abacusai.eda

Classes

`EdaVersion`	A version of an eda object
`RefreshSchedule`	A refresh schedule for an object. Defines when the next version of the object will be created
`AbstractApiClass`
`Eda`	A exploratory data analysis object

Module Contents

class abacusai.eda.EdaVersion(client, edaVersion=None, status=None, edaId=None, edaStartedAt=None, edaCompletedAt=None, referenceFeatureGroupVersion=None, testFeatureGroupVersion=None, error=None)

Bases: abacusai.return_class.AbstractApiClass

A version of an eda object

Parameters:

client (ApiClient) – An authenticated API Client instance
edaVersion (str) – The unique identifier of a eda version.
status (str) – The current status of the eda object.
edaId (str) – A reference to the eda this version belongs to.
edaStartedAt (str) – The start time and date of the eda process.
edaCompletedAt (str) – The end time and date of the eda process.
referenceFeatureGroupVersion (list[str]) – Feature group version IDs that this refresh pipeline run is analyzing.
testFeatureGroupVersion (list[str]) – Feature group version IDs that this refresh pipeline run is analyzing.
error (str) – Relevant error if the status is FAILED.

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: EdaVersion

describe()

Retrieves a full description of the specified EDA version.

Parameters:: eda_version (str) – Unique string identifier of the EDA version.
Returns:: An EDA version.
Return type:: EdaVersion

delete()

Deletes the specified EDA version.

Parameters:: eda_version (str) – Unique string identifier of the EDA version to delete.

get_eda_collinearity()

Gets the Collinearity between all features for the Exploratory Data Analysis.

Parameters:: eda_version (str) – Unique string identifier associated with the EDA instance.
Returns:: An object with a record of correlations between each feature for the EDA.
Return type:: EdaCollinearity

get_eda_data_consistency(transformation_feature=None)

Gets the data consistency for the Exploratory Data Analysis.

Parameters:: transformation_feature (str) – The transformation feature to get consistency for.
Returns:: Object with duplication, deletion, and transformation data for data consistency analysis for an EDA.
Return type:: EdaDataConsistency

get_collinearity_for_feature(feature_name=None)

Gets the Collinearity for the given feature from the Exploratory Data Analysis.

Parameters:: feature_name (str) – Name of the feature for which correlation is shown.
Returns:: Object with a record of correlations for the provided feature for an EDA.
Return type:: EdaFeatureCollinearity

get_feature_association(reference_feature_name, test_feature_name)

Gets the Feature Association for the given features from the feature group version within the eda_version.

Parameters:

reference_feature_name (str) – Name of the feature for feature association (on x-axis for the plots generated for the Feature association in the product).
test_feature_name (str) – Name of the feature for feature association (on y-axis for the plots generated for the Feature association in the product).

Returns:

An object with a record of data for the feature association between the two given features for an EDA version.

Return type:

EdaFeatureAssociation

get_eda_forecasting_analysis()

Gets the Forecasting analysis for the Exploratory Data Analysis.

Parameters:: eda_version (str) – Unique string identifier associated with the EDA version.
Returns:: Object with forecasting analysis that includes sales_across_time, cummulative_contribution, missing_value_distribution, history_length, num_rows_histogram, product_maturity data.
Return type:: EdaForecastingAnalysis

wait_for_eda(timeout=1200)

A waiting call until eda version is ready.

Parameters:: timeout (int) – The waiting time given to the call to finish, if it doesn’t finish by the allocated time, the call is said to be timed out.

get_status()

Gets the status of the eda version.

Returns:: A string describing the status of the model monitor version, for e.g., pending, complete, etc.
Return type:: str

class abacusai.eda.RefreshSchedule(client, refreshPolicyId=None, nextRunTime=None, cron=None, refreshType=None, error=None)

Bases: abacusai.return_class.AbstractApiClass

A refresh schedule for an object. Defines when the next version of the object will be created

Parameters:

client (ApiClient) – An authenticated API Client instance
refreshPolicyId (str) – The unique identifier of the refresh policy
nextRunTime (str) – The next run time of the refresh policy. If null, the policy is paused.
cron (str) – A cron-style string that describes the when this refresh policy is to be executed in UTC
refreshType (str) – The type of refresh that will be run
error (str) – An error message for the last pipeline run of a policy

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

class abacusai.eda.AbstractApiClass(client, id)

__eq__(other): Return self==value.

_get_attribute_as_dict(attribute)

class abacusai.eda.Eda(client, edaId=None, name=None, createdAt=None, projectId=None, featureGroupId=None, referenceFeatureGroupVersion=None, testFeatureGroupVersion=None, edaConfigs=None, latestEdaVersion={}, refreshSchedules={})

Bases: abacusai.return_class.AbstractApiClass

A exploratory data analysis object

Parameters:

client (ApiClient) – An authenticated API Client instance
edaId (str) – The unique identifier of the eda object.
name (str) – The user-friendly name for the eda object.
createdAt (str) – Date and time at which the eda object was created.
projectId (str) – The project this eda object belongs to.
featureGroupId (str) – Feature group ID for which eda analysis is being done.
referenceFeatureGroupVersion (str) – Reference Feature group version for data consistency analysis, will be latest feature group version for collinearity analysis.
testFeatureGroupVersion (str) – Test Feature group version for data consistency analysis, will be latest feature group version for collinearity analysis.
edaConfigs (dict) – Configurations for eda object.
latestEdaVersion (EdaVersion) – The latest eda object version.
refreshSchedules (RefreshSchedule) – List of refresh schedules that indicate when the next model version will be trained.

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

rerun()

Reruns the specified EDA object.

Parameters:: eda_id (str) – Unique string identifier of the EDA object to rerun.
Returns:: The EDA object that is being rerun.
Return type:: Eda

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: Eda

describe()

Retrieves a full description of the specified EDA object.

Parameters:: eda_id (str) – Unique string identifier associated with the EDA object.
Returns:: Description of the EDA object.
Return type:: Eda

list_versions(limit=100, start_after_version=None)

Retrieves a list of versions for a given EDA object.

Parameters:

limit (int) – The maximum length of the list of all EDA versions.
start_after_version (str) – The ID of the version after which the list starts.

Returns:

A list of EDA versions.

Return type:

list[EdaVersion]

rename(name)

Renames an EDA

Parameters:: name (str) – The new name to apply to the model monitor.

delete()

Deletes the specified EDA and all its versions.

Parameters:: eda_id (str) – Unique string identifier of the EDA to delete.