mstrio.project_objects.datasets package

Submodules

mstrio.project_objects.datasets.cube module

class mstrio.project_objects.datasets.cube.CubeStates(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

ACTIVE = 2
DIRTY = 16
DIRTY_INFO = 8
FOREIGN = 2048
IMPORTED = 1024
LOADED = 32
LOAD_PENDING = 128
PENDING_FOR_ENGINE = 512
PERSISTED = 4
PROCESSING = 1
READY = 64
RESERVED = 0
UNKNOWN1 = 4096
UNKNOWN2 = 8192
UNKNOWN3 = 16384
UNLOAD_PENDING = 256
classmethod show_status(status: int) → list[str]

Show states of a cube calculated from numerical value of its state. Additionally list of those states’ names is returned.

Parameters:

status (integer) – numerical value of cube’s status

Returns:

List with names of cube’s states.

mstrio.project_objects.datasets.cube.list_all_cubes(connection: Connection, name: str | None = None, search_pattern: mstrio.object_management.search_enums.SearchPattern | int = SearchPattern.CONTAINS, project_id: str | None = None, project_name: str | None = None, to_dictionary: bool = False, limit: int | None = None, **filters) → list[OlapCube | SuperCube] | list[dict]

Get list of Cube objects (OlapCube or SuperCube) or dicts with them. Optionally filter cubes by specifying ‘name’.

Optionally use to_dictionary to choose output format.

Wildcards available for ‘name’:

? - any character * - 0 or more of any characters e.g. name = ?onny will return Sonny and Tonny

Specify either project_id or project_name. When project_id is provided (not None), project_name is omitted.

Note

When project_id is None and project_name is None, then its value is overwritten by project_id from connection object.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection()

  • name (string, optional) – value the search pattern is set to, which will be applied to the names of cubes being searched

  • search_pattern (SearchPattern enum or int, optional) – pattern to search for, such as Begin With or Contains. Possible values are available in ENUM mstrio.object_management.SearchPattern. Default value is BEGIN WITH (4).

  • project_id (string, optional) – Project ID

  • project_name (str, optional) – Project name

  • to_dictionary (bool, optional) – If True returns dict, by default (False) returns SuperCube/OlapCube objects

  • limit (integer, optional) – limit the number of elements returned. If None all object are returned.

  • **filters – Available filter parameters: [‘id’, ‘name’, ‘type’, ‘subtype’, ‘date_created’, ‘date_modified’, ‘version’, ‘owner’, ‘ext_type’, ‘view_media’, ‘certified_info’]

Returns:

list with OlapCubes and SuperCubes or list of dictionaries

mstrio.project_objects.datasets.cube.load_cube(connection: Connection, cube_id: str | None = None, cube_name: str | None = None, folder_id: str | None = None, instance_id: str | None = None) → OlapCube | SuperCube | list[OlapCube | SuperCube]

Load single cube specified by either ‘cube_id’ or both ‘cube_name’ and ‘folder_id’.

It is also possible to load cube by providing only cube_name, but in that case we may retrieve more than one cube as cube’s name is unique only within a folder.

instance_id is used only when a single cube is retrieved.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection()

  • cube_id (string, optional) – ID of cube

  • cube_name (string, optional) – name of cube

  • folder_id (string, optional) – ID of folder in which the cube is stored

  • instance_id (str, optional) – Identifier of an instance if cube instance has been already initialized. Will be used if only one cube is found. None by default.

Returns:

object of type OlapCube or SuperCube based on the subtype of a cube returned from metadata.

Raises:

ValueError when neither cube_id nor cube_name are provided. –

mstrio.project_objects.datasets.cube_cache module

class mstrio.project_objects.datasets.cube_cache.CubeCache(connection: Connection, cache_id: str, cube_cache_dict: dict | None = None)

Bases: Cache

Manage cube cache.

activate()

Activate cube cache.

deactivate()

Deactivate cube cache.

delete(force: bool = False)

Delete cube cache.

Parameters:

force – If True, then no additional prompt will be shown before deleting CubeCache.

Returns:

True for success. False otherwise.

fetch()
classmethod from_dict(connection: Connection, caches: list[dict]) → list['CubeCache']
get_manipulation_status(manipulation_id: str) → dict

Get manipulation status of cube cache.

list_properties()

List properties for cube cache.

load()

Load cache.

unload()

Unload cache.

mstrio.project_objects.datasets.cube_cache.delete_cube_cache(connection: Connection, id: str, force: bool = False)

Delete single cube cache.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection().

  • id (string) – cube cache ID

  • force (bool, optional) – If True, then no additional prompt will be shown before deleting caches for given cube. Default is False.

Returns:

True for success. False otherwise.

mstrio.project_objects.datasets.cube_cache.delete_cube_caches(connection: Connection, loaded: bool = False, force: bool = False, nodes: list[str] | str | None = None, cube_id: str | None = None, db_connection_id: str | None = None) → dict | None

Delete all cube caches on a given node.

Optionally it is possible to specify for which cube or for which database connection caches will be deleted. It is also possible to delete only loaded caches.

You can specify from which nodes caches will be deleted. If nodes are None then all nodes are retrieved from cluster.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection().

  • nodes (list of strings or string, optional) – names of nodes from which caches will be deleted. By default it equals None and in that case all nodes names are loaded from the cluster.

  • cube_id (string, optional) – When provided, only caches for the cube with given ID will be deleted (if any).

  • db_connection_id (string, optional) – When provided, only caches for the database connection with given ID will be deleted (if any).

  • loaded (bool, optional) – If True then only loaded caches will be deleted. Otherwise all cubes will be returned.

  • force (bool, optional) – If True, then no additional prompt will be shown before deleting caches for given cube. Default is False.

Returns:

  • ‘succeeded’ - list with IDs of caches which were deleted

  • ’failed’ - list with IDS of caches which were not deleted

or None when user doesn’t agree for deletion when prompted

Return type:

Dictionary with two keys

mstrio.project_objects.datasets.cube_cache.list_cube_caches(connection: Connection, nodes: list[str] | str | None = None, cube_id: str | None = None, loaded: bool | None = False, db_connection_id: str | None = None, project_ids: list[str] | None = None, to_dictionary: bool | None = False, limit: int | None = None) → list['CubeCache'] | list[dict]

List cube caches. You can filter them by cube (cube_id), database connection (db_connection_id) and projects (project_ids). You can also obtain only loaded caches (loaded=True).

You can specify from which nodes caches will be retrieved. If nodes are None then all nodes are retrieved from the cluster.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection().

  • nodes (list of strings or string, optional) – names of nodes on which caches will be searched. By default it equals None and in that case all nodes’ names are loaded from the cluster.

  • cube_id (string, optional) – When provided, only caches for the cube with given ID will be returned (if any).

  • loaded (bool, optional) – If True then only loaded caches will be retrieved. Otherwise all cubes will be returned.

  • db_connection_id (string, optional) – When provided, only caches for the database connection with given ID will be returned (if any).

  • project_ids (list of string, optional) – When provided only caches for projects with given IDs will be returned (if any).

  • to_dictionary (bool, optional) – If True returns dict, by default (False) returns CubeCache objects

  • limit (integer, optional) – Cut-off value for the number of objects returned. Default value is None which means no limit.

Returns:

List of CubeCache objects when parameter to_dictionary is set to False (default value) or list of dictionaries otherwise.

mstrio.project_objects.datasets.helpers module

class mstrio.project_objects.datasets.helpers.AdvancedProperties(metric_join_types: list[mstrio.project_objects.datasets.helpers.MetricJoinType] = <factory>, attribute_join_types: list[mstrio.project_objects.datasets.helpers.AttributeJoinType] = <factory>)

Bases: Dictable

Class representation of advanced properties containing joining information.

metric_join_types

List containing joining information for each metric that appears in the template.

Type:

list[MetricJoinType], optional

attribute_join_types

List containing joining information for each attribute that appears in the template.

Type:

list[AttributeJoinType], optional

attribute_join_types: list[mstrio.project_objects.datasets.helpers.AttributeJoinType]
metric_join_types: list[mstrio.project_objects.datasets.helpers.MetricJoinType]
to_dict(camel_case: bool = True) → dict

Converts an object to a dictionary excluding object’s private properties. When converting the object to a dictionary, the object’s attributes become the dictionary’s keys and are in camel case by default Attribute values stored as objects are automatically converted to non-/ primitive data structures.

Parameters:

camel_case (bool, optional) – Set to True if attribute names should be converted from snake case to camel case. Defaults to True.

Returns:

A dictionary representation of object’s attributes and values.

By default, the dictionary keys are in camel case.

Return type:

dict

class mstrio.project_objects.datasets.helpers.AttributeFormReference(id: str, name: str | None = None)

Bases: Dictable

Class representation of single attribute form.

id

ID of the referenced attribute.

Type:

str

name

Name of attribute.

Type:

str, optional

id: str
name: str | None = None
class mstrio.project_objects.datasets.helpers.AttributeJoinType(attribute: SchemaObjectReference, no_participation_in_preserve_row: bool, resolved_location: ResolvedLocation = ResolvedLocation.DEFAULT, is_inherited: bool = True, next_no_participation_in_preserve_row: bool | None = None, next_resolved_location: mstrio.utils.vldb_mixin.ResolvedLocation | None = None)

Bases: Dictable

Class representation of single joining operation for attribute.

attribute

Reference to the attribute used for joining.

Type:

SchemaObjectReference

no_participation_in_preserve_row

Value corresponding to the targeted VLDB setting of given attribute.

Type:

bool

resolved_location

Type of location where value of related VLDB setting was last time resolved.

Type:

ResolvedLocation, optional

is_inherited

Whether the related VLDB setting value is inherited from other objects or not. If False value is set on the object. If True, value is inherited from other objects.

Type:

bool, optional

next_no_participation_in_preserve_row

Previously set value of attribute targeted VLDB setting.

Type:

bool, optional

next_resolved_location

Previously set resolved_location.

Type:

ResolvedLocation, optional

attribute: SchemaObjectReference
is_inherited: bool = True
next_no_participation_in_preserve_row: bool | None = None
next_resolved_location: mstrio.utils.vldb_mixin.ResolvedLocation | None = None
no_participation_in_preserve_row: bool
resolved_location: ResolvedLocation = 'default'
class mstrio.project_objects.datasets.helpers.AttributeTemplateUnit(id: str, name: str | None = None, alias: str | None = None, forms: list[mstrio.project_objects.datasets.helpers.AttributeFormReference] | None = None)

Bases: TemplateUnit

Class representation of single attribute template unit.

id

ID of the referenced attribute.

Type:

str

name

Name of attribute.

Type:

str, optional

alias

Alias for attribute.

Type:

str, optional

forms

Referenced attribute forms.

Type:

list[AttributeFormReference], optional

alias: str | None = None
forms: list[mstrio.project_objects.datasets.helpers.AttributeFormReference] | None = None
id: str
name: str | None = None
class mstrio.project_objects.datasets.helpers.CubeOptions(data_languages: ~mstrio.project_objects.datasets.helpers.DataLanguages = <factory>, data_refresh: ~mstrio.project_objects.datasets.helpers.DataRefreshType = DataRefreshType.REPLACE, data_partition: ~mstrio.project_objects.datasets.helpers.DataPartition = <factory>)

Bases: Dictable

Class representation of cube options for cube.

data_languages

Information related to data languages configuration.

Type:

DataLanguages, optional

data_refresh

Type of data refresh operation, default ‘DataRefreshType.REPLACE’.

Type:

DataRefreshType, optional

data_partition

Object which represents information about data partition.

Type:

DataPartition, optional

data_languages: DataLanguages
data_partition: DataPartition
data_refresh: DataRefreshType = 'replace'
class mstrio.project_objects.datasets.helpers.DataLanguageType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: AutoName

Enumeration constant indicating type of data language configuration type.

ALL_PROJECT_DATA_LANGUAGE = 'all_project_data_language'
PROJECT_DEFAULT = 'project_default'
SPECIFIC_LANGUAGES = 'specific_languages'
class mstrio.project_objects.datasets.helpers.DataLanguages(data_language_type: ~mstrio.project_objects.datasets.helpers.DataLanguageType = DataLanguageType.PROJECT_DEFAULT, selected_languages: list[str] | None = <factory>)

Bases: Dictable

Class representation of data language configuration.

data_language_type

Type of used data language configuration.

Type:

DataLanguageType

selected_languages

List with selected languages passed as abbreviations.

Type:

list[str], optional

data_language_type: DataLanguageType = 'project_default'
selected_languages: list[str] | None
class mstrio.project_objects.datasets.helpers.DataPartition(partition_attribute: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None, number_of_partitions: int | None = None, fetch_data_slices_in_parallel: bool = False)

Bases: Dictable

Class representation of data partition.

partition_attribute

Reference to attribute used in partition.

Type:

SchemaObjectReference, optional

number_of_partitions

Number of data partitions.

Type:

int, optional

fetch_data_slices_in_parallel

Bool indicating whether to fetch data in parallel, default False.

Type:

bool, optional

fetch_data_slices_in_parallel: bool = False
classmethod from_dict(source: dict[str, Any], connection: Optional[Connection] = None, to_snake_case: bool = True) → T

Initialize DataPartition object from dictionary.

number_of_partitions: int | None = None
partition_attribute: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None
to_dict(camel_case: bool = True) → dict

Converts an object to a dictionary excluding object’s private properties. When converting the object to a dictionary, the object’s attributes become the dictionary’s keys and are in camel case by default Attribute values stored as objects are automatically converted to non-/ primitive data structures.

Parameters:

camel_case (bool, optional) – Set to True if attribute names should be converted from snake case to camel case. Defaults to True.

Returns:

A dictionary representation of object’s attributes and values.

By default, the dictionary keys are in camel case.

Return type:

dict

class mstrio.project_objects.datasets.helpers.DataRefreshType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: AutoName

Enumeration constant indicating type of data refresh operation.

ADD = 'add'
DYNAMIC_REFRESH = 'dynamic_refresh'
REPLACE = 'replace'
UPSERT = 'upsert'
class mstrio.project_objects.datasets.helpers.JoinType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: AutoName

Enumeration constant indicating type of metric joining operation.

INNER = 'inner'
OUTER = 'outer'
class mstrio.project_objects.datasets.helpers.MetricElement(id: str, name: str | None = None, alias: str | None = None)

Bases: Dictable

Class representation of single metric element.

id

ID of the referenced metric.

Type:

str

name

Name of metric.

Type:

str, optional

alias

Alias for metric.

Type:

str, optional

alias: str | None = None
id: str
name: str | None = None
to_dict(camel_case: bool = True) → dict

Converts an object to a dictionary excluding object’s private properties. When converting the object to a dictionary, the object’s attributes become the dictionary’s keys and are in camel case by default Attribute values stored as objects are automatically converted to non-/ primitive data structures.

Parameters:

camel_case (bool, optional) – Set to True if attribute names should be converted from snake case to camel case. Defaults to True.

Returns:

A dictionary representation of object’s attributes and values.

By default, the dictionary keys are in camel case.

Return type:

dict

class mstrio.project_objects.datasets.helpers.MetricJoinType(metric: SchemaObjectReference, join_type: JoinType, resolved_location: ResolvedLocation = ResolvedLocation.DEFAULT, is_inherited: bool = True, next_join_type: mstrio.project_objects.datasets.helpers.JoinType | None = None, next_resolved_location: mstrio.utils.vldb_mixin.ResolvedLocation | None = None)

Bases: Dictable

Class representation of single joining operation for metric.

metric

Reference to the metric used for joining.

Type:

SchemaObjectReference

join_type

Value corresponding to the targeted VLDB setting of given metric.

Type:

JoinType

resolved_location

Type of location where value of related VLDB setting was last time resolved.

Type:

ResolvedLocation, optional

is_inherited

Whether the related VLDB setting value is inherited from other objects or not. If False value is set on the object. If True, value is inherited from other objects.

Type:

bool, optional

next_join_type

Previously set value of metric targeted VLDB setting.

Type:

JoinType, optional

next_resolved_location

Previously set resolved_location.

Type:

ResolvedLocation, optional

is_inherited: bool = True
join_type: JoinType
metric: SchemaObjectReference
next_join_type: mstrio.project_objects.datasets.helpers.JoinType | None = None
next_resolved_location: mstrio.utils.vldb_mixin.ResolvedLocation | None = None
resolved_location: ResolvedLocation = 'default'
class mstrio.project_objects.datasets.helpers.MetricTemplateUnit(elements: list[mstrio.project_objects.datasets.helpers.MetricElement])

Bases: TemplateUnit

Class representation of single metric element.

elements

List containing metric elements used in template.

Type:

list[MetricElement]

elements: list[mstrio.project_objects.datasets.helpers.MetricElement]
class mstrio.project_objects.datasets.helpers.Template(rows: list[mstrio.project_objects.datasets.helpers.TemplateUnit] = <factory>, columns: list[mstrio.project_objects.datasets.helpers.TemplateUnit] = <factory>, page_by: list[mstrio.project_objects.datasets.helpers.TemplateUnit] = <factory>)

Bases: Dictable

Class representation of single template.

rows

List containing attribute and metric elements used in template rows.

Type:

list[TemplateUnit], optional

columns

List containing attribute and metric elements used in template columns.

Type:

list[TemplateUnit], optional

page_by

List containing attribute elements used in template for paging.

Type:

list[TemplateUnit], optional

columns: list[mstrio.project_objects.datasets.helpers.TemplateUnit]
page_by: list[mstrio.project_objects.datasets.helpers.TemplateUnit]
rows: list[mstrio.project_objects.datasets.helpers.TemplateUnit]
class mstrio.project_objects.datasets.helpers.TemplateUnit

Bases: Dictable

Class representation of single template unit.

static dispatch(source, connection: mstrio.connection.Connection | None = None) → type[mstrio.project_objects.datasets.helpers.TemplateUnit]
to_dict(camel_case: bool = True) → dict

Converts an object to a dictionary excluding object’s private properties. When converting the object to a dictionary, the object’s attributes become the dictionary’s keys and are in camel case by default Attribute values stored as objects are automatically converted to non-/ primitive data structures.

Parameters:

camel_case (bool, optional) – Set to True if attribute names should be converted from snake case to camel case. Defaults to True.

Returns:

A dictionary representation of object’s attributes and values.

By default, the dictionary keys are in camel case.

Return type:

dict

class mstrio.project_objects.datasets.helpers.TemplateUnitType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: AutoName

Enumeration constant indicating type of single template unit.

ATTRIBUTE = 'attribute'
CONSOLIDATION = 'consolidation'
CUSTOM_GROUP = 'custom_group'
DIMENSION = 'dimension'
METRICS = 'metrics'
PROMPT = 'prompt'
RAW_UNIT = 'raw_unit'
class mstrio.project_objects.datasets.helpers.TimeBasedSettings(timezone: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None, calendar: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None, enable_timezone_and_calendar_reporting: bool = True)

Bases: Dictable

Class representation of time based settings.

timezone

Reference to timezone object or None.

Type:

SchemaObjectReference, optional

calendar

Reference to calendar object or None.

Type:

SchemaObjectReference, optional

enable_timezone_and_calendar_reporting

Bool indicating whether to enable timezone and calendar reporting, default True.

Type:

bool, optional

calendar: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None
enable_timezone_and_calendar_reporting: bool = True
classmethod from_dict(source: dict[str, Any], connection: Optional[Connection] = None, to_snake_case: bool = True) → T

Initialize TimeBasedSettings object from dictionary.

timezone: mstrio.modeling.schema.helpers.SchemaObjectReference | None = None

mstrio.project_objects.datasets.olap_cube module

class mstrio.project_objects.datasets.olap_cube.OlapCube(connection: Connection, id: str, name: str | None = None, instance_id: str | None = None, parallel: bool = True, progress_bar: bool = True, show_expression_as: mstrio.modeling.expression.enums.ExpressionFormat | str = ExpressionFormat.TREE, show_filter_tokens: bool = False)

Bases: ModelVldbMixin, _Cube

Manage single table cube - according to EnumDSSXMLObjectSubTypes its subtype is 776 (DssXmlSubTypeReportCube). It inherits all properties from Cube.

connection

MicroStrategy connection object returned by connection.Connection().

id

Identifier of a pre-existing cube.

Type:

str

instance_id

Identifier of a cube instance if already initialized, None by default.

Type:

str

name

Name of the OlapCube.

Type:

str

size

Size of cube.

Type:

int

status

Status of cube.

Type:

int

path

Full path of the cube on environment.

Type:

str

owner_id

ID of cube’s owner.

Type:

str

attributes

All attributes of cube.

Type:

list

metrics

All metrics of cube.

Type:

list

attr_elements

All attributes elements of cube.

Type:

list

selected_attributes

IDs of filtered attributes.

Type:

list

selected_metrics

IDs of filtered metrics.

Type:

list

selected_attr_elements

IDs of filtered attribute elements.

Type:

list

dataframe

Content of a cube extracted into a Pandas DataFrame.

Type:

DataFrame

template

Template defining OLAP Cube structure with references to attributes in rows and to metrics in columns.

Type:

Template

filter

Filtering element for OLAP Cube, needs to be in either ‘tree’ or ‘tokens’ format. If both are provided, only ‘tree’ is used.

Type:

Expression

options

Options specifying the behavior of cube. Includes possibilities for setting languages, refresh of data and partitioning by attribute.

Type:

CubeOptions

advanced_properties

Properties containing metric join type for every metric and attribute join type for every attribute provided in the template.

Type:

AdvancedProperties

time_based_settings

Settings of timezone and calendar objects specified with references by ID.

Type:

TimeBasedSettings

show_expression_as

Specify how expressions should be presented, default ‘ExpressionFormat.TREE’. Available values: - ExpressionFormat.TREE.

(expression is returned in text and tree formats)

  • ExpressionFormat.TOKENS.

    (expression is returned in text and tokens formats)

Type:

ExpressionFormat

show_filter_tokens

Specify whether ‘filter’ is returned in ‘tokens’ format, along with text and tree formats, default False. - If omitted or False, only text and tree formats are

returned.

  • If True, all text, ‘tree’ and tokens formats are returned.

Type:

bool

alter(name: str | None = None, description: str | None = None, abbreviation: str | None = None, template: mstrio.project_objects.datasets.helpers.Template | dict | None = None, filter: mstrio.modeling.expression.expression.Expression | dict | None = None, options: mstrio.project_objects.datasets.helpers.CubeOptions | dict | None = None, time_based_settings: mstrio.project_objects.datasets.helpers.TimeBasedSettings | dict | None = None) → None

Alter OLAP Cube properties by providing new name, description, abbreviation, template, filter, options or time_based_settings parameters.

Note

All types of expressions can be represented in the form of tokens, but some expressions with type predicate are yet not supported to be used for creation or modification in tokens form. For example: ‘expression_nodes.ElementListPredicate’ or ‘expression_nodes.FilterQualificationPredicate’ and some cases other involving embedded objects. Expected errors while be thrown in such cases.

Parameters:

  • name (str, optional) – New name for the OLAP Cube.

  • description (str, optional) – New description for the OLAP Cube.

  • abbreviation (str, optional) – New abbreviation for the OLAP Cube.

  • template (Template, dict, str, optional) – Template defining OLAP Cube structure with references to attributes in rows and to metrics in columns.

  • filter (Expression, dict, optional) – Filtering element for OLAP Cube, needs to be in either ‘tree’ or ‘tokens’ format. If both are provided, only ‘tree’ is used.

  • options (CubeOptions, dict, optional) – Options specifying the behavior of cube. Includes possibilities for setting languages, refresh of data and partitioning by attribute.

  • time_based_settings (TimeBasedSettings, dict, optional) – Settings of timezone and calendar objects specified with references by ID.

Raises:

  • ValueError – When arguments for altering were not provided or given template is empty.

  • helper.IServerError – When there was an error on IServer side when trying to alter an OLAP Cube.

Returns:

None

classmethod available_attribute_forms(connection: Connection, basic_info_only: bool = True, to_dataframe: bool = False) → list[dict] | list[pandas.core.frame.DataFrame]

Get all attribute forms available on I-Server. :param connection: MicroStrategy connection object returned by

connection.Connection()

Parameters:

  • basic_info_only (boolean, optional) – When True (default value) only values of id, name and type will be returned for each attribute form. When False, then all properties of each attribute form will be returned.

  • to_dataframe – When False (default value) then attribute forms are returned as a list of dictionaries. When True then attribute forms are returned as Pandas ‘DataFrame’.

Returns:

List of attribute forms or attribute forms as Pandas DataFrame.

classmethod available_attributes(connection: Connection, basic_info_only: bool = True, to_dataframe: bool = False) → list[dict] | list[pandas.core.frame.DataFrame]

Get all attributes available on I-Server. :param connection: MicroStrategy connection object returned by

connection.Connection()

Parameters:

  • basic_info_only (boolean, optional) – When True (default value) only values of id, name and type will be returned for each attribute. When False, then all properties of each attribute will be returned.

  • to_dataframe – When False (default value) then attributes are returned as a list of dictionaries. When True then attributes are returned as Pandas ‘DataFrame’.

Returns:

List of attributes or attributes as Pandas DataFrame.

classmethod available_metrics(connection: Connection, basic_info_only: bool = True, to_dataframe: bool = False) → list[dict] | list[pandas.core.frame.DataFrame]

Get all metrics available on I-Server. :param connection: MicroStrategy connection object returned by

connection.Connection()

Parameters:

  • basic_info_only (boolean, optional) – When True (default value) only values of id, name and type will be returned for each metric. When False, then all properties of each metric will be returned.

  • to_dataframe – When False (default value) then metrics are returned as a list of dictionaries. When True then metrics are returned as Pandas ‘DataFrame’.

Returns:

List of attributes or attributes as Pandas DataFrame.

classmethod create(connection: Connection, name: str, folder_id: str, description: str | None = None, template: mstrio.project_objects.datasets.helpers.Template | dict | None = None, filter: mstrio.modeling.expression.expression.Expression | dict | None = None, options: mstrio.project_objects.datasets.helpers.CubeOptions | dict | None = None, advanced_properties: mstrio.project_objects.datasets.helpers.AdvancedProperties | dict | None = None, time_based_settings: mstrio.project_objects.datasets.helpers.TimeBasedSettings | dict | None = None, template_cube: Optional[Union[OlapCube, str]] = None, show_expression_as: mstrio.modeling.expression.enums.ExpressionFormat | str = ExpressionFormat.TREE, show_filter_tokens: bool = False) → mstrio.project_objects.datasets.olap_cube.OlapCube | None

Create an OLAP Cube by defining its name, destination folder ID, description, attributes and metrics or template from ‘Template’ class to specify structure of cube additionally providing filter, options, advanced properties and time based settings.

Note

All types of expressions can be represented in the form of tokens, but some expressions with type predicate are yet not supported to be used for creation or modification in tokens form. For example: ‘expression_nodes.ElementListPredicate’ or ‘expression_nodes.FilterQualificationPredicate’ and some cases other involving embedded objects. Expected errors while be thrown in such cases.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection().

  • name (str) – OLAP Cube name.

  • folder_id (str) – ID of the folder where OLAP Cube should be saved.

  • description (str, optional) – OLAP Cube description.

  • template (Template, dict, optional) – Template defining OLAP Cube structure with references to attributes in rows and to metrics in columns.

  • filter (Expression, dict, optional) – Filtering element for OLAP Cube, needs to be in either ‘tree’ or ‘tokens’ format. If both are provided, only ‘tree’ is used.

  • options (CubeOptions, dict, optional) – Options specifying the behavior of cube. Includes possibilities for setting languages, refresh of data and partitioning by attribute.

  • advanced_properties (AdvancedProperties, dict, optional) – Properties containing metric join type for every metric and attribute join type for every attribute provided in the template.

  • time_based_settings (TimeBasedSettings, dict, optional) – Settings of timezone and calendar objects specified with references by ID.

  • template_cube (OlapCube, str, optional) – If specified, a newly created OLAP Cube will inherit its template from a provided OlapCube object. A filter of the referenced cube will be used in the case when a ‘filter’ parameter was not specified.

  • show_expression_as (ExpressionFormat, str, optional) –

    Specify how expressions should be presented, default ‘ExpressionFormat.TREE’. Available values: - None.

    (expression is returned in ‘text’ format)

    • ExpressionFormat.TREE or tree.

      (expression is returned in text and tree formats)

    • ExpressionFormat.TOKENS or tokens.

      (expression is returned in text and tokens formats)

  • show_filter_tokens (bool, optional) –

    Specify whether ‘filter’ is returned in ‘tokens’ format, along with text and tree formats, default False. - If omitted or False, only text and tree formats are

    returned.

    • If True, all text, ‘tree’ and tokens formats are returned.

Raises:

ValueError – When provided template is empty.

Returns:

Newly created OLAP Cube or None in case of incorrectly provided

arguments.

export_sql_view()

Export SQL View of an OLAP Cube. :returns: SQL View of an OLAP Cube.

list_attribute_forms() → list[dict[list[tuple], str]]

Listing forms for every attribute specified in template. If default forms for attribute were used, string indicating that will be returned instead of forms.

Returns:

List with dicts containing attribute name as key and forms as values or string indicating that they are default.

publish() → Job

Publish an OLAP Cube. Request to publish an OLAP Cube is an asynchronous operation, so the result of it can be seen after calling method refresh_status() inherited from Cube class. :returns: Job instance.

remove_partition_attribute() → None

Remove assigned to OLAP Cube partition attribute.

Returns:

None

set_partition_attribute(attribute: mstrio.modeling.schema.attribute.attribute.Attribute | str) → None

Assign new partition attribute to OLAP Cube.

Parameters:

attribute (Attribute, str) – Partition attribute that will be set, could be provided by ID or with ‘Attribute’ object.

Returns:

None

mstrio.project_objects.datasets.olap_cube.list_olap_cubes(connection: Connection, name: str | None = None, search_pattern: mstrio.object_management.search_enums.SearchPattern | int = SearchPattern.CONTAINS, project_id: str | None = None, project_name: str | None = None, to_dictionary: bool = False, limit: int | None = None, **filters) → list[mstrio.project_objects.datasets.olap_cube.OlapCube] | list[dict]

Get list of OlapCube objects or dicts with them. Optionally filter cubes by specifying ‘name’. Optionally use to_dictionary to choose output format. Wildcards available for ‘name’:

? - any character * - 0 or more of any characters e.g. name = ?onny will return Sonny and Tonny

Specify either project_id or project_name. When project_id is provided (not None), project_name is omitted. .. note:

When `project_id` is `None` and `project_name` is `None`,
then its value is overwritten by `project_id` from `connection` object.
Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection()

  • name (string, optional) – value the search pattern is set to, which will be applied to the names of olap cubes being searched

  • search_pattern (SearchPattern enum or int, optional) – pattern to search for, such as Begin With or Contains. Possible values are available in ENUM mstrio.object_management.SearchPattern. Default value is BEGIN WITH (4).

  • project_id (str, optional) – Project ID

  • project_name (str, optional) – Project name

  • to_dictionary (bool, optional) – If True returns dict, by default (False) returns OlapCube objects

  • limit (integer, optional) – limit the number of elements returned. If None all object are returned.

  • **filters – Available filter parameters: [‘id’, ‘name’, ‘type’, ‘subtype’, ‘date_created’, ‘date_modified’, ‘version’, ‘owner’, ‘ext_type’, ‘view_media’, ‘certified_info’]

Returns:

list with OlapCubes or list of dictionaries

mstrio.project_objects.datasets.super_cube module

class mstrio.project_objects.datasets.super_cube.SuperCube(connection: Connection, id: str | None = None, name: str | None = None, description: str | None = None, instance_id: str | None = None, progress_bar: bool = True, parallel: bool = True)

Bases: _Cube, CertifyMixin

Manage multiple table cube (MTDI aka Super Cube) - according to EnumDSSXMLObjectSubTypes its subtype is 779 (DssXmlSubTypeReportEmmaCube). It inherits all properties from Cube.

connection

MicroStrategy connection object returned by connection.Connection().

id

Identifier of a pre-existing cube.

instance_id

Identifier of a cube instance if already initialized, None by default.

Type:

str

name

Name of the SuperCube.

description

Description given to the SuperCube.

id

Unique identifier for the super cube. Used to update a existing super cube or generated after creating a new super cube. (deprecated)

upload_body

upload body of super cube

Type:

string

session_id

ID of session used for uploading and publishing super cube

Type:

string

size

size of cube

Type:

integer

status

status of cube

Type:

integer

path

full path of the cube on environment

Type:

string

owner_id

ID of cube’s owner

Type:

string

attributes

all attributes of cube

Type:

list

metrics

all metrics of cube

Type:

list

attr_elements

all attributes elements of cube

Type:

list

selected_attributes

IDs of filtered attributes

Type:

list

selected_metrics

IDs of filtered metrics

Type:

list

selected_attr_elements

IDs of filtered attribute elements

Type:

list

dataframe

content of a cube extracted into a Pandas DataFrame

Type:

object

table_definition
add_table(name, data_frame, update_policy, to_metric=None, to_attribute=None)

Add a Pandas.DataFrame to a collection of tables which are later used to populate the MicroStrategy super cube with data.

Parameters:

  • name (str) – Logical name of the table that is visible to users of the super cube in MicroStrategy.

  • data_frame (pandas.DataFrame) – Pandas DataFrame to add or update.

  • update_policy (str) – Update operation to perform. One of ‘add’ (inserts new, unique rows), ‘update’ (updates data in existing rows and columns), ‘upsert’ (updates existing data and inserts new rows), or ‘replace’ (replaces the existing data with new data).

  • to_metric (optional, list of str) – By default, Python numeric data types are treated as metrics while character and date types are treated as attributes. For example, a column of integer-like strings (“1”, “2”, “3”) would, by default, be an attribute. If the intent is to format this data as a metric, provide the respective column name as a string in a list to the to_metric parameter.

  • to_attribute (optional, list of str) – Logical opposite of to_metric. Helpful for formatting an integer-based row identifier as a primary key in the super cube.

create(folder_id: str | None = None, auto_upload: bool = True, auto_publish: bool = True, chunksize: int = 100000, force: bool = False, attribute_forms: list[mstrio.project_objects.datasets.super_cube.SuperCubeAttribute] | None = None) → None

Create a new super cube and initialize cube object after successful creation. This function does not return new super cube, but it updates object inplace.

Parameters:

  • folder_id (str, optional) – ID of the shared folder in which the super cube will be created. If None, defaults to the user’s My Reports folder.

  • auto_upload (bool, optional) – If True, automatically uploads the data to the I-Server. If False, simply creates the super cube definition but does not upload data to it.

  • auto_publish (bool, optional) – If True, automatically publishes the data used to create the super cube definition. If False, simply creates the super cube but does not publish it. To publish the super cube, data has to be uploaded first.

  • chunksize (int, optional) – Number of rows to transmit to the I-Server with each request when uploading.

  • force (bool, optional) – If True, skip checking if a super cube already exist in the folder with the given name. Defaults to False.

  • attribute_forms (list[SuperCubeAttribute], optional) – list

  • SuperCubeAttribute (of instances of) –

  • to (it contains mapping of columns) –

  • not (different forms of the same attribute. If this argument is) –

  • provided (name. If it is) –

  • column (a separate attribute is created for every distinct) –

  • provided –

  • to –

  • that (attributes as different form of an attribute. For all columns) –

  • expression (are not part of any attribute's form) –

  • attribute (separate) –

  • created. (will be) –

export_sql_view() → str

Export SQL View of a Super Cube.

Returns:

SQL View of a Super Cube.

publish() → bool

Publish the uploaded data to the selected super cube.

Note

A super cube can be published just once.

Returns:

True if the data was published successfully, else False.

publish_status()

Check the status of data that was uploaded to a super cube.

Returns: status: The status of the publication process as a dictionary.

In the ‘status’ key, “1” denotes completion.

remove_table(name)

Removes a table from a collection of tables which are later used to populate the MicroStrategy super cube with data.

Note: this operation is executed locally and is used only to prepare

data before sending it to server. You can check current state of tables with property tables.

Parameters:

name (str) – Logical name of the table that is visible to users of the super cube in MicroStrategy.

reset_session()

Reset upload session.

save_as(name: str, description: str | None = None, folder_id: str | None = None, table_name: str | None = None) → SuperCube

Creates a new single-table cube with the data frame stored in the SuperCube instance SuperCube.dataframe.

Parameters:

  • name (str) – Name of cube.

  • description (str) – Description of the cube.

  • folder_id (str, optional) – ID of the shared folder that the super cube should be created within. If None, defaults to the user’s My Reports folder.

  • table_name (str, optional) – Name of the table. If None (default), the first table name of the original cube will be used.

update(chunksize: int = 100000, auto_publish: bool = True)

Updates a super cube with new data.

Parameters:

  • chunksize (int, optional) – Number of rows to transmit to the server with each request.

  • auto_publish – If True, automatically publishes the data used to update the super cube definition to the super cube. If False, simply updates the super cube but does not publish it.

static upload_status(connection: Connection, id: str, session_id: str)

Check the status of data that was uploaded to a super cube.

Parameters:

  • connection (Optional[Connection]) – MicroStrategy connection object returned by connection.Connection().

  • id (Optional[str]) – Identifier of a pre-existing super cube.

  • session_id (Optional[str]) – Identifier of the server session used for collecting uploaded data.

Returns:

The status of the publication process as a dictionary. In

the ‘status’ key, “1” denotes completion.

Return type:

status

class mstrio.project_objects.datasets.super_cube.SuperCubeAttribute(name: str, forms: list[mstrio.project_objects.datasets.super_cube.SuperCubeAttributeForm])

Bases: object

A class representing a multiform attribute for Super Cubes.

name

a name of multiform attribute

Type:

str

forms

a list of attribute forms

Type:

list[SuperCubeAttributeForm]

forms: list[mstrio.project_objects.datasets.super_cube.SuperCubeAttributeForm]
name: str
to_dict()
class mstrio.project_objects.datasets.super_cube.SuperCubeAttributeForm(category: str, expressions: list[mstrio.project_objects.datasets.super_cube.SuperCubeFormExpression])

Bases: object

A class representing an attribute form for used to define multiform attributes for Super Cubes.

category

form’s category

Type:

str

expressions

list of form expressions

Type:

list[SuperCubeFormExpressions]

category: str
expressions: list[mstrio.project_objects.datasets.super_cube.SuperCubeFormExpression]
to_dict()
class mstrio.project_objects.datasets.super_cube.SuperCubeFormExpression(table: str, column: str)

Bases: object

A class representing a form expression used to define multiform attributes for Super Cubes. Links an attribute form to the column in the table.

table

name of a table

Type:

str

column

name of a column

Type:

str

column: str
table: str
to_dict()
mstrio.project_objects.datasets.super_cube.list_super_cubes(connection: Connection, name: str | None = None, search_pattern: mstrio.object_management.search_enums.SearchPattern | int = SearchPattern.CONTAINS, project_id: str | None = None, project_name: str | None = None, to_dictionary: bool = False, limit: int | None = None, **filters) → list[mstrio.project_objects.datasets.super_cube.SuperCube] | list[dict]

Get list of SuperCube objects or dicts with them. Optionally filter cubes by specifying ‘name’.

Optionally use to_dictionary to choose output format.

Wildcards available for ‘name’:

? - any character * - 0 or more of any characters e.g. name = ?onny will return Sonny and Tonny

Specify either project_id or project_name. When project_id is provided (not None), project_name is omitted.

Note

When project_id is None and project_name is None, then its value is overwritten by project_id from connection object.

Parameters:

  • connection – MicroStrategy connection object returned by connection.Connection()

  • name (string, optional) – value the search pattern is set to, which will be applied to the names of super cubes being searched

  • search_pattern (SearchPattern enum or int, optional) – pattern to search for, such as Begin With or Contains. Possible values are available in ENUM mstrio.object_management.SearchPattern. Default value is BEGIN WITH (4).

  • project_id (string, optional) – Project ID

  • project_name (string, optional) – Project name

  • to_dictionary (bool, optional) – If True returns dict, by default (False) returns SuperCube objects

  • limit (integer, optional) – limit the number of elements returned. If None all object are returned.

  • **filters – Available filter parameters: [‘id’, ‘name’, ‘type’, ‘subtype’, ‘date_created’, ‘date_modified’, ‘version’, ‘owner’, ‘ext_type’, ‘view_media’, ‘certified_info’]

Returns:

list with SuperCubes or list of dictionaries

Module contents