On Wed, Aug 26, 2015 at 5:18 PM, Denis Akhiyarov <denis.akhiya...@gmail.com>
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 really be that much of an
improvement over LRU, at least using the formula that it uses, at least for
the case of caching SymPy objects directly (caching the output of functions
that compute SymPy objects may be different).
Aaron Meurer
> in conclusion:
>
> * counts_ops or time() can be used for computation cost.
>
> ** __sizeof__ or number of Basic sympy objects for memory cost.
>
> On Wednesday, August 26, 2015 at 3:57:48 PM UTC-5, Aaron Meurer wrote:
>>
>> The whole point of the cache is to speed things up.
>>
>> Aaron Meurer
>>
>> On Wed, Aug 26, 2015 at 2:33 PM, Denis Akhiyarov <denis.a...@gmail.com>
>> 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 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 possible to override __sizeof__ just like the __hash__
>>> function in sympy objects.
>>>
>>>
>>> On Wednesday, August 26, 2015 at 1:42:40 PM UTC-5, Aaron Meurer wrote:
>>>>
>>>> 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 <denis.a...@gmail.com
>>>> > wrote:
>>>>
>>>>> 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 also highly optimized: the hash is memoized and
>>>>>> stored
>>>>>> in __slots__.
>>>>>>
>>>>>> If we really cared about sizes of objects, we could probably do a
>>>>>> similar thing. And it is probably sufficient to use heuristics rather
>>>>>> than
>>>>>> a true sizeof.
>>>>>>
>>>>>> Aaron Meurer
>>>>>>
>>>>>> On Tue, Aug 25, 2015 at 6:12 PM, Denis Akhiyarov <
>>>>>> denis.a...@gmail.com> wrote:
>>>>>>
>>>>>>> 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 50.9 KiB
>>>>>>> 8 byte aligned
>>>>>>> 8 byte sizeof(void*)
>>>>>>> 1 object given
>>>>>>> 222 objects sized
>>>>>>> 1840 objects seen
>>>>>>> 24 recursion depth
>>>>>>>
>>>>>>> 15 profiles: total (% of grand total), average, and largest flat
>>>>>>> size: largest object
>>>>>>> 42 class sympy.core.assumptions.StdFactKB objects: 42048 or 41.1
>>>>>>> KiB (81%), 1001, 1632 or 1.6 KiB: {'prime': False, 'infinite': False,
>>>>>>> 'r....maginary': False, 'irrational': False} leng 32!
>>>>>>> 44 class str objects: 2632 or 2.6 KiB (5%), 59, 64: 'infinite'
>>>>>>> leng 9!
>>>>>>> 28 class tuple objects: 1888 or 1.8 KiB (4%), 67, 80:
>>>>>>> (sqrt((c/(3*a) - b**2/(9*a**2))**3 + (..../(2*a), b**3/(27*a**3),
>>>>>>> -b*c/(6*a**2)) leng 4
>>>>>>> 49 class int objects: 1848 or 1.8 KiB (4%), 37, 40:
>>>>>>> 5976377932654160047 leng 2!
>>>>>>> 12 class sympy.core.mul.Mul objects: 864 (2%), 72, 72:
>>>>>>> -(sqrt((c/(3*a) - b**2/(9*a**2))**3 + .... b*c/(6*a**2) +
>>>>>>> b**3/(27*a**3))**(1/3)
>>>>>>> 10 class sympy.core.power.Pow objects: 720 (1%), 72, 72:
>>>>>>> (sqrt((c/(3*a) - b**2/(9*a**2))**3 + (.... b*c/(6*a**2) +
>>>>>>> b**3/(27*a**3))**(1/3)
>>>>>>> 7 class sympy.core.numbers.Rational objects: 560 (1%), 80, 80:
>>>>>>> -1/9
>>>>>>> 5 class sympy.core.add.Add objects: 360 (1%), 72, 72: (c/(3*a) -
>>>>>>> b**2/(9*a**2))/(sqrt((c/(3*....*2) + b**3/(27*a**3))**(1/3) - b/(3*a)
>>>>>>> 4 class sympy.core.numbers.Integer objects: 352 (1%), 88, 88: -2
>>>>>>> 4 class pympler.asizeof._Slots objects: 336 (1%), 84, 88: ('p',
>>>>>>> 'q', '_assumptions', '_args', '_mhash') leng 4
>>>>>>> 4 class sympy.core.symbol.Symbol objects: 288 (1%), 72, 72: a
>>>>>>> 1 class sympy.core.numbers.NegativeOne object: 88 (0%), 88, 88:
>>>>>>> -1
>>>>>>> 1 class sympy.core.numbers.Half object: 80 (0%), 80, 80: 1/2
>>>>>>> 2 class bool objects: 56 (0%), 28, 32: True
>>>>>>> 1 class NoneType object: 16 (0%), 16, 16: None
>>>>>>>
>>>>>>> 42 static types: basicsize, itemsize, _len_(), _refs()
>>>>>>> class Exception: 88, 0, n/a, _exc_refs
>>>>>>> class NoneType: 16, 0, n/a, n/a
>>>>>>> class NotImplementedType: 16, 0, n/a, n/a
>>>>>>> class Struct: 56, 1, _len_struct, n/a
>>>>>>> class array.array: 64, 1, _len_array, n/a
>>>>>>> class bool: 32, 4, n/a, n/a
>>>>>>> class bytearray: 56, 1, _len_bytearray, n/a
>>>>>>> class bytearray_iterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class callable_iterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class complex: 32, 0, n/a, n/a
>>>>>>> class dict: 64, 24, _len_dict, _dict_refs
>>>>>>> class dict_itemiterator: 80, 0, _len_iter, _iter_refs
>>>>>>> class dict_keyiterator: 80, 0, _len_iter, _iter_refs
>>>>>>> class dict_valueiterator: 80, 0, _len_iter, _iter_refs
>>>>>>> class ellipsis: 16, 0, n/a, n/a
>>>>>>> class enumerate: 72, 0, n/a, _enum_refs
>>>>>>> class float: 24, 0, n/a, n/a
>>>>>>> class frozenset: 224, 16, _len_set, _seq_refs
>>>>>>> class getset_descriptor: 72, 0, n/a, n/a
>>>>>>> class int: 24, 4, _len_int, n/a
>>>>>>> class list: 64, 8, _len_list, _seq_refs
>>>>>>> class list_iterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class list_reverseiterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class mappingproxy: 48, 24, _len_dict, _dict_refs
>>>>>>> class member_descriptor: 72, 0, n/a, n/a
>>>>>>> class module: 88, 48, _len_module, _module_refs
>>>>>>> class os.stat_result: 48, 8, n/a, _stat_refs
>>>>>>> class property: 80, 0, n/a, _prop_refs
>>>>>>> class pympler.asizeof._Slots: 56, 8, _len_slots, n/a
>>>>>>> class range: 48, 0, n/a, n/a
>>>>>>> class reversed: 56, 0, n/a, _enum_refs
>>>>>>> class set: 224, 16, _len_set, _seq_refs
>>>>>>> class set_iterator: 72, 0, _len_iter, _iter_refs
>>>>>>> class slice: 40, 8, _len_slice, n/a
>>>>>>> class str: 80, 2, _len_unicode, n/a
>>>>>>> class str_iterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class traceback: 64, 0, n/a, _tb_refs
>>>>>>> class tuple: 48, 8, _len, _seq_refs
>>>>>>> class tuple_iterator: 56, 0, _len_iter, _iter_refs
>>>>>>> class weakproxy: 80, 0, n/a, n/a
>>>>>>> class weakref: 80, 0, n/a, _weak_refs
>>>>>>> class weakref.KeyedRef: 88, 0, n/a, _weak_refs
>>>>>>>
>>>>>>> 8 dynamic types: basicsize, itemsize, _len_(), _refs()
>>>>>>> class sympy.core.add.Add: 72, 0, n/a, _inst_refs
>>>>>>> class sympy.core.mul.Mul: 72, 0, n/a, _inst_refs
>>>>>>> class sympy.core.numbers.Half: 80, 0, n/a, _inst_refs
>>>>>>> class sympy.core.numbers.Integer: 88, 0, n/a, _inst_refs
>>>>>>> class sympy.core.numbers.NegativeOne: 88, 0, n/a, _inst_refs
>>>>>>> class sympy.core.numbers.Rational: 80, 0, n/a, _inst_refs
>>>>>>> class sympy.core.power.Pow: 72, 0, n/a, _inst_refs
>>>>>>> class sympy.core.symbol.Symbol: 72, 0, n/a, _inst_refs
>>>>>>>
>>>>>>> 1 derived type: basicsize, itemsize, _len_(), _refs()
>>>>>>> class sympy.core.assumptions.StdFactKB: 64, 24, _len_dict,
>>>>>>> _dict_refs
>>>>>>>
>>>>>>> 4 dict/-like classes:
>>>>>>> UserDict: (IterableUserDict, UserDict)
>>>>>>> weakref: (WeakKeyDictionary, WeakValueDictionary)
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Tuesday, August 25, 2015 at 11:38:45 AM UTC-5, Peter Brady wrote:
>>>>>>>
>>>>>>>> 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 [2]: from sympy.abc import a, b, c, d, e, x, y
>>>>>>>>
>>>>>>>> In [3]: from pympler.asizeof import asizeof
>>>>>>>>
>>>>>>>> In [4]: y=a*x**3+b*x**2+c*x+d
>>>>>>>>
>>>>>>>> In [5]: y1, y2, y3 = sympy.solve(y, x, check=False)
>>>>>>>>
>>>>>>>> In [6]: %time asizeof(y1)
>>>>>>>> CPU times: user 9.63 ms, sys: 0 ns, total: 9.63 ms
>>>>>>>> Wall time: 9.56 ms
>>>>>>>> Out[6]: 52608
>>>>>>>>
>>>>>>>> In [7]: %time hash(y1)
>>>>>>>> CPU times: user 14 µs, sys: 1 µs, total: 15 µs
>>>>>>>> Wall time: 19.8 µs
>>>>>>>> Out[7]: 5743556980832125790
>>>>>>>>
>>>>>>>> In [8]: y=a*x**4+b*x**3+c*x**2+d*x+e
>>>>>>>>
>>>>>>>> In [9]: y1,y2,y3,y4=sympy.solve(y,x,check=False)
>>>>>>>>
>>>>>>>> In [10]: %time asizeof(y4)
>>>>>>>> CPU times: user 16.7 ms, sys: 2.05 ms, total: 18.8 ms
>>>>>>>> Wall time: 18.6 ms
>>>>>>>> Out[10]: 85208
>>>>>>>>
>>>>>>>> In [11]: %time hash(y4)
>>>>>>>> CPU times: user 14 µs, sys: 1 µs, total: 15 µs
>>>>>>>> Wall time: 19.8 µs
>>>>>>>> Out[11]: 4388441583750016728
>>>>>>>>
>>>>>>>>
>>>>>>>> On Mon, Aug 24, 2015 at 10:49 PM, Denis Akhiyarov <
>>>>>>>> denis.a...@gmail.com> wrote:
>>>>>>>>
>>>>>>>>> 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 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.
>>>>>>>>>>
>>>>>>>>> --
>>>>>>>>> You received this message because you are subscribed to a topic in
>>>>>>>>> the Google Groups "sympy" group.
>>>>>>>>> To unsubscribe from this topic, visit
>>>>>>>>> https://groups.google.com/d/topic/sympy/slKi02rzXVE/unsubscribe.
>>>>>>>>> To unsubscribe from this group and all its topics, send an email
>>>>>>>>> to sympy+un...@googlegroups.com.
>>>>>>>>> To post to this group, send email to sy...@googlegroups.com.
>>>>>>>>> Visit this group at http://groups.google.com/group/sympy.
>>>>>>>>> To view this discussion on the web visit
>>>>>>>>> https://groups.google.com/d/msgid/sympy/6e7f1a64-e8b9-46b9-9dd8-28f18de3a416%40googlegroups.com
>>>>>>>>> <https://groups.google.com/d/msgid/sympy/6e7f1a64-e8b9-46b9-9dd8-28f18de3a416%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>>>> .
>>>>>>>>>
>>>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>>>
>>>>>>>>
>>>>>>>> --
>>>>>>> You received this message because you are subscribed to the Google
>>>>>>> Groups "sympy" group.
>>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>>> send an email to sympy+un...@googlegroups.com.
>>>>>>> To post to this group, send email to sy...@googlegroups.com.
>>>>>>> Visit this group at http://groups.google.com/group/sympy.
>>>>>>> To view this discussion on the web visit
>>>>>>> https://groups.google.com/d/msgid/sympy/1ad279e2-41a6-44ec-bb8b-523b59cbca3b%40googlegroups.com
>>>>>>> <https://groups.google.com/d/msgid/sympy/1ad279e2-41a6-44ec-bb8b-523b59cbca3b%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>>> .
>>>>>>>
>>>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>>>
>>>>>>
>>>>>> --
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "sympy" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to sympy+un...@googlegroups.com.
>>>>> To post to this group, send email to sy...@googlegroups.com.
>>>>> Visit this group at http://groups.google.com/group/sympy.
>>>>> To view this discussion on the web visit
>>>>> https://groups.google.com/d/msgid/sympy/9dd5c8f6-29b7-40e8-91d5-9007a01b4605%40googlegroups.com
>>>>> <https://groups.google.com/d/msgid/sympy/9dd5c8f6-29b7-40e8-91d5-9007a01b4605%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>> .
>>>>>
>>>>> For more options, visit https://groups.google.com/d/optout.
>>>>>
>>>>
>>>> --
>>> You received this message because you are subscribed to the Google
>>> Groups "sympy" group.
>>> To unsubscribe from this group and stop receiving emails from it, send
>>> an email to sympy+un...@googlegroups.com.
>>> To post to this group, send email to sy...@googlegroups.com.
>>> Visit this group at http://groups.google.com/group/sympy.
>>> To view this discussion on the web visit
>>> https://groups.google.com/d/msgid/sympy/58b244c6-f5eb-4ea3-96be-1364eb0c2afd%40googlegroups.com
>>> <https://groups.google.com/d/msgid/sympy/58b244c6-f5eb-4ea3-96be-1364eb0c2afd%40googlegroups.com?utm_medium=email&utm_source=footer>
>>> .
>>>
>>> For more options, visit https://groups.google.com/d/optout.
>>>
>>
>> --
> You received this message because you are subscribed to the Google Groups
> "sympy" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to sympy+unsubscr...@googlegroups.com.
> To post to this group, send email to sympy@googlegroups.com.
> Visit this group at http://groups.google.com/group/sympy.
> To view this discussion on the web visit
> https://groups.google.com/d/msgid/sympy/75f26223-1a29-4961-8559-efa7c2cf61b8%40googlegroups.com
> <https://groups.google.com/d/msgid/sympy/75f26223-1a29-4961-8559-efa7c2cf61b8%40googlegroups.com?utm_medium=email&utm_source=footer>
> .
>
> For more options, visit https://groups.google.com/d/optout.
>
--
You received this message because you are subscribed to the Google Groups
"sympy" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to sympy+unsubscr...@googlegroups.com.
To post to this group, send email to sympy@googlegroups.com.
Visit this group at http://groups.google.com/group/sympy.
To view this discussion on the web visit
https://groups.google.com/d/msgid/sympy/CAKgW%3D6%2BusezCQ8bgdWze1gtqO943aYqqGWctW7%3DBxfZTaNxLSg%40mail.gmail.com.
For more options, visit https://groups.google.com/d/optout.
