python Cachetools can items have different ttl?












1















Im using @cachetools.func.ttl_cache(maxsize=3, ttl=3600, timer=time.time, typed=False) to cache different data frames. The function being wrapped doesn't build the DF itself, but given an argument calls the right function.



Depending on the argument the DF may be time consuming or fast to build, given that I want to modify the item ttl (time-to-live). So that item 1 may have ttl=3600 while item 2 ttl=10800.



Is that functionality supported? using a global variable or any other way? docs






python pandas caching







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    1















    Im using @cachetools.func.ttl_cache(maxsize=3, ttl=3600, timer=time.time, typed=False) to cache different data frames. The function being wrapped doesn't build the DF itself, but given an argument calls the right function.



    Depending on the argument the DF may be time consuming or fast to build, given that I want to modify the item ttl (time-to-live). So that item 1 may have ttl=3600 while item 2 ttl=10800.



    Is that functionality supported? using a global variable or any other way? docs






    python pandas caching







    share|improve this question

























      1












      1








      1








      Im using @cachetools.func.ttl_cache(maxsize=3, ttl=3600, timer=time.time, typed=False) to cache different data frames. The function being wrapped doesn't build the DF itself, but given an argument calls the right function.



      Depending on the argument the DF may be time consuming or fast to build, given that I want to modify the item ttl (time-to-live). So that item 1 may have ttl=3600 while item 2 ttl=10800.



      Is that functionality supported? using a global variable or any other way? docs






      python pandas caching







      share|improve this question














      Im using @cachetools.func.ttl_cache(maxsize=3, ttl=3600, timer=time.time, typed=False) to cache different data frames. The function being wrapped doesn't build the DF itself, but given an argument calls the right function.



      Depending on the argument the DF may be time consuming or fast to build, given that I want to modify the item ttl (time-to-live). So that item 1 may have ttl=3600 while item 2 ttl=10800.



      Is that functionality supported? using a global variable or any other way? docs






      python pandas caching




      python pandas caching






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 21 '18 at 4:53









      Carlos P CeballosCarlos P Ceballos

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          No.



          You can, however, create your own custom caches for use with cachetools. You can check out the implementation of the ttlcache in ttl.py for an example. It's pretty straightforward.



          Unfortunately, the ttlcache itself isn't really designed in such a way that you could conveniently subclass it and override the logic that determines when items in the cache expire. It would be easy enough to just go in and tamper with the expiration dates for the links, but the fact that they used double underscores to prefix all the link-related logic is kind of a clue that the author really didn't want you to do that.



          I'd recommend just implementing your own cache.






          share|improve this answer























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            No.



            You can, however, create your own custom caches for use with cachetools. You can check out the implementation of the ttlcache in ttl.py for an example. It's pretty straightforward.



            Unfortunately, the ttlcache itself isn't really designed in such a way that you could conveniently subclass it and override the logic that determines when items in the cache expire. It would be easy enough to just go in and tamper with the expiration dates for the links, but the fact that they used double underscores to prefix all the link-related logic is kind of a clue that the author really didn't want you to do that.



            I'd recommend just implementing your own cache.






            share|improve this answer




























              0














              No.



              You can, however, create your own custom caches for use with cachetools. You can check out the implementation of the ttlcache in ttl.py for an example. It's pretty straightforward.



              Unfortunately, the ttlcache itself isn't really designed in such a way that you could conveniently subclass it and override the logic that determines when items in the cache expire. It would be easy enough to just go in and tamper with the expiration dates for the links, but the fact that they used double underscores to prefix all the link-related logic is kind of a clue that the author really didn't want you to do that.



              I'd recommend just implementing your own cache.






              share|improve this answer


























                0












                0








                0







                No.



                You can, however, create your own custom caches for use with cachetools. You can check out the implementation of the ttlcache in ttl.py for an example. It's pretty straightforward.



                Unfortunately, the ttlcache itself isn't really designed in such a way that you could conveniently subclass it and override the logic that determines when items in the cache expire. It would be easy enough to just go in and tamper with the expiration dates for the links, but the fact that they used double underscores to prefix all the link-related logic is kind of a clue that the author really didn't want you to do that.



                I'd recommend just implementing your own cache.






                share|improve this answer













                No.



                You can, however, create your own custom caches for use with cachetools. You can check out the implementation of the ttlcache in ttl.py for an example. It's pretty straightforward.



                Unfortunately, the ttlcache itself isn't really designed in such a way that you could conveniently subclass it and override the logic that determines when items in the cache expire. It would be easy enough to just go in and tamper with the expiration dates for the links, but the fact that they used double underscores to prefix all the link-related logic is kind of a clue that the author really didn't want you to do that.



                I'd recommend just implementing your own cache.







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Jan 27 at 8:41









                WillWill

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