The Traits package for the Python language allows Python programmers to use a special kind of type definition called a trait. This document introduces the concepts behind, and usage of, the Traits package.
For more information on the Traits package, refer to the Traits GitHub repository. Additional documentation for the Traits package is available, including:
- Traits API Reference
- TraitsUI User Manual
- Traits Technical Notes
What Are Traits?¶
A trait is a type definition that can be used for normal Python object attributes, giving the attributes some additional characteristics:
- Initialization: A trait has a default value, which is automatically set as the initial value of an attribute, before its first use in a program.
- Validation: A trait attribute is explicitly typed. The type of a trait-based attribute is evident in the code, and only values that meet a programmer-specified set of criteria (i.e., the trait definition) can be assigned to that attribute. Note that the default value need not meet the criteria defined for assignment of values. Traits 4.0 also supports defining and using abstract interfaces, as well as adapters between interfaces.
- Deferral: The value of a trait attribute can be contained either in the defining object or in another object that is deferred to by the trait.
- Notification: Setting the value of a trait attribute can notify other parts of the program that the value has changed.
- Visualization: User interfaces that allow a user to interactively modify the values of trait attributes can be automatically constructed using the traits’ definitions. This feature requires that a supported GUI toolkit be installed. However, if this feature is not used, the Traits package does not otherwise require GUI support. For details on the visualization features of Traits, see the TraitsUI User Manual.
A class can freely mix trait-based attributes with normal Python attributes, or can opt to allow the use of only a fixed or open set of trait attributes within the class. Trait attributes defined by a class are automatically inherited by any subclass derived from the class.
The following example  illustrates each of the features of the Traits package. These features are elaborated in the rest of this guide.
# all_traits_features.py --- Shows primary features of the Traits # package from traits.api import Delegate, HasTraits, Instance,\ Int, Str class Parent ( HasTraits ): # INITIALIZATION: last_name' is initialized to '': last_name = Str( '' ) class Child ( HasTraits ): age = Int # VALIDATION: 'father' must be a Parent instance: father = Instance( Parent ) # DELEGATION: 'last_name' is delegated to father's 'last_name': last_name = Delegate( 'father' ) # NOTIFICATION: This method is called when 'age' changes: def _age_changed ( self, old, new ): print 'Age changed from %s to %s ' % ( old, new ) # Set up the example: joe = Parent() joe.last_name = 'Johnson' moe = Child() moe.father = joe # DELEGATION in action: print "Moe's last name is %s " % moe.last_name # Result: # Moe's last name is Johnson # NOTIFICATION in action moe.age = 10 # Result: # Age changed from 0 to 10 # VISUALIZATION: Displays a UI for editing moe's attributes # (if a supported GUI toolkit is installed) moe.configure_traits()
Python does not require the data type of variables to be declared. As any experienced Python programmer knows, this flexibility has both good and bad points. The Traits package was developed to address some of the problems caused by not having declared variable types, in those cases where problems might arise. In particular, the motivation for Traits came as a direct result of work done on Chaco, an open source scientific plotting package.
Chaco provides a set of high-level plotting objects, each of which has a number of user-settable attributes, such as line color, text font, relative location, and so on. To make the objects easy for scientists and engineers to use, the attributes attempt to accept a wide variety and style of values. For example, a color-related attribute of a Chaco object might accept any of the following as legal values for the color red:
- ( 1.0, 0.0, 0.0, 1.0 )
Thus, the user might write:
plotitem.color = 'red'
In a predecessor to Chaco, providing such flexibility came at a cost:
- When the value of an attribute was used by an object internally (for example, setting the correct pen color when drawing a plot line), the object would often have to map the user-supplied value to a suitable internal representation, a potentially expensive operation in some cases.
- If the user supplied a value outside the realm accepted by the object internally, it often caused disastrous or mysterious program behavior. This behavior was often difficult to track down because the cause and effect were usually widely separated in terms of the logic flow of the program.
So, one of the main goals of the Traits package is to provide a form of type checking that:
- Allows for flexibility in the set of values an attribute can have, such as allowing ‘red’, 0xFF0000 and ( 1.0, 0.0, 0.0, 1.0 ) as equivalent ways of expressing the color red.
- Catches illegal value assignments at the point of error, and provides a meaningful and useful explanation of the error and the set of allowable values.
- Eliminates the need for an object’s implementation to map user-supplied attribute values into a separate internal representation.
In the process of meeting these design goals, the Traits package evolved into a useful component in its own right, satisfying all of the above requirements and introducing several additional, powerful features of its own. In projects where the Traits package has been used, it has proven valuable for enhancing programmers’ ability to understand code, during both concurrent development and maintenance.
The Traits 4.0 package works with version 2.7 and later of Python, and is similar in some ways to the Python property language feature. Standard Python properties provide the similar capabilities to the Traits package, but with more work on the part of the programmer.
All code examples in this guide that include a file name are also available as examples in the tutorials/doc_examples/examples subdirectory of the Traits docs directory. You can run them individually, or view them in a tutorial program by running:
python <Traits dir>/traits/tutor/tutor.py <Traits dir>/docs/tutorials/doc_examples