 99th %ile)
  • Memory usage: 0.97x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: flaskblogging, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

linux x86_64 (pythonperf2)

vs. 3.10.4

  • Geometric mean: 1.28x faster (HPT: reliability of 100.00%, 1.20x faster at 99th %ile)
  • Memory usage: 1.12x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.07x faster (HPT: reliability of 99.10%, 1.00x faster at 99th %ile)
  • Memory usage: 1.04x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.01x slower (HPT: reliability of 82.90%, 1.00x slower at 99th %ile)
  • Memory usage: 0.92x
  • missing benchmarks: aiohttp, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: flaskblogging, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

windows amd64 (pythonperf1)

vs. 3.10.4

  • Geometric mean: 1.26x faster (HPT: reliability of 100.00%, 1.18x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.13x faster (HPT: reliability of 100.00%, 1.07x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.07x faster (HPT: reliability of 100.00%, 1.04x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: flaskblogging, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

windows x86 (pythonperf1_win32)

vs. 3.10.4

  • Geometric mean: 1.20x faster (HPT: reliability of 100.00%, 1.11x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.32x faster (HPT: reliability of 100.00%, 1.26x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.21x faster (HPT: reliability of 100.00%, 1.18x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: flaskblogging, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

darwin arm64 (darwin)

vs. 3.10.4

  • Geometric mean: 1.26x faster (HPT: reliability of 100.00%, 1.19x faster at 99th %ile)
  • Memory usage: 0.83x
  • missing benchmarks: aiohttp, dulwich_log, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_cpu_io_mixed_tg, async_tree_eager, async_tree_eager_cpu_io_mixed, async_tree_eager_cpu_io_mixed_tg, async_tree_eager_io, async_tree_eager_io_tg, async_tree_eager_memoization, async_tree_eager_memoization_tg, async_tree_eager_tg, async_tree_io_tg, async_tree_memoization_tg, async_tree_none_tg
  • 📄table
  • 📈time plot

vs. 3.11.0

  • Geometric mean: 1.04x faster (HPT: reliability of 93.67%, 1.00x faster at 99th %ile)
  • Memory usage: 0.76x
  • missing benchmarks: aiohttp, dulwich_log, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_eager, async_tree_eager_cpu_io_mixed, async_tree_eager_cpu_io_mixed_tg, async_tree_eager_io, async_tree_eager_io_tg, async_tree_eager_memoization, async_tree_eager_memoization_tg, async_tree_eager_tg
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.07x faster (HPT: reliability of 100.00%, 1.04x faster at 99th %ile)
  • Memory usage: 0.74x
  • missing benchmarks: aiohttp, dulwich_log, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: async_tree_eager, async_tree_eager_cpu_io_mixed, async_tree_eager_cpu_io_mixed_tg, async_tree_eager_io, async_tree_eager_io_tg, async_tree_eager_memoization, async_tree_eager_memoization_tg, async_tree_eager_tg, flaskblogging, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot