opendp 0.14.2-dev.20260401.2

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
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>>> dp.enable_features("contrib")
>>> input_space = dp.vector_domain(dp.atom_domain(T=int)), dp.linf_distance(T=int)
>>> select_index = input_space >> dp.m.then_report_noisy_max_gumbel(scale=1.0, optimize='max')
>>> print('2?', select_index([1, 2, 3, 2, 1]))
2? ...