@@ -1367,35 +1367,47 @@ Misc
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FAQ
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---
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- | Q: How should I write my code to utilize these speedups?
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- |
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- | A: You don't have to change your code. Write Pythonic code that follows common
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- best practices. The Faster CPython project optimizes for common code
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- patterns we observe.
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- |
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- |
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- | Q: Will CPython 3.11 use more memory?
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- |
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- | A: Maybe not. We don't expect memory use to exceed 20% more than 3.10.
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- This is offset by memory optimizations for frame objects and object
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- dictionaries as mentioned above.
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- |
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- |
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- | Q: I don't see any speedups in my workload. Why?
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- |
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- | A: Certain code won't have noticeable benefits. If your code spends most of
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- its time on I/O operations, or already does most of its
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- computation in a C extension library like numpy, there won't be significant
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- speedup. This project currently benefits pure-Python workloads the most.
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- |
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- | Furthermore, the pyperformance figures are a geometric mean. Even within the
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- pyperformance benchmarks, certain benchmarks have slowed down slightly, while
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- others have sped up by nearly 2x!
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- |
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- |
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- | Q: Is there a JIT compiler?
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- |
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- | A: No. We're still exploring other optimizations.
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+ .. _faster-cpython-faq-my-code :
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+
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+ How should I write my code to utilize these speedups?
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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+
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+ You don't have to change your code. Write Pythonic code that follows common
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+ best practices. The Faster CPython project optimizes for common code
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+ patterns we observe.
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+
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+
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+ .. _faster-cpython-faq-memory :
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+
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+ Will CPython 3.11 use more memory?
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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+
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+ Maybe not. We don't expect memory use to exceed 20% more than 3.10.
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+ This is offset by memory optimizations for frame objects and object
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+ dictionaries as mentioned above.
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+
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+
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+ .. _faster-cpython-ymmv :
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+
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+ I don't see any speedups in my workload. Why?
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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+
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+ Certain code won't have noticeable benefits. If your code spends most of
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+ its time on I/O operations, or already does most of its
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+ computation in a C extension library like numpy, there won't be significant
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+ speedup. This project currently benefits pure-Python workloads the most.
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+
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+ Furthermore, the pyperformance figures are a geometric mean. Even within the
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+ pyperformance benchmarks, certain benchmarks have slowed down slightly, while
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+ others have sped up by nearly 2x!
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+
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+
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+ .. _faster-cpython-jit :
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+
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+ Is there a JIT compiler?
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+ ^^^^^^^^^^^^^^^^^^^^^^^^
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+
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+ No. We're still exploring other optimizations.
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.. _whatsnew311-faster-cpython-about :
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