image-match/python/py/Lib/site-packages/networkx/utils/tests/test_backends.py

import pickle

import pytest

import networkx as nx

sp = pytest.importorskip("scipy")
pytest.importorskip("numpy")


@nx._dispatchable(implemented_by_nx=False)
def _stub_func(G):
    raise NotImplementedError("_stub_func is a stub")


def test_dispatch_kwds_vs_args():
    G = nx.path_graph(4)
    nx.pagerank(G)
    nx.pagerank(G=G)
    with pytest.raises(TypeError):
        nx.pagerank()


def test_pickle():
    count = 0
    for name, func in nx.utils.backends._registered_algorithms.items():
        pickled = pickle.dumps(func.__wrapped__)
        assert pickle.loads(pickled) is func.__wrapped__
        try:
            # Some functions can't be pickled, but it's not b/c of _dispatchable
            pickled = pickle.dumps(func)
        except pickle.PicklingError:
            continue
        assert pickle.loads(pickled) is func
        count += 1
    assert count > 0
    assert pickle.loads(pickle.dumps(nx.inverse_line_graph)) is nx.inverse_line_graph


@pytest.mark.skipif(
    "not nx.config.backend_priority.algos "
    "or nx.config.backend_priority.algos[0] != 'nx_loopback'"
)
def test_graph_converter_needs_backend():
    # When testing, `nx.from_scipy_sparse_array` will *always* call the backend
    # implementation if it's implemented. If `backend=` isn't given, then the result
    # will be converted back to NetworkX via `convert_to_nx`.
    # If not testing, then calling `nx.from_scipy_sparse_array` w/o `backend=` will
    # always call the original version. `backend=` is *required* to call the backend.
    from networkx.classes.tests.dispatch_interface import (
        LoopbackBackendInterface,
        LoopbackGraph,
    )

    A = sp.sparse.coo_array([[0, 3, 2], [3, 0, 1], [2, 1, 0]])

    side_effects = []

    def from_scipy_sparse_array(self, *args, **kwargs):
        side_effects.append(1)  # Just to prove this was called
        return self.convert_from_nx(
            self.__getattr__("from_scipy_sparse_array")(*args, **kwargs),
            preserve_edge_attrs=True,
            preserve_node_attrs=True,
            preserve_graph_attrs=True,
        )

    @staticmethod
    def convert_to_nx(obj, *, name=None):
        if type(obj) is nx.Graph:
            return obj
        return nx.Graph(obj)

    # *This mutates LoopbackBackendInterface!*
    orig_convert_to_nx = LoopbackBackendInterface.convert_to_nx
    LoopbackBackendInterface.convert_to_nx = convert_to_nx
    LoopbackBackendInterface.from_scipy_sparse_array = from_scipy_sparse_array

    try:
        assert side_effects == []
        assert type(nx.from_scipy_sparse_array(A)) is nx.Graph
        assert side_effects == [1]
        assert (
            type(nx.from_scipy_sparse_array(A, backend="nx_loopback")) is LoopbackGraph
        )
        assert side_effects == [1, 1]
        # backend="networkx" is default implementation
        assert type(nx.from_scipy_sparse_array(A, backend="networkx")) is nx.Graph
        assert side_effects == [1, 1]
    finally:
        LoopbackBackendInterface.convert_to_nx = staticmethod(orig_convert_to_nx)
        del LoopbackBackendInterface.from_scipy_sparse_array
    with pytest.raises(ImportError, match="backend is not installed"):
        nx.from_scipy_sparse_array(A, backend="bad-backend-name")


@pytest.mark.skipif(
    "not nx.config.backend_priority.algos "
    "or nx.config.backend_priority.algos[0] != 'nx_loopback'"
)
def test_networkx_backend():
    """Test using `backend="networkx"` in a dispatchable function."""
    # (Implementing this test is harder than it should be)
    from networkx.classes.tests.dispatch_interface import (
        LoopbackBackendInterface,
        LoopbackGraph,
    )

    G = LoopbackGraph()
    G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4)])

    @staticmethod
    def convert_to_nx(obj, *, name=None):
        if isinstance(obj, LoopbackGraph):
            new_graph = nx.Graph()
            new_graph.__dict__.update(obj.__dict__)
            return new_graph
        return obj

    # *This mutates LoopbackBackendInterface!*
    # This uses the same trick as in the previous test.
    orig_convert_to_nx = LoopbackBackendInterface.convert_to_nx
    LoopbackBackendInterface.convert_to_nx = convert_to_nx
    try:
        G2 = nx.ego_graph(G, 0, backend="networkx")
        assert type(G2) is nx.Graph
    finally:
        LoopbackBackendInterface.convert_to_nx = staticmethod(orig_convert_to_nx)


def test_dispatchable_are_functions():
    assert type(nx.pagerank) is type(nx.pagerank.orig_func)


@pytest.mark.skipif("not nx.utils.backends.backends")
def test_mixing_backend_graphs():
    from networkx.classes.tests import dispatch_interface

    G = nx.Graph()
    G.add_edge(1, 2)
    G.add_edge(2, 3)
    H = nx.Graph()
    H.add_edge(2, 3)
    rv = nx.intersection(G, H)
    assert set(nx.intersection(G, H)) == {2, 3}
    G2 = dispatch_interface.convert(G)
    H2 = dispatch_interface.convert(H)
    if "nx_loopback" in nx.config.backend_priority:
        # Auto-convert
        assert set(nx.intersection(G2, H)) == {2, 3}
        assert set(nx.intersection(G, H2)) == {2, 3}
    elif not nx.config.backend_priority and "nx_loopback" not in nx.config.backends:
        # G2 and H2 are backend objects for a backend that is not registered!
        with pytest.raises(ImportError, match="backend is not installed"):
            nx.intersection(G2, H)
        with pytest.raises(ImportError, match="backend is not installed"):
            nx.intersection(G, H2)
    # It would be nice to test passing graphs from *different* backends,
    # but we are not set up to do this yet.


def test_bad_backend_name():
    """Using `backend=` raises with unknown backend even if there are no backends."""
    with pytest.raises(
        ImportError, match="'this_backend_does_not_exist' backend is not installed"
    ):
        nx.null_graph(backend="this_backend_does_not_exist")


def test_not_implemented_by_nx():
    assert "networkx" in nx.pagerank.backends
    assert "networkx" not in _stub_func.backends

    if "nx_loopback" in nx.config.backends:
        from networkx.classes.tests.dispatch_interface import LoopbackBackendInterface

        def stub_func_implementation(G):
            return True

        LoopbackBackendInterface._stub_func = staticmethod(stub_func_implementation)
        try:
            assert _stub_func(nx.Graph()) is True
        finally:
            del LoopbackBackendInterface._stub_func

    with pytest.raises(NotImplementedError):
        _stub_func(nx.Graph())


@pytest.mark.skipif(
    "not nx.config.backend_priority.algos "
    "or nx.config.backend_priority.algos[0] != 'nx_loopback'"
)
def test_dispatch_graph_new():
    from networkx.classes.tests.dispatch_interface import LoopbackGraph

    G = nx.Graph()
    assert not isinstance(G, LoopbackGraph)

    # `backend=` argument that gets passed to __init__ is ignored.
    # Best practice is that it should not be in the `.graph` dict.
    G = nx.Graph(backend="networkx")
    assert type(G) is nx.Graph
    assert "backend" not in G.graph

    G = nx.Graph(backend="nx_loopback")
    assert isinstance(G, LoopbackGraph)
    assert "backend" not in G.graph

    # Args are passed
    G1 = nx.Graph([(0, 1), (1, 2)])
    assert not isinstance(G1, LoopbackGraph)
    G2 = nx.Graph([(0, 1), (1, 2)], backend="nx_loopback")
    assert isinstance(G2, LoopbackGraph)
    assert nx.utils.misc.graphs_equal(G1, G2)

    # Test config for automatic usage
    with nx.config.backend_priority(classes=["nx_loopback"]):
        G = nx.Graph()
        assert isinstance(G, LoopbackGraph)
        # LoopbackDiGraph __new__ is not implemented
        G = nx.DiGraph()
        assert not isinstance(G, LoopbackGraph)
    G = nx.Graph()
    assert not isinstance(G, LoopbackGraph)