Possible with pure, especially with regard to memory allocation.Īt exit from an immutably pure function, all memory allocated by that function and its subfunctions can be collected, except for anything which is reachable through the function return value.Įven for a weakly-pure function, the set of roots for gc is limited to However, several other very interesting optimisations are I agree with this, especially with regard to memoization. > I suspect all these considerations might be very difficult to guarantee on a non-VM environment. For this to happen, amongst other things the compiler and OS would need to ensure that the spawned threads would not starve the rest of the threads of that program. > The consequences for program and whole-machine scheduling would not be trivial and easy to understand. > Similarly for parallelism, how would the compiler know that it's ok to spawn 10 or 100 new threads to parallelize the execution of some loop? I doubt we would ever have something like memoization, which would incur memory costs (potentially quite big ones), and so the compiler almost certainly would not be able to know (without additional metadata/anotations or compile options) if that trade-off is acceptable. > Caching might be done, but only a temporary sense (caching under a limited execution scope). > we could expect from a D compiler and pure functions. > I think we need to be more realistic with what kinds of optimizations > would have to declare all its inputs immutable or use an appropriate In order to guarantee a function is strongly pure, one > these guarantees, but allow a much larger number of functions to be Weakly-pure functions, don't provide either of > that pure does today and can be automatically parallelized or cached Strongly-pure functions provide all the guarantees > This division is internal to the compiler, and isn't expressed in the > up into two groups (weak and strong) based on their function signatures. In long the proposal is for pure functions become broken So we're giving up on the "can parallelize with no > On topic: this means a pure function can take a reference to data that The first feature (max number of items using LRU) may be done wrapping the associative array keys inside a linked list. An optional max number of bytes used by the cache (this is not present in Python std lib, but I have found this useful). An optional max number of items stored in the cache, using a LRU strategy (Python 3.2 standard library has this). If you want to add other features to a memoizing function, here are two useful features: If the programmer wants to use floats, then it's not the job of the memoizing function to define tolerances, etc. For other types you need to make sure there's no undue aliasing, etc. For example, for doubles you'd need to do some interpolation and there are several ways of interpolating. Whether you've seen dozens of Say Yes to the Dress episodes or haven't watched one, you may now find yourself a little (or a lot) more interested in wedding movies and shows.> Speaking of which - memoization should be implementable safely and efficiently in a library. You'll watch wedding movies and TV shows differently. If you agree with the advice, take it if not, thank them and move on with your plans. Graciously accept it as a sign of their friendship-there's no need to get defensive. Our Advice: If a friend offers wedding planning advice (like, "You shouldn't invite kids to your wedding," or anything else that starts with, "You should/shouldn't."), take it in stride. Others may just think they're doing you a favor. Some friends may be going through the postwedding blues and miss the excitement of planning their own weddings. There are plenty of reasons this happens. Recently married friends will suddenly become wedding planning experts and give you (oftentimes unsolicited) advice. Our Advice: Lean on the friends who express excitement for you (and celebrate your newly-engaged status often!).
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