# Requirements for Tensorflow Privacy.
#
# If you add a *new* dependency and it is required by the TensorFlow Federated
# package, also add the dependency to `setup.py`.
#
# If you update the version of an *existing* dependency and it is required by
# the TensorFlow Federated package, also update the version of the dependency in
# `setup.py`.
#
# *   For packages that have a stable release, we use a version that is
#     compatible with that release (e.g. `~=x.y`). See
#     https://peps.python.org/pep-0440/#compatible-release for more information.
# *   For packages that do not have a stable release, we use a version that
#     matches a release that has been tested (e.g. `==x.y.z`). See
#     https://peps.python.org/pep-0440/#version-matching for more information.
#
# This assumes that the packages follows Semantic Versioning, see
# https://semver.org/. If a package follows a different versioning scheme or
# requires unique handling, we use a different version specifier and comment the
# versioning scheme or reasoning.
#
# Note: As of 2022-08-17 there is bug in `pip` when multiple packages use the
# compatible release operator `~=` to specify a version and one of those
# versions ends in `0`. See https://github.com/pypa/pip/issues/9613 for more
# information. In this case, use the equivalent clause `>=x.0,==x.*` instead of
# `~=x.0`.

absl-py>=1.0,==1.*
dm-tree==0.1.8
dp-accounting==0.4.4
immutabledict~=2.2
matplotlib~=3.3
numpy~=1.21
packaging~=22.0
pandas~=1.4
scikit-learn>=1.0,==1.*
scipy~=1.9
statsmodels==0.14.0
tensorflow-datasets~=4.5
tensorflow-estimator~=2.4
tensorflow-probability~=0.22.0
tensorflow>=2.4.0,<=2.15.0
tf-models-official~=2.13