Search results
Results from the WOW.Com Content Network
If the expression is itself an iterator, it is used directly by the for loop through an implementation of IntoIterator for all Iterators that returns the iterator unchanged. The loop calls the Iterator::next method on the iterator before executing the loop body. If Iterator::next returns Some(_), the value inside is assigned to the pattern and ...
Iterating over a container is done using this form of loop: for e in c while w do # loop body od; The in c clause specifies the container, which may be a list, set, sum, product, unevaluated function, array, or object implementing an iterator. A for-loop may be terminated by od, end, or end do.
Some object-oriented languages such as C#, C++ (later versions), Delphi (later versions), Go, Java (later versions), Lua, Perl, Python, Ruby provide an intrinsic way of iterating through the elements of a collection without an explicit iterator. An iterator object may exist, but is not represented in the source code.
In mathematics, iteration may refer to the process of iterating a function, i.e. applying a function repeatedly, using the output from one iteration as the input to the next. Iteration of apparently simple functions can produce complex behaviors and difficult problems – for examples, see the Collatz conjecture and juggler sequences .
(with-hash-table-iterator (entry-generator phone-book) (loop do (multiple-value-bind (has-entry key value) (entry-generator) (if has-entry (format T "~&~s => ~s" key value) (loop-finish))))) It is easy to construct composite abstract data types in Lisp, using structures or object-oriented programming features, in conjunction with lists, arrays ...
A loop invariant is an assertion which must be true before the first loop iteration and remain true after each iteration. This implies that when a loop terminates correctly, both the exit condition and the loop invariant are satisfied. Loop invariants are used to monitor specific properties of a loop during successive iterations.
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.
Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...