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Convert FAQ from manually-formatted to section headings + ref targets
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Doc/whatsnew/3.11.rst

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@@ -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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How should I write my code to utilize these speedups?
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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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.. _faster-cpython-faq-memory:
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Will CPython 3.11 use more memory?
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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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.. _faster-cpython-ymmv:
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I don't see any speedups in my workload. Why?
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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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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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.. _faster-cpython-jit:
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Is there a JIT compiler?
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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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