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List comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists. It follows the form of the mathematical set-builder notation (set comprehension) as distinct from the use of map and filter functions.
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
Foreach loops; While loops; For loops; ... List comprehension; ... List of "Hello World" programs; Comparison of individual languages.
Inline vs. prologue – an inline comment follows code on the same line and a prologue comment precedes program code to which it pertains; line or block comments can be used as either inline or prologue
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.
The types of objects that can be iterated across (my_list in the example) are based on classes that inherit from the library class ITERABLE. The iteration form of the Eiffel loop can also be used as a boolean expression when the keyword loop is replaced by either all (effecting universal quantification) or some (effecting existential ...
The example above, of list comprehension in the sin() function, is a useful feature in of itself. By using implicit parallelism, languages effectively have to provide such useful constructs to users simply to support required functionality (a language without a decent for loop, for example, is one few programmers will use).
The programming control structures on which autoparallelization places the most focus are loops, because, in general, most of the execution time of a program takes place inside some form of loop. There are two main approaches to parallelization of loops: pipelined multi-threading and cyclic multi-threading. [3]