Haydi (Haystack diver) is a framework for generating discrete structures. It provides a way to define a structure from basic building blocks (e.g. Cartesian product, mappings) and then enumerate all elements, all non-isomorphic elements, or generate random elements.
- Pure Python implementation (Python 2.7+, PyPy supported)
- MIT license
- Sequential or distributed computation (via dask/distributed (https://github.com/dask/distributed)
Full documentation is available at: https://haydi.readthedocs.io/en/latest/
- Let us define directed graphs on two vertices (represented as a set of edges):
>>> import haydi as hd
>>> nodes = hd.USet(2, "n") # A two-element set with (unlabeled) elements {n0, n1}
>>> graphs = hd.Subsets(nodes * nodes) # Subsets of a cartesian product- Now we can iterate all elements:
>>> list(graphs.iterate())
[{}, {(n0, n0)}, {(n0, n0), (n0, n1)}, {(n0, n0), (n0, n1), (n1, n0)}, {(n0,
# ... 3 lines removed ...
n1)}, {(n1, n0)}, {(n1, n0), (n1, n1)}, {(n1, n1)}]- or iterate all non-isomorphic ones:
>>> list(graphs.cnfs()) # cnfs = canonical forms
[{}, {(n0, n0)}, {(n0, n0), (n1, n1)}, {(n0, n0), (n0, n1)}, {(n0, n0), (n0,
n1), (n1, n1)}, {(n0, n0), (n0, n1), (n1, n0)}, {(n0, n0), (n0, n1), (n1, n0),
(n1, n1)}, {(n0, n0), (n1, n0)}, {(n0, n1)}, {(n0, n1), (n1, n0)}]- or generate random instances:
>>> list(graphs.generate(3))
[{(n1, n0)}, {(n1, n1), (n0, n0)}, {(n0, n1), (n1, n0)}]- Haydi supports standard operations like map, filter and reduce:
>>> op = graphs.map(lambda g: len(g)).reduce(lambda x, y: x + y)
# Just a demonstration pipeline; nothing usefull
>>> op.run()- We can run it transparently as a distributed application:
>>> from haydi import DistributedContext
# We are now assuming that dask/distributed is running at hostname:1234
>>> context = DistributedContext("hostname", 1234)
>>> op.run(ctx=context)- Stanislav Böhm <stanislav.bohm at vsb.cz>
- Jakub Beránek
- Martin Šurkovský <martin.surkovsky at gmail.com>
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