Utilities

These classes are various utilities that are used in various parts of the API.

class dataikuapi.dss.utils.DSSDatasetSelectionBuilder

Builder for a “dataset selection”. In DSS, a dataset selection is used to select a part of a dataset for processing.

Depending on the location where it is used, a selection can include: * Sampling * Filtering by partitions (for partitioned datasets) * Filtering by an expression * Selection of columns * Ordering

Please see the sampling documentation of DSS for a detailed explanation of the sampling methods.

build()

Returns:

the built selection dict

Return type:

dict

with_head_sampling(limit)

Sets the sampling to ‘first records’ mode

Parameters:

limit (int) – Maximum number of rows in the sample

with_all_data_sampling()

Sets the sampling to ‘no sampling, all data’ mode

with_random_fixed_nb_sampling(nb)

Sets the sampling to ‘Random sampling, fixed number of records’ mode

Parameters:

nb (int) – Maximum number of rows in the sample

with_selected_partitions(ids)

Sets partition filtering on the given partition identifiers.

Warning

The dataset to select must be partitioned.

Parameters:

ids (list) – list of selected partitions

class dataikuapi.dss.utils.DSSFilterBuilder

Builder for a “filter”. In DSS, a filter is used to define a subset of rows for processing.

build()

Returns:

the built filter

Return type:

dict

with_distinct()

Sets the filter to deduplicate

with_formula(expression)

Sets the formula (DSS formula) used to filter rows

Parameters:

expression (str) – the DSS formula

class dataikuapi.dss.utils.DSSInfoMessages(data)

Contains a list of dataikuapi.dss.utils.DSSInfoMessage.

Important

Do not instantiate this class.

property messages

The messages as a list of dataikuapi.dss.utils.DSSInfoMessage

property has_messages

True if there is any message

property has_error

True if there is any error message

property max_severity

The max severity of the messages

property has_success

True if there is any success message

property has_warning

True if there is any warning message

class dataikuapi.dss.utils.DSSInfoMessage(data)

A message with a code, a title, a severity and a content.

Important

Do not instantiate this class.

property severity

The severity of the message

property code

The code of the message

property details

The details of the message

property title

The title of the message

property message

The full message

class dataikuapi.dss.utils.DSSSimpleFilter(operator, column=None, value=None, clauses=None)

A simplified representation of a DSS filter. It can be built from scratch or from an existing DSSFilter.

A simple filter is a dictionary with the following keys:

• operator: one of the values of DSSSimpleFilterOperator

• column: the column to apply the filter on (for unary and binary operators)

• value: the value to compare with (for binary operators)

• clauses: a list of other simple filters (for AND/OR operators)

to_dss_filter()

Converts the simple filter to a DSS filter dictionary.

Returns:

A DSS filter dictionary that can be used in visual recipes.

Return type:

dict

static from_dss_filter(dss_filter)

Converts a DSS filter dictionary to a simple filter.

Parameters:

dss_filter (dict) – A DSS filter dictionary.

Returns:

A simple filter object.

Return type:

DSSSimpleFilter

to_dict()

Converts the simple filter to a serializable dictionary.

Returns:

A dictionary representation of the simple filter.

Return type:

dict

static and_(clauses)

static or_(clauses)

static eq(column, value)

static neq(column, value)

static gt(column, value)

static gte(column, value)

static lt(column, value)

static lte(column, value)

static empty(column)

static not_empty(column)

static contains(column, value)

static matches(column, value)

static in_any_of(column, values)

static in_none_of(column, values)

class dataikuapi.dss.utils.DSSSimpleFilterOperator(value)

Operators for the DSSSimpleFilter.

EQUALS = 'EQUALS'

NOT_EQUALS = 'NOT_EQUALS'

GREATER_THAN = 'GREATER_THAN'

LESS_THAN = 'LESS_THAN'

GREATER_OR_EQUAL = 'GREATER_OR_EQUAL'

LESS_OR_EQUAL = 'LESS_OR_EQUAL'

DEFINED = 'DEFINED'

NOT_DEFINED = 'NOT_DEFINED'

CONTAINS = 'CONTAINS'

MATCHES = 'MATCHES'

IN_ANY_OF = 'IN_ANY_OF'

IN_NONE_OF = 'IN_NONE_OF'

AND = 'AND'

OR = 'OR'