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classification
Title: functools.lru_cache: a way to set decorator arguments at runtime
Type: enhancement Stage: test needed
Components: Versions: Python 3.6
process
Status: closed Resolution: rejected
Dependencies: Superseder:
Assigned To: rhettinger Nosy List: Marek Otahal, r.david.murray, rhettinger
Priority: low Keywords:

Created on 2015-08-31 15:47 by Marek Otahal, last changed 2022-04-11 14:58 by admin. This issue is now closed.

Messages (8)
msg249406 - (view) Author: Marek Otahal (Marek Otahal) Date: 2015-08-31 15:47
I'd like to use @lru_cache in a library. The problem is I can't know the optimal values for 'maxsize', I need to set them at runtime. 

I came with 2 possibilities: 
1/ set cache's size from a hardcoded argument of the decorated method: 
@lru_cache
def foo_long(self, arg1, ..., **kwds):
  pass

# use
foo_long('hi', cacheSize = 1000)

This approach allows the users to customize cache size for their problem. 

2/ from function's **kwds retrieve a name (string) of an instance member of the class which will hold the cache's size value. This is not as clean as 1/, but offers greated functionality for the use in a library sw: we can compute desired cache size from internal values of the unstance, and the use of cache can be totally transparent to the end user: 
@lru_cache
def foo_long(self, arg1, .. , **kwds)
#use
foo_long('hi', cacheSizeRef='_cacheSize')

What do you think about the proposal? 
best regards, Mark
msg249407 - (view) Author: R. David Murray (r.david.murray) * (Python committer) Date: 2015-08-31 15:54
How is (1) different from:

  @lru_cache(maxsize=1000)
   def foo_long(self, arg1...)

As for computing it at runtime: if you need to compute it, you can compute it and *then* define the decorator wrapped function.
msg249408 - (view) Author: Marek Otahal (Marek Otahal) Date: 2015-08-31 16:00
Hope this example is not too confusing, it's a patch to my code and lru_cache (backport for python 2.7 from ActiveState)

It implements both approaches as highlighted above, and in the test both of them are used (that does not make much sense, normally one would use either of them only)
msg249409 - (view) Author: Marek Otahal (Marek Otahal) Date: 2015-08-31 16:09
Hi David, 

> How is (1) different from:
  @lru_cache(maxsize=1000)
   def foo_long(self, arg1...)

As I mentioned, for use in a library that is called by end-users. They can call functions and modify params, but do not edit the code. It's up to me (lib devs) to prepare the cache decorator. Ie.:
class MyLib():
  @lru_cache
  def foo_long(self, arg1, **kwds):
    pass
#user
import MyLib 
i = MyLib()
i.foo_long(1337)

> As for computing it at runtime: if you need to compute it, you can compute it and *then* define the decorator wrapped function.

ditto as above, at runtime no new decorator definitions should be needed for a library. 
+ a speed penalty, I'd have to wrap a wrapper in 1 or 2 more nested functions, which incures a speed penalty, and we're focusing at cache here. I esp. mention this as I've noticed the ongoing effort to use a C implementation of lru_cache here.
msg249410 - (view) Author: Marek Otahal (Marek Otahal) Date: 2015-08-31 16:15
EDIT: 
> i.foo_long(1337)

ofc, this should be: 
i.foo_long('hi', cacheSize=1337)

or for (2): 

class MyLib():
  def __init__(arg1, arg2):
    self._cacheSize = someComputation(arg1, arg2) # returns a number
  @lru_cache
  def foo_long(self, arg1, **kwds):
    pass
#user
import MyLib 
i = MyLib(100, 21)
# not to make it so simple: 
i.changeInternalStateSomehow() # updates arg1, arg2, and also _cacheSize
i.foo_long(1337, cacheSizeName='_cacheSize') # ref to self._cacheSize
msg249421 - (view) Author: R. David Murray (r.david.murray) * (Python committer) Date: 2015-08-31 18:53
There is no patch/example attached. 

It seems like what you really want is an API on lru_cache for updating the cache size.

What I'm saying is that the cache size can be passed in on the MyLib call, and the decorator/function constructed as part of MyLib's initialization.
msg249447 - (view) Author: Raymond Hettinger (rhettinger) * (Python committer) Date: 2015-09-01 02:57
> The problem is I can't know the optimal values for 'maxsize',
> I need to set them at runtime. 

The easiest way to go is to wait to start caching until you know the cache size you want:
   
   def foo(a, b, c):
        pass

   size = get_user_request()
   foo = lru_cache(foo, maxsize=size)

If there is a subsequent need to change the cache size, just rewrap it:

   size = get_user_request()
   original_function = foo.__wrapped__
   foo = lru_cache(foo, maxsize=size)
msg249933 - (view) Author: Raymond Hettinger (rhettinger) * (Python committer) Date: 2015-09-05 21:47
Sorry, I'm going to reject this one.  This option was considered during the design of the LRU cache and not included because it complicated the design, because the use cases were not common (the norm is set and forget), and because the __wrapped__ attribute provides a means of rewrapping or unwrapping as needed (i.e. there are reasonable workarounds).
History
Date User Action Args
2022-04-11 14:58:20adminsetgithub: 69157
2015-09-05 21:47:38rhettingersetstatus: open -> closed
resolution: rejected
messages: + msg249933
2015-09-04 18:26:29terry.reedysetstage: test needed
2015-09-01 02:57:05rhettingersetpriority: normal -> low

messages: + msg249447
2015-09-01 02:50:29rhettingersetassignee: rhettinger

nosy: + rhettinger
versions: + Python 3.6
2015-08-31 18:53:33r.david.murraysetmessages: + msg249421
2015-08-31 16:15:19Marek Otahalsetmessages: + msg249410
2015-08-31 16:09:12Marek Otahalsetmessages: + msg249409
2015-08-31 16:00:01Marek Otahalsetmessages: + msg249408
2015-08-31 15:54:08r.david.murraysetnosy: + r.david.murray
messages: + msg249407
2015-08-31 15:47:20Marek Otahalcreate