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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.
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 uses an English-based syntax. Haskell replaces the set-builder's braces with square brackets and uses symbols, including the standard set-builder vertical bar. The same can be achieved in Scala using Sequence Comprehensions, where the "for" keyword returns a list of the yielded variables using the "yield" keyword. [6]
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 ).
Python list comprehensions (such as [x*x for x in range(10)] for a list of squares) and decorators (such as @staticmethod). In Haskell, a string, denoted in quotation marks, is semantically equivalent to a list of characters.
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})
(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 ...