Using Traitlets¶
In short, traitlets let the user define classes that have
- Attributes (traits) with type checking and dynamically computed default values
- Traits emit change events when attributes are modified
- 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()
@default('username')
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
observe¶
Traitlets implement the observer pattern
class Foo(HasTraits):
bar = Int()
baz = Unicode()
foo = Foo()
def func(change):
print(change['old'])
print(change['new']) # as of traitlets 4.3, one should be able to
# write print(change.new) instead
foo.observe(func, names=['bar'])
foo.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()
@observe('bar')
def _observe_bar(self, change):
print(change['old'])
print(change['new'])
Validation¶
Custom validation logic on trait classes
from traitlets import HasTraits, TraitError, Int, Bool, validate
class Parity(HasTraits):
value = Int()
parity = Int()
@validate('value')
def _valid_value(self, proposal):
if proposal['value'] % 2 != self.parity:
raise TraitError('value and parity should be consistent')
return proposal['value']
@validate('parity')
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.