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# Traitlets [](https://travis-ci.org/ipython/traitlets) [](https://traitlets.readthedocs.io/en/latest/?badge=latest) | | | |---------------|----------------------------------------| | **home** | https://github.com/ipython/traitlets | | **pypi-repo** | https://pypi.org/project/traitlets/ | | **docs** | https://traitlets.readthedocs.io/ | | **license** | Modified BSD License | Traitlets is a pure Python library enabling: - the enforcement of strong typing for attributes of Python objects (typed attributes are called *"traits"*); - dynamically calculated default values; - automatic validation and coercion of trait attributes when attempting a change; - registering for receiving notifications when trait values change; - reading configuring values from files or from command line arguments - a distinct layer on top of traitlets, so you may use traitlets without the configuration machinery. Its implementation relies on the [descriptor](https://docs.python.org/howto/descriptor.html) pattern, and it is a lightweight pure-python alternative of the [*traits* library](http://code.enthought.com/pages/traits.html). Traitlets powers the configuration system of IPython and Jupyter and the declarative API of IPython interactive widgets. ## Installation For a local installation, make sure you have [pip installed](https://pip.pypa.io/en/stable/installing/) and run: ```bash pip install traitlets ``` For a **development installation**, clone this repository, change into the `traitlets` root directory, and run pip: ```bash git clone https://github.com/ipython/traitlets.git cd traitlets pip install -e . ``` ## Running the tests ```bash pip install "traitlets[test]" py.test traitlets ``` ## Usage Any class with trait attributes must inherit from `HasTraits`. For the list of available trait types and their properties, see the [Trait Types](https://traitlets.readthedocs.io/en/latest/trait_types.html) section of the documentation. ### Dynamic default values To calculate a default value dynamically, decorate a method of your class with `@default({traitname})`. This method will be called on the instance, and should return the default value. In this example, the `_username_default` method is decorated with `@default('username')`: ```Python import getpass from traitlets import HasTraits, Unicode, default class Identity(HasTraits): username = Unicode() @default('username') def _username_default(self): return getpass.getuser() ``` ### Callbacks when a trait attribute changes When a trait changes, an application can follow this trait change with additional actions. To do something when a trait attribute is changed, decorate a method with [`traitlets.observe()`](https://traitlets.readthedocs.io/en/latest/api.html?highlight=observe#traitlets.observe). The method will be called with a single argument, a dictionary which contains an owner, new value, old value, name of the changed trait, and the event type. In this example, the `_num_changed` method is decorated with ``@observe(`num`)``: ```Python from traitlets import HasTraits, Integer, observe class TraitletsExample(HasTraits): num = Integer(5, help="a number").tag(config=True) @observe('num') def _num_changed(self, change): print("{name} changed from {old} to {new}".format(**change)) ``` and is passed the following dictionary when called: ```Python { 'owner': object, # The HasTraits instance 'new': 6, # The new value 'old': 5, # The old value 'name': "foo", # The name of the changed trait 'type': 'change', # The event type of the notification, usually 'change' } ``` ### Validation and coercion 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. For example: ```Python 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.