aisquared.config.analytic package

Submodules

aisquared.config.analytic.DeployedAnalytic module

class aisquared.config.analytic.DeployedAnalytic.DeployedAnalytic(url: str, method: str, input_type: str, headers: dict | None = None, body: dict | None = None)[source]

Bases: BaseObject

Interaction with a remote endpoint.

Example usage:

>>> import aisquared
>>> analytic = aisquared.config.analytic.DeployedAnalytic(
    'model_url',
    'POST',
    'text',
    {
        'Content-Type' : 'application/json'
    },
    {
        'data_to_be_sent' : '{{input}}'
    }
)
>>> analytic.to_dict()

property body

property headers

property input_type

property method

to_dict() → dict[source]: Get the object as a dictionary

property url

aisquared.config.analytic.DeployedModel module

class aisquared.config.analytic.DeployedModel.DeployedModel(url: str, input_type: str, headers: dict | None = None, body_key: str | None = None, return_key: str | None = None, body_setup: dict | None = None, body_setup_replace_value: str = '{DATAPOINT}')[source]

Bases: BaseObject

Interaction with a remote model

Example usage:

>>> import aisquared
>>> analytic = aisquared.config.analytic.DeployedModel(
    'model_url',
    'text'
)
>>> analytic.to_dict()
{'className': 'DeployedModel',
'params': {'url': 'model_url',
'inputType': 'text',
'headers': None,
'bodyKey': None,
'returnKey': None,
'bodySetup': None,
'bodySetupReplaceValue': None}}

property body_key

property body_setup

property body_setup_replace_value

property headers

property input_type

property return_key

to_dict() → dict[source]: Get the config object as a dictionary

property url

aisquared.config.analytic.LocalAnalytic module

class aisquared.config.analytic.LocalAnalytic.LocalAnalytic(path: str, input_type: str, all: bool = False)[source]

Bases: BaseObject

Interaction with an analytic (lookup table) saved to the local file system

Example usage:

>>> import aisquared
>>> analytic = aisquared.config.analytic.LocalAnalytic(
    'analytic_path',
    'text'
)
>>> analytic.to_dict()
{'className': 'LocalAnalytic',
'params': {'path': 'analytic_path',
'inputType': 'text',
'all': False}}

property all

property input_type

property path

to_dict() → dict[source]: Get the configuration object as a dictionary

aisquared.config.analytic.LocalModel module

class aisquared.config.analytic.LocalModel.LocalModel(path: str, input_type: str)[source]

Bases: BaseObject

Interaction with a model currently saved to the local file system

Example usage:

>>> import aisquared
>>> analytic = aisquared.config.analytic.LocalModel(
    'model_path',
    'text'
)
>>> analytic.to_dict()
{'className': 'LocalModel',
'params': {'path': 'model_path',
'inputType': 'text'}}

property input_type

property path

to_dict() → dict[source]: Get the configuration object as a dictionary

aisquared.config.analytic.ReverseMLWorkflow module

class aisquared.config.analytic.ReverseMLWorkflow.ReverseMLWorkflow(label: str, connector_type: str, connector_action: str = 'read', input_type: str = 'text', filter_type: str = 'input', file_names: list = [], bucket: str = '', filter_by_columns: list = [], all: bool = False, arn: str = '', host: str = '', path: str = '', port: str = '', role: str = '', soql: str = '', query: str = '', token: str = '', column: str = '', db_name: str = '', db_user: str = '', period: int | None = None, schema: str = '', secret: str = '', account: str = '', data_map: list = [], db_table: str = '', client_id: str = '', file_name: str = '', password: str = '', schedule: str = '', sync_keys: dict = {'destination': '', 'source': ''}, warehouse: str = '', data_source: str = '', cluster_name: str = '', client_secret: str = '', organization: str = '', authentication_type: str = '')[source]

Bases: BaseObject

Creation of a ReverseML Workflow to interact with remote data sources

to_dict() → dict[source]: Get the configuration object as a dictionary

Module contents

The aisquared.config.analytic subpackage contains objects for packaging individual analytics.