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In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
Specifically, the for loop will call a value's into_iter() method, which returns an iterator that in turn yields the elements to the loop. The for loop (or indeed, any method that consumes the iterator), proceeds until the next() method returns a None value (iterations yielding elements return a Some(T) value, where T is the element type).
However, a generator is an object with persistent state, which can repeatedly enter and leave the same scope. A generator call can then be used in place of a list, or other structure whose elements will be iterated over. Whenever the for loop in the example requires the next item, the generator is called, and yields the next item.
State-based CRDTs (also called convergent replicated data types, or CvRDTs) are defined by two types, a type for local states and a type for actions on the state, together with three functions: A function to produce an initial state, a merge function of states, and a function to apply an action to update a state.
The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring). Elixir. The above trick used in Python also works in Elixir, but the compiler will throw a warning if it spots this.
In computer science, Luby transform codes (LT codes) are the first class of practical fountain codes that are near-optimal erasure correcting codes. They were invented by Michael Luby in 1998 and published in 2002. [1] Like some other fountain codes, LT codes depend on sparse bipartite graphs to trade reception overhead for encoding and ...
The transform can be interpreted as the multiplication of the vector (x 0, ...., x N−1) by an N-by-N matrix; therefore, the discrete Hartley transform is a linear operator. The matrix is invertible; the inverse transformation, which allows one to recover the x n from the H k, is simply the DHT of H k multiplied by 1/N.
The two examples below, written in Python, present a while loop with an inner for loop and a while loop without an inner loop. Although both have the same terminating condition for their while loops, the first example will finish faster because of the inner for loop. The variable innermax is a fraction of the maxticketno variable in the first ...