Plotly

zenml.integrations.plotly special

Initialization of the Plotly integration.

PlotlyIntegration (Integration)

Definition of Plotly integration for ZenML.

Source code in zenml/integrations/plotly/__init__.py

class PlotlyIntegration(Integration):
    """Definition of Plotly integration for ZenML."""

    NAME = PLOTLY
    REQUIREMENTS = ["plotly>=5.4.0"]

visualizers special

Initialization of the Plotly Visualizer.

pipeline_lineage_visualizer

Implementation of the Plotly Pipeline Lineage Visualizer.

PipelineLineageVisualizer (BaseVisualizer)

Visualize the lineage of runs in a pipeline using plotly.

Source code in zenml/integrations/plotly/visualizers/pipeline_lineage_visualizer.py

class PipelineLineageVisualizer(BaseVisualizer):
    """Visualize the lineage of runs in a pipeline using plotly."""

    @abstractmethod
    def visualize(
        self, object: PipelineView, *args: Any, **kwargs: Any
    ) -> Figure:
        """Creates a pipeline lineage diagram using plotly.

        Args:
            object: The pipeline view to visualize.
            *args: Additional arguments to pass to the visualization.
            **kwargs: Additional keyword arguments to pass to the visualization.

        Returns:
            A plotly figure.
        """
        logger.warning(
            "This integration is not completed yet. Results might be unexpected."
        )

        category_dict = {}
        dimensions = ["run"]
        for run in object.runs:
            category_dict[run.name] = {"run": run.name}
            for step in run.steps:
                category_dict[run.name].update(
                    {
                        step.entrypoint_name: str(step.id),
                    }
                )
                if step.entrypoint_name not in dimensions:
                    dimensions.append(f"{step.entrypoint_name}")

        category_df = pd.DataFrame.from_dict(category_dict, orient="index")

        category_df = category_df.reset_index()

        fig = px.parallel_categories(
            category_df,
            dimensions,
            color=None,
            labels="status",
        )

        fig.show()
        return fig

visualize(self, object, *args, **kwargs)

Creates a pipeline lineage diagram using plotly.

Parameters:

Name	Type	Description	Default
object	PipelineView	The pipeline view to visualize.	required
*args	Any	Additional arguments to pass to the visualization.	()
**kwargs	Any	Additional keyword arguments to pass to the visualization.	{}

Returns:

Type	Description
Figure	A plotly figure.

Source code in zenml/integrations/plotly/visualizers/pipeline_lineage_visualizer.py

@abstractmethod
def visualize(
    self, object: PipelineView, *args: Any, **kwargs: Any
) -> Figure:
    """Creates a pipeline lineage diagram using plotly.

    Args:
        object: The pipeline view to visualize.
        *args: Additional arguments to pass to the visualization.
        **kwargs: Additional keyword arguments to pass to the visualization.

    Returns:
        A plotly figure.
    """
    logger.warning(
        "This integration is not completed yet. Results might be unexpected."
    )

    category_dict = {}
    dimensions = ["run"]
    for run in object.runs:
        category_dict[run.name] = {"run": run.name}
        for step in run.steps:
            category_dict[run.name].update(
                {
                    step.entrypoint_name: str(step.id),
                }
            )
            if step.entrypoint_name not in dimensions:
                dimensions.append(f"{step.entrypoint_name}")

    category_df = pd.DataFrame.from_dict(category_dict, orient="index")

    category_df = category_df.reset_index()

    fig = px.parallel_categories(
        category_df,
        dimensions,
        color=None,
        labels="status",
    )

    fig.show()
    return fig