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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 ...
One of the very useful aspects of Python is the concept of collection (or container) types. In general a collection is an object that contains other objects in a way that is easily referenced or indexed. Collections come in two basic forms: sequences and mappings. The ordered sequential types are lists (dynamic arrays), tuples, and strings.
The C language does not have collections or a foreach construct. However, it has several standard data structures that can be used as collections, and foreach can be made easily with a macro. However, two obvious problems occur: The macro is unhygienic: it declares a new variable in the existing scope which remains after the loop.
In computer programming, a weak reference is a reference that does not protect the referenced object from collection by a garbage collector, unlike a strong reference.An object referenced only by weak references – meaning "every chain of references that reaches the object includes at least one weak reference as a link" – is considered weakly reachable, and can be treated as unreachable and ...
The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]
Few cuts of meat feel as special as a ruby-red slice of prime rib, whether it’s served at a formal steakhouse, a Sunday afternoon buffet, or a holiday party.This well-marbled cut is flavorful ...
A collection may provide multiple iterators via its interface that provide items in different orders, such as forwards and backwards. An iterator is often implemented in terms of the structure underlying a collection implementation and is often tightly coupled to the collection to enable the operational semantics of the iterator.
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.