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Results

linux aarch64 (arminc)

vs. 3.10.4

  • Geometric mean: 1.20x faster (HPT: reliability of 100.00%, 1.08x faster at 99th %ile)
  • Memory usage: 1.22x
  • missing benchmarks: aiohttp, chameleon, flaskblogging, 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: 1.02x slower (HPT: reliability of 98.92%, 1.00x slower at 99th %ile)
  • Memory usage: 1.12x
  • missing benchmarks: aiohttp, chameleon, flaskblogging, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.06x slower (HPT: reliability of 100.00%, 1.02x slower at 99th %ile)
  • Memory usage: 0.98x
  • missing benchmarks: aiohttp, chameleon, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative
  • 📄table
  • 📈time plot

vs. base

linux x86_64 (azure)

vs. base

linux x86_64 (linux)

vs. 3.10.4

  • Geometric mean: 1.34x faster (HPT: reliability of 100.00%, 1.24x faster at 99th %ile)
  • Memory usage: 1.18x
  • missing benchmarks: aiohttp, chameleon, djangocms, flaskblogging, 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 99.38%, 1.00x faster at 99th %ile)
  • Memory usage: 1.10x
  • missing benchmarks: aiohttp, chameleon, djangocms, flaskblogging, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.04x faster (HPT: reliability of 99.40%, 1.00x faster at 99th %ile)
  • Memory usage: 1.03x
  • missing benchmarks: aiohttp, chameleon, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

vs. base

linux x86_64 (pythonperf2)

vs. 3.10.4

  • Geometric mean: 1.28x faster (HPT: reliability of 100.00%, 1.19x faster at 99th %ile)
  • Memory usage: 1.20x
  • missing benchmarks: aiohttp, chameleon, flaskblogging, 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 99.92%, 1.01x faster at 99th %ile)
  • Memory usage: 1.11x
  • missing benchmarks: aiohttp, chameleon, flaskblogging, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.01x slower (HPT: reliability of 64.51%, 1.00x faster at 99th %ile)
  • Memory usage: 0.98x
  • missing benchmarks: aiohttp, chameleon, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

vs. base

windows amd64 (pythonperf1)

vs. 3.10.4

  • Geometric mean: 1.24x faster (HPT: reliability of 100.00%, 1.14x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, flaskblogging, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, 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: 1.11x faster (HPT: reliability of 100.00%, 1.03x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, flaskblogging, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.05x faster (HPT: reliability of 99.92%, 1.01x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, unpack_sequence
  • new benchmarks: genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

vs. base

  • Geometric mean: 1.00x faster (HPT: reliability of 90.33%, 1.00x slower at 99th %ile)
  • Memory usage: unknown
  • 📄table
  • 📈time plot

windows x86 (pythonperf1_win32)

vs. 3.10.4

  • Geometric mean: 1.24x faster (HPT: reliability of 100.00%, 1.14x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, flaskblogging, 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: 1.35x faster (HPT: reliability of 100.00%, 1.27x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, flaskblogging, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • 📄table
  • 📈time plot

vs. 3.12.0

  • Geometric mean: 1.24x faster (HPT: reliability of 100.00%, 1.16x faster at 99th %ile)
  • Memory usage: unknown
  • missing benchmarks: aiohttp, chameleon, dask, dulwich_log, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, unpack_sequence
  • new benchmarks: genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

vs. base

  • Geometric mean: 1.01x faster (HPT: reliability of 96.96%, 1.00x faster at 99th %ile)
  • Memory usage: unknown
  • 📄table
  • 📈time plot

darwin arm64 (darwin)

vs. 3.10.4

  • Geometric mean: 1.24x faster (HPT: reliability of 100.00%, 1.17x faster at 99th %ile)
  • Memory usage: 1.12x
  • missing benchmarks: aiohttp, chameleon, dulwich_log, flaskblogging, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, 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: 1.02x faster (HPT: reliability of 58.88%, 1.00x slower at 99th %ile)
  • Memory usage: 0.88x
  • missing benchmarks: aiohttp, chameleon, dulwich_log, flaskblogging, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, 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: 1.05x faster (HPT: reliability of 100.00%, 1.02x faster at 99th %ile)
  • Memory usage: 0.85x
  • missing benchmarks: aiohttp, chameleon, dulwich_log, gunicorn, mypy2, sqlalchemy_declarative, sqlalchemy_imperative, sqlglot_normalize, 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, genshi_text, genshi_xml, html5lib, pylint, thrift
  • 📄table
  • 📈time plot

vs. base