Source code for

import weakref

import bokeh
import as bp
import param as pm

from bokeh.model import DataModel
from bokeh.models import ColumnDataSource

from ..reactive import Syncable
from .notebook import push_on_root

[docs]class Parameterized( """ Accept a Parameterized object. This property only exists to support type validation, e.g. for "accepts" clauses. It is not serializable itself, and is not useful to add to Bokeh models directly. """ def validate(self, value, detail=True): super().validate(value, detail) if isinstance(value, pm.Parameterized): return msg = "" if not detail else f"expected param.Parameterized, got {value!r}" raise ValueError(msg)
[docs]class ParameterizedList( """ Accept a list of Parameterized objects. This property only exists to support type validation, e.g. for "accepts" clauses. It is not serializable itself, and is not useful to add to Bokeh models directly. """
[docs] def validate(self, value, detail=True): super().validate(value, detail) if isinstance(value, list) and all(isinstance(v, pm.Parameterized) for v in value): return msg = "" if not detail else f"expected list of param.Parameterized, got {value!r}" raise ValueError(msg)
_DATA_MODELS = weakref.WeakKeyDictionary() # The Bokeh Color property has `_default_help` set which causes # an error to be raise when Nullable is called on it. This converter # overrides the Bokeh _help to set it to None and avoid the error. # See def color_param_to_ppt(p, kwargs): ppt = bp.Color(**kwargs) ppt._help = None return ppt def list_param_to_ppt(p, kwargs): if isinstance(p.item_type, type) and issubclass(p.item_type, pm.Parameterized): return bp.List(bp.Instance(DataModel)), [(ParameterizedList, lambda ps: [create_linked_datamodel(p) for p in ps])] return bp.List(bp.Any, **kwargs) PARAM_MAPPING = { pm.Array: lambda p, kwargs: bp.Array(bp.Any, **kwargs), pm.Boolean: lambda p, kwargs: bp.Bool(**kwargs), pm.CalendarDate: lambda p, kwargs: bp.Date(**kwargs), pm.CalendarDateRange: lambda p, kwargs: bp.Tuple(bp.Date, bp.Date, **kwargs), pm.ClassSelector: lambda p, kwargs: ( (bp.Instance(DataModel, **kwargs), [(Parameterized, create_linked_datamodel)]) if isinstance(p.class_, type) and issubclass(p.class_, pm.Parameterized) else bp.Any(**kwargs) ), pm.Color: color_param_to_ppt, pm.DataFrame: lambda p, kwargs: ( bp.ColumnData(bp.Any, bp.Seq(bp.Any), **kwargs), [(bp.PandasDataFrame, lambda x: ColumnDataSource._data_from_df(x))] ), pm.DateRange: lambda p, kwargs: bp.Tuple(bp.Datetime, bp.Datetime, **kwargs), pm.Date: lambda p, kwargs: bp.Datetime(**kwargs), pm.Dict: lambda p, kwargs: bp.Dict(bp.String, bp.Any, **kwargs), pm.Event: lambda p, kwargs: bp.Bool(**kwargs), pm.Integer: lambda p, kwargs: bp.Int(**kwargs), pm.List: list_param_to_ppt, pm.Number: lambda p, kwargs: bp.Float(**kwargs), pm.NumericTuple: lambda p, kwargs: bp.Tuple(*(bp.Float for p in range(p.length)), **kwargs), pm.Range: lambda p, kwargs: bp.Tuple(bp.Float, bp.Float, **kwargs), pm.String: lambda p, kwargs: bp.String(**kwargs), pm.Tuple: lambda p, kwargs: bp.Tuple(*(bp.Any for p in range(p.length)), **kwargs), }
[docs]def construct_data_model(parameterized, name=None, ignore=[], types={}): """ Dynamically creates a Bokeh DataModel class from a Parameterized object. Arguments --------- parameterized: param.Parameterized The Parameterized class or instance from which to create the DataModel name: str or None Name of the dynamically created DataModel class ignore: list(str) List of parameters to ignore. types: dict A dictionary mapping from parameter name to a Parameter type, making it possible to override the default parameter types. Returns ------- DataModel """ properties = {} for pname in parameterized.param: if pname in ignore: continue p = parameterized.param[pname] if p.precedence and p.precedence < 0: continue ptype = types.get(pname, type(p)) prop = PARAM_MAPPING.get(ptype) if isinstance(parameterized, Syncable): pname = parameterized._rename.get(pname, pname) if pname == 'name' or pname is None: continue nullable = getattr(p, 'allow_None', False) kwargs = {'default': p.default, 'help': p.doc} if prop is None: bk_prop, accepts = bp.Any(**kwargs), [] else: bkp = prop(p, {} if nullable else kwargs) bk_prop, accepts = bkp if isinstance(bkp, tuple) else (bkp, []) if nullable: bk_prop = bp.Nullable(bk_prop, **kwargs) for bkp, convert in accepts: bk_prop = bk_prop.accepts(bkp, convert) properties[pname] = bk_prop name = name or return type(name, (DataModel,), properties)
[docs]def create_linked_datamodel(obj, root=None): """ Creates a Bokeh DataModel from a Parameterized class or instance which automatically links the parameters bi-directionally. Arguments --------- obj: param.Parameterized The Parameterized class to create a linked DataModel for. Returns ------- DataModel instance linked to the Parameterized object. """ if isinstance(obj, type) and issubclass(obj, pm.Parameterized): cls = obj elif isinstance(obj, pm.Parameterized): cls = type(obj) else: raise TypeError('Can only create DataModel for Parameterized class or instance.') if cls in _DATA_MODELS: model = _DATA_MODELS[cls] else: _DATA_MODELS[cls] = model = construct_data_model(obj) properties = model = model(**{k: v for k, v in obj.param.values().items() if k in properties}) _changing = [] def cb_bokeh(attr, old, new): if attr in _changing: return try: _changing.append(attr) obj.param.update(**{attr: new}) finally: _changing.remove(attr) def cb_param(*events): update = { for event in events if not in _changing } try: _changing.extend(list(update)) model.update(**update) tags = [tag for tag in model.tags if tag.startswith('__ref:')] if root: push_on_root(root.ref['id']) elif tags: ref = tags[0].split('__ref:')[-1] push_on_root(ref) finally: for attr in update: _changing.remove(attr) for p in obj.param: if p in properties: model.on_change(p, cb_bokeh), list(set(properties) & set(obj.param))) return model