Diff-priv-laplace-python

- Added `postprocess` parameter (enabled by default) to `DiffPrivStatistics.count` and `DiffPrivStatistics.proportion` which enforces that the returned anonymized values are within their corresponding ranges: `[0, n]` and `[0.0, 1.0]` respectively.
- Simplified exception names:
- `DiffPrivStatisticsInvalidDimensions` => `DiffPrivInvalidDimensions`
- `DiffPrivStatisticsSizeMismatch` => `DiffPrivSizeMismatch`
- Added support to allow skipping calculation of statistics for a given data slice by using a kind value of `None` instead of a defined `DiffPrivStatisticKind` value.
- Added Laplace sanitizer `DiffPrivLaplaceSanitizer`.

- Added sequential (`DiffPrivSequentialStatisticsQuery`) and parallel (`DiffPrivParallelStatisticsQuery`) composition query functionality.

- Added support for calculating data anonymized statistics through `DiffPrivStatistics`.

- Added Laplace mechanism anonymization for operations:
- `min`
- `max`
- `median`
- `sum`

- Added baseline Laplace mechanism anonymization for operations:
- `count`
- `mean`
- `proportion`
- `variance`