Convert Plotly datetimes

panel/pane/plotly.py

@@ -14,7 +14,8 @@
 from bokeh.models import ColumnDataSource
 from pyviz_comms import JupyterComm
 
-from ..util import isdatetime, lazy_load
+from ..util import lazy_load
+from ..util.checks import datetime_types, isdatetime
 from ..viewable import Layoutable
 from .base import ModelPane
 
@@ -132,8 +133,8 @@ def _get_sources_for_trace(json, data, parent_path=''):
         for key, value in list(json.items()):
             full_path = key if not parent_path else f"{parent_path}.{key}"
             if isinstance(value, np.ndarray):
-                # Extract numpy array
-                data[full_path] = [json.pop(key)]
+                array = json.pop(key)
+                data[full_path] = [array]
             elif isinstance(value, dict):
                 # Recurse into dictionaries:
                 Plotly._get_sources_for_trace(value, data=data, parent_path=full_path)
@@ -251,17 +252,21 @@ def _plotly_json_wrapper(fig):
         For #382: Map datetime elements to strings.
         """
         json = fig.to_plotly_json()
+        layout = json['layout']
         data = json['data']
-
-        for idx in range(len(data)):
-            for key in data[idx]:
-                if isdatetime(data[idx][key]):
-                    arr = data[idx][key]
-                    if isinstance(arr, np.ndarray):
-                        arr = arr.astype(str)
-                    else:
-                        arr = [str(v) for v in arr]
-                    data[idx][key] = arr
+        shapes = layout.get('shapes', [])
+        for trace in data+shapes:
+            for key in trace:
+                if not isdatetime(trace[key]):
+                    continue
+                arr = trace[key]
+                if isinstance(arr, np.ndarray):
+                    arr = arr.astype(str)
+                elif isinstance(arr, datetime_types):
+                    arr = str(arr)
+                else:
+                    arr = [str(v) for v in arr]
+                trace[key] = arr
         return json
 
     def _init_params(self):

panel/tests/pane/test_plotly.py

@@ -243,3 +243,58 @@ def test_plotly_swap_traces(document, comm):
 
     assert 'x' not in cds.data
     assert len(cds.data['y'][0]) == 500
+
+
+@plotly_available
+def test_plotly_shape_datetime_converted(document, comm):
+    # see https://github.com/holoviz/panel/issues/5252
+    start = pd.Timestamp('2022-05-11 0:00:00', tz=dt.timezone.utc)
+    date_range = pd.date_range(start=start, periods=20, freq='h')
+
+    df = pd.DataFrame({
+        "x": date_range,
+        "y": list(range(len(date_range))),
+    })
+
+    fig = px.scatter(df, x="x", y="y")
+    fig.add_vline(x=pd.Timestamp('2022-05-11 9:00:00', tz=dt.timezone.utc))
+
+    p = Plotly(fig)
+
+    model = p.get_root(document, comm)
+
+    assert model.layout['shapes'][0]['x0'] == '2022-05-11 09:00:00+00:00'
+
+
+@plotly_available
+def test_plotly_datetime_converted_2d_array(document, comm):
+    # see https://github.com/holoviz/panel/issues/7309
+    n_points = 3
+    data = pd.DataFrame({
+        'timestamp': pd.date_range(start='2023-01-01', periods=n_points, freq='min'),
+        'latitude': np.cumsum(np.random.randn(n_points) * 0.01) + 52.3702,  # Centered around Amsterdam
+        'longitude': np.cumsum(np.random.randn(n_points) * 0.01) + 4.8952,  # Centered around Amsterdam
+    })
+
+    fig = px.scatter_mapbox(data, lon='longitude', lat='latitude', custom_data='timestamp')
+
+    p = Plotly(fig)
+
+    model = p.get_root(document, comm)
+
+    assert len(model.data_sources) == 1
+
+    cds = model.data_sources[0]
+    assert isinstance(cds.data['customdata'], list)
+    assert len(cds.data['customdata']) == 1
+    data = cds.data['customdata'][0]
+    assert isinstance(data, np.ndarray)
+    assert data.dtype.kind == 'U'
+    np.testing.assert_equal(
+        data,
+        np.array([
+            ['2023-01-01 00:00:00'],
+            ['2023-01-01 00:01:00'],
+            ['2023-01-01 00:02:00']
+        ])
+    )

panel/util/checks.py

@@ -109,7 +109,7 @@ def isdatetime(value) -> bool:
         return (
             value.dtype.kind == "M" or
             (value.dtype.kind == "O" and len(value) != 0 and
-             isinstance(value[0], datetime_types))
+             isinstance(np.take(value, 0), datetime_types))
         )
     elif isinstance(value, list):
         return all(isinstance(d, datetime_types) for d in value)