def to_dict(self, validate=True, ignore=[], context={}):
type_ = getattr(self, 'type', Undefined)
if type_ is Undefined and 'data' in context:
kwds = parse_shorthand_plus_data(self.field, context['data'])
else:
kwds = parse_shorthand(self.field)
self._kwds.update(kwds)
return super(Column, self).to_dict(validate=validate, ignore=ignore, context=context)
def to_dict(self, validate=True, ignore=(), context=None):
context = context or {}
condition = getattr(self, 'condition', Undefined)
copy = self # don't copy unless we need to
if condition is not Undefined:
if isinstance(condition, core.SchemaBase):
pass
elif 'field' in condition and 'type' not in condition:
kwds = parse_shorthand(condition['field'], context.get('data', None))
copy = self.copy()
copy.condition.update(kwds)
return super(ValueChannelMixin, copy).to_dict(validate=validate,
ignore=ignore,
context=context)
def to_dict(self, validate=True, ignore=(), context=None):
context = context or {}
condition = getattr(self, 'condition', Undefined)
copy = self # don't copy unless we need to
if condition is not Undefined:
if isinstance(condition, core.SchemaBase):
pass
elif 'field' in condition and 'type' not in condition:
kwds = parse_shorthand(condition['field'], context.get('data', None))
copy = self.copy()
copy.condition.update(kwds)
return super(ValueChannelMixin, copy).to_dict(validate=validate,
ignore=ignore,
context=context)
def to_dict(self, validate=True, ignore=(), context=None):
type_ = getattr(self, 'type', Undefined)
context = context or {}
if not isinstance(self.field, six.string_types):
# field is a RepeatSpec or similar; cannot infer type
kwds = {}
elif type_ is Undefined and 'data' in context:
kwds = parse_shorthand_plus_data(self.field, context['data'])
else:
kwds = parse_shorthand(self.field)
self._kwds.update(kwds)
return super(Order, self).to_dict(validate=validate,
ignore=ignore,
context=context)
def to_dict(self, validate=True, ignore=(), context=None):
context = context or {}
if self.shorthand is Undefined:
kwds = {}
elif isinstance(self.shorthand, (tuple, list)):
# If given a list of shorthands, then transform it to a list of classes
kwds = self._kwds.copy()
kwds.pop('shorthand')
return [
self.__class__(shorthand, **kwds).to_dict()
for shorthand in self.shorthand
]
elif isinstance(self.shorthand, six.string_types):
kwds = parse_shorthand(self.shorthand,
data=context.get('data', None))
type_defined = self._kwds.get('type', Undefined) is not Undefined
if not (type_defined or 'type' in kwds):
if isinstance(context.get('data', None), pd.DataFrame):
raise ValueError(
"{} encoding field is specified without a type; "
"the type cannot be inferred because it does not "
"match any column in the data.".format(self.shorthand))
else:
raise ValueError(
"{} encoding field is specified without a type; "
"the type cannot be automatically inferred because "
"the data is not specified as a pandas.DataFrame."
"".format(self.shorthand))
else:
# shorthand is not a string; we pass the definition to field
if self.field is not Undefined:
raise ValueError("both shorthand and field specified in {}"
"".format(self.__class__.__name__))
# field is a RepeatSpec or similar; cannot infer type
kwds = {'field': self.shorthand}
# set shorthand to Undefined, because it's not part of the schema
self.shorthand = Undefined
self._kwds.update({
k: v
for k, v in kwds.items()
if self._kwds.get(k, Undefined) is Undefined
})
return super(FieldChannelMixin, self).to_dict(validate=validate,
ignore=ignore,
context=context)
def to_dict(self, validate=True, ignore=(), context=None):
context = context or {}
if self.shorthand is Undefined:
kwds = {}
elif isinstance(self.shorthand, (tuple, list)):
# If given a list of shorthands, then transform it to a list of classes
kwds = self._kwds.copy()
kwds.pop('shorthand')
return [self.__class__(shorthand, **kwds).to_dict()
for shorthand in self.shorthand]
elif isinstance(self.shorthand, six.string_types):
kwds = parse_shorthand(self.shorthand, data=context.get('data', None))
type_defined = self._kwds.get('type', Undefined) is not Undefined
if not (type_defined or 'type' in kwds):
if isinstance(context.get('data', None), pd.DataFrame):
raise ValueError("{} encoding field is specified without a type; "
"the type cannot be inferred because it does not "
"match any column in the data.".format(self.shorthand))
else:
raise ValueError("{} encoding field is specified without a type; "
"the type cannot be automatically inferred because "
"the data is not specified as a pandas.DataFrame."
"".format(self.shorthand))
else:
# shorthand is not a string; we pass the definition to field
if self.field is not Undefined:
raise ValueError("both shorthand and field specified in {}"
"".format(self.__class__.__name__))
# field is a RepeatSpec or similar; cannot infer type
kwds = {'field': self.shorthand}
# set shorthand to Undefined, because it's not part of the schema
self.shorthand = Undefined
self._kwds.update({k: v for k, v in kwds.items()
if self._kwds.get(k, Undefined) is Undefined})
return super(FieldChannelMixin, self).to_dict(
validate=validate,
ignore=ignore,
context=context
)
def __init__(self, field, **kwargs):
kwds = parse_shorthand(field)
kwds.update(kwargs)
super(Size, self).__init__(**kwds)
