Changelog#

0.3.2 - 2022-06-23#

Moved IMMUTABLE_TYPES from utils/testing.py to utils/type_utils to avoid importing nose when accessing IMMUTABLE_TYPES

Fixed copy_if_mutable so that it works with containers that can’t be deep-copied.
Reverted change from 0.3.0 “Add checks in ParallelComposition constructor to only permit L1/L2 over SymmetricDifference or AbsoluteDifference.”
Temporarily disabled flaky statistical tests.

Added new transformations DropInfs and ReplaceInfs for handling infinities in data.
Added IfGroupedBy(X, SymmetricDifference()) input metric.
- Added support for this metric to Filter, Map, FlatMap, PublicJoin, Select, Rename, DropNaNs, DropNulls, DropInfs, ReplaceNulls, ReplaceNaNs, and ReplaceInfs.
Added new truncation transformations for IfGroupedBy(X, SymmetricDifference()): LimitRowsPerGroup, LimitKeysPerGroup
Added AddUniqueColumn for switching from SymmetricDifference to IfGroupedBy(X, SymmetricDifference()).
Added a topic guide around NaNs, nulls and infinities.

Moved truncation transformations used by PrivateJoin to be functions (now in utils/truncation.py).
Change GroupBy and PartitionByKeys to have an use_l2 argument instead of output_metric.
Fixed bug in AddUniqueColumn.
Operations that group on null values are now supported.
Modify CountDistinctGrouped and CountDistinct so they work as expected with null values.
Changed ReplaceNulls, ReplaceNaNs, and ReplaceInfs to only support specific IfGroupedBy metrics.
Fixed bug in ReplaceNulls to not allow replacing values for grouping column in IfGroupedBy.
PrivateJoin has a new parameter for __init__: join_on_nulls. When join_on_nulls is True, the PrivateJoin can join null values between both dataframes.
Changed transformations and measurements to make a copy of mutable constructor arguments.
Add checks in ParallelComposition constructor to only permit L1/L2 over SymmetricDifference or AbsoluteDifference.

Removed old examples from examples/. Future examples will be added directly to the documentation.

Added SparkDateColumnDescriptor and SparkTimestampColumnDescriptor, enabling support for Spark dates and timestamps.
Added two exception types, InsufficientBudgetError and InactiveAccountantError, to PrivacyAccountants.
Future documentation will include any exceptions defined in this library.
Added cleanup.remove_all_temp_tables() function, which will remove all temporary tables created by Core.
Added new components DropNaNs, DropNulls, ReplaceNulls, and ReplaceNaNs.

Added new implementations for SequentialComposition and ParallelComposition.
Added new spark transformations: Persist, Unpersist and SparkAction.
Added PrivacyAccountant.
Installation on Python 3.7.1 through 3.7.3 is now allowed.
Added DecorateQueryable, DecoratedQueryable and create_adaptive_composition components.

Fixed a bug where create_quantile_measurement would always be created with PureDP as the output measure.
PySparkTest now runs tmlt.core.utils.cleanup.cleanup() during tearDownClass.
Refactored noise distribution tests.
Remove sorting from GroupedDataFrame.apply_in_pandas and GroupedDataFrame.agg.
Repartition DataFrames output by SparkMeasurement to prevent privacy violation.
Updated repartitioning in SparkMeasurement to use a random column.
Changed quantile implementation to use arblib.
Changed Laplace implementation to use arblib.

Removed ExponentialMechanism and PermuteAndFlip components.
Removed AddNoise, AddLaplaceNoise, AddGeometricNoise, and AddDiscreteGaussianNoise from tmlt.core.measurements.pandas.series.
Removed SequentialComposition, ParallelComposition and corresponding Queryables from tmlt.core.measurements.composition.
Removed tmlt.core.transformations.cache.