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In Python, iterators are objects representing streams of data. [7] ... Users can create custom iterators by creating a type implementing the Iterator trait.
It implicitly calls the IntoIterator::into_iter method on the expression, and uses the resulting value, which must implement the Iterator trait. If the expression is itself an iterator, it is used directly by the for loop through an implementation of IntoIterator for all Iterators that returns the iterator unchanged.
For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per iteration. The header often declares an explicit loop counter or loop variable. This allows the body to know which iteration is being executed.
In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
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.
In some (non-polling) implementations of the publish-subscribe pattern, this is solved by creating a dedicated message queue server (and sometimes an extra message handler object) as an extra stage between the observer and the object being observed, thus decoupling the components. In these cases, the message queue server is accessed by the ...
Instead of creating print methods for each node subclass (Wheel, Engine, Body, and Car), one visitor class (CarElementPrintVisitor) performs the required printing action. Because different node subclasses require slightly different actions to print properly, CarElementPrintVisitor dispatches actions based on the class of the argument passed to ...
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})