[FEA]: Cleanup Existing MG Tests

[nv-rliu]

Is this a new feature, an improvement, or a change to existing functionality?

Improvement

How would you describe the priority of this feature request

Medium

Please provide a clear description of problem this feature solves

A lot of our existing Python MG algorithm tests are cluttered with old ways of creating edge lists and graphs. We also use a lot of nested pytest fixtures in-place of using the @pytest.parametrize feature, which could improve clarity and reduce the amount of code needed for the same behavior.

Example:

# Outdated code
datasets = utils.DATASETS_UNDIRECTED + [
    utils.RAPIDS_DATASET_ROOT_DIR_PATH / "email-Eu-core.csv"
]

G = utils.generate_cugraph_graph_from_file(
        input_data_path, directed=directed, edgevals=True
    )

ddf = dask_cudf.read_csv(
        input_data_path,
        chunksize=chunksize,
        delimiter=" ",
        names=["src", "dst", "value"],
        dtype=["int32", "int32", "float32"],
    )

dg = cugraph.Graph(directed=directed)
dg.from_dask_cudf_edgelist(
        ddf,
        source="src",
        destination="dst",
        edge_attr="value",
        renumber=True,
        store_transposed=True,
    )

@pytest.fixture(scope="module")
def input_expected_output(input_combo):
   ...

And as a result, the tests also depend on helper functions that could be cleaned up and simplified to pytest fixtures.

Describe your ideal solution

The MG tests can be cleaned up using the cugraph.datasets API, which also now supports creation of dask_cudf edge lists.
We can also use @pytest.mark.parametrize in place of input_expected_output

Describe any alternatives you have considered

No response

Additional context

No response

Code of Conduct

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• I have searched the open feature requests and have found no duplicates for this feature request