Skip to content

Impact

Source code in docs_src/capo_cost_explorer/types/impact.py 
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
class Impact(TypedDict, closed=True):
    max_impact: "capo_cost_explorer.types.generic_double.GenericDouble"
    """<p>The maximum dollar value that's observed for an anomaly.</p>"""
    total_impact: "capo_cost_explorer.types.generic_double.GenericDouble"
    """<p>The cumulative dollar difference between the total actual spend and total expected spend. It is calculated as <code>TotalActualSpend - TotalExpectedSpend</code>.</p>"""
    total_actual_spend: NotRequired[
        "capo_cost_explorer.types.nullable_non_negative_double.NullableNonNegativeDouble"
    ]
    """<p>The cumulative dollar amount that was actually spent during the anomaly.</p>"""
    total_expected_spend: NotRequired[
        "capo_cost_explorer.types.nullable_non_negative_double.NullableNonNegativeDouble"
    ]
    """<p>The cumulative dollar amount that was expected to be spent during the anomaly. It is calculated using advanced machine learning models to determine the typical spending pattern based on historical data for a customer.</p>"""
    total_impact_percentage: NotRequired[
        "capo_cost_explorer.types.nullable_non_negative_double.NullableNonNegativeDouble"
    ]
    """<p>The cumulative percentage difference between the total actual spend and total expected spend. It is calculated as <code>(TotalImpact / TotalExpectedSpend) * 100</code>. When <code>TotalExpectedSpend</code> is zero, this field is omitted. Expected spend can be zero in situations such as when you start to use a service for the first time.</p>"""

max_impact instance-attribute 

max_impact: GenericDouble

The maximum dollar value that's observed for an anomaly.

total_actual_spend instance-attribute 

total_actual_spend: NotRequired[NullableNonNegativeDouble]

The cumulative dollar amount that was actually spent during the anomaly.

total_expected_spend instance-attribute 

total_expected_spend: NotRequired[NullableNonNegativeDouble]

The cumulative dollar amount that was expected to be spent during the anomaly. It is calculated using advanced machine learning models to determine the typical spending pattern based on historical data for a customer.

total_impact instance-attribute 

total_impact: GenericDouble

The cumulative dollar difference between the total actual spend and total expected spend. It is calculated as TotalActualSpend - TotalExpectedSpend.

total_impact_percentage instance-attribute 

total_impact_percentage: NotRequired[NullableNonNegativeDouble]

The cumulative percentage difference between the total actual spend and total expected spend. It is calculated as (TotalImpact / TotalExpectedSpend) * 100. When TotalExpectedSpend is zero, this field is omitted. Expected spend can be zero in situations such as when you start to use a service for the first time.