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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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ComputeSharp
A .NET library to run C# code in parallel on the GPU through DX12, D2D1, and dynamically generated HLSL compute and pixel shaders, with the goal of making GPU computing easy to use for all .NET developers! 🚀
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
// Must call the below range pipeline to produce a string on an lvalue. Since // we end the pipeline with to_string everything is evaluated here, so no // lifetime issue. auto rows = this -> rows_iter(); namespace rv = ranges::views; // See dynamic width https://fmt.dev/7.1.3/syntax.html#format-examples return rows | rv::transform([elem_delim, width](const auto& row) { // For every row return rv::all(row) // For each row | rv::transform([width](const auto& elem) { // Format each element with padding return fmt::format("{:>{}}", elem, width); }) // Can't use views::join because views::transform returns a // temporary. // Can't use actions::join as it doesn't support a delimiter // https://github.com/ericniebler/range-v3/issues/1406 // views::intersperse and actions::join works // // Add delimiters, combine into one string for the row | rv::intersperse(std::string{elem_delim}) | ranges::actions::join; }) | rv::cache1 | rv::join(row_delim) | ranges::to();
I don’t want to come over as a show off but I’m pretty sure my own library is more readable. It also hasn’t any of the lifetime issues (AFAIK) because everything is stored in the iterator itself, giving more readability at the expense of a tiny tiny bit more overhead.
Idk if it qualifies as "real-world" but here is a shameless plug: https://github.com/Ayenem/k-means
Could you share some reading on some of the languages you mentioned that are working on better C++ interop support? I've been keeping up with Swift's effort via this document, but haven't kept up with any others.
And thanks to the community there are even some GPGPU efforts, like https://github.com/Sergio0694/ComputeSharp, but yeah don't expect CUDA or SYSCL like tooling.