Note
This documentation is for a development version of Traitlets. There may be significant differences from the latest stable release.
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 and Coercion¶
Custom Cross-Validation¶
Each trait type (Int
, Unicode
, Dict
etc.) may have its own
validation or coercion logic. In addition, we can register custom
cross-validators that may depend on the state of other attributes.
Basic Example: Validating the Parity of a Trait¶
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
However, we recommend that custom cross-validators don’t modify the state of the HasTraits instance.
Advanced Example: Validating the Schema¶
The List
and Dict
trait types allow the validation of nested
properties.
from traitlets import HasTraits, Dict, Bool, Unicode
class Nested(HasTraits):
value = Dict(traits={
'configuration': Dict(trait=Unicode()),
'flag': Bool()
})
n = Nested()
n.value = dict(flag=True, configuration={}) # OK
n.value = dict(flag=True, configuration='') # raises a TraitError.
However, for deeply nested properties it might be more appropriate to use an external validator:
import jsonschema
value_schema = {
'type' : 'object',
'properties' : {
'price' : { 'type' : 'number' },
'name' : { 'type' : 'string' },
},
}
from traitlets import HasTraits, Dict, TraitError, validate, default
class Schema(HasTraits):
value = Dict()
@default('value')
def _default_value(self):
return dict(name='', price=1)
@validate('value')
def _validate_value(self, proposal):
try:
jsonschema.validate(proposal['value'], value_schema)
except jsonschema.ValidationError as e:
raise TraitError(e)
return proposal['value']
s = Schema()
s.value = dict(name='', price='1') # raises a TraitError
Holding Trait Cross-Validation and Notifications¶
Sometimes if may be impossible to transition from to valid states for a
HasTraits
instance by change attributes one by one. The
hold_trait_notifications
context manager can be used to hold the custom
cross validation until the context manager is released. If a validation error
occurs, changes are rolled back to the initial state.
Custom Events¶
Finally, trait types can emit other events types 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.