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Method chaining is a common syntax for invoking multiple method calls in object-oriented programming languages. Each method returns an object, allowing the calls to be chained together in a single statement without requiring variables to store the intermediate results.
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.
Cascading can be implemented in terms of chaining by having the methods return the target object (receiver, this, self).However, this requires that the method be implemented this way already – or the original object be wrapped in another object that does this – and that the method not return some other, potentially useful value (or nothing if that would be more appropriate, as in setters).
However, a generator is an object with persistent state, which can repeatedly enter and leave the same scope. A generator call can then be used in place of a list, or other structure whose elements will be iterated over. Whenever the for loop in the example requires the next item, the generator is called, and yields the next item.
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]
In computer programming, the specification pattern is a particular software design pattern, whereby business rules can be recombined by chaining the business rules together using boolean logic. The pattern is frequently used in the context of domain-driven design.
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In Python, a generator is an iterator constructor: a function that returns an iterator. An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement follows: