databricks-api 0.1.0

Databricks API client interface.

[This documentation is auto-generated]

This package provides a simplified interface for the Databricks REST API. The interface is autogenerated on instantiation using the underlying client library used in the official databricks-cli python package.

The docs here describe the interface for version 0.8.2 of the databricks-cli package for API version 2.0. Assuming there are no major changes to the databricks-cli package structure, this package should continue to work without a required update.

The databricks-api package contains a DatabricksAPI class which provides instance attributes for the databricks-cli ApiClient, as well as each of the available service instances. The attributes of a DatabricksAPI instance are:

• DatabricksAPI.client <databricks_cli.sdk.api_client.ApiClient>
• DatabricksAPI.jobs <databricks_cli.sdk.service.JobsService>
• DatabricksAPI.cluster <databricks_cli.sdk.service.ClusterService>
• DatabricksAPI.managed_library <databricks_cli.sdk.service.ManagedLibraryService>
• DatabricksAPI.dbfs <databricks_cli.sdk.service.DbfsService>
• DatabricksAPI.workspace <databricks_cli.sdk.service.WorkspaceService>
• DatabricksAPI.secret <databricks_cli.sdk.service.SecretService>
• DatabricksAPI.groups <databricks_cli.sdk.service.GroupsService>

To instantiate the client, provide the databricks host and either a token or user and password. Also shown is the full signature of the underlying ApiClient.__init__

from databricks_api import DatabricksAPI

# Provide a host and token
db = DatabricksAPI(
    host="example.cloud.databricks.com",
    token="dpapi123..."
)

# OR a host and user and password
db = DatabricksAPI(
    host="example.cloud.databricks.com",
    user="[e-mail]",
    password="password"
)

# Full __init__ signature
db = DatabricksAPI(
    user=None,
    password=None,
    host=None,
    token=None,
    apiVersion=2.0,
    default_headers={},
    verify=True,
    command_name=''
)

Refer to the official documentation on the functionality and required arguments of each method below.

Each of the service instance attributes provides the following public methods:

DatabricksAPI.jobs

DatabricksAPI.jobs.cancel_run(run_id)

DatabricksAPI.jobs.create_job(
    name=None,
    existing_cluster_id=None,
    new_cluster=None,
    libraries=None,
    email_notifications=None,
    timeout_seconds=None,
    max_retries=None,
    min_retry_interval_millis=None,
    retry_on_timeout=None,
    schedule=None,
    notebook_task=None,
    spark_jar_task=None,
    spark_python_task=None,
    spark_submit_task=None,
    max_concurrent_runs=None
)

DatabricksAPI.jobs.delete_job(job_id)

DatabricksAPI.jobs.delete_run(run_id=None)

DatabricksAPI.jobs.export_run(
    run_id,
    views_to_export=None
)

DatabricksAPI.jobs.get_job(job_id)

DatabricksAPI.jobs.get_run(run_id=None)

DatabricksAPI.jobs.get_run_output(run_id)

DatabricksAPI.jobs.list_jobs()

DatabricksAPI.jobs.list_runs(
    job_id=None,
    active_only=None,
    completed_only=None,
    offset=None,
    limit=None
)

DatabricksAPI.jobs.reset_job(
    job_id,
    new_settings
)

DatabricksAPI.jobs.run_now(
    job_id=None,
    jar_params=None,
    notebook_params=None,
    python_params=None,
    spark_submit_params=None
)

DatabricksAPI.jobs.submit_run(
    run_name=None,
    existing_cluster_id=None,
    new_cluster=None,
    libraries=None,
    notebook_task=None,
    spark_jar_task=None,
    spark_python_task=None,
    spark_submit_task=None,
    timeout_seconds=None
)

DatabricksAPI.cluster

DatabricksAPI.cluster.create_cluster(
    num_workers=None,
    autoscale=None,
    cluster_name=None,
    spark_version=None,
    spark_conf=None,
    aws_attributes=None,
    node_type_id=None,
    driver_node_type_id=None,
    ssh_public_keys=None,
    custom_tags=None,
    cluster_log_conf=None,
    spark_env_vars=None,
    autotermination_minutes=None,
    enable_elastic_disk=None,
    cluster_source=None
)

DatabricksAPI.cluster.delete_cluster(cluster_id)

DatabricksAPI.cluster.edit_cluster(
    cluster_id,
    num_workers=None,
    autoscale=None,
    cluster_name=None,
    spark_version=None,
    spark_conf=None,
    aws_attributes=None,
    node_type_id=None,
    driver_node_type_id=None,
    ssh_public_keys=None,
    custom_tags=None,
    cluster_log_conf=None,
    spark_env_vars=None,
    autotermination_minutes=None,
    enable_elastic_disk=None,
    cluster_source=None
)

DatabricksAPI.cluster.get_cluster(cluster_id)

DatabricksAPI.cluster.list_available_zones()

DatabricksAPI.cluster.list_clusters()

DatabricksAPI.cluster.list_node_types()

DatabricksAPI.cluster.list_spark_versions()

DatabricksAPI.cluster.resize_cluster(
    cluster_id,
    num_workers=None,
    autoscale=None
)

DatabricksAPI.cluster.restart_cluster(cluster_id)

DatabricksAPI.cluster.start_cluster(cluster_id)

DatabricksAPI.managed_library

DatabricksAPI.managed_library.all_cluster_statuses()

DatabricksAPI.managed_library.cluster_status(cluster_id)

DatabricksAPI.managed_library.install_libraries(
    cluster_id,
    libraries=None
)

DatabricksAPI.managed_library.uninstall_libraries(
    cluster_id,
    libraries=None
)

DatabricksAPI.dbfs

DatabricksAPI.dbfs.add_block(
    handle,
    data
)

DatabricksAPI.dbfs.close(handle)

DatabricksAPI.dbfs.create(
    path,
    overwrite=None
)

DatabricksAPI.dbfs.delete(
    path,
    recursive=None
)

DatabricksAPI.dbfs.get_status(path)

DatabricksAPI.dbfs.list(path)

DatabricksAPI.dbfs.mkdirs(path)

DatabricksAPI.dbfs.move(
    source_path,
    destination_path
)

DatabricksAPI.dbfs.put(
    path,
    contents=None,
    overwrite=None
)

DatabricksAPI.dbfs.read(
    path,
    offset=None,
    length=None
)

DatabricksAPI.workspace

DatabricksAPI.workspace.delete(
    path,
    recursive=None
)

DatabricksAPI.workspace.export_workspace(
    path,
    format=None,
    direct_download=None
)

DatabricksAPI.workspace.get_status(path)

DatabricksAPI.workspace.import_workspace(
    path,
    format=None,
    language=None,
    content=None,
    overwrite=None
)

DatabricksAPI.workspace.list(path)

DatabricksAPI.workspace.mkdirs(path)

DatabricksAPI.secret

DatabricksAPI.secret.create_scope(
    scope,
    initial_manage_principal=None
)

DatabricksAPI.secret.delete_acl(
    scope,
    principal
)

DatabricksAPI.secret.delete_scope(scope)

DatabricksAPI.secret.delete_secret(
    scope,
    key
)

DatabricksAPI.secret.get_acl(
    scope,
    principal
)

DatabricksAPI.secret.list_acls(scope)

DatabricksAPI.secret.list_scopes()

DatabricksAPI.secret.list_secrets(scope)

DatabricksAPI.secret.put_acl(
    scope,
    principal,
    permission
)

DatabricksAPI.secret.put_secret(
    scope,
    key,
    string_value=None,
    bytes_value=None
)

DatabricksAPI.groups

DatabricksAPI.groups.add_to_group(
    parent_name,
    user_name=None,
    group_name=None
)

DatabricksAPI.groups.create_group(group_name)

DatabricksAPI.groups.get_group_members(group_name)

DatabricksAPI.groups.get_groups()

DatabricksAPI.groups.get_groups_for_principal(
    user_name=None,
    group_name=None
)

DatabricksAPI.groups.remove_from_group(
    parent_name,
    user_name=None,
    group_name=None
)

DatabricksAPI.groups.remove_group(group_name)