Using Traitlets

In short, traitlets let the user define classes that have

  1. Attributes (traits) with type checking and dynamically computed default values
  2. Traits emit change events when attributes are modified
  3. Traitlets perform some validation and allow coercion of new trait values on assignment. They also allow the user to define custom validation logic for attributes based on the value of other attributes.

Default values, and checking type and value

At its most basic, traitlets provides type checking, and dynamic default value generation of attributes on :class:traitlets.HasTraits subclasses:

import getpass

class Identity(HasTraits):
    username = Unicode()

    def _default_username(self):
        return getpass.getuser()
class Foo(HasTraits):
    bar = Int()

foo = Foo(bar='3')  # raises a TraitError
TraitError: The 'bar' trait of a Foo instance must be an int,
but a value of '3' <class 'str'> was specified


Traitlets implement the observer pattern

class Foo(HasTraits):
    bar = Int()
    baz = Unicode()

foo = Foo()

def func(change):
    print(change['new'])   # as of traitlets 4.3, one should be able to
                           # write print( instead

foo.observe(func, names=['bar']) = 1  # prints '0\n 1'
foo.baz = 'abc'  # prints nothing

When observers are methods of the class, a decorator syntax can be used.

class Foo(HasTraits):
    bar = Int()
    baz = Unicode()

    def _observe_bar(self, change):


Custom validation logic on trait classes

from traitlets import HasTraits, TraitError, Int, Bool, validate

class Parity(HasTraits):
    value = Int()
    parity = Int()

    def _valid_value(self, proposal):
        if proposal['value'] % 2 != self.parity:
            raise TraitError('value and parity should be consistent')
        return proposal['value']

    def _valid_parity(self, proposal):
        parity = proposal['value']
        if parity not in [0, 1]:
            raise TraitError('parity should be 0 or 1')
        if self.value % 2 != parity:
            raise TraitError('value and parity should be consistent')
        return proposal['value']

parity_check = Parity(value=2)

# Changing required parity and value together while holding cross validation
with parity_check.hold_trait_notifications():
    parity_check.value = 1
    parity_check.parity = 1

In the case where the a validation error occurs when hold_trait_notifications context manager is released, changes are rolled back to the initial state.

  • Finally, trait type can have other events than trait changes. This capability was added so as to enable notifications on change of values in container classes. The items available in the dictionary passed to the observer registered with observe depends on the event type.