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_bernoulli_exp(x) -> bool:
    while x > 1:
        if sample_bernoulli_exp1(1):  # |\label{line:B_i}|
            x -= 1
        else:
            return False
    return sample_bernoulli_exp1(x)  # |\label{line:C}|