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jupyter_chart.py
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jupyter_chart.py
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import json
import anywidget
import traitlets
import pathlib
from typing import Any, Set, Optional
import altair as alt
from altair.utils._vegafusion_data import (
using_vegafusion,
compile_to_vegafusion_chart_state,
)
from altair import TopLevelSpec
from altair.utils.selection import IndexSelection, PointSelection, IntervalSelection
_here = pathlib.Path(__file__).parent
class Params(traitlets.HasTraits):
"""
Traitlet class storing a JupyterChart's params
"""
def __init__(self, trait_values):
super().__init__()
for key, value in trait_values.items():
if isinstance(value, (int, float)):
traitlet_type = traitlets.Float()
elif isinstance(value, str):
traitlet_type = traitlets.Unicode()
elif isinstance(value, list):
traitlet_type = traitlets.List()
elif isinstance(value, dict):
traitlet_type = traitlets.Dict()
else:
traitlet_type = traitlets.Any()
# Add the new trait.
self.add_traits(**{key: traitlet_type})
# Set the trait's value.
setattr(self, key, value)
def __repr__(self):
return f"Params({self.trait_values()})"
class Selections(traitlets.HasTraits):
"""
Traitlet class storing a JupyterChart's selections
"""
def __init__(self, trait_values):
super().__init__()
for key, value in trait_values.items():
if isinstance(value, IndexSelection):
traitlet_type = traitlets.Instance(IndexSelection)
elif isinstance(value, PointSelection):
traitlet_type = traitlets.Instance(PointSelection)
elif isinstance(value, IntervalSelection):
traitlet_type = traitlets.Instance(IntervalSelection)
else:
raise ValueError(f"Unexpected selection type: {type(value)}")
# Add the new trait.
self.add_traits(**{key: traitlet_type})
# Set the trait's value.
setattr(self, key, value)
# Make read-only
self.observe(self._make_read_only, names=key)
def __repr__(self):
return f"Selections({self.trait_values()})"
def _make_read_only(self, change):
"""
Work around to make traits read-only, but still allow us to change
them internally
"""
if change["name"] in self.traits() and change["old"] != change["new"]:
self._set_value(change["name"], change["old"])
raise ValueError(
"Selections may not be set from Python.\n"
f"Attempted to set select: {change['name']}"
)
def _set_value(self, key, value):
self.unobserve(self._make_read_only, names=key)
setattr(self, key, value)
self.observe(self._make_read_only, names=key)
def load_js_src() -> str:
return (_here / "js" / "index.js").read_text()
class JupyterChart(anywidget.AnyWidget):
_esm = load_js_src()
_css = r"""
.vega-embed {
/* Make sure action menu isn't cut off */
overflow: visible;
}
"""
# Public traitlets
chart = traitlets.Instance(TopLevelSpec, allow_none=True)
spec = traitlets.Dict(allow_none=True).tag(sync=True)
debounce_wait = traitlets.Float(default_value=10).tag(sync=True)
max_wait = traitlets.Bool(default_value=True).tag(sync=True)
local_tz = traitlets.Unicode(default_value=None, allow_none=True).tag(sync=True)
debug = traitlets.Bool(default_value=False)
embed_options = traitlets.Dict(default_value=None, allow_none=True).tag(sync=True)
# Internal selection traitlets
_selection_types = traitlets.Dict()
_vl_selections = traitlets.Dict().tag(sync=True)
# Internal param traitlets
_params = traitlets.Dict().tag(sync=True)
# Internal comm traitlets for VegaFusion support
_chart_state = traitlets.Any(allow_none=True)
_js_watch_plan = traitlets.Any(allow_none=True).tag(sync=True)
_js_to_py_updates = traitlets.Any(allow_none=True).tag(sync=True)
_py_to_js_updates = traitlets.Any(allow_none=True).tag(sync=True)
# Track whether charts are configured for offline use
_is_offline = False
@classmethod
def enable_offline(cls, offline: bool = True):
"""
Configure JupyterChart's offline behavior
Parameters
----------
offline: bool
If True, configure JupyterChart to operate in offline mode where JavaScript
dependencies are loaded from vl-convert.
If False, configure it to operate in online mode where JavaScript dependencies
are loaded from CDN dynamically. This is the default behavior.
"""
from altair.utils._importers import import_vl_convert, vl_version_for_vl_convert
if offline:
if cls._is_offline:
# Already offline
return
vlc = import_vl_convert()
src_lines = load_js_src().split("\n")
# Remove leading lines with only whitespace, comments, or imports
while src_lines and (
len(src_lines[0].strip()) == 0
or src_lines[0].startswith("import")
or src_lines[0].startswith("//")
):
src_lines.pop(0)
src = "\n".join(src_lines)
# vl-convert's javascript_bundle function creates a self-contained JavaScript bundle
# for JavaScript snippets that import from a small set of dependencies that
# vl-convert includes. To see the available imports and their imported names, run
# import vl_convert as vlc
# help(vlc.javascript_bundle)
bundled_src = vlc.javascript_bundle(
src, vl_version=vl_version_for_vl_convert()
)
cls._esm = bundled_src
cls._is_offline = True
else:
cls._esm = load_js_src()
cls._is_offline = False
def __init__(
self,
chart: TopLevelSpec,
debounce_wait: int = 10,
max_wait: bool = True,
debug: bool = False,
embed_options: Optional[dict] = None,
**kwargs: Any,
):
"""
Jupyter Widget for displaying and updating Altair Charts, and
retrieving selection and parameter values
Parameters
----------
chart: Chart
Altair Chart instance
debounce_wait: int
Debouncing wait time in milliseconds. Updates will be sent from the client to the kernel
after debounce_wait milliseconds of no chart interactions.
max_wait: bool
If True (default), updates will be sent from the client to the kernel every debounce_wait
milliseconds even if there are ongoing chart interactions. If False, updates will not be
sent until chart interactions have completed.
debug: bool
If True, debug messages will be printed
embed_options: dict
Options to pass to vega-embed.
See https://github.com/vega/vega-embed?tab=readme-ov-file#options
"""
self.params = Params({})
self.selections = Selections({})
super().__init__(
chart=chart,
debounce_wait=debounce_wait,
max_wait=max_wait,
debug=debug,
embed_options=embed_options,
**kwargs,
)
@traitlets.observe("chart")
def _on_change_chart(self, change):
"""
Internal callback function that updates the JupyterChart's internal
state when the wrapped Chart instance changes
"""
new_chart = change.new
selection_watches = []
selection_types = {}
initial_params = {}
initial_vl_selections = {}
empty_selections = {}
if new_chart is None:
with self.hold_sync():
self.spec = None
self._selection_types = selection_types
self._vl_selections = initial_vl_selections
self._params = initial_params
return
params = getattr(new_chart, "params", [])
if params is not alt.Undefined:
for param in new_chart.params:
if isinstance(param.name, alt.ParameterName):
clean_name = param.name.to_json().strip('"')
else:
clean_name = param.name
select = getattr(param, "select", alt.Undefined)
if select != alt.Undefined:
if not isinstance(select, dict):
select = select.to_dict()
select_type = select["type"]
if select_type == "point":
if not (
select.get("fields", None) or select.get("encodings", None)
):
# Point selection with no associated fields or encodings specified.
# This is an index-based selection
selection_types[clean_name] = "index"
empty_selections[clean_name] = IndexSelection(
name=clean_name, value=[], store=[]
)
else:
selection_types[clean_name] = "point"
empty_selections[clean_name] = PointSelection(
name=clean_name, value=[], store=[]
)
elif select_type == "interval":
selection_types[clean_name] = "interval"
empty_selections[clean_name] = IntervalSelection(
name=clean_name, value={}, store=[]
)
else:
raise ValueError(f"Unexpected selection type {select.type}")
selection_watches.append(clean_name)
initial_vl_selections[clean_name] = {"value": None, "store": []}
else:
clean_value = param.value if param.value != alt.Undefined else None
initial_params[clean_name] = clean_value
# Handle the params generated by transforms
for param_name in collect_transform_params(new_chart):
initial_params[param_name] = None
# Setup params
self.params = Params(initial_params)
def on_param_traitlet_changed(param_change):
new_params = dict(self._params)
new_params[param_change["name"]] = param_change["new"]
self._params = new_params
self.params.observe(on_param_traitlet_changed)
# Setup selections
self.selections = Selections(empty_selections)
# Update properties all together
with self.hold_sync():
if using_vegafusion():
if self.local_tz is None:
self.spec = None
def on_local_tz_change(change):
self._init_with_vegafusion(change["new"])
self.observe(on_local_tz_change, ["local_tz"])
else:
self._init_with_vegafusion(self.local_tz)
else:
self.spec = new_chart.to_dict()
self._selection_types = selection_types
self._vl_selections = initial_vl_selections
self._params = initial_params
def _init_with_vegafusion(self, local_tz: str):
if self.chart is not None:
vegalite_spec = self.chart.to_dict(context={"pre_transform": False})
with self.hold_sync():
self._chart_state = compile_to_vegafusion_chart_state(
vegalite_spec, local_tz
)
self._js_watch_plan = self._chart_state.get_watch_plan()[
"client_to_server"
]
self.spec = self._chart_state.get_transformed_spec()
# Callback to update chart state and send updates back to client
def on_js_to_py_updates(change):
if self.debug:
updates_str = json.dumps(change["new"], indent=2)
print(
f"JavaScript to Python VegaFusion updates:\n {updates_str}"
)
updates = self._chart_state.update(change["new"])
if self.debug:
updates_str = json.dumps(updates, indent=2)
print(
f"Python to JavaScript VegaFusion updates:\n {updates_str}"
)
self._py_to_js_updates = updates
self.observe(on_js_to_py_updates, ["_js_to_py_updates"])
@traitlets.observe("_params")
def _on_change_params(self, change):
for param_name, value in change.new.items():
setattr(self.params, param_name, value)
@traitlets.observe("_vl_selections")
def _on_change_selections(self, change):
"""
Internal callback function that updates the JupyterChart's public
selections traitlet in response to changes that the JavaScript logic
makes to the internal _selections traitlet.
"""
for selection_name, selection_dict in change.new.items():
value = selection_dict["value"]
store = selection_dict["store"]
selection_type = self._selection_types[selection_name]
if selection_type == "index":
self.selections._set_value(
selection_name,
IndexSelection.from_vega(selection_name, signal=value, store=store),
)
elif selection_type == "point":
self.selections._set_value(
selection_name,
PointSelection.from_vega(selection_name, signal=value, store=store),
)
elif selection_type == "interval":
self.selections._set_value(
selection_name,
IntervalSelection.from_vega(
selection_name, signal=value, store=store
),
)
def collect_transform_params(chart: TopLevelSpec) -> Set[str]:
"""
Collect the names of params that are defined by transforms
Parameters
----------
chart: Chart from which to extract transform params
Returns
-------
set of param names
"""
transform_params = set()
# Handle recursive case
for prop in ("layer", "concat", "hconcat", "vconcat"):
for child in getattr(chart, prop, []):
transform_params.update(collect_transform_params(child))
# Handle chart's own transforms
transforms = getattr(chart, "transform", [])
transforms = transforms if transforms != alt.Undefined else []
for tx in transforms:
if hasattr(tx, "param"):
transform_params.add(tx.param)
return transform_params