User Guide

The core client here is intended to be used as an API, meaning you can derive facts and relations and then run a model. It is intended for higher level libraries to use this module for custom command line parsing of specific domain-oriented entities. If you haven’t read Installation you should do that first.

Examples

For full examples, try running the scripts under examples after you install compspec. We will be adding a sphinx gallery with full examples here.

$ python examples/asp/basic-graph/run.py
$ python examples/asp/basic-diff/run.py
$ python examples/asp/combine-graphs/run.py

The dwarf examples have a Makefile to build with make and then can be run based on the name. See the README.md for dwarf for how to do this. We also have an example that takes an iterative approach to compare groups:

$ python examples/asp/python/tensorflow-module-example.py
$ python examples/asp/python/tensorflow-function-example.py
$ python examples/asp/python/tensorflow-example.py

That example is best if you are interested in breaking a problem space into multiple graphs.

Additional Functionality

Given that you have a graph:

A = Graph()
for node_id, name, value in [
    ["id0", "func", "goodbye_world"],
    ["id1", "func", "hello_world"],
    ["id3", "parameter", "name"],
    ["id4", "default", "Squidward"],
]:
    A.new_node(name, value, node_id)

for fromid, relation, toid in [
    ["id1", "has", "id3"],
    ["id3", "has", "id4"],
    ["id3", "has", "id5"],
    ["id1", "has", "id6"],
    ["id6", "has", "id7"],
]:
    A.new_relation(fromid, toid, relation)

You can convert it to a dictionary:

obj = A.to_dict()

And given that loaded (e.g., from json), we can then populate a new graph!

g = Graph.from_dict(obj)

These are very simple operations to define graphs, and primarily the work is done manually to create the nodes, relations, and identifiers. It is expected that specific domains that intend to create graphs will load in some object (e.g., a binary file) and do this creation on behalf of the user.