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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 ...
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.
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.
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 quantification). This iteration is a boolean expression which is true if all items in my_list have counts greater than three:
a b c Deep breaks may be accomplished in APL, C, C++ and C# through the use of labels and gotos. a Iteration over objects was added in PHP 5. a b c A counting loop can be simulated by iterating over an incrementing list or generator, for instance, Python's range() .
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
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.
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.