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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.
Introduced in Python 2.4, generator expressions are the lazy evaluation equivalent of list comprehensions. Using the prime number generator provided in the above section, we might define a lazy, but not quite infinite collection.
a declarator_list is a comma-separated list of declarators, which can be of the form identifier As object_creation_expression (object initializer declarator) , modified_identifier «As non_array_type « array_rank_specifier »»« = initial_value» (single declarator) , or
Python's is operator may be used to compare object identities (comparison by reference), and comparisons may be chained—for example, a <= b <= c. Python uses and, or, and not as Boolean operators. Python has a type of expression named a list comprehension, and a more general expression named a generator expression. [78]
The else clause in the above example is linked to the for statement, and not the inner if statement. Both Python's for and while loops support such an else clause, which is executed only if early exit of the loop has not occurred. Some languages support breaking out of nested loops; in theory circles, these are called multi-level breaks.
Python The use of the triple-quotes to comment-out lines of source, does not actually form a comment. [ 19 ] 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 ).
In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop.All generators are also iterators. [1] A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values.