Concatenates file paths together and returns the result as a string

@return The number of rows contained in the DataFrame

Performs inference on the specified input and produces a result

The run metadata, such as the run id, start time, and status. :rtype: :py:class:`mlflow.entities.RunInfo`

Return a default client based on the MLFLOW_TRACKING_URI environment variable.

Converts a message to JSON, using snake_case for field names.

Obtains the configuration for the specified flavor from the specified MLflow model path. If the model does not contain the specified flavor,

Catch exceptions and log a warning to avoid autolog throwing.

Log a metric against the run ID. :param run_id: The run id to which the metric should be logged. :param key: Metric name.

<code>optional string message = 2;</code>

:param artifact_uri: The *absolute* URI of the artifact to download. :param output_path: The local filesystem path to which to download the a

Load a model from its YAML representation.

<pre> Value associated with this param. </pre> <code>optional string value = 2;</code>

Search experiments that fit the search criteria. :param experiment_ids: List of experiment IDs, or a single int or string id.

Filters a set of runs based on a search filter string.

* This function is our implementation of Immutable.fromJS, but fixes a bug with * their implementation. * @param {object} pojo - a javascript ob

<code>optional string message = 2;</code>

<pre> Key identifying this param. </pre> <code>optional string key = 1;</code>

Set a tag on the run with the specified ID. Value is converted to a string. :param run_id: String ID of the run. :param key:

* @param {Immutable.Record schema} AnemicRecord: generated Immutable Record * @param {Object<string, func>} prototypeFuncs: functions to add to

<pre> [Deprecated, use run_id instead] ID of the run under which to log the tag. This field will be removed in a future MLflow version. </pre> <code>

Log a parameter against the run ID. Value is converted to a string.

Creates a Conda environment with the specified package channels and dependencies. :param path: Local filesystem path where the conda env fil

<pre> ID of the run under which to log the tag. Must be provided. </pre> <code>optional string run_id = 4;</code>

Fetch the run from backend store. The resulting :py:class:`Run <mlflow.entities.Run>` contains a collection of run metadata -- :py:cl

Log a metric dict for the given run.

* Apply the filter to an array of keys, returning a new array with the keys that pass the filter * in the order the user wants them displayed.

<pre> Experiment details. </pre> <code>optional .mlflow.Experiment experiment = 1;</code>

:param name: Name of the registered model to update. :return: A single :py:class:`mlflow.entities.model_registry.RegisteredModel` obj

<pre> The experiment ID. </pre> <code>optional string experiment_id = 2;</code>

Get an artifact repository from the registry based on the scheme of artifact_uri :param store_uri: The store URI. This URI is used to select whic