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Comment by edparcell | Hacker News Reader

My team has been working on a Python library called Loman that represents computations as graphs. We've open-sourced it [1][2]. One of our aims is to make it as natural as possible to use graph-based programming, and within an already-familiar programming language. Be interested to know what you think.

[1] https://github.com/janusassetallocation/loman [2] http://loman.readthedocs.io/en/latest/user/intro.html

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Can you demo your library with a more complex example, e.g. the Dining Philosophers Problem. Here[1] is the solution using TBB, and here[2] a more recent version - using a multioutput function node to optimize the flow.

[1] - https://software.intel.com/en-us/blogs/2011/01/10/using-the-...

[2] - https://software.intel.com/en-us/blogs/2011/09/13/using-inte...

Thanks for the links. I took a look, and I think that the intention is quite different between the libraries. Our library would not directly apply to the Dining Philosophers Problem. Both libraries use graphs to represent dependencies between tasks, but they do so for different reasons, and to cover different uses. The Intel library does it with the intention of scheduling a given workload. Our library uses a directed acyclic graph to track state as either the data or function for given nodes of the graph are exogenously updated, either interactively during research, or from new incoming data in a real-time system. We cover where we think our library is useful in more depth in the introduction section of our documentation[1].

[1] http://loman.readthedocs.io/en/latest/user/intro.html

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