opendp 0.16.0

A library of differential privacy algorithms for the statistical analysis of sensitive private data.
Documentation 
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# type: ignore
def sample_geometric_exp_slow(x) -> int:
    k = 0
    while True:
        if sample_bernoulli_exp(x):  # |\label{line:B}|
            k += 1
        else:
            return k