fix: Improve TimePreprocessor code (#455)

Tests were failing on #453 due to some parsing issues
This is similar to
deephaven/deephaven-core#5373 which I thought
was fixed.
Regardless, we shouldn't be using `to_j_instant` in this way due to poor
performance. For now I think assuming the column is an `Instant` is
fine.

plugins/plotly-express/src/deephaven/plot/express/plots/bar.py

@@ -274,9 +274,9 @@ def timeline(
       table: Table | None:  (Default value = None)
         A table to pull data from.
       x_start: str | None:  (Default value = None)
-        A column that contains starting x-axis values.
+        A column that contains starting x-axis values. Must be a `java.time.Instant` column.
       x_end: str | None:  (Default value = None)
-        A column that contains ending x-axis values.
+        A column that contains ending x-axis values. Must be a `java.time.Instant` column.
       by: str | list[str] | None:  (Default value = None)
         A column or list of columns that contain values to plot the figure traces by.
         All values or combination of values map to a unique design. The variable

plugins/plotly-express/src/deephaven/plot/express/preprocess/TimePreprocessor.py

@@ -4,9 +4,10 @@
 
 from ..shared import get_unique_names
 
-from deephaven.time import to_j_instant
 from deephaven.table import Table
 
+NANOS_PER_MILLI = 1_000_000
+
 
 class TimePreprocessor:
     """
@@ -45,12 +46,13 @@ def preprocess_partitioned_tables(
         x_diff = get_unique_names(table, ["x_diff"])["x_diff"]
 
         for table in tables:
+            # Times are assumed to be Instants which have nanosecond precision
+            # We convert them to milliseconds for plotly express
             yield table.update_view(
                 [
-                    f"{x_start} = (Instant) to_j_instant({x_start})",
-                    f"{x_end} = (Instant) to_j_instant({x_end})",
-                    f"{x_diff} = ((Instant) to_j_instant({x_end}) - "
-                    f"(Instant) to_j_instant({x_start})) / 1000000",
+                    f"{x_start} = {x_start}",
+                    f"{x_end} = {x_end}",
+                    f"{x_diff} = ({x_end} - {x_start}) / NANOS_PER_MILLI",
                     f"{y}",
                 ]
             ), {"x_diff": x_diff}