As of 0.7.6 sympy uses an LRU cache by default. cachey looks interesting
but I think the "nbytes" may be challenging to compute for sympy objects
and operations.
There was some discussion of adopting a similar caching policy a while
ago: https://github.com/sympy/sympy/issues/6321
On Wednesd
Nbytes is very hard in Python, and getsizeof() does not work very well. People
has addressed this using github.com/pympler.
Not sure if anyone tried it on sympy objects and how costly is that
calculation. Cachey has very simple nbytes calculation, mainly intended for
numpy and pandas objects.
-
https://gist.github.com/denfromufa/4d0e6a94f70fac155b66.js";>
On Monday, August 24, 2015 at 10:03:30 PM UTC-5, Denis Akhiyarov wrote:
>
> Nbytes is very hard in Python, and getsizeof() does not work very well.
> People has addressed this using github.com/pympler.
> Not sure if anyone tried it
It looks like pympler works pretty well on sympy symbols, here is my
notebook:
https://gist.github.com/denfromufa/4d0e6a94f70fac155b66
On Monday, August 24, 2015 at 10:03:30 PM UTC-5, Denis Akhiyarov wrote:
>
> Nbytes is very hard in Python, and getsizeof() does not work very well.
> People ha
Thanks for trying that out. I had never heard of pympler before. The
current caching mechanism is based on hashing. By my tests,
'pympler.asizeof' is 500-1000x slower than hashing. That's a strong
deficit for cachey to overcome (as far as sympy objects are concerned).
In [1]: import sympy
In
pympler is very slow, hash is probably pure C, like fastcache.
But it is understandable why it can get slow for collecting all this
information in Python:
asizeof(y1,stats=8)
asizeof(((c/(3*a) - b**2/(9*a**2))/(sqrt((c/(3) + b**3/(27*a**3))**(1/3) -
b/(3*a),), stats=8) ...
52136 bytes or
Hashing in SymPy is done recursively (due to the nature of SymPy objects),
but amounts to hashes of tuples of integers and strings, which is done in
C. But it's also highly optimized: the hash is memoized and stored in
__slots__.
If we really cared about sizes of objects, we could probably do a si
That's a good point. I had forgotten that sympy optimized the hash
implementations.
On Tue, Aug 25, 2015 at 6:50 PM, Aaron Meurer wrote:
> Hashing in SymPy is done recursively (due to the nature of SymPy objects),
> but amounts to hashes of tuples of integers and strings, which is done in
> C.
what is the heuristic? number of **Basic** sympy objects?
On Tuesday, August 25, 2015 at 7:50:43 PM UTC-5, Aaron Meurer wrote:
>
> Hashing in SymPy is done recursively (due to the nature of SymPy objects),
> but amounts to hashes of tuples of integers and strings, which is done in
> C. But it's
Probably count_ops() would be a close approximation of both how expensive
an object is to create and how big it is (SymPy objects really shouldn't be
doing much computation at creation time).
Aaron Meurer
On Wed, Aug 26, 2015 at 12:51 PM, Denis Akhiyarov wrote:
> what is the heuristic? number o
1. regarding count_ops, are we now jumping to computation cost? :)
2. if size of sympy objects is proportional to computation cost involving
them, then cachey does not make sense for sympy at all.
3. not sure if computation cost should just be tracked using time()
function?
4. i think it is po
The whole point of the cache is to speed things up.
Aaron Meurer
On Wed, Aug 26, 2015 at 2:33 PM, Denis Akhiyarov
wrote:
> 1. regarding count_ops, are we now jumping to computation cost? :)
>
> 2. if size of sympy objects is proportional to computation cost involving
> them, then cachey does no
i agree, but cachey needs 2 main parameters as input: nbytes and
computation cost.
so using count_ops for both parameters is like reducing the formula down to
LRU or something similar.
in conclusion:
* counts_ops or time() can be used for computation cost.
** __sizeof__ or number of Basic sym
On Wed, Aug 26, 2015 at 5:18 PM, Denis Akhiyarov
wrote:
> i agree, but cachey needs 2 main parameters as input: nbytes and
> computation cost.
>
> so using count_ops for both parameters is like reducing the formula down
> to LRU or something similar.
>
I think you're right. Cachey would not real
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