Reference API documentation¶

This is the reference API documentation of the Python API client.

class dataikuapi.dssclient.DSSClient(host, api_key=None, internal_ticket=None)¶

Entry point for the DSS API client

create_connection(name, type=None, params=None, usable_by='ALL', allowed_groups=None)¶

Create a connection, and return a handle to interact with it

Note: this call requires an API key with admin rights

Args:

name: the name of the new connection type: the type of the new connection params: the parameters of the new connection, as a JSON object usable_by: the type of access control for the connection. Either ‘ALL’ (=no access control)

or ‘ALLOWED’ (=access restricted to users of a list of groups)

allowed_groups: when using access control (that is, setting usable_by=’ALLOWED’), the list

of names of the groups whose users are allowed to use the new connection

Returns:

A dataikuapi.dss.admin.DSSConnection connection handle

create_group(name, description=None, source_type='LOCAL')¶

Create a group, and return a handle to interact with it

Note: this call requires an API key with admin rights

Args:

name: the name of the new group description: a description of the new group source_type: the type of the new group. Admissible values are ‘LOCAL’, ‘LDAP’, ‘SAAS’

Returns:

A dataikuapi.dss.admin.DSSGroup group handle

create_meaning(id, label, type, description=None, values=None, mappings=None, pattern=None, normalizationMode=None, detectable=False)¶

Create a meaning, and return a handle to interact with it

Note: this call requires an API key with admin rights

Args:

id: the ID of the new meaning type: the type of the new meaning. Admissible values are ‘DECLARATIVE’, ‘VALUES_LIST’, ‘VALUES_MAPPING’ and ‘PATTERN’ description (optional): the description of the new meaning values (optional): when type is ‘VALUES_LIST’, the list of values mappings (optional): when type is ‘VALUES_MAPPING’, the mapping, as a list of objects with this

structure: {‘from’: ‘value_1’, ‘to’: ‘value_a’}

pattern (optional): when type is ‘PATTERN’, the pattern normalizationMode (optional): when type is ‘VALUES_LIST’, ‘VALUES_MAPPING’ or ‘PATTERN’, the normalization

mode to use for value matching. One of ‘EXACT’, ‘LOWERCASE’, or ‘NORMALIZED’ (not available for ‘PATTERN’ type). Defaults to ‘EXACT’.

detectable (optional): whether DSS should consider assigning the meaning to columns set to ‘Auto-detect’. Defaults to False.

Returns:

A dataikuapi.dss.meaning.DSSMeaning meaning handle

create_project(project_key, name, owner, description=None, settings=None)¶

Create a project, and return a project handle to interact with it.

Note: this call requires an API key with admin rights

Args:

project_key: the identifier to use for the project. name: the name for the project. owner: the owner of the project. description: a short description for the project.

Returns:

A dataikuapi.dss.project.DSSProject project handle

create_project_from_bundle_archive(fp)¶

create_project_from_bundle_local_archive(archive_path)¶

create_user(login, password, display_name='', source_type='LOCAL', groups=[], profile='DATA_SCIENTIST')¶

Create a user, and return a handle to interact with it

Note: this call requires an API key with admin rights

Parameters:	login (str) – the login of the new user password (str) – the password of the new user display_name (str) – the displayed name for the new user source_type (str) – the type of new user. Admissible values are ‘LOCAL’ or ‘LDAP’ groups (list) – the names of the groups the new user belongs to profile (str) – The profile for the new user, can be one of READER, DATA_ANALYST or DATA_SCIENTIST
Returns:	A dataikuapi.dss.admin.DSSUser user handle

get_connection(name)¶

Get a handle to interact with a specific connection

Args:

name: the name of the desired connection

Returns:

A dataikuapi.dss.admin.DSSConnection connection handle

get_future(job_id)¶

Get a handle to interact with a specific long task (a.k.a future).

Args:

job_id: the job_id key of the desired future

Returns:

A dataikuapi.dss.future.DSSFuture

get_group(name)¶

Get a handle to interact with a specific group

Args:

name: the name of the desired group

Returns:

A dataikuapi.dss.admin.DSSGroup group handle

get_log(name)¶

Get a specific log

Note: this call requires an API key with admin rights

Args:

name: the name of the desired log

Returns:

The full log, as a string

get_meaning(id)¶

Get a handle to interact with a specific user-defined meaning

Note: this call requires an API key with admin rights

Args:

id: the ID of the desired meaning

Returns:

A dataikuapi.dss.meaning.DSSMeaning meaning handle

get_plugin(plugin_id)¶

Get a handle to interact with a specific dev plugin.

Args:

plugin_id: the identifier of the desired plugin

Returns:

A dataikuapi.dss.project.DSSPlugin

get_project(project_key)¶

Get a handle to interact with a specific project.

Args:

project_key: the project key of the desired project

Returns:

A dataikuapi.dss.project.DSSProject

get_user(login)¶

Get a handle to interact with a specific user

Parameters:	login (str) – the login of the desired user
Returns:	A dataikuapi.dss.admin.DSSUser user handle

get_variables()¶

Get the DSS instance’s variables

Note: this call requires an API key with admin rights

Returns:

A JSON object

list_connections()¶

List all connections setup on the DSS instance

Note: this call requires an API key with admin rights

Returns:

All connections, as a map of connection name to connection definition

list_futures(as_objects=False, all_users=False)¶

List the currently-running long tasks (a.k.a futures)

Returns:

list of futures. Each object contains at least a ‘jobId’ field

list_groups()¶

List all groups setup on the DSS instance

Note: this call requires an API key with admin rights

Returns:

A list of groups, as an array of JSON objects

list_logs()¶

List all logs on the DSS instance

Note: this call requires an API key with admin rights

Returns:

A list of log names

list_meanings()¶

List all user-defined meanings on the DSS instance

Note: this call requires an API key with admin rights

Returns:

A list of meanings, as an array of JSON objects

list_plugins()¶

List the installed plugins

Returns:

list of objects. Each object contains at least a ‘projectKey’ field

list_project_keys()¶

List the project keys (=project identifiers).

Returns:

list of identifiers (=strings)

list_projects()¶

List the projects

Returns:

list of objects. Each object contains at least a ‘projectKey’ field

list_running_scenarios(all_users=False)¶

List the running scenarios

Returns:

the list of scenarios, each one as a JSON object containing a jobId field for the future hosting the scenario run, and a payload field with scenario identifiers

list_users()¶

List all users setup on the DSS instance

Note: this call requires an API key with admin rights

Returns:	A list of users, as an array of dicts.

prepare_project_import(f)¶

Prepares import of a project archive

@param: fp: the input stream, as a file-like object

Returns a handle for the prepared import

set_variables(variables)¶

Set the DSS instance’s variables

Note: this call requires an API key with admin rights

Args:

variables: the new state of all variables of the instance, as a JSON object

sql_query(query, connection=None, database=None, dataset_full_name=None, pre_queries=None, post_queries=None, type='sql', extra_conf={})¶

Initiate a SQL, Hive or Impala query and get a handle to retrieve the results of the query. Internally, the query is run by DSS. The database to run the query on is specified either by passing a connection name, or by passing a database name, or by passing a dataset full name (whose connection is then used to retrieve the database)

Args:

query: the query to run connection: the connection on which the query should be run (exclusive of database and dataset_full_name) database: the database on which the query should be run (exclusive of connection and dataset_full_name) dataset_full_name: the dataset on the connection of which the query should be run (exclusive of connection and database) pre_queries: (optional) array of queries to run before the query post_queries: (optional) array of queries to run after the query type: the type of query : either ‘sql’, ‘hive’ or ‘impala’

Returns:

A dataikuapi.dss.sqlquery.DSSSQLQuery query handle

class dataikuapi.dssclient.TemporaryImportHandle(client, import_id)¶

execute(settings={})¶

Executes the import with provided settings. @warning: You must check the ‘success’ flag

class dataikuapi.dss.project.DSSProject(client, project_key)¶

A project on the DSS instance

activate_bundle(bundle_id)¶

create_dataset(dataset_name, type, params={}, formatType=None, formatParams={})¶

Create a new dataset in the project, and return a handle to interact with it

Args:

dataset_name: the name for the new dataset type: the type of the dataset params: the parameters for the type, as a JSON object formatType: an optional format to create the dataset with formatParams: the parameters to the format, as a JSON object

Returns:

A dataikuapi.dss.dataset.DSSDataset dataset handle

create_managed_folder(name)¶

Create a new managed folder in the project, and return a handle to interact with it

Args:

name: the name of the managed folder

Returns:

A dataikuapi.dss.managedfolder.DSSManagedFolder managed folder handle

create_recipe(recipe_name, type, recipe_inputs=[], recipe_outputs=[], recipe_params={})¶

Create a new recipe in the project, and return a handle to interact with it. Some recipe types take additional parameters in recipe_params:

• ‘grouping’ : a ‘groupKey’ column name
• ‘python’, ‘sql_query’, ‘hive’, ‘impala’ : the code of the recipe as a ‘payload’ string

Args:

recipe_name: the name for the new recipe type: the type of the recipe (‘sync’, ‘grouping’, ‘join’, ‘vstack’, ‘python’, ‘sql_query’, ‘hive’, ‘impala’) recipe_inputs: an array of recipes inputs, as objects {‘ref’:’...’, ‘deps’:[...]} recipe_outputs: an array of recipes outputs, as objects {‘ref’:’...’, ‘appendMode’:True/False} recipe_params: additional parameters for the recipe creation

Returns:

A dataikuapi.dss.recipe.DSSRecipe recipe handle

create_scenario(scenario_name, type, definition={})¶

Create a new scenario in the project, and return a handle to interact with it

Args:

scenario_name: the name for the new scenario type: the type of the scenario (‘step_based’ or ‘custom_python’) definition: the definition of the scenario, as a JSON object

Returns:

A dataikuapi.dss.scenario.DSSScenario scenario handle

delete()¶

Delete the project

Note: this call requires an API key with admin rights

download_exported_bundle_archive_to_file(bundle_id, path)¶

Download a bundle archive that can be deployed in a DSS automation Node into the given output file. @param path if “-”, will write to /dev/stdout

export_bundle(bundle_id)¶

export_to_file(path, options={})¶

Export the project to a file Args:

path: the path of the file in which the exported project should be saved

get_api_service(service_id)¶

Get a handle to interact with a specific API service

Args:

service_id: the ID of the desired API service

Returns:

A dataikuapi.dss.dataset.DSSAPIService API Service handle

get_dataset(dataset_name)¶

Get a handle to interact with a specific dataset

Args:

dataset_name: the name of the desired dataset

Returns:

A dataikuapi.dss.dataset.DSSDataset dataset handle

get_export_stream(options={})¶

Return a stream of the exported project

Warning: this stream will monopolize the DSSClient until closed

get_exported_bundle_archive_stream(bundle_id)¶

Download a bundle archive that can be deployed in a DSS automation Node, as a binary stream. Warning: this stream will monopolize the DSSClient until closed.

get_job(id)¶

Get a handler to interact with a specific job

Returns:

A dataikuapi.dss.job.DSSJob job handle

get_managed_folder(odb_id)¶

Get a handle to interact with a specific managed folder

Args:

odb_id: the identifier of the desired managed folder

Returns:

A dataikuapi.dss.managedfolder.DSSManagedFolder managed folder handle

get_metadata()¶

Get the metadata attached to this project. The metadata contains label, description checklists, tags and custom metadata of the project

Returns:

a dict object. For more information on available metadata, please see https://doc.dataiku.com/dss/api/latest

get_permissions()¶

Get the permissions attached to this project

Returns:

a JSON object, containing the owner and the permissions, as a list of pairs of group name and permission type

get_recipe(recipe_name)¶

Get a handle to interact with a specific recipe

Args:

recipe_name: the name of the desired recipe

Returns:

A dataikuapi.dss.recipe.DSSRecipe recipe handle

get_saved_model(sm_id)¶

Get a handle to interact with a specific saved model

Args:

sm_id: the identifier of the desired saved model

Returns:

A dataikuapi.dss.savedmodel.DSSSavedModel saved model handle

get_scenario(scenario_id)¶

Get a handle to interact with a specific scenario

Args:

scenario_id: the ID of the desired scenario

Returns:

A dataikuapi.dss.scenario.DSSScenario scenario handle

get_variables()¶

Gets the variables of this project.

Returns:

a dictionary containing two dictionaries : “standard” and “local”. “standard” are regular variables, exported with bundles. “local” variables are not part of the bundles for this project

import_bundle_from_archive(archive_path)¶

list_api_services()¶

List the API services in this project

Returns:

the list of API services, each one as a JSON object

list_datasets()¶

List the datasets in this project

Returns:

the list of the datasets, each one as a JSON object

list_exported_bundles()¶

list_imported_bundles()¶

list_jobs()¶

List the jobs in this project

Returns:

a list of the jobs, each one as a JSON object, containing both the definition and the state

list_managed_folders()¶

List the managed folders in this project

Returns:

the list of the managed folders, each one as a JSON object

list_recipes()¶

List the recipes in this project

Returns:

the list of the recipes, each one as a JSON object

list_saved_models()¶

List the saved models in this project

Returns:

the list of the saved models, each one as a JSON object

list_scenarios()¶

List the scenarios in this project

Returns:

the list of scenarios, each one as a JSON object.

set_metadata(metadata)¶

Set the metadata on this project.

Args:

metadata: the new state of the metadata for the project. You should only set a metadata object that has been retrieved using the get_metadata call.

set_permissions(permissions)¶

Set the permissions on this project

Args:

permissions: a JSON object of the same structure as the one returned by get_permissions call

set_variables(obj)¶

Sets the variables of this project. @param obj: must be a modified version of the object returned by get_variables

start_job(definition)¶

Create a new job, and return a handle to interact with it

Args:

definition: the definition for the job to create. The definition must contain the type of job (RECURSIVE_BUILD, NON_RECURSIVE_FORCED_BUILD, RECURSIVE_FORCED_BUILD, RECURSIVE_MISSING_ONLY_BUILD) and a list of outputs to build. Optionally, a refreshHiveMetastore field can specify whether to re-synchronize the Hive metastore for recomputed HDFS datasets.

Returns:

A dataikuapi.dss.job.DSSJob job handle

sync_datasets_acls()¶

Resync permissions on HDFS datasets in this project

Returns:

a DSSFuture handle to the task of resynchronizing the permissions

Note: this call requires an API key with admin rights

class dataikuapi.dss.dataset.DSSDataset(client, project_key, dataset_name)¶

A dataset on the DSS instance

clear(partitions=None)¶

Clear all data in this dataset

Args:

partitions: (optional) a list of partitions to clear. When not provided, the entire dataset is cleared

compute_metrics(partition='', metric_ids=None, probes=None)¶

Compute metrics on a partition of this dataset. If neither metric ids nor custom probes set are specified, the metrics setup on the dataset are used.

delete()¶

Delete the dataset

get_definition()¶

Get the definition of the dataset

Returns:

the definition, as a JSON object

get_last_metric_values(partition='')¶

Get the last values of the metrics on this dataset

Returns:

a list of metric objects and their value

get_metadata()¶

Get the metadata attached to this dataset. The metadata contains label, description checklists, tags and custom metadata of the dataset

Returns:

a dict object. For more information on available metadata, please see https://doc.dataiku.com/dss/api/latest

get_metric_history(metric, partition='')¶

Get the history of the values of the metric on this dataset

Returns:

an object containing the values of the metric, cast to the appropriate type (double, boolean,...)

get_schema()¶

Get the schema of the dataset

Returns:

a JSON object of the schema, with the list of columns

get_usages()¶

Get the recipes or analyses referencing this dataset

Returns:

a list of usages

iter_rows(partitions=None)¶

Get the dataset’s data

Return:

an iterator over the rows, each row being a tuple of values. The order of values in the tuples is the same as the order of columns in the schema returned by get_schema

list_partitions()¶

Get the list of all partitions of this dataset

Returns:

the list of partitions, as a list of strings

run_checks(partition='', checks=None)¶

Run checks on a partition of this dataset. If the checks are not specified, the checks setup on the dataset are used.

set_definition(definition)¶

Set the definition of the dataset

Args:

definition: the definition, as a JSON object. You should only set a definition object that has been retrieved using the get_definition call.

set_metadata(metadata)¶

Set the metadata on this dataset.

Args:

metadata: the new state of the metadata for the dataset. You should only set a metadata object that has been retrieved using the get_metadata call.

set_schema(schema)¶

Set the schema of the dataset

Args:

schema: the desired schema for the dataset, as a JSON object. All columns have to provide their name and type

synchronize_hive_metastore()¶

Synchronize this dataset with the Hive metastore

class dataikuapi.dss.recipe.DSSRecipe(client, project_key, recipe_name)¶

A recipe on the DSS instance

delete()¶

Delete the recipe

get_definition_and_payload()¶

Get the definition of the recipe

Returns:

the definition, as a DSSRecipeDefinitionAndPayload object, containing the recipe definition itself and its payload

get_metadata()¶

Get the metadata attached to this recipe. The metadata contains label, description checklists, tags and custom metadata of the recipe

Returns:

a dict object. For more information on available metadata, please see https://doc.dataiku.com/dss/api/latest

set_definition_and_payload(definition)¶

Set the definition of the recipe

Args:

definition: the definition, as a DSSRecipeDefinitionAndPayload object. You should only set a definition object that has been retrieved using the get_definition call.

set_metadata(metadata)¶

Set the metadata on this recipe.

Args:

metadata: the new state of the metadata for the recipe. You should only set a metadata object that has been retrieved using the get_metadata call.

class dataikuapi.dss.recipe.DSSRecipeCreator(type, name, project)¶

Helper to create new recipes

build()¶

Create a new recipe in the project, and return a handle to interact with it.

Returns:

A dataikuapi.dss.recipe.DSSRecipe recipe handle

with_input(dataset_name, project_key=None)¶

with_output(dataset_name, append=False)¶

class dataikuapi.dss.recipe.DSSRecipeDefinitionAndPayload(data)¶

Definition for a recipe, that is, the recipe definition itself and its payload

get_json_payload()¶

get_payload()¶

get_recipe_inputs()¶

get_recipe_outputs()¶

get_recipe_params()¶

get_recipe_raw_definition()¶

set_json_payload(payload)¶

set_payload(payload)¶

class dataikuapi.dss.recipe.GroupingRecipeCreator(name, project)¶

with_group_key(group_key)¶

class dataikuapi.dss.recipe.JoinRecipeCreator(name, project)¶

class dataikuapi.dss.recipe.SQLQueryRecipeCreator(name, project)¶

class dataikuapi.dss.recipe.SamplingRecipeCreator(name, project)¶

class dataikuapi.dss.recipe.SingleOutputRecipeCreator(type, name, project)¶

with_existing_output(dataset_name, append=False)¶

with_new_output(dataset_name, connection_id, format_option_id=None, partitioning_option_id=None, append=False)¶

with_output(dataset_name, append=False)¶

class dataikuapi.dss.recipe.StackRecipeCreator(name, project)¶

class dataikuapi.dss.recipe.SyncRecipeCreator(name, project)¶

class dataikuapi.dss.recipe.VirtualInputsSingleOutputRecipeCreator(type, name, project)¶

with_input(dataset_name, project_key=None)¶

class dataikuapi.dss.recipe.WindowRecipeCreator(name, project)¶

class dataikuapi.dss.managedfolder.DSSManagedFolder(client, project_key, odb_id)¶

A managed folder on the DSS instance

compute_metrics(metric_ids=None, probes=None)¶

Compute metrics on this managed folder. If the metrics are not specified, the metrics setup on the managed folder are used.

delete()¶

Delete the managed folder

delete_file(path)¶

Delete a file from the managed folder

get_definition()¶

Get the definition of the managed folder

Returns:

the definition, as a JSON object

get_file(path)¶

Get a file from the managed folder

Returns:

the file’s content, as a stream

get_last_metric_values()¶

Get the last values of the metrics on this managed folder

Returns:

a list of metric objects and their value

get_metric_history(metric)¶

Get the history of the values of the metric on this dataset

Returns:

an object containing the values of the metric, cast to the appropriate type (double, boolean,...)

get_usages()¶

Get the recipes referencing this folder

Returns:

a list of usages

list_contents()¶

Get the list of files in the managed folder

Returns:

the list of files, as a JSON object

put_file(name, f)¶

Upload the file to the managed folder

Args:

f: the file contents, as a stream name: the name of the file

set_definition(definition)¶

Set the definition of the managed folder

Args:

definition: the definition, as a JSON object. You should only set a definition object that has been retrieved using the get_definition call.

class dataikuapi.dss.job.DSSJob(client, project_key, id)¶

A job on the DSS instance

abort()¶

Aborts the job

get_log(activity=None)¶

Get the logs of the job

Args:

activity: (optional) the name of the activity in the job whose log is requested

Returns:

the log, as a string

get_status()¶

Get the current status of the job

Returns:

the state of the job, as a JSON object

class dataikuapi.dss.meaning.DSSMeaning(client, id)¶

A user-defined meaning on the DSS instance

get_definition()¶

Get the meaning’s definition.

Note: this call requires an API key with admin rights

Returns:

the meaning definition, as a JSON object

set_definition(definition)¶

Set the meaning’s definition.

Note: this call requires an API key with admin rights

Args:

definition: the definition for the meaning, as a JSON object

class dataikuapi.dss.metrics.ComputedMetrics(raw)¶

get_all_ids()¶

get_first_partition_data(metric_id)¶

get_global_data(metric_id)¶

get_global_value(metric_id)¶

get_metric_by_id(id)¶

get_partition_data(metric_id, partition)¶

get_partition_value(metric_id, partition)¶

static get_value_from_data(data)¶

class dataikuapi.dss.admin.DSSConnection(client, name)¶

A connection on the DSS instance

delete()¶

Delete the connection

Note: this call requires an API key with admin rights

get_definition()¶

Get the connection’s definition (type, name, params, usage restrictions)

Note: this call requires an API key with admin rights

Returns:

the connection definition, as a JSON object

set_definition(description)¶

Set the connection’s definition.

Note: this call requires an API key with admin rights

Args:

definition: the definition for the connection, as a JSON object.

sync_datasets_acls()¶

Resync permissions on datasets in this connection path

Returns:

a DSSFuture handle to the task of resynchronizing the permissions

Note: this call requires an API key with admin rights

sync_root_acls()¶

Resync root permissions on this connection path

Returns:

a DSSFuture handle to the task of resynchronizing the permissions

Note: this call requires an API key with admin rights

class dataikuapi.dss.admin.DSSGroup(client, name)¶

A group on the DSS instance

delete()¶

Delete the group

Note: this call requires an API key with admin rights

get_definition()¶

Get the group’s definition (name, description, admin abilities, type, ldap name mapping)

Note: this call requires an API key with admin rights

Returns:

the group definition, as a JSON object

set_definition(definition)¶

Set the group’s definition.

Note: this call requires an API key with admin rights

Args:

definition: the definition for the group, as a JSON object.

class dataikuapi.dss.admin.DSSUser(client, login)¶

A handle for a user on the DSS instance

delete()¶

Deletes the user

Note: this call requires an API key with admin rights

get_definition()¶

Get the user’s definition (login, type, display name, permissions, ...)

Note: this call requires an API key with admin rights

Returns:	the user’s definition, as a dict

set_definition(definition)¶

Set the user’s definition.

Note: this call requires an API key with admin rights

Parameters:	definition (dict) – the definition for the user, as a dict. You should obtain the definition using get_definition, not create one. The fields that can be changed are: email displayName groups userProfile password

class dataikuapi.dss.scenario.DSSScenario(client, project_key, id)¶

A handle to interact with a scenario on the DSS instance

abort()¶

Aborts the scenario if it currently running

get_average_duration(limit=3)¶

Get the average duration (in fractional seconds) of the last runs of this scenario that finished, where finished means it ended with SUCCESS or WARNING. If there are not enough runs to perform the average, returns None

Args:

limit: number of last runs to average on

get_current_run()¶

Get the current run of the scenario, or None if it is not running at the moment

Returns:	A dataikuapi.dss.scenario.DSSScenarioRun

get_definition(with_status=True)¶

Returns the definition of the scenario

Args:

with_status: if True, the definition contains the run status of the scenario but not its

actions’ definition. If False, the definition doesn’t contain the run status but has the scenario’s actions definition

get_last_runs(limit=10, only_finished_runs=False)¶

Get the list of the last runs of the scenario.

Returns:	A list of dataikuapi.dss.scenario.DSSScenarioRun

get_payload(extension='py')¶

Returns the payload of the scenario

Parameters:	extension (str) – the type of script. Default is ‘py’ for python

get_run(run_id)¶

Get a handle to a run of the scenario

Returns:	A dataikuapi.dss.scenario.DSSScenarioRun

run(params={})¶

Requests a run of the scenario, which will start after a few seconds.

Params dict params:
	additional parameters that will be passed to the scenario through trigger params

set_definition(definition, with_status=True)¶

Updates the definition of this scenario

Args:

with_status: should be the same as the value passed to get_definition(). If True, the params,

triggers and reporters fields of the scenario are ignored,

set_payload(script, with_status=True)¶

Updates the payload of this scenario

Parameters:	extension (str) – the type of script. Default is ‘py’ for python

class dataikuapi.dss.scenario.DSSScenarioRun(client, run)¶

A handle containing basic info about a past run of a scenario.

This handle can also be used to fetch additional information about the urn

get_details()¶

Get the full details of the scenario run, including its step runs.

Note: this perform another API call

get_duration()¶

Get the duration of this run (in fractional seconds).

If the run is still running, get the duration since it started

get_info()¶

Get the basic information of the scenario run

get_start_time()¶

Get the start time of the scenario run

class dataikuapi.dss.scenario.DSSTriggerFire(scenario, trigger_fire)¶

The activation of a trigger on the DSS instance

get_scenario_run()¶

Get the run of the scenario that this trigger activation launched

class dataikuapi.dss.apiservice.DSSAPIService(client, project_key, service_id)¶

An API Service on the DSS instance

create_package(package_id)¶

Prepare a package of this API service

delete_package(package_id)¶

Delete a package of this API service

download_package_stream(package_id)¶

Download a package archive that can be deployed in a DSS API Node, as a binary stream.

Warning: this stream will monopolize the DSSClient until closed.

download_package_to_file(package_id, path)¶

Download a package archive that can be deployed in a DSS API Node, into the given output file.

list_packages()¶

List the packages of this API services

Returns:

the list of API service packages, each one as a JSON object