[DRAFT] Autogenerating lazy initialization everywhere

[Erotemic]

Forked from the conversation in #4349 this is a test to see how easy it is to switch to mkinit for __init__.py file management. This tests to see if lazy imports work. So far I have pytest running with 134 failed, 4115 passed.

The top level __init__.py looks somewhat like this now:

__getattr__ = lazy_import(
    __name__,
    submodules={
        "algorithms",
        "classes",
        "conftest",
        "convert",
        "convert_matrix",
        "drawing",
        "exception",
        "generators",
        "linalg",
        "readwrite",
        "relabel",
        "release",
        "testing",
        "tests",
        "utils",
        "version",
    },
    submod_attrs={
        "algorithms": [
            "CGInverseLaplacian",
            "CurrentEdge",
            "DiGraphMatcher",
            "EdgeComponentAuxGraph",
            "Edmonds",
       ...
            "vitality",
            "volume",
            "voronoi",
            "voronoi_cells",
            "voterank",
            "voterank_alg",
            "weakly_connected",
            "weakly_connected_components",
            "weighted",
            "weighted_projected_graph",
            "weisfeiler_lehman_graph_hash",
            "wiener",
            "wiener_index",
            "within_inter_cluster",
            "write_edgelist",
        ],
        "classes": [
            "AdjacencyView",
            "AtlasView",
            "DegreeView",
            "DiDegreeView",
            "DiGraph",
            "DiMultiDegreeView",
            "EdgeDataView",
            "EdgeView",
       ...
            "selfloop_edges",
            "set_edge_attributes",
            "set_node_attributes",
            "show_diedges",
            "show_edges",
            "show_multidiedges",
            "show_multiedges",
            "show_nodes",
            "subgraph",
            "subgraph_view",
            "tests",
            "to_directed",
            "to_undirected",
        ],
        "conftest": [
            "add_nx",
            "collect_ignore",
            "has_matplotlib",
            "has_numpy",
            "has_ogr",
       ...
            "pytest_addoption",
            "pytest_collection_modifyitems",
            "pytest_configure",
            "set_warnings",
        ],
        "convert": [
            "from_dict_of_dicts",
            "from_dict_of_lists",
            "from_edgelist",
            "to_dict_of_dicts",
            "to_dict_of_lists",
            "to_edgelist",
            "to_networkx_graph",
        ],
        "convert_matrix": [
            "from_numpy_array",
            "from_numpy_matrix",
            "from_pandas_adjacency",
            "from_pandas_edgelist",
            "from_scipy_sparse_matrix",
            "to_numpy_array",
            "to_numpy_matrix",
            "to_numpy_recarray",
            "to_pandas_adjacency",
            "to_pandas_edgelist",
            "to_scipy_sparse_matrix",
        ],
        "drawing": [
            "bipartite_layout",
            "circular_layout",
            "draw",
            "draw_circular",
            "draw_kamada_kawai",
            "draw_networkx",
            "draw_networkx_edge_labels",
            "draw_networkx_edges",
            "draw_networkx_labels",
            "draw_networkx_nodes",
...
            "spring_layout",
            "tests",
            "to_agraph",
            "to_pydot",
            "view_pygraphviz",
            "write_dot",
        ],
        "exception": [
            "AmbiguousSolution",
            "ExceededMaxIterations",
            "HasACycle",
            "NetworkXAlgorithmError",
            "NetworkXError",
            "NetworkXException",
            "NetworkXNoCycle",
            "NetworkXNoPath",
            "NetworkXNotImplemented",
            "NetworkXPointlessConcept",
            "NetworkXUnbounded",
            "NetworkXUnfeasible",
            "NodeNotFound",
            "PowerIterationFailedConvergence",
        ],
        "generators": [
            "LCF_graph",
            "LFR_benchmark_graph",
            "atlas",
            "balanced_tree",
            "barabasi_albert_graph",
            "barbell_graph",
            "binomial_graph",
            "binomial_tree",
            "bull_graph",
            "caveman_graph",
            "chordal_cycle_graph",
            "chvatal_graph",
            "circulant_graph",
            "circular_ladder_graph",
            "classic",
            "cographs",...
            "triads",
            "triangular_lattice_graph",
            "trivial_graph",
            "truncated_cube_graph",
            "truncated_tetrahedron_graph",
            "turan_graph",
            "tutte_graph",
            "uniform_random_intersection_graph",
            "watts_strogatz_graph",
            "waxman_graph",
            "wheel_graph",
            "windmill_graph",
        ],
        "linalg": [
            "adj_matrix",
            "adjacency_matrix",
            "adjacency_spectrum",
            "algebraic_connectivity",
            "algebraicconnectivity",
            "attr_matrix",
            "attr_sparse_matrix",
...
            "modularity_matrix",
            "modularity_spectrum",
            "modularitymatrix",
            "normalized_laplacian_matrix",
            "normalized_laplacian_spectrum",
            "spectral_ordering",
            "spectrum",
            "tests",
        ],
        "readwrite": [
            "GraphMLReader",
            "GraphMLWriter",
            "adjacency",
            "adjacency_data",
            "adjacency_graph",
            "adjlist",
            "cytoscape",
            "cytoscape_data",
            "cytoscape_graph",
            "edgelist",
            "forest_str",
            "from_graph6_bytes",
            "from_sparse6_bytes",
            "generate_adjlist",
            "generate_edgelist",
            "generate_gexf",
            "generate_gml",
            "generate_graphml",
            "generate_multiline_adjlist",
            "generate_pajek",
            "gexf",
            "gml",
            "gpickle",
...            "write_p2g",
            "write_pajek",
            "write_shp",
            "write_sparse6",
            "write_weighted_edgelist",
            "write_yaml",
        ],
        "relabel": [
            "convert_node_labels_to_integers",
            "relabel_nodes",
        ],
        "testing": [
            "almost_equal",
            "assert_edges_equal",
            "assert_graphs_equal",
            "assert_nodes_equal",
            "run",
            "test",
            "tests",
            "utils",
        ],
        "utils": [
            "BinaryHeap",
            "MappedQueue",
            "MinHeap",
            "PairingHeap",
            "PythonRandomInterface",
            "UnionFind",
            "arbitrary_element",
            ...
            "reverse_cuthill_mckee_ordering",
            "reversed",
            "tests",
            "to_tuple",
            "union_find",
            "weighted_choice",
            "zipf_rv",
        ],
        "version": [
            "date",
            "date_info",
            "dev",
            "vcs_info",
            "version",
            "version_info",
        ],
    },
)


def __dir__():
    return __all__


__all__ = [
    "AdjacencyView",
    "AmbiguousSolution",
    "AtlasView",
    "BinaryHeap",
    "CGInverseLaplacian",
    "CurrentEdge",
    "DegreeView",
    "DiDegreeView",
    "DiGraph",
    "DiGraphMatcher",
    "DiMultiDegreeView",
    "EdgeComponentAuxGraph",
    "EdgeDataView",
    "EdgeView",
    "Edmonds",
    "ExceededMaxIterations",
    "FilterAdjacency",
    "FilterAtlas",
    "FilterMultiAdjacency",
    "FilterMultiInner",
...
    "write_adjlist",
    "write_dot",
    "write_edgelist",
    "write_gexf",
    "write_gml",
    "write_gpickle",
    "write_graph6",
    "write_graphml",
    "write_graphml_lxml",
    "write_graphml_xml",
    "write_multiline_adjlist",
    "write_p2g",
    "write_pajek",
    "write_shp",
    "write_sparse6",
    "write_weighted_edgelist",
    "write_yaml",
    "zipf_rv",
]

[stefanv]

It'd be great if mkinit could support the new stubs loader as well.

See also #6048

[Erotemic]

@stefanv Initial support for using lazy_loader inside mkinit is added in the 1.0.0 branch: Erotemic/mkinit#32 (which I will release when tests pass).

Using mkinit --lazy_loader will now use the lazy_loader module instead of using its own boilerplate. Not quite sure how you were thinking of integrating stubs support with mkinit. Please make an issue on the mkinit repo if you can provide more details on your thoughts there.

[stefanv]

Thanks, Jon! I'm out of office for a bit, but will check when I get back.