Index

Module to interact with Knowledge Models.

This module contains class to interact with Knowledge Models in Studio.

Typical usage example:

```python
knowledge_model = package.get_knowledge_model(ANALYSIS_ID)
knowledge_model = package.create_knowledge_model(content)
knowledge_model.delete()
```

KnowledgeModel

Bases: ContentNode

Knowledge model object to interact with knowledge model specific studio endpoints.

permissions class-attribute instance-attribute

permissions = Field(alias='permissions')

tenant_id class-attribute instance-attribute

tenant_id = Field(alias='tenantId')

id instance-attribute

id

Id of studio content node.

key instance-attribute

key

Key of studio content node.

name class-attribute instance-attribute

name = Field(alias='name')

root_node_key class-attribute instance-attribute

root_node_key = Field(alias='rootNodeKey')

base class-attribute instance-attribute

base = Field(alias='base')

asset_type class-attribute instance-attribute

asset_type = Field(alias='assetType')

node_type class-attribute instance-attribute

node_type = Field(alias='nodeType')

parent_node_key class-attribute instance-attribute

parent_node_key = Field(alias='parentNodeKey')

parent_node_id class-attribute instance-attribute

parent_node_id = Field(alias='parentNodeId')

invalid_content class-attribute instance-attribute

invalid_content = Field(alias='invalidContent')

serialized_content instance-attribute

serialized_content

Serialized content of content node.

serialization_type class-attribute instance-attribute

serialization_type = Field(alias='serializationType')

draft_id class-attribute instance-attribute

draft_id = Field(alias='draftId')

working_draft_id class-attribute instance-attribute

working_draft_id = Field(alias='workingDraftId')

activated_draft_id class-attribute instance-attribute

activated_draft_id = Field(alias='activatedDraftId')

show_in_viewer_mode class-attribute instance-attribute

show_in_viewer_mode = Field(alias='showInViewerMode')

public_available class-attribute instance-attribute

public_available = Field(alias='publicAvailable')

embeddable class-attribute instance-attribute

embeddable = Field(alias='embeddable')

root_node_id class-attribute instance-attribute

root_node_id = Field(alias='rootNodeId')

order class-attribute instance-attribute

order = Field(alias='order')

source class-attribute instance-attribute

source = Field(alias='source')

asset_metadata_transport class-attribute instance-attribute

asset_metadata_transport = Field(
    alias="assetMetadataTransport"
)

space_id instance-attribute

space_id

Id of space where content node is located.

change_date class-attribute instance-attribute

change_date = Field(alias='changeDate')

created_by_id class-attribute instance-attribute

created_by_id = Field(alias='createdById')

creation_date class-attribute instance-attribute

creation_date = Field(alias='creationDate')

created_by_name class-attribute instance-attribute

created_by_name = Field(alias='createdByName')

updated_by class-attribute instance-attribute

updated_by = Field(alias='updatedBy')

root class-attribute instance-attribute

root = Field(alias='root')

asset class-attribute instance-attribute

asset = Field(alias='asset')

object_id class-attribute instance-attribute

object_id = Field(alias='objectId')

root_with_key instance-attribute

root_with_key

identifier class-attribute instance-attribute

identifier = Field(alias='identifier')

client class-attribute instance-attribute

client = Field(..., exclude=True)

from_transport classmethod

from_transport(client, content_node_transport)

Creates high-level content node object from given ContentNodeTransport.

Parameters:

• client (Client) –

  Client to use to make API calls for given content node.

• content_node_transport (ContentNodeTransport) –

  ContentNodeTransport object containing properties of content node.

Returns:

• ContentNode –

  A ContentNode object with properties from transport and given client.

update

update()

Pushes local changes of content node to EMS and updates properties with response from EMS.

sync

sync()

Syncs content node properties with EMS.

delete

delete()

Deletes content node.

is_package staticmethod

is_package(content_node_transport)

Returns whether content node transport is package.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is package.

is_folder staticmethod

is_folder(content_node_transport)

Returns whether content node transport is package.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is folder.

is_analysis staticmethod

is_analysis(content_node_transport)

Returns whether content node transport is analysis.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is analysis.

is_knowledge_model staticmethod

is_knowledge_model(content_node_transport)

Returns whether content node transport is knowledge model.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is knowledge model.

is_action_flow staticmethod

is_action_flow(content_node_transport)

Returns whether content node transport is action flow.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is action flow.

is_view staticmethod

is_view(content_node_transport)

Returns whether content node transport is view.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is view.

is_simulation staticmethod

is_simulation(content_node_transport)

Returns whether content node transport is simulation.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is simulation.

is_skill staticmethod

is_skill(content_node_transport)

Returns whether content node transport is skill.

Parameters:

• content_node_transport (ContentNodeTransport) –

  Content node transport to check.

Returns:

• bool –

  Boolean if transport is skill.

create_kpi

create_kpi(id_, display_name, pql, **kwargs)

Creates new kpi with id, display name, and pql in given knowledge model.

Parameters:

• id_ (str) –

  Id of new kpi.

• display_name (str) –

  Display name of new kpi.

• pql (str) –

  PQL query of new kpi.

• **kwargs (Any, default: {} ) –

  Additional parameters set for KpiMetadata object.

Returns:

• Kpi –

  A Kpi object for newly created kpi.

Examples:

Create a kpi:

kpi = knowledge_model.create_kpi(
    id_="TEST_KPI",
    display_name="Test KPI",
    pql='COUNT("BSEG"."BELNR")',
)

get_kpi

get_kpi(id_)

Gets kpi with given id.

Parameters:

• id_ (str) –

  Id of kpi.

Returns:

• Kpi –

  A Kpi object for kpi with given id.

get_kpis

get_kpis()

Gets all kpis of knowledge model.

Returns:

• CelonisCollection[Kpi] –

  A list containing all kpis.

create_variable

create_variable(id_, display_name, value, **kwargs)

Creates new variable with id, display name, and pql in given knowledge model.

Parameters:

• id_ (str) –

  Id of new variable.

• display_name (str) –

  Display name of new variable.

• value (str) –

  Value of new variable.

• **kwargs (Any, default: {} ) –

  Additional parameters set for VariableMetadata object.

Returns:

• Variable –

  A Variable object for newly created variable.

Examples:

Create a variable:

variable = knowledge_model.create_variable(
    id_="TEST_VARIABLE",
    display_name="Test Variable",
    value='Test Value',
)

get_variable

get_variable(id_)

Gets variable with given id.

Parameters:

• id_ (str) –

  Id of variable.

Returns:

• Variable –

  A Variable object for variable with given id.

get_variables

get_variables()

Gets all variables of knowledge model.

Returns:

• CelonisCollection[Variable] –

  A list containing all variables.

create_filter

create_filter(id_, display_name, pql, **kwargs)

Creates new filter with id, display name, and pql in given knowledge model.

Parameters:

• id_ (str) –

  Id of new filter.

• display_name (str) –

  Display name of new filter.

• pql (str) –

  PQL query of new filter.

• **kwargs (Any, default: {} ) –

  Additional parameters set for FilterMetadata object.

Returns:

• Filter –

  A Filter object for newly created filter.

Examples:

Create a filter:

filter = knowledge_model.create_filter(
    id_="TEST_FILTER",
    display_name="Test FILTER",
    pql='FILTER "BSEG"."BELNR" = \'TEST\''
)

get_filter

get_filter(id_)

Gets filter with given id.

Parameters:

• id_ (str) –

  Id of filter.

Returns:

• Filter –

  A Filter object for filter with given id.

get_filters

get_filters()

Gets all filters of knowledge model.

Returns:

• CelonisCollection[Filter] –

  A list containing all filters.

get_content

get_content(
    with_variable_replacement=True,
    with_autogenerated_data_model_data=True,
    with_default_values=True,
    validate_pql=True,
    with_unknown_variables_validation=True,
)

Returns final read only content of knowledge model (including inherited properties).

Parameters:

• with_variable_replacement (bool, default: True ) –

  Specifies if variables are replaced by their values in knowledge model.

• with_autogenerated_data_model_data (bool, default: True ) –

  Specifies whether auto generated KPIs and records for data model should be added to content.

• with_default_values (bool, default: True ) –

  Specifies if default values are added to content.

• validate_pql (bool, default: True ) –

  Specifies if PQLs in knowledge model are validated.

• with_unknown_variables_validation (bool, default: True ) –

  Specifies if unknown variables are validated.

Returns:

• Optional[FinalKnowledgeModelContent] –

  Knowledge model content.

Examples:

Extract data based on PQLs from knowledge model:

from pycelonis.pql import PQL, PQLColumn

record = knowledge_model.get_content().records.find_by_id('ACTIVITIES')
attribute = record.attributes.find_by_id('ACTIVITY_EN')

query = PQL() + attribute.get_column()

data_query, query_environment = knowledge_model.resolve_query(query)
df = data_model.export_data_frame(data_query, query_environment)

resolve_query

resolve_query(query, draft=True, **kwargs)

Returns Data Query and Query environment for a knowledge model.

Warning

The method knowledge_model.resolve_query has been deprecated and will be removed in future versions. Please use SaolaPy from now on to export PQL queries:

import pycelonis.pql as pql
from pycelonis.pql.saola_connector import KnowledgeModelSaolaConnector

df = pql.DataFrame.from_pql(query, saola_connector=KnowledgeModelSaolaConnector(
    data_model, knowledge_model
))
df.head()

Use this method to resolve queries that are based on Knowledge Model content. The returned DataQuery and QueryEnvironment can than be used to query data via DataModel.export_data_frame.

Parameters:

• query (PQL) –

  PQL query to be resolved.

• draft (bool, default: True ) –

  If true, uses draft of knowledge model, if false uses published version.

• **kwargs (Any, default: {} ) –

  Key word arguments are passed to get_content function.

Returns:

• Tuple[DataQuery, Optional[QueryEnvironment]] –

  Returns Data Query and Query environment.

Examples:

Extract data based on PQLs from knowledge model:

from pycelonis.pql import PQL, PQLColumn

record = knowledge_model.get_content().records.find_by_id('ACTIVITIES')
attribute = record.attributes.find_by_id('ACTIVITY_EN')

query = PQL() + attribute.get_column()

data_query, query_environment = knowledge_model.resolve_query(query)
df = data_model.export_data_frame(data_query, query_environment)