config.configurable

Module: config.configurable

Inheritance diagram for IPython.config.configurable:

A base class for objects that are configurable.

Authors:

• Brian Granger
• Fernando Perez
• Min RK

Classes

Configurable

class IPython.config.configurable.Configurable(**kwargs)

Bases: IPython.utils.traitlets.HasTraits

__init__(**kwargs)

Create a configurable given a config config.

Parameters :

config : Config

If this is empty, default values are used. If config is a Config instance, it will be used to configure the instance.

Notes

Subclasses of Configurable must call the __init__() method of Configurable before doing anything else and using super():

class MyConfigurable(Configurable):
    def __init__(self, config=None):
        super(MyConfigurable, self).__init__(config)
        # Then any other code you need to finish initialization.

This ensures that instances will be configured properly.

classmethod class_config_section()

Get the config class config section

classmethod class_get_help()

Get the help string for this class in ReST format.

classmethod class_get_trait_help(trait)

Get the help string for a single trait.

classmethod class_print_help()

Get the help string for a single trait and print it.

classmethod class_trait_names(**metadata)

Get a list of all the names of this classes traits.

This method is just like the trait_names() method, but is unbound.

classmethod class_traits(**metadata)

Get a list of all the traits of this class.

This method is just like the traits() method, but is unbound.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

config

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

created = None

on_trait_change(handler, name=None, remove=False)

Setup a handler to be called when a trait changes.

This is used to setup dynamic notifications of trait changes.

Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

Parameters :

handler : callable

A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new).

name : list, str, None

If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name.

remove : bool

If False (the default), then install the handler. If True then unintall it.

trait_metadata(traitname, key)

Get metadata values for trait by key.

trait_names(**metadata)

Get a list of all the names of this classes traits.

traits(**metadata)

Get a list of all the traits of this class.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

ConfigurableError

class IPython.config.configurable.ConfigurableError

Bases: exceptions.Exception

__init__()

x.__init__(...) initializes x; see x.__class__.__doc__ for signature

args

message

LoggingConfigurable

class IPython.config.configurable.LoggingConfigurable(**kwargs)

Bases: IPython.config.configurable.Configurable

A parent class for Configurables that log.

Subclasses have a log trait, and the default behavior is to get the logger from the currently running Application via Application.instance().log.

__init__(**kwargs)

Create a configurable given a config config.

Parameters :

config : Config

If this is empty, default values are used. If config is a Config instance, it will be used to configure the instance.

Notes

Subclasses of Configurable must call the __init__() method of Configurable before doing anything else and using super():

class MyConfigurable(Configurable):
    def __init__(self, config=None):
        super(MyConfigurable, self).__init__(config)
        # Then any other code you need to finish initialization.

This ensures that instances will be configured properly.

classmethod class_config_section()

Get the config class config section

classmethod class_get_help()

Get the help string for this class in ReST format.

classmethod class_get_trait_help(trait)

Get the help string for a single trait.

classmethod class_print_help()

Get the help string for a single trait and print it.

classmethod class_trait_names(**metadata)

Get a list of all the names of this classes traits.

This method is just like the trait_names() method, but is unbound.

classmethod class_traits(**metadata)

Get a list of all the traits of this class.

This method is just like the traits() method, but is unbound.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

config

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

created = None

log

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

on_trait_change(handler, name=None, remove=False)

Setup a handler to be called when a trait changes.

This is used to setup dynamic notifications of trait changes.

Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

Parameters :

handler : callable

A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new).

name : list, str, None

If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name.

remove : bool

If False (the default), then install the handler. If True then unintall it.

trait_metadata(traitname, key)

Get metadata values for trait by key.

trait_names(**metadata)

Get a list of all the names of this classes traits.

traits(**metadata)

Get a list of all the traits of this class.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

MultipleInstanceError

class IPython.config.configurable.MultipleInstanceError

Bases: IPython.config.configurable.ConfigurableError

__init__()

x.__init__(...) initializes x; see x.__class__.__doc__ for signature

args

message

SingletonConfigurable

class IPython.config.configurable.SingletonConfigurable(**kwargs)

Bases: IPython.config.configurable.Configurable

A configurable that only allows one instance.

This class is for classes that should only have one instance of itself or any subclass. To create and retrieve such a class use the SingletonConfigurable.instance() method.

__init__(**kwargs)

Create a configurable given a config config.

Parameters :

config : Config

If this is empty, default values are used. If config is a Config instance, it will be used to configure the instance.

Notes

Subclasses of Configurable must call the __init__() method of Configurable before doing anything else and using super():

class MyConfigurable(Configurable):
    def __init__(self, config=None):
        super(MyConfigurable, self).__init__(config)
        # Then any other code you need to finish initialization.

This ensures that instances will be configured properly.

classmethod class_config_section()

Get the config class config section

classmethod class_get_help()

Get the help string for this class in ReST format.

classmethod class_get_trait_help(trait)

Get the help string for a single trait.

classmethod class_print_help()

Get the help string for a single trait and print it.

classmethod class_trait_names(**metadata)

Get a list of all the names of this classes traits.

This method is just like the trait_names() method, but is unbound.

classmethod class_traits(**metadata)

Get a list of all the traits of this class.

This method is just like the traits() method, but is unbound.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.

classmethod clear_instance()

unset _instance for this class and singleton parents.

config

A trait whose value must be an instance of a specified class.

The value can also be an instance of a subclass of the specified class.

created = None

classmethod initialized()

Has an instance been created?

classmethod instance(*args, **kwargs)

Returns a global instance of this class.

This method create a new instance if none have previously been created and returns a previously created instance is one already exists.

The arguments and keyword arguments passed to this method are passed on to the __init__() method of the class upon instantiation.

Examples

Create a singleton class using instance, and retrieve it:

>>> from IPython.config.configurable import SingletonConfigurable
>>> class Foo(SingletonConfigurable): pass
>>> foo = Foo.instance()
>>> foo == Foo.instance()
True

Create a subclass that is retrived using the base class instance:

>>> class Bar(SingletonConfigurable): pass
>>> class Bam(Bar): pass
>>> bam = Bam.instance()
>>> bam == Bar.instance()
True

on_trait_change(handler, name=None, remove=False)

Setup a handler to be called when a trait changes.

This is used to setup dynamic notifications of trait changes.

Static handlers can be created by creating methods on a HasTraits subclass with the naming convention ‘_[traitname]_changed’. Thus, to create static handler for the trait ‘a’, create the method _a_changed(self, name, old, new) (fewer arguments can be used, see below).

Parameters :

handler : callable

A callable that is called when a trait changes. Its signature can be handler(), handler(name), handler(name, new) or handler(name, old, new).

name : list, str, None

If None, the handler will apply to all traits. If a list of str, handler will apply to all names in the list. If a str, the handler will apply just to that name.

remove : bool

If False (the default), then install the handler. If True then unintall it.

trait_metadata(traitname, key)

Get metadata values for trait by key.

trait_names(**metadata)

Get a list of all the names of this classes traits.

traits(**metadata)

Get a list of all the traits of this class.

The TraitTypes returned don’t know anything about the values that the various HasTrait’s instances are holding.

This follows the same algorithm as traits does and does not allow for any simple way of specifying merely that a metadata name exists, but has any value. This is because get_metadata returns None if a metadata key doesn’t exist.