lazy-evaluation

问题 How does subscripting a lazy filter work? let ary = [0,1,2,3] let empty = ary.lazy.filter { $0 > 4 }.map { $0 + 1 } print(Array(empty)) // [] print(empty[2]) // 3 It looks like it just ignores the filter and does the map anyway. Is this documented somewhere? What other lazy collections have exceptional behavior like this? 回答1: It comes down to subscripting a LazyFilterCollection with an integer which in this case ignores the predicate and forwards the subscript operation to the base. For

问题 How does subscripting a lazy filter work? let ary = [0,1,2,3] let empty = ary.lazy.filter { $0 > 4 }.map { $0 + 1 } print(Array(empty)) // [] print(empty[2]) // 3 It looks like it just ignores the filter and does the map anyway. Is this documented somewhere? What other lazy collections have exceptional behavior like this? 回答1: It comes down to subscripting a LazyFilterCollection with an integer which in this case ignores the predicate and forwards the subscript operation to the base. For

问题 On the MSDN documentation for Lazy.Force<T> extension method says: Forces the execution of this value and returns its result. Same as Value. Mutual exclusion is used to prevent other threads from also computing the value. Does it mean that it's equivalent to creating a Lazy<T> instance with ExecutionAndPublication LazyThreadSafetyMode so that only one thread can initialize the instance? Thanks 回答1: Yes. They are both the same, and both make sure that the value will be computed only once. 回答2:

问题 Set up: Similar to this question on a MSDN forum, I have a measure that switches between various other measures (some of them much more complex than others). The measure looks like this (my actual measure has more cases): VariableMeasure = VAR ReturnType = SELECTEDVALUE ( ParamReturnType[ReturnType] ) SWITCH ( ReturnType, "NAV", [Nav], "Income", [Income], "ROI", [Roi], "BM", [Benchmark], BLANK () ) Context: The reason for the switching measure is to have the ability to choose which measures

问题 Recently, I've come across a piece of code like this (not the real one, but a shorter example based upon it): #include <stdio.h> int main() { int n; printf ("n? "); scanf ("%d", &n); n%2 && printf ("N is odd\n"); /* <-- this is it */ return 0; } In case anybody didn't get it, this code is the equivalent of: int main() { int n; printf ("n? "); scanf ("%d", &n); if (n%2) printf ("N is odd\n"); return 0; } A disassembly of this code compiled with GCC 4.4.5-8 for x86-64 bits gives this for the

问题 In a .NET Core 2.1 project, I'm using EF Core with Command pattern (using MediatR library) on a SQL Server database. I setup the project to avoid client query evaluation, by using these settings: var phaseOptions = new DbContextOptionsBuilder<PhaseDbContext>().UseSqlServer(configuration.GetConnectionString("PhaseDbContext"), sqlServerOptions => sqlServerOptions .EnableRetryOnFailure( maxRetryCount: 5, maxRetryDelay: TimeSpan.FromSeconds(30), errorNumbersToAdd: null)) .ConfigureWarnings

问题 I am new to Scala and I just learned that LazyList was created to replace Stream , and at the same time they added the .view methods to all collections. So, I am wondering why was LazyList added to Scala collections library, when we can do List.view ? I just looked at the Scaladoc, and it seems that the only difference is that LazyList has memoization, while View does not. Am I right or wrong? 回答1: Stream elements are realized lazily except for the 1st (head) element. That was seen as a

问题 I'm following a book's example to implement a Steam class using lazy evaluation in Scala. sealed trait Stream[+A] case object Empty extends Stream[Nothing] case class Cons[+A](h: () => A, t: () => Stream[A]) extends Stream[A] object Stream { def cons[A](hd: => A, tl: => Stream[A]): Stream[A] = { lazy val head = hd lazy val tail = tl Cons(() => head, () => tail) } def empty[A]: Stream[A] = Empty def apply[A](as: A*): Stream[A] = { if (as.isEmpty) empty else cons(as.head, apply(as.tail: _*)) }

问题 I'm following a book's example to implement a Steam class using lazy evaluation in Scala. sealed trait Stream[+A] case object Empty extends Stream[Nothing] case class Cons[+A](h: () => A, t: () => Stream[A]) extends Stream[A] object Stream { def cons[A](hd: => A, tl: => Stream[A]): Stream[A] = { lazy val head = hd lazy val tail = tl Cons(() => head, () => tail) } def empty[A]: Stream[A] = Empty def apply[A](as: A*): Stream[A] = { if (as.isEmpty) empty else cons(as.head, apply(as.tail: _*)) }

问题 I'm using IO to encapsulate randomness. I am trying to write a method which iterates a next function n times, but the next function produces a result wrapped in IO because of the randomness. Basically, my next function has this signature: next :: IO Frame -> IO Frame and I want to start with an initial Frame , then use the same pattern as iterate to get a list [Frame] with length n . Essentially, I'd like to be able to write the following: runSimulation :: {- parameters -} -> IO [Frame]