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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.
Method chaining, also known as named parameter idiom, 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.
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).
Exception chaining, or exception wrapping, is an object-oriented programming technique of handling exceptions by re-throwing a caught exception after wrapping it inside a new exception. The original exception is saved as a property (such as cause) of the new exception. The idea is that a method should throw exceptions defined at the same ...
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.
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.
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]
One example of how this can be used is to restore an object to its previous state (undo via rollback), another is versioning, another is custom serialization. The memento pattern is implemented with three objects: the originator, a caretaker and a memento. The originator is some object that has an internal state.