MlflowChart¶

Live-updating canvas-based line chart for MLflow metrics. Supports multiple runs for side-by-side comparison with smoothing, tooltips, and an interactive legend.

Basic usage¶

from mlflow_widgets import MlflowChart

chart = MlflowChart(
    tracking_uri="http://localhost:5000",
    experiment_id="1",
    metric_key="loss",
)
chart

From specific runs¶

Pass run objects, run ID strings, or dicts with id and label keys:

chart = MlflowChart(
    tracking_uri="http://localhost:5000",
    runs=["run_id_1", "run_id_2"],
    metric_key="loss",
)

Or with MLflow Run objects:

import mlflow

with mlflow.start_run() as run:
    mlflow.log_metric("loss", 0.5)
    chart = MlflowChart(runs=[run], metric_key="loss")

X-axis modes¶

Control what the x-axis represents:

Mode	Description
`"step"`	MLflow step number (default)
`"wall"`	Wall clock time
`"relative"`	Time relative to the first logged point

chart = MlflowChart(
    experiment_id="1",
    metric_key="loss",
    x_axis="relative",
)

Smoothing¶

Three smoothing algorithms are available:

Kind	Parameter	Description
`"rolling"`	Window size (integer >= 2)	Rolling mean
`"exponential"`	Alpha (0 < alpha < 1)	Exponential moving average
`"gaussian"`	Sigma (> 0)	Gaussian smoothing (default)

chart = MlflowChart(
    experiment_id="1",
    metric_key="loss",
    smoothing_kind="exponential",
    smoothing_param=0.3,
)

Set show_slider=False to hide the smoothing slider from the UI.

Auto-polling¶

By default, the chart polls every 5 seconds. Customize or disable:

# Poll every 10 seconds
chart = MlflowChart(experiment_id="1", metric_key="loss", poll_seconds=10)

# Manual refresh only
chart = MlflowChart(experiment_id="1", metric_key="loss", poll_seconds=None)

Always clean up timers

Call chart.stop() or chart.close() when done to cancel background polling timers.

API reference¶

See MlflowChart for the full API.