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Wed Nov 4 15:34:24 EST 2015 · https://mail.python.org/pipermail/python-dev/2015-November/142118.html

typo: "chance" instead of "change"

On 04.11.2015 21:14, Sven R. Kunze wrote:
> Hi Victor,
>
> great to hear. I think everybody here appreciates your efforts.
>
> Do you think there will be any change of merging this back into CPython?
>
> Best,
> Sven
>
> On 04.11.2015 09:50, Victor Stinner wrote:
>> Hi,
>>
>> I'm writing a new "FAT Python" project to try to implement 
>> optimizations in CPython (inlining, constant folding, move invariants 
>> out of loops, etc.) using a "static" optimizer (not a JIT). For the 
>> background, see the thread on python-ideas:
>> https://mail.python.org/pipermail/python-ideas/2015-October/036908.html
>>
>> See also the documentation:
>> https://hg.python.org/sandbox/fatpython/file/tip/FATPYTHON.rst
>> https://hg.python.org/sandbox/fatpython/file/tip/ASTOPTIMIZER.rst
>>
>> I implemented the most basic optimization to test my code: replace 
>> calls to builtin functions (with constant arguments) with the result. 
>> For example, len("abc") is replaced with 3. I reached the second 
>> milestone: it's now possible to run the full Python test suite with 
>> these optimizations enabled. It confirms that the optimizations don't 
>> break the Python semantic.
>>
>> Example:
>> ---
>> >>> def func():
>> ...     return len("abc")
>> ...
>> >>> import dis
>> >>> dis.dis(func)
>>   2           0 LOAD_GLOBAL              0 (len)
>>               3 LOAD_CONST               1 ('abc')
>>               6 CALL_FUNCTION            1 (1 positional, 0 keyword pair)
>>               9 RETURN_VALUE
>>
>> >>> len(func.get_specialized())
>> 1
>> >>> specialized=func.get_specialized()[0]
>> >>> dis.dis(specialized['code'])
>>   2           0 LOAD_CONST               1 (3)
>>               3 RETURN_VALUE
>> >>> len(specialized['guards'])
>> 2
>>
>> >>> func()
>> 3
>>
>> >>> len=lambda obj: "mock"
>> >>> func()
>> 'mock'
>> >>> func.get_specialized()
>> []
>> ---
>>
>> The function func() has specialized bytecode which returns directly 3 
>> instead of calling len("abc"). The specialized bytecode has two 
>> guards dictionary keys: builtins.__dict__['len'] and 
>> globals()['len']. If one of these keys is modified, the specialized 
>> bytecode is simply removed (when the function is called) and the 
>> original bytecode is executed.
>>
>>
>> You cannot expect any speedup at this milestone, it's just to 
>> validate the implementation. You can only get speedup if you 
>> implement *manually* optimizations. See for example posixpath.isabs() 
>> which inlines manually the call to the _get_sep() function. More 
>> optimizations will be implemented in the third milestone. I don't 
>> know yet if I will be able to implement constant folding, function 
>> inlining and/or moving invariants out of loops.
>>
>>
>> Download, compile and test FAT Python with:
>>
>>     hg clone http://hg.python.org/sandbox/fatpython
>>     ./configure && make && ./python -m test test_astoptimizer test_fat
>>
>>
>> Currently, only 24 functions are specialized in the standard library. 
>> Calling a builtin function with constant arguments in not common (it 
>> was expected, it's only the first step for my optimizer). But 161 
>> functions are specialized in tests.
>>
>>
>> To be honest, I had to modify some tests to make them pass in FAT 
>> mode. But most changes are related to the .pyc filename, or to the 
>> exact size in bytes of dictionary objects.
>>
>> FAT Python is still experimental. Currently, the main bug is that the 
>> AST optimizer can optimize a call to a function which is not the 
>> expected builtin function. I already started to implement code to 
>> understand namespaces (detect global and local variables), but it's 
>> not enough yet to detect when a builtin is overriden. See TODO.rst 
>> for known bugs and limitations.
>>
>> Victor
>>
>>
>> _______________________________________________
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>
>
>
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[Python-Dev] Second milestone of FAT Python