mlflow/mlflow · warning · UserWarning

Failure attempting to register default experimentcontext pro

Error message

Failure attempting to register default experimentcontext provider "{entrypoint.name}": {exc}

What it means

The default-experiment provider registry loads `mlflow.default_experiment_provider` entry points at startup. If a provider package raises AttributeError or ImportError on import, a warning reports the entrypoint name and the exception.

Source

Thrown at mlflow/tracking/default_experiment/registry.py:41

    MLflow Experiment IDs based on the current context where the MLflow client is running when
    the user has not explicitly set an experiment. Implementations declared though the entrypoints
    `mlflow.default_experiment_provider` group can be automatically registered through the
    `register_entrypoints` method.
    """

    def __init__(self):
        self._registry = []

    def register(self, default_experiment_provider_cls):
        self._registry.append(default_experiment_provider_cls())

    def register_entrypoints(self):
        """Register tracking stores provided by other packages"""
        for entrypoint in get_entry_points("mlflow.default_experiment_provider"):
            try:
                self.register(entrypoint.load())
            except (AttributeError, ImportError) as exc:
                warnings.warn(
                    "Failure attempting to register default experiment"
                    + f'context provider "{entrypoint.name}": {exc}',
                    stacklevel=2,
                )

    def __iter__(self):
        return iter(self._registry)


_default_experiment_provider_registry = DefaultExperimentProviderRegistry()
for exp_provider in _EXPERIMENT_PROVIDERS:
    _default_experiment_provider_registry.register(exp_provider)

_default_experiment_provider_registry.register_entrypoints()


def get_experiment_id() -> str | None:
    """Get an experiment ID for the current context.

View on GitHub (pinned to 6a27f2decc)

Solutions

1. Inspect the exception text, then reinstall the failing provider package.
2. Uninstall the plugin if it is not needed.
3. Rebuild the environment/venv to remove stale entry points.

Example fix

// before
import my_default_exp_provider  # ImportError
// after
# pip install --force-reinstall my-mlflow-default-experiment-provider

from importlib.metadata import entry_points
for ep in entry_points(group="mlflow.default_experiment_provider"):
    try:
        ep.load()
    except Exception as e:
        print(f"broken provider {ep.name}: {e}")

import warnings
with warnings.catch_warnings(record=True) as w:
    warnings.simplefilter("always")
    import mlflow
for warn in w:
    if "default experiment" in str(warn.message):
        fix_or_remove_plugin(warn)

When it happens

Trigger: An installed package declaring the `mlflow.default_experiment_provider` entry point whose referenced module or attribute cannot be loaded.

Common situations: Broken plugin installs, mismatched dependency versions after upgrades, leftover metadata from uninstalled packages in the environment.

Related errors

• Failure attempting to register context provider "{}": {}
• Failure attempting to register store for scheme "{}": {}
• Failure attempting to register request auth provider "{}": {
• Failure attempting to register request header provider "{}":
• Failed to load the plugin "{item}": {exc}

AI-assisted analysis of mlflow/mlflow@6a27f2decc (2026-08-29). Data as JSON: /api/errors/156b2da13356158a. Report an issue: GitHub.