Client to an MLflow Tracking Sever.
Returns a default client based on the MLFLOW_TRACKING_URI environment variable.
Creates a new MlflowClient; users should prefer constructing ApiClients via MlflowClient() or MlflowClient(String) if possible.
Instantiates a new client using the provided tracking uri.
Creates a new experiment using the default artifact location provided by the server.
Creates a new run under the default experiment with no application name.
Creates a new run under the given experiment with no application name.
Creates a new run under the given experiment with the given application name.
Deletes a run with the given ID.
Returns a local directory containing *all* artifacts within the run's artifact directory.
Returns a local file or directory containing all artifacts within the given artifactPath within the run's root artifactDirectory.
Lists the artifacts immediately under the run's root artifact directory.
Lists the artifacts immediately under the given artifactPath within the run's root artifact directory.
Uploads the given local file to the run's root artifact directory.
Uploads the given local file to an artifactPath within the run's root directory.
Uploads all files within the given local directory the run's root artifact directory.
Uploads all files within the given local director an artifactPath within the run's root artifact directory.
Logs a new metric against the given run, as a key-value pair.
Logs a parameter against the given run, as a key-value pair.
Restores a deleted run with the given ID.
Send a GET to the following path, including query parameters.
Send a POST to the following path, with a String-encoded JSON body.
Logs a new tag against the given run, as a key-value pair.
Sets the status of a run to be FINISHED at the current time.
Sets the status of a run to be completed at the current time.
Sets the status of a run to be completed at the given endTime.
run associated with the id.
a list of all RunInfos associated with the given experiment.
a list of all Experiments.
an experiment with the given id.
the experiment associated with the given name or Optional.empty if none exists.
experimentName - Name of the experiment. This must be unique across all experiments.
experiment id of the newly created experiment.
Logs a parameter against the given run, as a key-value pair. This cannot be called against the same parameter key more than once.
Logs a new metric against the given run, as a key-value pair. New values for the same metric may be recorded over time, and are marked with a timestamp.
Send a GET to the following path, including query parameters. This is mostly an internal API, but allows making lower-level or unsupported requests.
Send a POST to the following path, with a String-encoded JSON body. This is mostly an internal API, but allows making lower-level or unsupported requests.
runId - Run ID of an existing MLflow run.
localFile - File to upload. Must exist, and must be a simple file (not a directory).
listArtifacts(runId, "model") // returns "model/localModel"
(i.e., the localModel file is now available in model/localModel).
artifactPath - Artifact path relative to the run's root directory. Should NOT start with a /.
listArtifacts(runId) // returns "file1" and "file2"
localDir - Directory to upload. Must exist, and must be a directory (not a simple file).
listArtifacts(runId, "model") // returns "model/file1" and "model/file2"
(i.e., the contents of the local directory are now available in model/).
Lists the artifacts immediately under the run's root artifact directory. This does not recursively list; instead, it will return FileInfos with isDir=true where further listing may be done.
Lists the artifacts immediately under the given artifactPath within the run's root artifact directory. This does not recursively list; instead, it will return FileInfos with isDir=true where further listing may be done.
Returns a local directory containing *all* artifacts within the run's artifact directory. Note that this will download the entire directory path, and so may be expensive if the directory has a lot of data.
downloadArtifacts(runId, "model") // returns a local directory containing "file1" and "file2"
downloadArtifacts(runId, "model/file1") // returns a local *file* with the contents of file1.
Note that this will download the entire subdirectory path, and so may be expensive if the subdirectory has a lot of data.