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typo: semantic => semantics

This commit is contained in:
Victor Stinner 2016-01-11 10:18:52 +01:00
parent d59e5c14d1
commit ded45b06f1
2 changed files with 7 additions and 7 deletions
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4
pep-0509.txt
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@ -30,8 +30,8 @@ a function) is usually optimized to an array, but it can be a dict too.
Python is hard to optimize because almost everything is mutable: builtin
functions, function code, global variables, local variables, ... can be
modified at runtime. Implementing optimizations respecting the Python
semantic requires to detect when "something changes": we will call these
checks "guards".
semantics requires to detect when "something changes": we will call
these checks "guards".
The speedup of optimizations depends on the speed of guard checks. This
PEP proposes to add a version to dictionaries to implement efficient

10
pep-0510.txt
View File

@ -14,19 +14,19 @@ Abstract
========
Add an API to add specialized functions with guards to functions, to
support static optimizers respecting the Python semantic.
support static optimizers respecting the Python semantics.
Rationale
=========
Python semantic
---------------
Python semantics
----------------
Python is hard to optimize because almost everything is mutable: builtin
functions, function code, global variables, local variables, ... can be
modified at runtime. Implement optimizations respecting the Python
semantic requires to detect when "something changes", we will call these
semantics requires to detect when "something changes", we will call these
checks "guards".
This PEP proposes to add a ``specialize()`` method to functions to add a
@ -50,7 +50,7 @@ There are multiple JIT compilers for Python actively developed:
Numba is specific to numerical computation. Pyston and Pyjion are still
young. PyPy is the most complete Python interpreter, it is much faster
than CPython and has a very good compatibility with CPython (it respects
the Python semantic). There are still issues with Python JIT compilers
the Python semantics). There are still issues with Python JIT compilers
which avoid them to be widely used instead of CPython.
Many popular libraries like numpy, PyGTK, PyQt, PySide and wxPython are