Am 28.01.10 22:12, schrieb Yingjie Lan:
We all know that Python is dynamically typed, and dynamically typed languages
are generally slower than statically typed ones. I wonder if it is possible at
all for Python to mix statically-typed-ness with dynamically-typed-ness to
boost up its speed a little bit, especially when speed is needed. For example,
you define a function like this:
def speed(float dist, float time):
return dist/time
then the compiler would generate code to first check parameter types (or even
do some casts if appropriate, say cast an int into float) in the beginning of
this function. and the rest of the function would then be compiled with the
assumption that 'dist' and 'time' are of the type float.
Of course, dynamically-typed-ness is still the same as before. Python is well
known for providing multiple programming paradigms, I wonder if we could also
sneak this in nicely.
There are various attempts to achieve this.
The most generic one, which is most promising in the long run is PyPy,
the implementation of Python in itself, with the added benefit of making
code-generators that emit e.g. C based on Python-code.
Then there is Cython, which blends Python with C & integrates very nicely.
Last but not least, for you actual example, psyco is the easiest thing
to use, it's a JIT aimed to especially optimize numeric operations as
the one you present.
Diez
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