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Vanilla.PDF is a modern, high-performance, open-source C++17 SDK designed for creating, editing, signing, and analyzing PDF documents across multiple platforms. It requires no external runtime dependencies, making it lightweight and ideal for embedding into desktop applications, servers, or automation pipelines. The SDK offers full cross-platform support including Windows, Linux, macOS, and Android, with builds available for major compilers and architectures. Vanilla.PDF supports advanced PDF features such as adding CMS (PKCS#7) digital signatures, modifying content streams and metadata, and working with encryption and permissions based on standard PDF security models. ...

JSON is everywhere on the Internet. Servers spend a *lot* of time parsing it. We need a fresh approach. The simdjson library uses commonly available SIMD instructions and microparallel algorithms to parse JSON 4x faster than RapidJSON and 25x faster than JSON for Modern C++. The simdjson library uses three-quarters less instructions than state-of-the-art parser RapidJSON. To our knowledge, simdjson is the first fully-validating JSON parser to run at gigabytes per second (GB/s) on commodity...

.... --- Highlights: --- org.knowceans.util: IndexQuickSort, TableList: apply order of one array/list to others +++ Vectors, ArrayUtils: array convenience +++ RandomSamplers, CokusRandom, ArmSampler, Densities: random sampling and distributions +++ Arguments: command line parser +++ StopWatch, Which, ExternalProcess: runtime stuff +++ ParallelFor: OpenMP workalike +++ PatternString, NamedGroupRegex: regex convenience --- org.knowceans.corpus: CorpusSearcher: full-text search engine +++ LabelNumCorpus: svmlight corpus storage and filtering +++ NIPS corpus with text, authors, labels and citations --- org.knowceans.map: InvertibleHashMultiMap, BijectiveHashMap: implement n:m and 1:1 relations. --- Other libs: knowceans-arms = port of the Adaptive Rejection Metropolis Sampler (ARMS) for arbitrary distributions +++ lda-j = port of lda-c, implementing Latent Dirichlet Allocation (LDA)