Changelog

0.13.0 - 2024-04-03

Changed

• Updated calculate_noise_scale() to return a noise scale of 0 when both the d_in and d_out are infinite.

• Adjusted error messages related to spending privacy budgets in classes of type PrivacyBudget.

• Moved InsufficientBudgetError from interactive_measurements to measures.

• Adjusted tmlt.core.measurements.aggregations.create_variance_measurement() and tmlt.core.measurements.aggregations.create_standard_deviation_measurement() to calculate sample variance and sample standard deviation instead of population variance and population standard deviation.

• In GroupBy and GroupedDataFrame removed restriction on empty dataframes with non-empty columns.

Fixed

• SumGrouped now correctly handles the case with both empty input dataframes and empty group keys.

• SumGrouped, CountDistinct, and CountDistinctGrouped now always returns the correct output datatypes.

• tmlt.core.domains.collections.DictDomain.validate() will no longer raise a TypeError when its dictionary keys cannot be sorted.

0.12.0 - 2024-02-26

Added

• Added a non-truncating truncation strategy with infinite stability.

• Added functions implementing various mechanisms to support slow scaling PRDP.

Changed

• Changed truncate_large_groups() and limit_keys_per_group() to use SHA-2 (256 bits) instead of Spark’s default hash (Murmur3). This results in a minor performance hit, but these functions should be less likely to have collisions which could impact utility. Note that this may change the output of transformations which use these functions. In particular, PrivateJoin, LimitRowsPerGroup, LimitKeysPerGroup, and LimitRowsPerKeyPerGroup.

• Expanded the explanation of GroupingFlatMap’s stability.

• Support all metrics for the flat map transformation.

Fixed

• Fixed missing minus sign in the documentation of the discrete Gaussian pmf.

• Fixed create_partition_selection_measurement() behavior when called with infinite budgets.

• Fixed create_partition_selection_measurement() crashing when called with very large budgets.

0.11.6 - 2024-02-21

0.11.6 was yanked. Those changes will be released in 0.12.0.

0.11.5 - 2023-11-29

Fixed

• Addressed a serious security vulnerability in PyArrow: CVE-2023-47248.

  • Python 3.8+ now requires PyArrow 14.0.1 or higher, which is the recommended fix and addresses the vulnerability.

  • Python 3.7 uses the hotfix, as PyArrow 14.0.1 is not compatible with Python 3.7. Note that if you are using 3.7 the hotfix must be imported before your Spark code. Core imports the hotfix, so importing Core before Spark will also work.

  • It is strongly recommended to upgrade if you are using an older version of Core.

  • Also see the GitHub Advisory entry for more information.

• Fixed a reference to an uninitialized variable that could cause arb_union() to crash the Python interpreter.

0.11.4 - 2023-11-01

Fixed a typo that prevented PyArrow from being installed on Python 3.8.

0.11.3 - 2023-10-31

Fixed a typo that prevented PySpark from being installed on Python 3.8.

0.11.2 - 2023-10-27

Added

• Added support for Python 3.11.

0.11.1 - 2023-09-25

Added

• Added documentation for known vulnerabilities related to Parallel Composition and the use of SymPy.

0.11.0 - 2023-08-15

Changed

• Replaced the group_keys for constructing SparkGroupedDataFrameDomains with groupby_columns.

• Modified SymmetricDifference to define the distance between two elements of SparkGroupedDataFrameDomains to be infinite when the two elements have different group_keys.

• Updated maximum version for pyspark from 3.3.1 to 3.3.2.

0.10.2 - 2023-07-18

Changed

• Build wheels for macOS 11 instead of macOS 13.

• Updated dependency version for typing_extenstions to 4.1.0

0.10.1 - 2023-06-08

Added

• Added support for Python 3.10.

• Added the arb_exp(), arb_const_pi(), arb_neg(), arb_product(), arb_sum(), arb_union(), arb_erf(), and arb_erfc() functions.

• Added a new error, DomainMismatchError, which is raised when two or more domains should match but do not.

• Added a new error, UnsupportedMetricError, which is raised when an unsupported metric is used.

• Added a new error, MetricMismatchError, which is raised when two or more metrics should match but do not.

• Added a new error, UnsupportedMeasureError, which is raised when an unsupported measure is used.

• Added a new error, MeasureMismatchError, which is raised when two or more measures should match but do not.

• Added a new error, UnsupportedCombinationError, which is raised when some combination of domain, metric, and measure is not supported (but each one is individually valid).

• Added a new error, UnsupportedNoiseMechanismError, which is raised when a user tries to create a measurement with a noise mechanism that is not supported.

• Added a new error, UnsupportedSympyExprError, which is raised when a user tries to create an ExactNumber with an invalid SymPy expression.

Changed

• Restructured the repository to keep code under the src directory.

0.10.0 - 2023-05-17

Added

• Added the BoundSelection spark measurement.

Changed

• Replaced many existing exceptions in Core with new classes that contain metadata about the inputs causing the exception.

Fixed

• Fixed bug in limit_keys_per_group().

• Fixed bug in gaussian().

• cleanup() now emits a warning rather than an exception if it fails to get a Spark session. This should prevent unexpected exceptions in the atexit cleanup handler.

0.9.2 - 2023-05-16

0.9.2 was yanked, as it contained breaking changes. Those changes will be released in 0.10.0.

0.9.1 - 2023-04-20

Added

• Subclasses of Measure now have equations defining the distance they represent.

0.9.0 - 2023-04-14

Added

• join, which contains utilities for validating join parameters, propogating domains through joins, and joining dataframes.

Changed

• truncate_large_groups() does not clump identical records together in hash-based ordering.

• TransformValue no longer fails when renaming the id column using RenameValue.

Fixed

• groupby no longer outputs nan values when both tables are views on the same original table

• private join no longer drops Nulls on non-join columns when join_on_nulls=False

• groupby average and variance no longer drops groups containing null values

0.8.3 - 2023-03-08

Changed

• Functions in aggregations now support ApproxDP.

0.8.2 - 2023-03-02

Added

• Added LimitKeysPerGroupValue transformation

Changed

• Updated LimitKeysPerGroup to require an output metric, and to support the IfGroupedBy(grouping_column, SymmetricDifference()) output metric. Dropped the ‘use_l2’ parameter.

0.8.1 - 2023-02-24

Added

• Added LimitRowsPerKeyPerGroup and LimitRowsPerKeyPerGroupValue transformations

Changed

• Faster implementation of discrete_gaussian_inverse_cmf.

0.8.0 - 2023-02-14

Added

• Added LimitRowsPerGroupValue transformation

Changed

• Updated LimitRowsPerGroup to require an output metric, and to support the IfGroupedBy(column, SymmetricDifference()) output metric.

• Added a check so that TransformValue can no longer be instantiated without subclassing.

0.7.0 - 2023-02-02

Added

• Added measurement for adding Gaussian noise.

0.6.3 - 2022-12-20

Changed

• On Linux, Core previously used MPIR as a multi-precision arithmetic library to support FLINT and Arb. MPIR is no longer maintained, so Core now uses GMP instead. This change does not affect macOS builds, which have always used GMP, and does not change Core’s Python API.

Fixed

• Fixed a bug where PrivateJoin’s privacy relation would only accept string keys in the d_in. It now accepts any type of key.

0.6.2 - 2022-12-07

This is a maintenance release which introduces a number of documentation improvements, but has no publicly-visible API changes.

Fixed

• check_java11() now has the correct behavior when Java is not installed.

0.6.1 - 2022-12-05

Added

• Added approximate DP support to interactive mechanisms.

• Added support for Spark 3.1 through 3.3, in addition to existing support for Spark 3.0.

Fixed

• Validation for SparkedGroupDataFrameDomains used to fail with a Spark AnalysisException in some environments. That should no longer happen.

0.6.0 - 2022-11-14

Added

• Added new PrivateJoinOnKey transformation that works with AddRemoveKeys.

• Added inverse CDF methods to noise mechanisms.

0.5.1 - 2022-11-03

Fixed

• Domains and metrics make copies of mutable constructor arguments and return copies of mutable properties.

0.5.0 - 2022-10-14

Changed

• Core no longer depends on the python-flint package, and instead packages libflint and libarb itself. Binary wheels are available, and the source distribution includes scripting to build these dependencies from source.

Fixed

• Equality checks on SparkGroupedDataFrameDomains used to occasionally fail with a Spark AnalysisException in some environments. That should no longer happen.

• AddRemoveKeys now allows different names for the key column in each dataframe.

0.4.3 - 2022-09-01

• Core now checks to see if the user is running Java 11 or higher. If they are, Core either sets the appropriate Spark options (if Spark is not yet running) or raises an informative exception (if Spark is running and configured incorrectly).

0.4.2 - 2022-08-24

Changed

• Replaced uses of PySpark DataFrame’s intersect with inner joins. See https://issues.apache.org/jira/browse/SPARK-40181 for background.

0.4.1 - 2022-07-25

Added

• Added an alternate prng for non-intel architectures that don’t support RDRAND.

• Add new metric AddRemoveKeys for multiple tables using IfGroupedBy(X, SymmetricDifference()).

• Add new TransformValue base class for wrapping transformations to support AddRemoveKeys.

• Add many new transformations using TransformValue: FilterValue, PublicJoinValue, FlatMapValue, MapValue, DropInfsValue, DropNaNsValue, DropNullsValue, ReplaceInfsValue, ReplaceNaNsValue, ReplaceNullsValue, PersistValue, UnpersistValue, SparkActionValue, RenameValue, SelectValue.

Changed

• Fixed bug in ReplaceNulls to not allow replacing values for grouping column in IfGroupedBy.

• Changed ReplaceNulls, ReplaceNaNs, and ReplaceInfs to only support specific IfGroupedBy metrics.

0.3.2 - 2022-06-23

Changed

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

0.3.1 - 2022-06-23

Changed

• 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.

0.3.0 - 2022-06-22

Added

• 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.

Changed

• 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

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

0.2.0 - 2022-04-12 (internal release)

Added

• 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.

0.1.1 - 2022-02-24 (internal release)

Added

• 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.

Changed

• 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

• 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.

0.1.0 - 2022-02-14 (internal release)

Added

• Initial release.