Latest 1.92.0.beta1 1.91.0 1.90.0 1.89.0 1.88.0 1.87.0 1.86.0 1.85.0 1.84.0 1.83.0 1.82.0 1.81.0 1.80.0 1.79.0 1.78.0 1.77.0 1.76.0 1.75.0 1.74.0 1.73.0 1.72.0 1.71.0 1.70.0 1.69.0 1.68.0 1.67.0 1.66.0 1.65.1 1.65.0 1.64.0 1.63.0 1.62.0 1.61.0 1.60.0 1.59.0 1.58.0 1.57.0 1.56.0 1.55.0 1.54.0 1.53.0 1.52.0 1.51.0 1.50.0 1.49.0 1.48.0 1.47.0 1.46.1 1.46.0 1.45.0 1.44.0 1.43.0 1.42.0 1.41.0 1.40.0 1.39.0 1.38.0 1.37.0 1.36.0 1.35.0 1.34.1 1.34.0 1.33.1 1.33.0 1.32.0 1.31.0 1.30.2 1.30.1 1.30.0 1.29.0 1.28.0 1.27.0 1.26.0 1.25.1-bgl 1.25.1 1.25.0 1.24.0 1.23.0 1.22.0 1.21.2 1.21.1 1.21.0 1.20.2 1.20.1 1.20.0 1.19.0 1.18.3 1.18.2 1.18.0 1.17.0 1.16.1
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Latest 1.92.0.beta1 1.91.0 1.90.0 1.89.0 1.88.0 1.87.0 1.86.0 1.85.0 1.84.0 1.83.0 1.82.0 1.81.0 1.80.0 1.79.0 1.78.0 1.77.0 1.76.0 1.75.0 1.74.0 1.73.0 1.72.0 1.71.0 1.70.0 1.69.0 1.68.0 1.67.0 1.66.0 1.65.1 1.65.0 1.64.0 1.63.0 1.62.0 1.61.0 1.60.0 1.59.0 1.58.0 1.57.0 1.56.0 1.55.0 1.54.0 1.53.0 1.52.0 1.51.0 1.50.0 1.49.0 1.48.0 1.47.0 1.46.1 1.46.0 1.45.0 1.44.0 1.43.0 1.42.0 1.41.0 1.40.0 1.39.0 1.38.0 1.37.0 1.36.0 1.35.0 1.34.1 1.34.0 1.33.1 1.33.0 1.32.0 1.31.0 1.30.2 1.30.1 1.30.0 1.29.0 1.28.0 1.27.0 1.26.0 1.25.1-bgl 1.25.1 1.25.0 1.24.0 1.23.0 1.22.0 1.21.2 1.21.1 1.21.0 1.20.2 1.20.1 1.20.0 1.19.0 1.18.3 1.18.2 1.18.0 1.17.0 1.16.1
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New Library for 1.89 - Boost.Bloom

Boost.Bloom is a header-only C++ library for efficient probabilistic set membership testing.

It allows you to check whether an element might be in a set, with minimal memory overhead and no false negatives, ideal for high-throughput scenarios like caching, deduplication, and indexing.

The filter is highly space-efficient, and can dramatically reduce the cost of negative lookups in systems where accessing the full data set is expensive.

Repo: https://github.com/boostorg/bloom
Docs: https://boost.org/libs/bloom

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