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A mechanism for maintaining consistency betweeninter-dependant values with caching and lazy evaluation You can think of Cellulose like a spreadsheet program: many cells are are calculated from the values of other cells. When one cell changes, all of the dependant cells get updated with new values.However, Cellulose goes quite a ways beyond this. It guarantees that when a value is read, it is consistant with all the values it depends on. Cellulose also is lazy (read: efficient.) Calculating a value is put off till the very last possible moment, and only recalculated when absolutely needed.Cache invalidation and dependency discovery are fully transparent and automatic. This greatly reduces a major source of bugs in software.A goal of the project is to be as simple as possible, (but no simpler,) so that anyone wanting to seriously use it could easily understand the internals.Cellulose is similar in purpose to PyCells, but is in a way 'lower level'. It tries real hard to stay out of your way, but, as a result, lacks some of the helpers that PyCells provides. The most essential algorithmic difference is probably that Cellulose desperately wants to be lazy, while in PyCells everything is calculated immediately (by default.) (On the flipside of this, observers in PyCells are quite a bit easier to work with.) What's New in This Release: · All tests pass with Python 2.5. · ComputedCell is now thread safe. · ComputedDict is now a little more friendly for subclassing. · The 'restrictions' functionality has been moved into it's own set of classes. · InputCellDescriptor will now take a default value. · Cell descriptors in general are easier to subclass. · DependantCell.dependency_changed now takes the dependency as an argument.

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