CodeTools TutorialΒΆ

Namespaces are one honking great idea — let’s do more of those!

—Tim Peters, The Zen of Python (PEP 20)

This tutorial introduces the key concepts behind the CodeTools modules, as well as highlighting some of their potential applications. This tutorial assumes some familiarity with Traits, and uses Chaco to illustrate some potential uses. Some familiarity with Numpy is also potentially useful for the more involved examples.

The two building-blocks of the CodeTools system are the Block class and the DataContext class (and its various subclasses).

A Block object simply holds a set of executable content, such as might be run by a Python exec command. However, unlike a simple code string, the Block object performs analysis of the code it contains so that it can identify which of its variables depend on which other variables.

A DataContext can be thought of as a Traits-aware dictionary object. The base DataContext simply emits Traits events whenever an item is added, modified or deleted. Subclasses allow more sophisticated actions to take place on access or modification.

This system of code and data objects evolved out of Enthought’s scientific applications as a common pattern where a series of computationally expensive transformations and calculations needed to be repeatedly performed on different sets of data. These calculations often involved with simple permutations of inputs into the calculation blocks, and often were applied in interactive situations where responsiveness is important. The Block object, by being aware of how data flows through the code that it contains, can restrict the code that it actually needs to execute based on a permutation of an input. The DataContext, by being able to trigger Traits events whenever it changes, can call upon a Block to recalculate dependent variables, and user-interface objects can listen to the events it generates to update based upon changes in its namespace.

Subclasses of the DataContext class extend its functionality to provide functionality such as unit conversion, data masking, name translation and datatype separation.

Put together, these concepts allow the creation of applications where the science code and the underlying application code are kept almost completely separate.

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