_base_builder#
Building blocks of modular builders used by various Analytics objects.
Classes#
A base for various builders of privacy-tracking objects. |
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Adds support for setting the privacy budget for a builder. |
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A private dataframe and its protected change. |
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Adds private and public dataframe support to a builder. |
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Adds support for setting parameters to a builder. |
- class BaseBuilder#
Bases:
abc.ABC
A base for various builders of privacy-tracking objects.
- abstract build()#
Constructs the type that this builder builds.
- Return type
Any
- class PrivacyBudgetMixin#
Adds support for setting the privacy budget for a builder.
- with_privacy_budget(privacy_budget)#
Set the privacy budget for the object being built.
- Parameters
privacy_budget (tmlt.analytics.privacy_budget.PrivacyBudget) –
- class PrivateDataFrame#
Bases:
NamedTuple
A private dataframe and its protected change.
- class DataFrameMixin#
Adds private and public dataframe support to a builder.
- with_private_dataframe(source_id, dataframe, protected_change)#
Adds a Spark DataFrame as a private source.
Not all Spark column types are supported in private sources; see
tmlt.analytics.session.SUPPORTED_SPARK_TYPES
for information about which types are supported.- Parameters
source_id (str) – Source id for the private source dataframe.
dataframe (pyspark.sql.DataFrame) – Private source dataframe to perform queries on, corresponding to the
source_id
.protected_change (tmlt.analytics.protected_change.ProtectedChange) – A
ProtectedChange
specifying what changes to the input data should be protected.
- with_public_dataframe(source_id, dataframe)#
Adds a public dataframe.
- Parameters
source_id (str) –
dataframe (pyspark.sql.DataFrame) –
- with_id_space(id_space)#
Adds an identifier space.
This defines a space of identifiers that map 1-to-1 to the identifiers being protected by a table with the
AddRowsWithID
protected change. Any table with such a protected change must be a member of some identifier space.- Parameters
id_space (str) –