Source code for bokeh.core.property.bases

''' Provide base classes for the Bokeh property system.

.. note::
    These classes form part of the very low-level machinery that implements
    the Bokeh model and property system. It is unlikely that any of these
    classes or their methods will be applicable to any standard usage or to
    anyone who is not directly developing on Bokeh's own infrastructure.

'''
from __future__ import absolute_import

import logging
logger = logging.getLogger(__name__)

from copy import copy
import types

from six import string_types

from ...util.string import nice_join
from .containers import PropertyValueList, PropertyValueDict
from .descriptor_factory import PropertyDescriptorFactory
from .descriptors import BasicPropertyDescriptor

class DeserializationError(Exception):
    pass

[docs]class Property(PropertyDescriptorFactory): ''' Base class for Bokeh property instances, which can be added to Bokeh Models. Args: default (obj or None, optional) : A default value for attributes created from this property to have (default: None) help (str or None, optional) : A documentation string for this property. It will be automatically used by the :ref:`bokeh.sphinxext.bokeh_prop` extension when generating Spinx documentation. (default: None) serialized (bool, optional) : Whether attributes created from this property should be included in serialization (default: True) readonly (bool, optional) : Whether attributes created from this property are read-only. (default: False) ''' def __init__(self, default=None, help=None, serialized=True, readonly=False): # This is how the descriptor is created in the class declaration. self._serialized = False if readonly else serialized self._readonly = readonly self._default = default self.__doc__ = help self.alternatives = [] self.assertions = [] # "fail early" when a default is invalid self.validate(self._raw_default()) def __str__(self): return self.__class__.__name__ @classmethod def _sphinx_prop_link(cls): ''' Generate a sphinx :class: link to this property. ''' return ":class:`~bokeh.core.properties.%s` " % cls.__name__ @staticmethod def _sphinx_model_link(name): ''' Generate a sphinx :class: link to given named model. ''' return ":class:`~%s` " % name def _sphinx_type(self): ''' Generate a Sphinx-style reference to this type for documentation automation purposes. ''' return self._sphinx_prop_link()
[docs] def make_descriptors(self, base_name): ''' Return a list of ``BasicPropertyDescriptor`` instances to install on a class, in order to delegate attribute access to this property. Args: name (str) : the name of the property these descriptors are for Returns: list[BasicPropertyDescriptor] The descriptors returned are collected by the ``MetaHasProps`` metaclass and added to ``HasProps`` subclasses during class creation. ''' return [ BasicPropertyDescriptor(base_name, self) ]
def _may_have_unstable_default(self): ''' False if we have a default that is immutable, and will be the same every time (some defaults are generated on demand by a function to be called). ''' return isinstance(self._default, types.FunctionType) @classmethod def _copy_default(cls, default): ''' Return a copy of the default, or a new value if the default is specified by a function. ''' if not isinstance(default, types.FunctionType): return copy(default) else: return default() def _raw_default(self): ''' Return the untransformed default value. The raw_default() needs to be validated and transformed by prepare_value() before use, and may also be replaced later by subclass overrides or by themes. ''' return self._copy_default(self._default)
[docs] def themed_default(self, cls, name, theme_overrides): ''' The default, transformed by prepare_value() and the theme overrides. ''' overrides = theme_overrides if overrides is None or name not in overrides: overrides = cls._overridden_defaults() if name in overrides: default = self._copy_default(overrides[name]) else: default = self._raw_default() return self.prepare_value(cls, name, default)
@property def serialized(self): ''' Whether the property should be serialized when serializing an object. This would be False for a "virtual" or "convenience" property that duplicates information already available in other properties, for example. ''' return self._serialized @property def readonly(self): ''' Whether this property is read-only. Read-only properties may only be modified by the client (i.e., by BokehJS in the browser). ''' return self._readonly def matches(self, new, old): # XXX: originally this code warned about not being able to compare values, but that # doesn't make sense, because most comparisons involving numpy arrays will fail with # ValueError exception, thus warning about inevitable. try: if new is None or old is None: return new is old # XXX: silence FutureWarning from NumPy else: return new == old except (KeyboardInterrupt, SystemExit): raise except Exception: # if we cannot compare (e.g. arrays) just punt return False for match pass return False
[docs] def from_json(self, json, models=None): ''' Convert from JSON-compatible values into a value for this property. JSON-compatible values are: list, dict, number, string, bool, None ''' return json
[docs] def serialize_value(self, value): ''' Change the value into a JSON serializable format. ''' return value
[docs] def transform(self, value): ''' Change the value into the canonical format for this property. Args: value (obj) : the value to apply transformation to. Returns: obj: transformed value ''' return value
[docs] def validate(self, value): ''' Determine whether we can set this property from this value. Validation happens before transform() Args: value (obj) : the value to validate against this property type Returns: None Raises: ValueError if the value is not valid for this property type ''' pass
[docs] def is_valid(self, value): ''' Whether the value passes validation Args: value (obj) : the value to validate against this property type Returns: True if valid, False otherwise ''' try: self.validate(value) except ValueError: return False else: return True
@classmethod def _wrap_container(cls, value): if isinstance(value, list): if isinstance(value, PropertyValueList): return value else: return PropertyValueList(value) elif isinstance(value, dict): if isinstance(value, PropertyValueDict): return value else: return PropertyValueDict(value) else: return value def prepare_value(self, obj_or_cls, name, value): try: self.validate(value) except ValueError as e: for tp, converter in self.alternatives: if tp.is_valid(value): value = converter(value) break else: raise e else: value = self.transform(value) from ..has_props import HasProps if isinstance(obj_or_cls, HasProps): obj = obj_or_cls for fn, msg_or_fn in self.assertions: if isinstance(fn, bool): result = fn else: result = fn(obj, value) if isinstance(result, bool): if not result: if isinstance(msg_or_fn, string_types): raise ValueError(msg_or_fn) else: msg_or_fn() elif result is not None: if isinstance(msg_or_fn, string_types): raise ValueError(msg_or_fn % result) else: msg_or_fn(result) return self._wrap_container(value) @property def has_ref(self): return False def accepts(self, tp, converter): tp = ParameterizedProperty._validate_type_param(tp) self.alternatives.append((tp, converter)) return self def asserts(self, fn, msg_or_fn): self.assertions.append((fn, msg_or_fn)) return self
[docs]class ParameterizedProperty(Property): ''' A base class for Properties that have type parameters, e.g. ``List(String)``. ''' @staticmethod def _validate_type_param(type_param): if isinstance(type_param, type): if issubclass(type_param, Property): return type_param() else: type_param = type_param.__name__ elif isinstance(type_param, Property): return type_param raise ValueError("expected a Propertyas type parameter, got %s" % type_param) @property def type_params(self): raise NotImplementedError("abstract method") @property def has_ref(self): return any(type_param.has_ref for type_param in self.type_params)
[docs]class PrimitiveProperty(Property): ''' A base class for simple property types. Subclasses should define a class attribute ``_underlying_type`` that is a tuple of acceptable type values for the property. Example: A trivial version of a ``Float`` property might look like: .. code-block:: python class Float(PrimitiveProperty): _underlying_type = (numbers.Real,) ''' _underlying_type = None def validate(self, value): super(PrimitiveProperty, self).validate(value) if not (value is None or isinstance(value, self._underlying_type)): raise ValueError("expected a value of type %s, got %s of type %s" % (nice_join([ cls.__name__ for cls in self._underlying_type ]), value, type(value).__name__)) def from_json(self, json, models=None): if json is None or isinstance(json, self._underlying_type): return json else: expected = nice_join([ cls.__name__ for cls in self._underlying_type ]) raise DeserializationError("%s expected %s, got %s" % (self, expected, json)) def _sphinx_type(self): return self._sphinx_prop_link()
[docs]class ContainerProperty(ParameterizedProperty): ''' A base class for Container-like type properties. ''' def _may_have_unstable_default(self): # all containers are mutable, so the default can be modified return True