diff --git a/README.md b/README.md
index 51880acd..67798352 100644
--- a/README.md
+++ b/README.md
@@ -53,6 +53,7 @@ Stubs for the following libraries now exist in typeshed or the libraries themsel
 - jmespath
 - markdown
 - netaddr
+- networkx
 - openpyxl
 - opencv-python (see <https://github.com/opencv/opencv>; please upgrade opencv-python to 4.8.0+ and file any issues there)
 - packaging
diff --git a/pyproject.toml b/pyproject.toml
index 403063a3..b3ee3475 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,11 +20,11 @@ tests = [
     "pandas-stubs",
     "pytest",
     "scipy-stubs",
+    "types-networkx",
     "typing_extensions",
 
     # The libraries we're stubbing.
     # Needed for stubtest and downloads their dependencies to get known import symbols
-    "networkx",
     "scikit-image",
     "scikit-learn <1.7.0", # TODO: Update stubs for sklearn
     "sympy",
@@ -41,7 +41,6 @@ dev = [{ include-group = "hygiene" }, { include-group = "tests" }]
 # see https://github.com/microsoft/python-type-stubs/issues/315
 [tool.setuptools.package-dir]
 # See README.md as to why matplotlib is not included
-"networkx-stubs" = "stubs/networkx"
 "skimage-stubs" = "stubs/skimage"
 "sklearn-stubs" = "stubs/sklearn"
 "sympy-stubs" = "stubs/sympy-stubs"
diff --git a/stubs/networkx/README.md b/stubs/networkx/README.md
deleted file mode 100644
index 4a7c49d8..00000000
--- a/stubs/networkx/README.md
+++ /dev/null
@@ -1 +0,0 @@
-These stubs were created with https://github.com/gramster/docs2stubs.
diff --git a/stubs/networkx/__init__.pyi b/stubs/networkx/__init__.pyi
deleted file mode 100644
index 901f9d56..00000000
--- a/stubs/networkx/__init__.pyi
+++ /dev/null
@@ -1,66 +0,0 @@
-__version__: str = ...
-
-# These are imported in order as listed
-
-# Need to test with SciPy, when available
-from . import (
-    algorithms as algorithms,
-    classes as classes,
-    convert as convert,
-    convert_matrix as convert_matrix,
-    drawing as drawing,
-    generators as generators,
-    linalg as linalg,
-    readwrite as readwrite,
-    relabel as relabel,
-    utils as utils,
-)
-from .algorithms import *
-from .classes import *
-from .classes import filters as filters
-from .convert import (
-    from_dict_of_dicts as from_dict_of_dicts,
-    from_dict_of_lists as from_dict_of_lists,
-    from_edgelist as from_edgelist,
-    to_dict_of_dicts as to_dict_of_dicts,
-    to_dict_of_lists as to_dict_of_lists,
-    to_edgelist as to_edgelist,
-    to_networkx_graph as to_networkx_graph,
-)
-from .convert_matrix import (
-    from_numpy_array as from_numpy_array,
-    from_numpy_matrix as from_numpy_matrix,
-    from_pandas_adjacency as from_pandas_adjacency,
-    from_pandas_edgelist as from_pandas_edgelist,
-    from_scipy_sparse_array as from_scipy_sparse_array,
-    from_scipy_sparse_matrix as from_scipy_sparse_matrix,
-    to_numpy_array as to_numpy_array,
-    to_numpy_matrix as to_numpy_matrix,
-    to_numpy_recarray as to_numpy_recarray,
-    to_pandas_adjacency as to_pandas_adjacency,
-    to_pandas_edgelist as to_pandas_edgelist,
-    to_scipy_sparse_array as to_scipy_sparse_array,
-    to_scipy_sparse_matrix as to_scipy_sparse_matrix,
-)
-from .drawing import *
-from .exception import (
-    AmbiguousSolution as AmbiguousSolution,
-    ExceededMaxIterations as ExceededMaxIterations,
-    HasACycle as HasACycle,
-    NetworkXAlgorithmError as NetworkXAlgorithmError,
-    NetworkXError as NetworkXError,
-    NetworkXException as NetworkXException,
-    NetworkXNoCycle as NetworkXNoCycle,
-    NetworkXNoPath as NetworkXNoPath,
-    NetworkXNotImplemented as NetworkXNotImplemented,
-    NetworkXPointlessConcept as NetworkXPointlessConcept,
-    NetworkXUnbounded as NetworkXUnbounded,
-    NetworkXUnfeasible as NetworkXUnfeasible,
-    NodeNotFound as NodeNotFound,
-    PowerIterationFailedConvergence as PowerIterationFailedConvergence,
-)
-from .generators import *
-from .linalg import *
-from .readwrite import *
-from .relabel import convert_node_labels_to_integers as convert_node_labels_to_integers, relabel_nodes as relabel_nodes
-from .testing.test import run as test
diff --git a/stubs/networkx/_typing.pyi b/stubs/networkx/_typing.pyi
deleted file mode 100644
index 48eb475c..00000000
--- a/stubs/networkx/_typing.pyi
+++ /dev/null
@@ -1,27 +0,0 @@
-import decimal
-import io
-import typing_extensions
-
-import numpy.typing
-import pandas as pd
-
-Decimal = decimal.Decimal
-PythonScalar: typing_extensions.TypeAlias = str | int | float | bool
-
-ArrayLike = numpy.typing.ArrayLike
-FileLike = io.IOBase
-PathLike = str
-
-PandasScalar: typing_extensions.TypeAlias = pd.Period | pd.Timestamp | pd.Timedelta | pd.Interval
-Scalar: typing_extensions.TypeAlias = PythonScalar | PandasScalar
-
-Color: typing_extensions.TypeAlias = tuple[float, float, float] | str
-
-__all__ = [
-    "ArrayLike",
-    "Color",
-    "Decimal",
-    "FileLike",
-    "PathLike",
-    "Scalar",
-]
diff --git a/stubs/networkx/algorithms/__init__.pyi b/stubs/networkx/algorithms/__init__.pyi
deleted file mode 100644
index b5ed972d..00000000
--- a/stubs/networkx/algorithms/__init__.pyi
+++ /dev/null
@@ -1,308 +0,0 @@
-# Make certain subpackages available to the user as direct imports from
-# the `networkx` namespace.
-from . import (
-    approximation as approximation,
-    assortativity as assortativity,
-    bipartite as bipartite,
-    centrality as centrality,
-    chordal as chordal,
-    clique as clique,
-    cluster as cluster,
-    coloring as coloring,
-    community as community,
-    components as components,
-    connectivity as connectivity,
-    flow as flow,
-    isomorphism as isomorphism,
-    link_analysis as link_analysis,
-    lowest_common_ancestors as lowest_common_ancestors,
-    node_classification as node_classification,
-    operators as operators,
-    shortest_paths as shortest_paths,
-    tournament as tournament,
-    traversal as traversal,
-    tree as tree,
-)
-from .assortativity import *
-from .asteroidal import find_asteroidal_triple as find_asteroidal_triple, is_at_free as is_at_free
-
-# Make certain functions from some of the previous subpackages available
-# to the user as direct imports from the `networkx` namespace.
-from .bipartite import (
-    complete_bipartite_graph as complete_bipartite_graph,
-    is_bipartite as is_bipartite,
-    project as project,
-    projected_graph as projected_graph,
-)
-from .boundary import edge_boundary as edge_boundary, node_boundary as node_boundary
-from .bridges import bridges as bridges, has_bridges as has_bridges, local_bridges as local_bridges
-from .centrality import *
-from .chains import chain_decomposition as chain_decomposition
-from .chordal import (
-    NetworkXTreewidthBoundExceeded as NetworkXTreewidthBoundExceeded,
-    chordal_graph_cliques as chordal_graph_cliques,
-    chordal_graph_treewidth as chordal_graph_treewidth,
-    complete_to_chordal_graph as complete_to_chordal_graph,
-    find_induced_nodes as find_induced_nodes,
-    is_chordal as is_chordal,
-)
-from .clique import (
-    cliques_containing_node as cliques_containing_node,
-    enumerate_all_cliques as enumerate_all_cliques,
-    find_cliques as find_cliques,
-    find_cliques_recursive as find_cliques_recursive,
-    graph_clique_number as graph_clique_number,
-    graph_number_of_cliques as graph_number_of_cliques,
-    make_clique_bipartite as make_clique_bipartite,
-    make_max_clique_graph as make_max_clique_graph,
-    max_weight_clique as max_weight_clique,
-    node_clique_number as node_clique_number,
-    number_of_cliques as number_of_cliques,
-)
-from .cluster import (
-    average_clustering as average_clustering,
-    clustering as clustering,
-    generalized_degree as generalized_degree,
-    square_clustering as square_clustering,
-    transitivity as transitivity,
-    triangles as triangles,
-)
-from .coloring import *
-from .communicability_alg import communicability as communicability, communicability_exp as communicability_exp
-from .components import *
-from .connectivity import (
-    all_node_cuts as all_node_cuts,
-    all_pairs_node_connectivity as all_pairs_node_connectivity,
-    average_node_connectivity as average_node_connectivity,
-    edge_connectivity as edge_connectivity,
-    edge_disjoint_paths as edge_disjoint_paths,
-    is_k_edge_connected as is_k_edge_connected,
-    k_components as k_components,
-    k_edge_augmentation as k_edge_augmentation,
-    k_edge_components as k_edge_components,
-    k_edge_subgraphs as k_edge_subgraphs,
-    minimum_edge_cut as minimum_edge_cut,
-    minimum_node_cut as minimum_node_cut,
-    node_connectivity as node_connectivity,
-    node_disjoint_paths as node_disjoint_paths,
-    stoer_wagner as stoer_wagner,
-)
-from .core import (
-    core_number as core_number,
-    find_cores as find_cores,
-    k_core as k_core,
-    k_corona as k_corona,
-    k_crust as k_crust,
-    k_shell as k_shell,
-    k_truss as k_truss,
-    onion_layers as onion_layers,
-)
-from .covering import is_edge_cover as is_edge_cover, min_edge_cover as min_edge_cover
-from .cuts import (
-    boundary_expansion as boundary_expansion,
-    conductance as conductance,
-    cut_size as cut_size,
-    edge_expansion as edge_expansion,
-    mixing_expansion as mixing_expansion,
-    node_expansion as node_expansion,
-    normalized_cut_size as normalized_cut_size,
-    volume as volume,
-)
-from .cycles import (
-    cycle_basis as cycle_basis,
-    find_cycle as find_cycle,
-    minimum_cycle_basis as minimum_cycle_basis,
-    recursive_simple_cycles as recursive_simple_cycles,
-    simple_cycles as simple_cycles,
-)
-from .d_separation import d_separated as d_separated
-from .dag import (
-    all_topological_sorts as all_topological_sorts,
-    ancestors as ancestors,
-    antichains as antichains,
-    dag_longest_path as dag_longest_path,
-    dag_longest_path_length as dag_longest_path_length,
-    dag_to_branching as dag_to_branching,
-    descendants as descendants,
-    is_aperiodic as is_aperiodic,
-    is_directed_acyclic_graph as is_directed_acyclic_graph,
-    lexicographical_topological_sort as lexicographical_topological_sort,
-    topological_generations as topological_generations,
-    topological_sort as topological_sort,
-    transitive_closure as transitive_closure,
-    transitive_closure_dag as transitive_closure_dag,
-    transitive_reduction as transitive_reduction,
-)
-from .distance_measures import (
-    barycenter as barycenter,
-    center as center,
-    diameter as diameter,
-    eccentricity as eccentricity,
-    extrema_bounding as extrema_bounding,
-    periphery as periphery,
-    radius as radius,
-    resistance_distance as resistance_distance,
-)
-from .distance_regular import (
-    global_parameters as global_parameters,
-    intersection_array as intersection_array,
-    is_distance_regular as is_distance_regular,
-    is_strongly_regular as is_strongly_regular,
-)
-from .dominance import dominance_frontiers as dominance_frontiers, immediate_dominators as immediate_dominators
-from .dominating import dominating_set as dominating_set, is_dominating_set as is_dominating_set
-from .efficiency_measures import (
-    efficiency as efficiency,
-    global_efficiency as global_efficiency,
-    local_efficiency as local_efficiency,
-)
-from .euler import (
-    eulerian_circuit as eulerian_circuit,
-    eulerian_path as eulerian_path,
-    eulerize as eulerize,
-    has_eulerian_path as has_eulerian_path,
-    is_eulerian as is_eulerian,
-    is_semieulerian as is_semieulerian,
-)
-from .flow import (
-    capacity_scaling as capacity_scaling,
-    cost_of_flow as cost_of_flow,
-    gomory_hu_tree as gomory_hu_tree,
-    max_flow_min_cost as max_flow_min_cost,
-    maximum_flow as maximum_flow,
-    maximum_flow_value as maximum_flow_value,
-    min_cost_flow as min_cost_flow,
-    min_cost_flow_cost as min_cost_flow_cost,
-    minimum_cut as minimum_cut,
-    minimum_cut_value as minimum_cut_value,
-    network_simplex as network_simplex,
-)
-from .graph_hashing import (
-    weisfeiler_lehman_graph_hash as weisfeiler_lehman_graph_hash,
-    weisfeiler_lehman_subgraph_hashes as weisfeiler_lehman_subgraph_hashes,
-)
-from .graphical import (
-    is_digraphical as is_digraphical,
-    is_graphical as is_graphical,
-    is_multigraphical as is_multigraphical,
-    is_pseudographical as is_pseudographical,
-    is_valid_degree_sequence_erdos_gallai as is_valid_degree_sequence_erdos_gallai,
-    is_valid_degree_sequence_havel_hakimi as is_valid_degree_sequence_havel_hakimi,
-)
-from .hierarchy import flow_hierarchy as flow_hierarchy
-from .hybrid import is_kl_connected as is_kl_connected, kl_connected_subgraph as kl_connected_subgraph
-from .isolate import is_isolate as is_isolate, isolates as isolates, number_of_isolates as number_of_isolates
-from .isomorphism import (
-    could_be_isomorphic as could_be_isomorphic,
-    fast_could_be_isomorphic as fast_could_be_isomorphic,
-    faster_could_be_isomorphic as faster_could_be_isomorphic,
-    is_isomorphic as is_isomorphic,
-)
-from .link_analysis import *
-from .link_prediction import (
-    adamic_adar_index as adamic_adar_index,
-    cn_soundarajan_hopcroft as cn_soundarajan_hopcroft,
-    common_neighbor_centrality as common_neighbor_centrality,
-    jaccard_coefficient as jaccard_coefficient,
-    preferential_attachment as preferential_attachment,
-    ra_index_soundarajan_hopcroft as ra_index_soundarajan_hopcroft,
-    resource_allocation_index as resource_allocation_index,
-    within_inter_cluster as within_inter_cluster,
-)
-from .lowest_common_ancestors import (
-    all_pairs_lowest_common_ancestor as all_pairs_lowest_common_ancestor,
-    lowest_common_ancestor as lowest_common_ancestor,
-    tree_all_pairs_lowest_common_ancestor as tree_all_pairs_lowest_common_ancestor,
-)
-from .matching import (
-    is_matching as is_matching,
-    is_maximal_matching as is_maximal_matching,
-    is_perfect_matching as is_perfect_matching,
-    max_weight_matching as max_weight_matching,
-    maximal_matching as maximal_matching,
-    min_weight_matching as min_weight_matching,
-)
-from .minors import *
-from .mis import maximal_independent_set as maximal_independent_set
-from .moral import moral_graph as moral_graph
-from .non_randomness import non_randomness as non_randomness
-from .operators import *
-from .planar_drawing import combinatorial_embedding_to_pos as combinatorial_embedding_to_pos
-from .planarity import PlanarEmbedding as PlanarEmbedding, check_planarity as check_planarity, is_planar as is_planar
-from .polynomials import chromatic_polynomial as chromatic_polynomial, tutte_polynomial as tutte_polynomial
-from .reciprocity import overall_reciprocity as overall_reciprocity, reciprocity as reciprocity
-from .regular import is_k_regular as is_k_regular, is_regular as is_regular, k_factor as k_factor
-from .richclub import rich_club_coefficient as rich_club_coefficient
-from .shortest_paths import *
-from .similarity import (
-    generate_random_paths as generate_random_paths,
-    graph_edit_distance as graph_edit_distance,
-    optimal_edit_paths as optimal_edit_paths,
-    optimize_edit_paths as optimize_edit_paths,
-    optimize_graph_edit_distance as optimize_graph_edit_distance,
-    panther_similarity as panther_similarity,
-    simrank_similarity as simrank_similarity,
-    simrank_similarity_numpy as simrank_similarity_numpy,
-)
-from .simple_paths import (
-    all_simple_edge_paths as all_simple_edge_paths,
-    all_simple_paths as all_simple_paths,
-    is_simple_path as is_simple_path,
-    shortest_simple_paths as shortest_simple_paths,
-)
-from .smallworld import (
-    lattice_reference as lattice_reference,
-    omega as omega,
-    random_reference as random_reference,
-    sigma as sigma,
-)
-from .smetric import s_metric as s_metric
-from .sparsifiers import spanner as spanner
-from .structuralholes import constraint as constraint, effective_size as effective_size, local_constraint as local_constraint
-from .summarization import dedensify as dedensify, snap_aggregation as snap_aggregation
-from .swap import connected_double_edge_swap as connected_double_edge_swap, double_edge_swap as double_edge_swap
-from .traversal import *
-from .tree.branchings import (
-    ArborescenceIterator as ArborescenceIterator,
-    maximum_branching as maximum_branching,
-    maximum_spanning_arborescence as maximum_spanning_arborescence,
-    minimum_branching as minimum_branching,
-    minimum_spanning_arborescence as minimum_spanning_arborescence,
-)
-from .tree.coding import (
-    NotATree as NotATree,
-    from_nested_tuple as from_nested_tuple,
-    from_prufer_sequence as from_prufer_sequence,
-    to_nested_tuple as to_nested_tuple,
-    to_prufer_sequence as to_prufer_sequence,
-)
-from .tree.decomposition import junction_tree as junction_tree
-from .tree.mst import (
-    EdgePartition as EdgePartition,
-    SpanningTreeIterator as SpanningTreeIterator,
-    maximum_spanning_edges as maximum_spanning_edges,
-    maximum_spanning_tree as maximum_spanning_tree,
-    minimum_spanning_edges as minimum_spanning_edges,
-    minimum_spanning_tree as minimum_spanning_tree,
-    partition_spanning_tree as partition_spanning_tree,
-    random_spanning_tree as random_spanning_tree,
-)
-from .tree.operations import join as join
-from .tree.recognition import (
-    is_arborescence as is_arborescence,
-    is_branching as is_branching,
-    is_forest as is_forest,
-    is_tree as is_tree,
-)
-from .triads import (
-    all_triads as all_triads,
-    all_triplets as all_triplets,
-    is_triad as is_triad,
-    random_triad as random_triad,
-    triad_type as triad_type,
-    triadic_census as triadic_census,
-    triads_by_type as triads_by_type,
-)
-from .vitality import closeness_vitality as closeness_vitality
-from .voronoi import voronoi_cells as voronoi_cells
-from .wiener import wiener_index as wiener_index
diff --git a/stubs/networkx/algorithms/approximation/__init__.pyi b/stubs/networkx/algorithms/approximation/__init__.pyi
deleted file mode 100644
index b12b9871..00000000
--- a/stubs/networkx/algorithms/approximation/__init__.pyi
+++ /dev/null
@@ -1,32 +0,0 @@
-from ...algorithms.approximation.clique import (
-    clique_removal as clique_removal,
-    large_clique_size as large_clique_size,
-    max_clique as max_clique,
-    maximum_independent_set as maximum_independent_set,
-)
-from .clustering_coefficient import average_clustering as average_clustering
-from .connectivity import (
-    all_pairs_node_connectivity as all_pairs_node_connectivity,
-    local_node_connectivity as local_node_connectivity,
-    node_connectivity as node_connectivity,
-)
-from .distance_measures import diameter as diameter
-from .dominating_set import (
-    min_edge_dominating_set as min_edge_dominating_set,
-    min_weighted_dominating_set as min_weighted_dominating_set,
-)
-from .kcomponents import k_components as k_components
-from .matching import min_maximal_matching as min_maximal_matching
-from .maxcut import one_exchange as one_exchange, randomized_partitioning as randomized_partitioning
-from .ramsey import ramsey_R2 as ramsey_R2
-from .steinertree import metric_closure as metric_closure, steiner_tree as steiner_tree
-from .traveling_salesman import (
-    asadpour_atsp as asadpour_atsp,
-    christofides as christofides,
-    greedy_tsp as greedy_tsp,
-    simulated_annealing_tsp as simulated_annealing_tsp,
-    threshold_accepting_tsp as threshold_accepting_tsp,
-    traveling_salesman_problem as traveling_salesman_problem,
-)
-from .treewidth import treewidth_min_degree as treewidth_min_degree, treewidth_min_fill_in as treewidth_min_fill_in
-from .vertex_cover import min_weighted_vertex_cover as min_weighted_vertex_cover
diff --git a/stubs/networkx/algorithms/approximation/clique.pyi b/stubs/networkx/algorithms/approximation/clique.pyi
deleted file mode 100644
index 1bf58945..00000000
--- a/stubs/networkx/algorithms/approximation/clique.pyi
+++ /dev/null
@@ -1,14 +0,0 @@
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = [
-    "clique_removal",
-    "max_clique",
-    "large_clique_size",
-    "maximum_independent_set",
-]
-
-def maximum_independent_set(G: Graph) -> set: ...
-def max_clique(G: Graph) -> set: ...
-def clique_removal(G: Graph): ...
-def large_clique_size(G: Graph): ...
diff --git a/stubs/networkx/algorithms/approximation/clustering_coefficient.pyi b/stubs/networkx/algorithms/approximation/clustering_coefficient.pyi
deleted file mode 100644
index 099da4d3..00000000
--- a/stubs/networkx/algorithms/approximation/clustering_coefficient.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, py_random_state
-
-__all__ = ["average_clustering"]
-
-@py_random_state(2)
-def average_clustering(G: Graph, trials=1000, seed=None) -> float: ...
diff --git a/stubs/networkx/algorithms/approximation/connectivity.pyi b/stubs/networkx/algorithms/approximation/connectivity.pyi
deleted file mode 100644
index 1359a74c..00000000
--- a/stubs/networkx/algorithms/approximation/connectivity.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-import itertools
-from collections.abc import Mapping
-from operator import itemgetter
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "local_node_connectivity",
-    "node_connectivity",
-    "all_pairs_node_connectivity",
-]
-
-def local_node_connectivity(G: Graph, source, target, cutoff=None): ...
-def node_connectivity(G: Graph, s=None, t=None): ...
-def all_pairs_node_connectivity(G: Graph, nbunch=None, cutoff=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/approximation/distance_measures.pyi b/stubs/networkx/algorithms/approximation/distance_measures.pyi
deleted file mode 100644
index 28092329..00000000
--- a/stubs/networkx/algorithms/approximation/distance_measures.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ...classes.graph import Graph
-from ...utils.decorators import py_random_state
-
-__all__ = ["diameter"]
-
-@py_random_state(1)
-def diameter(G: Graph, seed=None): ...
diff --git a/stubs/networkx/algorithms/approximation/dominating_set.pyi b/stubs/networkx/algorithms/approximation/dominating_set.pyi
deleted file mode 100644
index 014f9d12..00000000
--- a/stubs/networkx/algorithms/approximation/dominating_set.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["min_weighted_dominating_set", "min_edge_dominating_set"]
-
-def min_weighted_dominating_set(G: Graph, weight: str | None = None) -> set: ...
-def min_edge_dominating_set(G: Graph) -> set: ...
diff --git a/stubs/networkx/algorithms/approximation/kcomponents.pyi b/stubs/networkx/algorithms/approximation/kcomponents.pyi
deleted file mode 100644
index c247a294..00000000
--- a/stubs/networkx/algorithms/approximation/kcomponents.pyi
+++ /dev/null
@@ -1,24 +0,0 @@
-from collections.abc import Mapping
-from functools import cached_property
-
-from ...classes.graph import Graph
-
-__all__ = ["k_components"]
-
-def k_components(G: Graph, min_density: float = 0.95) -> Mapping: ...
-
-class _AntiGraph(Graph):
-    all_edge_dict: dict = ...
-
-    def single_edge_dict(self): ...
-
-    edge_attr_dict_factory = single_edge_dict
-
-    def __getitem__(self, n) -> Mapping: ...
-    def neighbors(self, n): ...
-    @cached_property
-    def adj(self): ...
-    def subgraph(self, nodes): ...
-    @cached_property
-    def degree(self): ...
-    def adjacency(self): ...
diff --git a/stubs/networkx/algorithms/approximation/matching.pyi b/stubs/networkx/algorithms/approximation/matching.pyi
deleted file mode 100644
index 289d3fdc..00000000
--- a/stubs/networkx/algorithms/approximation/matching.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["min_maximal_matching"]
-
-def min_maximal_matching(G: Graph) -> set: ...
diff --git a/stubs/networkx/algorithms/approximation/maxcut.pyi b/stubs/networkx/algorithms/approximation/maxcut.pyi
deleted file mode 100644
index 5f488f27..00000000
--- a/stubs/networkx/algorithms/approximation/maxcut.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from typing import Any
-
-from ..._typing import Scalar
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for, py_random_state
-
-__all__ = ["randomized_partitioning", "one_exchange"]
-
-@py_random_state(1)
-def randomized_partitioning(G: Graph, seed=None, p: Scalar = 0.5, weight: Any = None): ...
-@py_random_state(2)
-def one_exchange(G: Graph, initial_cut: set | None = None, seed=None, weight: Any = None): ...
diff --git a/stubs/networkx/algorithms/approximation/ramsey.pyi b/stubs/networkx/algorithms/approximation/ramsey.pyi
deleted file mode 100644
index 0d2bfb92..00000000
--- a/stubs/networkx/algorithms/approximation/ramsey.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-from ...utils import arbitrary_element, not_implemented_for
-
-__all__ = ["ramsey_R2"]
-
-def ramsey_R2(G: Graph): ...
diff --git a/stubs/networkx/algorithms/approximation/steinertree.pyi b/stubs/networkx/algorithms/approximation/steinertree.pyi
deleted file mode 100644
index 90dfc960..00000000
--- a/stubs/networkx/algorithms/approximation/steinertree.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from itertools import chain
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, pairwise
-
-__all__ = ["metric_closure", "steiner_tree"]
-
-def metric_closure(G: Graph, weight="weight"): ...
-def steiner_tree(G: Graph, terminal_nodes: ArrayLike, weight="weight"): ...
diff --git a/stubs/networkx/algorithms/approximation/traveling_salesman.pyi b/stubs/networkx/algorithms/approximation/traveling_salesman.pyi
deleted file mode 100644
index 5175236b..00000000
--- a/stubs/networkx/algorithms/approximation/traveling_salesman.pyi
+++ /dev/null
@@ -1,54 +0,0 @@
-import math
-from collections.abc import Mapping
-from typing import Literal
-
-from numpy.typing import ArrayLike
-
-from ...algorithms.tree.mst import random_spanning_tree
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, pairwise, py_random_state
-
-__all__ = [
-    "traveling_salesman_problem",
-    "christofides",
-    "asadpour_atsp",
-    "greedy_tsp",
-    "simulated_annealing_tsp",
-    "threshold_accepting_tsp",
-]
-
-def swap_two_nodes(soln, seed) -> ArrayLike: ...
-def move_one_node(soln, seed) -> ArrayLike: ...
-def christofides(G: Graph, weight="weight", tree=None) -> ArrayLike: ...
-def traveling_salesman_problem(G: Graph, weight="weight", nodes=None, cycle=True, method=None) -> ArrayLike: ...
-@py_random_state(2)
-def asadpour_atsp(G: Graph, weight="weight", seed=None, source=None): ...
-def held_karp_ascent(G: Graph, weight="weight"): ...
-def spanning_tree_distribution(G: Graph, z: Mapping) -> Mapping: ...
-def greedy_tsp(G: Graph, weight="weight", source=None): ...
-@py_random_state(9)
-def simulated_annealing_tsp(
-    G: Graph,
-    init_cycle,
-    weight="weight",
-    source=None,
-    temp=100,
-    move="1-1",
-    max_iterations=10,
-    N_inner=100,
-    alpha=0.01,
-    seed=None,
-): ...
-@py_random_state(9)
-def threshold_accepting_tsp(
-    G: Graph,
-    init_cycle: ArrayLike | Literal["greedy"],
-    weight="weight",
-    source=None,
-    threshold=1,
-    move="1-1",
-    max_iterations=10,
-    N_inner=100,
-    alpha=0.1,
-    seed=None,
-): ...
diff --git a/stubs/networkx/algorithms/approximation/treewidth.pyi b/stubs/networkx/algorithms/approximation/treewidth.pyi
deleted file mode 100644
index a9eb41d5..00000000
--- a/stubs/networkx/algorithms/approximation/treewidth.pyi
+++ /dev/null
@@ -1,18 +0,0 @@
-import itertools
-import sys
-from heapq import heapify, heappop, heappush
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = ["treewidth_min_degree", "treewidth_min_fill_in"]
-
-def treewidth_min_degree(G: Graph): ...
-def treewidth_min_fill_in(G: Graph): ...
-
-class MinDegreeHeuristic:
-    def __init__(self, graph): ...
-    def best_node(self, graph): ...
-
-def min_fill_in_heuristic(graph): ...
-def treewidth_decomp(G: Graph, heuristic=...): ...
diff --git a/stubs/networkx/algorithms/approximation/vertex_cover.pyi b/stubs/networkx/algorithms/approximation/vertex_cover.pyi
deleted file mode 100644
index 00ab01b3..00000000
--- a/stubs/networkx/algorithms/approximation/vertex_cover.pyi
+++ /dev/null
@@ -1,4 +0,0 @@
-__all__ = ["min_weighted_vertex_cover"]
-from ...classes.graph import Graph
-
-def min_weighted_vertex_cover(G: Graph, weight=None) -> set: ...
diff --git a/stubs/networkx/algorithms/assortativity/__init__.pyi b/stubs/networkx/algorithms/assortativity/__init__.pyi
deleted file mode 100644
index 3343e1c4..00000000
--- a/stubs/networkx/algorithms/assortativity/__init__.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from .connectivity import average_degree_connectivity as average_degree_connectivity, k_nearest_neighbors as k_nearest_neighbors
-from .correlation import (
-    attribute_assortativity_coefficient as attribute_assortativity_coefficient,
-    degree_assortativity_coefficient as degree_assortativity_coefficient,
-    degree_pearson_correlation_coefficient as degree_pearson_correlation_coefficient,
-    numeric_assortativity_coefficient as numeric_assortativity_coefficient,
-)
-from .mixing import (
-    attribute_mixing_dict as attribute_mixing_dict,
-    attribute_mixing_matrix as attribute_mixing_matrix,
-    degree_mixing_dict as degree_mixing_dict,
-    degree_mixing_matrix as degree_mixing_matrix,
-    mixing_dict as mixing_dict,
-    numeric_mixing_matrix as numeric_mixing_matrix,
-)
-from .neighbor_degree import average_neighbor_degree as average_neighbor_degree
-from .pairs import node_attribute_xy as node_attribute_xy, node_degree_xy as node_degree_xy
diff --git a/stubs/networkx/algorithms/assortativity/connectivity.pyi b/stubs/networkx/algorithms/assortativity/connectivity.pyi
deleted file mode 100644
index 86bba7b8..00000000
--- a/stubs/networkx/algorithms/assortativity/connectivity.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-from typing import Literal
-
-from ...classes.graph import Graph
-
-__all__ = ["average_degree_connectivity", "k_nearest_neighbors"]
-
-def average_degree_connectivity(
-    G: Graph,
-    source="in+out",
-    target: Literal["in+out", "out", "in"] = "in+out",
-    nodes=None,
-    weight=None,
-) -> Mapping: ...
-def k_nearest_neighbors(G: Graph, source="in+out", target="in+out", nodes=None, weight=None): ...
diff --git a/stubs/networkx/algorithms/assortativity/correlation.pyi b/stubs/networkx/algorithms/assortativity/correlation.pyi
deleted file mode 100644
index ada1eb16..00000000
--- a/stubs/networkx/algorithms/assortativity/correlation.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from ...classes.graph import Graph
-from .mixing import attribute_mixing_matrix, degree_mixing_matrix
-from .pairs import node_degree_xy
-
-__all__ = [
-    "degree_pearson_correlation_coefficient",
-    "degree_assortativity_coefficient",
-    "attribute_assortativity_coefficient",
-    "numeric_assortativity_coefficient",
-]
-
-def degree_assortativity_coefficient(G: Graph, x="out", y="in", weight=None, nodes=None) -> float: ...
-def degree_pearson_correlation_coefficient(G: Graph, x="out", y="in", weight=None, nodes=None) -> float: ...
-def attribute_assortativity_coefficient(G: Graph, attribute: str, nodes=None) -> float: ...
-def numeric_assortativity_coefficient(G: Graph, attribute: str, nodes=None) -> float: ...
-def attribute_ac(M): ...
diff --git a/stubs/networkx/algorithms/assortativity/mixing.pyi b/stubs/networkx/algorithms/assortativity/mixing.pyi
deleted file mode 100644
index 573b38f5..00000000
--- a/stubs/networkx/algorithms/assortativity/mixing.pyi
+++ /dev/null
@@ -1,41 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import dict_to_numpy_array
-from .pairs import node_attribute_xy, node_degree_xy
-
-__all__ = [
-    "attribute_mixing_matrix",
-    "attribute_mixing_dict",
-    "degree_mixing_matrix",
-    "degree_mixing_dict",
-    "numeric_mixing_matrix",
-    "mixing_dict",
-]
-
-def attribute_mixing_dict(G: Graph, attribute: str, nodes=None, normalized=False) -> Mapping: ...
-def attribute_mixing_matrix(
-    G: Graph,
-    attribute: str,
-    nodes=None,
-    mapping: Mapping | None = None,
-    normalized=True,
-): ...
-def degree_mixing_dict(G: Graph, x="out", y="in", weight=None, nodes=None, normalized=False) -> Mapping: ...
-def degree_mixing_matrix(
-    G: Graph,
-    x="out",
-    y="in",
-    weight=None,
-    nodes=None,
-    normalized=True,
-    mapping: Mapping | None = None,
-): ...
-def numeric_mixing_matrix(
-    G: Graph,
-    attribute: str,
-    nodes=None,
-    normalized=True,
-    mapping: Mapping | None = None,
-): ...
-def mixing_dict(xy, normalized=False) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/assortativity/neighbor_degree.pyi b/stubs/networkx/algorithms/assortativity/neighbor_degree.pyi
deleted file mode 100644
index 5c66e4bd..00000000
--- a/stubs/networkx/algorithms/assortativity/neighbor_degree.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["average_neighbor_degree"]
-
-def average_neighbor_degree(G: Graph, source="out", target="out", nodes=None, weight=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/assortativity/pairs.pyi b/stubs/networkx/algorithms/assortativity/pairs.pyi
deleted file mode 100644
index ce76b034..00000000
--- a/stubs/networkx/algorithms/assortativity/pairs.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["node_attribute_xy", "node_degree_xy"]
-
-def node_attribute_xy(G: Graph, attribute, nodes=None): ...
-def node_degree_xy(G: Graph, x="out", y="in", weight=None, nodes=None): ...
diff --git a/stubs/networkx/algorithms/asteroidal.pyi b/stubs/networkx/algorithms/asteroidal.pyi
deleted file mode 100644
index 3632aad6..00000000
--- a/stubs/networkx/algorithms/asteroidal.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["is_at_free", "find_asteroidal_triple"]
-
-def find_asteroidal_triple(G: Graph) -> list | None: ...
-def is_at_free(G: Graph) -> bool: ...
-def create_component_structure(G: Graph) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/bipartite/__init__.pyi b/stubs/networkx/algorithms/bipartite/__init__.pyi
deleted file mode 100644
index 34a5e895..00000000
--- a/stubs/networkx/algorithms/bipartite/__init__.pyi
+++ /dev/null
@@ -1,54 +0,0 @@
-from .basic import (
-    color as color,
-    degrees as degrees,
-    density as density,
-    is_bipartite as is_bipartite,
-    is_bipartite_node_set as is_bipartite_node_set,
-    sets as sets,
-)
-from .centrality import (
-    betweenness_centrality as betweenness_centrality,
-    closeness_centrality as closeness_centrality,
-    degree_centrality as degree_centrality,
-)
-from .cluster import (
-    average_clustering as average_clustering,
-    clustering as clustering,
-    latapy_clustering as latapy_clustering,
-    robins_alexander_clustering as robins_alexander_clustering,
-)
-from .covering import min_edge_cover as min_edge_cover
-from .edgelist import (
-    generate_edgelist as generate_edgelist,
-    parse_edgelist as parse_edgelist,
-    read_edgelist as read_edgelist,
-    write_edgelist as write_edgelist,
-)
-from .generators import (
-    alternating_havel_hakimi_graph as alternating_havel_hakimi_graph,
-    complete_bipartite_graph as complete_bipartite_graph,
-    configuration_model as configuration_model,
-    gnmk_random_graph as gnmk_random_graph,
-    havel_hakimi_graph as havel_hakimi_graph,
-    preferential_attachment_graph as preferential_attachment_graph,
-    random_graph as random_graph,
-    reverse_havel_hakimi_graph as reverse_havel_hakimi_graph,
-)
-from .matching import (
-    eppstein_matching as eppstein_matching,
-    hopcroft_karp_matching as hopcroft_karp_matching,
-    maximum_matching as maximum_matching,
-    minimum_weight_full_matching as minimum_weight_full_matching,
-    to_vertex_cover as to_vertex_cover,
-)
-from .matrix import biadjacency_matrix as biadjacency_matrix, from_biadjacency_matrix as from_biadjacency_matrix
-from .projection import (
-    collaboration_weighted_projected_graph as collaboration_weighted_projected_graph,
-    generic_weighted_projected_graph as generic_weighted_projected_graph,
-    overlap_weighted_projected_graph as overlap_weighted_projected_graph,
-    project as project,
-    projected_graph as projected_graph,
-    weighted_projected_graph as weighted_projected_graph,
-)
-from .redundancy import node_redundancy as node_redundancy
-from .spectral import spectral_bipartivity as spectral_bipartivity
diff --git a/stubs/networkx/algorithms/bipartite/basic.pyi b/stubs/networkx/algorithms/bipartite/basic.pyi
deleted file mode 100644
index 989d2dad..00000000
--- a/stubs/networkx/algorithms/bipartite/basic.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-from collections.abc import Mapping
-
-from ...algorithms.components import connected_components
-from ...classes.graph import Graph
-from ...exception import AmbiguousSolution
-
-__all__ = [
-    "is_bipartite",
-    "is_bipartite_node_set",
-    "color",
-    "sets",
-    "density",
-    "degrees",
-]
-
-def color(G: Graph) -> Mapping: ...
-def is_bipartite(G: Graph): ...
-def is_bipartite_node_set(G: Graph, nodes): ...
-def sets(G: Graph, top_nodes=None) -> tuple[set, set]: ...
-def density(B, nodes) -> float: ...
-def degrees(B, nodes, weight=None) -> tuple[dict, ...]: ...
diff --git a/stubs/networkx/algorithms/bipartite/centrality.pyi b/stubs/networkx/algorithms/bipartite/centrality.pyi
deleted file mode 100644
index 6d6a17aa..00000000
--- a/stubs/networkx/algorithms/bipartite/centrality.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["degree_centrality", "betweenness_centrality", "closeness_centrality"]
-
-def degree_centrality(G: Graph, nodes) -> Mapping: ...
-def betweenness_centrality(G: Graph, nodes) -> Mapping: ...
-def closeness_centrality(G: Graph, nodes, normalized: bool = True) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/bipartite/cluster.pyi b/stubs/networkx/algorithms/bipartite/cluster.pyi
deleted file mode 100644
index 2a331049..00000000
--- a/stubs/networkx/algorithms/bipartite/cluster.pyi
+++ /dev/null
@@ -1,26 +0,0 @@
-import itertools
-from collections.abc import Iterable, Mapping
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "clustering",
-    "average_clustering",
-    "latapy_clustering",
-    "robins_alexander_clustering",
-]
-
-def cc_dot(nu, nv): ...
-def cc_max(nu, nv): ...
-def cc_min(nu, nv): ...
-
-modes: dict = ...
-
-def latapy_clustering(G: Graph, nodes=None, mode: str = "dot") -> Mapping: ...
-
-clustering = ...
-
-def average_clustering(G: Graph, nodes: ArrayLike | Iterable | None = None, mode: str = "dot") -> float: ...
-def robins_alexander_clustering(G: Graph) -> float: ...
diff --git a/stubs/networkx/algorithms/bipartite/covering.pyi b/stubs/networkx/algorithms/bipartite/covering.pyi
deleted file mode 100644
index 87c16cea..00000000
--- a/stubs/networkx/algorithms/bipartite/covering.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ...algorithms.covering import min_edge_cover as _min_edge_cover
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-from .matching import hopcroft_karp_matching
-
-__all__ = ["min_edge_cover"]
-
-def min_edge_cover(G: Graph, matching_algorithm=None) -> set: ...
diff --git a/stubs/networkx/algorithms/bipartite/edgelist.pyi b/stubs/networkx/algorithms/bipartite/edgelist.pyi
deleted file mode 100644
index 8f28dd06..00000000
--- a/stubs/networkx/algorithms/bipartite/edgelist.pyi
+++ /dev/null
@@ -1,35 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = ["generate_edgelist", "write_edgelist", "parse_edgelist", "read_edgelist"]
-
-from ...utils import not_implemented_for, open_file
-
-def write_edgelist(
-    G: Graph,
-    path,
-    comments: str = "#",
-    delimiter: str = " ",
-    data: bool | ArrayLike = True,
-    encoding: str = "utf-8",
-): ...
-def generate_edgelist(G: Graph, delimiter: str = " ", data=True) -> str: ...
-def parse_edgelist(
-    lines,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    data=True,
-): ...
-def read_edgelist(
-    path,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    data=True,
-    edgetype=None,
-    encoding: str = "utf-8",
-): ...
diff --git a/stubs/networkx/algorithms/bipartite/generators.pyi b/stubs/networkx/algorithms/bipartite/generators.pyi
deleted file mode 100644
index 26c85621..00000000
--- a/stubs/networkx/algorithms/bipartite/generators.pyi
+++ /dev/null
@@ -1,32 +0,0 @@
-import math
-import numbers
-from functools import reduce
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import nodes_or_number, py_random_state
-
-__all__ = [
-    "configuration_model",
-    "havel_hakimi_graph",
-    "reverse_havel_hakimi_graph",
-    "alternating_havel_hakimi_graph",
-    "preferential_attachment_graph",
-    "random_graph",
-    "gnmk_random_graph",
-    "complete_bipartite_graph",
-]
-
-def complete_bipartite_graph(n1, n2, create_using=None): ...
-@py_random_state(3)
-def configuration_model(aseq: ArrayLike, bseq: ArrayLike, create_using=None, seed=None): ...
-def havel_hakimi_graph(aseq: ArrayLike, bseq: ArrayLike, create_using=None): ...
-def reverse_havel_hakimi_graph(aseq: ArrayLike, bseq: ArrayLike, create_using=None): ...
-def alternating_havel_hakimi_graph(aseq: ArrayLike, bseq: ArrayLike, create_using=None): ...
-@py_random_state(3)
-def preferential_attachment_graph(aseq: ArrayLike, p: float, create_using=None, seed=None): ...
-@py_random_state(3)
-def random_graph(n: int, m: int, p: float, seed=None, directed=False): ...
-@py_random_state(3)
-def gnmk_random_graph(n: int, m: int, k: int, seed=None, directed=False): ...
diff --git a/stubs/networkx/algorithms/bipartite/matching.pyi b/stubs/networkx/algorithms/bipartite/matching.pyi
deleted file mode 100644
index 8d9c502b..00000000
--- a/stubs/networkx/algorithms/bipartite/matching.pyi
+++ /dev/null
@@ -1,37 +0,0 @@
-# This module uses material from the Wikipedia article Hopcroft--Karp algorithm
-# <https://en.wikipedia.org/wiki/Hopcroft%E2%80%93Karp_algorithm>, accessed on
-# January 3, 2015, which is released under the Creative Commons
-# Attribution-Share-Alike License 3.0
-# <http://creativecommons.org/licenses/by-sa/3.0/>. That article includes
-# pseudocode, which has been translated into the corresponding Python code.
-#
-# Portions of this module use code from David Eppstein's Python Algorithms and
-# Data Structures (PADS) library, which is dedicated to the public domain (for
-# proof, see <http://www.ics.uci.edu/~eppstein/PADS/ABOUT-PADS.txt>).
-import collections
-import itertools
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from .matrix import biadjacency_matrix
-
-__all__ = [
-    "maximum_matching",
-    "hopcroft_karp_matching",
-    "eppstein_matching",
-    "to_vertex_cover",
-    "minimum_weight_full_matching",
-]
-
-INFINITY = ...
-
-def hopcroft_karp_matching(G: Graph, top_nodes=None) -> Mapping: ...
-def eppstein_matching(G: Graph, top_nodes=None) -> Mapping: ...
-def to_vertex_cover(G: Graph, matching: Mapping, top_nodes=None): ...
-
-#: Returns the maximum cardinality matching in the given bipartite graph.
-#:
-#: This function is simply an alias for :func:`hopcroft_karp_matching`.
-maximum_matching = ...
-
-def minimum_weight_full_matching(G: Graph, top_nodes=None, weight="weight") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/bipartite/matrix.pyi b/stubs/networkx/algorithms/bipartite/matrix.pyi
deleted file mode 100644
index 3f2f6ad7..00000000
--- a/stubs/networkx/algorithms/bipartite/matrix.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-import itertools
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = ["biadjacency_matrix", "from_biadjacency_matrix"]
-
-def biadjacency_matrix(
-    G: Graph,
-    row_order,
-    column_order: ArrayLike | None = None,
-    dtype=None,
-    weight="weight",
-    format="csr",
-): ...
-def from_biadjacency_matrix(A, create_using=None, edge_attribute: str = "weight"): ...
diff --git a/stubs/networkx/algorithms/bipartite/projection.pyi b/stubs/networkx/algorithms/bipartite/projection.pyi
deleted file mode 100644
index 9c9ac760..00000000
--- a/stubs/networkx/algorithms/bipartite/projection.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from collections.abc import Iterable
-
-from numpy.typing import ArrayLike
-
-from ...exception import NetworkXAlgorithmError
-from ...utils import not_implemented_for
-
-__all__ = [
-    "project",
-    "projected_graph",
-    "weighted_projected_graph",
-    "collaboration_weighted_projected_graph",
-    "overlap_weighted_projected_graph",
-    "generic_weighted_projected_graph",
-]
-
-def projected_graph(B, nodes: ArrayLike | Iterable, multigraph=False): ...
-def weighted_projected_graph(B, nodes: ArrayLike | Iterable, ratio=False): ...
-def collaboration_weighted_projected_graph(B, nodes: ArrayLike | Iterable): ...
-def overlap_weighted_projected_graph(B, nodes: ArrayLike | Iterable, jaccard=True): ...
-def generic_weighted_projected_graph(B, nodes: ArrayLike | Iterable, weight_function=None): ...
-def project(B, nodes, create_using=None): ...
diff --git a/stubs/networkx/algorithms/bipartite/redundancy.pyi b/stubs/networkx/algorithms/bipartite/redundancy.pyi
deleted file mode 100644
index b8b2957c..00000000
--- a/stubs/networkx/algorithms/bipartite/redundancy.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-from itertools import combinations
-
-from networkx import NetworkXError
-
-from ...classes.graph import Graph
-
-__all__ = ["node_redundancy"]
-
-def node_redundancy(G: Graph, nodes=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/bipartite/spectral.pyi b/stubs/networkx/algorithms/bipartite/spectral.pyi
deleted file mode 100644
index f34fb629..00000000
--- a/stubs/networkx/algorithms/bipartite/spectral.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-__all__ = ["spectral_bipartivity"]
-
-from ...classes.graph import Graph
-
-def spectral_bipartivity(G: Graph, nodes=None, weight="weight") -> float | dict: ...
diff --git a/stubs/networkx/algorithms/boundary.pyi b/stubs/networkx/algorithms/boundary.pyi
deleted file mode 100644
index ed7e4567..00000000
--- a/stubs/networkx/algorithms/boundary.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections.abc import Iterable
-from itertools import chain
-from typing import Any
-
-from ..classes.graph import Graph
-
-__all__ = ["edge_boundary", "node_boundary"]
-
-def edge_boundary(
-    G: Graph,
-    nbunch1: Iterable,
-    nbunch2: Iterable | None = None,
-    data: bool | Any = False,
-    keys: bool = False,
-    default: Any = None,
-): ...
-def node_boundary(G: Graph, nbunch1: Iterable, nbunch2: Iterable | None = None) -> set: ...
diff --git a/stubs/networkx/algorithms/bridges.pyi b/stubs/networkx/algorithms/bridges.pyi
deleted file mode 100644
index 8b706918..00000000
--- a/stubs/networkx/algorithms/bridges.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from itertools import chain
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["bridges", "has_bridges", "local_bridges"]
-
-def bridges(G: Graph, root=None): ...
-def has_bridges(G: Graph, root=None) -> bool: ...
-def local_bridges(G: Graph, with_span: bool = True, weight=None): ...
diff --git a/stubs/networkx/algorithms/centrality/__init__.pyi b/stubs/networkx/algorithms/centrality/__init__.pyi
deleted file mode 100644
index deb58992..00000000
--- a/stubs/networkx/algorithms/centrality/__init__.pyi
+++ /dev/null
@@ -1,66 +0,0 @@
-from .betweenness import (
-    betweenness_centrality as betweenness_centrality,
-    edge_betweenness as edge_betweenness,
-    edge_betweenness_centrality as edge_betweenness_centrality,
-)
-from .betweenness_subset import (
-    betweenness_centrality_source as betweenness_centrality_source,
-    betweenness_centrality_subset as betweenness_centrality_subset,
-    edge_betweenness_centrality_subset as edge_betweenness_centrality_subset,
-)
-from .closeness import (
-    closeness_centrality as closeness_centrality,
-    incremental_closeness_centrality as incremental_closeness_centrality,
-)
-from .current_flow_betweenness import (
-    approximate_current_flow_betweenness_centrality as approximate_current_flow_betweenness_centrality,
-    current_flow_betweenness_centrality as current_flow_betweenness_centrality,
-    edge_current_flow_betweenness_centrality as edge_current_flow_betweenness_centrality,
-)
-from .current_flow_betweenness_subset import (
-    current_flow_betweenness_centrality_subset as current_flow_betweenness_centrality_subset,
-    edge_current_flow_betweenness_centrality_subset as edge_current_flow_betweenness_centrality_subset,
-)
-from .current_flow_closeness import (
-    current_flow_closeness_centrality as current_flow_closeness_centrality,
-    information_centrality as information_centrality,
-)
-from .degree_alg import (
-    degree_centrality as degree_centrality,
-    in_degree_centrality as in_degree_centrality,
-    out_degree_centrality as out_degree_centrality,
-)
-from .dispersion import dispersion as dispersion
-from .eigenvector import (
-    eigenvector_centrality as eigenvector_centrality,
-    eigenvector_centrality_numpy as eigenvector_centrality_numpy,
-)
-from .group import (
-    group_betweenness_centrality as group_betweenness_centrality,
-    group_closeness_centrality as group_closeness_centrality,
-    group_degree_centrality as group_degree_centrality,
-    group_in_degree_centrality as group_in_degree_centrality,
-    group_out_degree_centrality as group_out_degree_centrality,
-    prominent_group as prominent_group,
-)
-from .harmonic import harmonic_centrality as harmonic_centrality
-from .katz import katz_centrality as katz_centrality, katz_centrality_numpy as katz_centrality_numpy
-from .load import edge_load_centrality as edge_load_centrality, load_centrality as load_centrality
-from .percolation import percolation_centrality as percolation_centrality
-from .reaching import (
-    global_reaching_centrality as global_reaching_centrality,
-    local_reaching_centrality as local_reaching_centrality,
-)
-from .second_order import second_order_centrality as second_order_centrality
-from .subgraph_alg import (
-    communicability_betweenness_centrality as communicability_betweenness_centrality,
-    estrada_index as estrada_index,
-    subgraph_centrality as subgraph_centrality,
-    subgraph_centrality_exp as subgraph_centrality_exp,
-)
-from .trophic import (
-    trophic_differences as trophic_differences,
-    trophic_incoherence_parameter as trophic_incoherence_parameter,
-    trophic_levels as trophic_levels,
-)
-from .voterank_alg import voterank as voterank
diff --git a/stubs/networkx/algorithms/centrality/betweenness.pyi b/stubs/networkx/algorithms/centrality/betweenness.pyi
deleted file mode 100644
index 5b76c540..00000000
--- a/stubs/networkx/algorithms/centrality/betweenness.pyi
+++ /dev/null
@@ -1,26 +0,0 @@
-import warnings
-from collections import deque
-from collections.abc import Mapping
-from heapq import heappop, heappush
-from itertools import count
-
-from ...classes.graph import Graph
-from ...utils import py_random_state
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["betweenness_centrality", "edge_betweenness_centrality", "edge_betweenness"]
-
-@py_random_state(5)
-def betweenness_centrality(
-    G: Graph,
-    k=None,
-    normalized: bool = True,
-    weight=None,
-    endpoints: bool = False,
-    seed=None,
-) -> Mapping: ...
-@py_random_state(4)
-def edge_betweenness_centrality(G: Graph, k=None, normalized: bool = True, weight=None, seed=None) -> Mapping: ...
-
-# obsolete name
-def edge_betweenness(G: Graph, k=None, normalized=True, weight=None, seed=None): ...
diff --git a/stubs/networkx/algorithms/centrality/betweenness_subset.pyi b/stubs/networkx/algorithms/centrality/betweenness_subset.pyi
deleted file mode 100644
index 40f42f73..00000000
--- a/stubs/networkx/algorithms/centrality/betweenness_subset.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-import warnings
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "betweenness_centrality_subset",
-    "betweenness_centrality_source",
-    "edge_betweenness_centrality_subset",
-]
-
-def betweenness_centrality_subset(G: Graph, sources, targets, normalized: bool = False, weight=None) -> Mapping: ...
-def edge_betweenness_centrality_subset(G: Graph, sources, targets, normalized: bool = False, weight=None) -> Mapping: ...
-
-# obsolete name
-def betweenness_centrality_source(G: Graph, normalized=True, weight=None, sources=None): ...
diff --git a/stubs/networkx/algorithms/centrality/closeness.pyi b/stubs/networkx/algorithms/centrality/closeness.pyi
deleted file mode 100644
index 435d1d46..00000000
--- a/stubs/networkx/algorithms/centrality/closeness.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-import functools
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...exception import NetworkXError
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["closeness_centrality", "incremental_closeness_centrality"]
-
-def closeness_centrality(G: Graph, u=None, distance=None, wf_improved=True) -> Mapping: ...
-def incremental_closeness_centrality(
-    G: Graph,
-    edge: tuple,
-    prev_cc: Mapping | None = None,
-    insertion: bool = True,
-    wf_improved=True,
-) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/current_flow_betweenness.pyi b/stubs/networkx/algorithms/centrality/current_flow_betweenness.pyi
deleted file mode 100644
index 2f61694d..00000000
--- a/stubs/networkx/algorithms/centrality/current_flow_betweenness.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, py_random_state, reverse_cuthill_mckee_ordering
-from .flow_matrix import CGInverseLaplacian, FullInverseLaplacian, SuperLUInverseLaplacian, flow_matrix_row
-
-__all__ = [
-    "current_flow_betweenness_centrality",
-    "approximate_current_flow_betweenness_centrality",
-    "edge_current_flow_betweenness_centrality",
-]
-
-@py_random_state(7)
-def approximate_current_flow_betweenness_centrality(
-    G: Graph,
-    normalized=True,
-    weight=None,
-    dtype=...,
-    solver="full",
-    epsilon: float = 0.5,
-    kmax: int = 10000,
-    seed=None,
-) -> Mapping: ...
-def current_flow_betweenness_centrality(G: Graph, normalized=True, weight=None, dtype=..., solver="full") -> Mapping: ...
-def edge_current_flow_betweenness_centrality(G: Graph, normalized=True, weight=None, dtype=..., solver="full") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/current_flow_betweenness_subset.pyi b/stubs/networkx/algorithms/centrality/current_flow_betweenness_subset.pyi
deleted file mode 100644
index 4ec8c04a..00000000
--- a/stubs/networkx/algorithms/centrality/current_flow_betweenness_subset.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, reverse_cuthill_mckee_ordering
-from .flow_matrix import flow_matrix_row
-
-__all__ = [
-    "current_flow_betweenness_centrality_subset",
-    "edge_current_flow_betweenness_centrality_subset",
-]
-
-def current_flow_betweenness_centrality_subset(
-    G: Graph, sources, targets, normalized=True, weight=None, dtype=..., solver="lu"
-) -> Mapping: ...
-def edge_current_flow_betweenness_centrality_subset(
-    G: Graph, sources, targets, normalized=True, weight=None, dtype=..., solver="lu"
-) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/current_flow_closeness.pyi b/stubs/networkx/algorithms/centrality/current_flow_closeness.pyi
deleted file mode 100644
index f92215f4..00000000
--- a/stubs/networkx/algorithms/centrality/current_flow_closeness.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, reverse_cuthill_mckee_ordering
-from .flow_matrix import CGInverseLaplacian, FullInverseLaplacian, SuperLUInverseLaplacian
-
-__all__ = ["current_flow_closeness_centrality", "information_centrality"]
-
-def current_flow_closeness_centrality(G: Graph, weight=None, dtype=..., solver="lu") -> Mapping: ...
-
-information_centrality = ...
diff --git a/stubs/networkx/algorithms/centrality/degree_alg.pyi b/stubs/networkx/algorithms/centrality/degree_alg.pyi
deleted file mode 100644
index 809aa1c5..00000000
--- a/stubs/networkx/algorithms/centrality/degree_alg.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["degree_centrality", "in_degree_centrality", "out_degree_centrality"]
-
-def degree_centrality(G: Graph) -> Mapping: ...
-def in_degree_centrality(G: Graph) -> Mapping: ...
-def out_degree_centrality(G: Graph) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/dispersion.pyi b/stubs/networkx/algorithms/centrality/dispersion.pyi
deleted file mode 100644
index e001c8f5..00000000
--- a/stubs/networkx/algorithms/centrality/dispersion.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections.abc import Mapping
-from itertools import combinations
-
-from ...classes.graph import Graph
-
-__all__ = ["dispersion"]
-
-def dispersion(G: Graph, u=None, v=None, normalized: bool = True, alpha=1.0, b=0.0, c=0.0) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/eigenvector.pyi b/stubs/networkx/algorithms/centrality/eigenvector.pyi
deleted file mode 100644
index f70c344d..00000000
--- a/stubs/networkx/algorithms/centrality/eigenvector.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-import math
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = ["eigenvector_centrality", "eigenvector_centrality_numpy"]
-
-def eigenvector_centrality(G: Graph, max_iter=100, tol=1.0e-6, nstart=None, weight=None) -> Mapping: ...
-def eigenvector_centrality_numpy(G: Graph, weight=None, max_iter=50, tol=0) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/flow_matrix.pyi b/stubs/networkx/algorithms/centrality/flow_matrix.pyi
deleted file mode 100644
index 8e9f69d3..00000000
--- a/stubs/networkx/algorithms/centrality/flow_matrix.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-# Helpers for current-flow betweenness and current-flow closness
-# Lazy computations for inverse Laplacian and flow-matrix rows.
-
-from ...classes.graph import Graph
-
-def flow_matrix_row(G: Graph, weight=None, dtype=..., solver="lu"): ...
-
-# Class to compute the inverse laplacian only for specified rows
-# Allows computation of the current-flow matrix without storing entire
-# inverse laplacian matrix
-class InverseLaplacian:
-    def __init__(self, L, width=None, dtype=None): ...
-    def init_solver(self, L): ...
-    def solve(self, r): ...
-    def solve_inverse(self, r): ...
-    def get_rows(self, r1, r2): ...
-    def get_row(self, r): ...
-    def width(self, L): ...
-
-class FullInverseLaplacian(InverseLaplacian):
-    def init_solver(self, L): ...
-    def solve(self, rhs): ...
-    def solve_inverse(self, r): ...
-
-class SuperLUInverseLaplacian(InverseLaplacian):
-    def init_solver(self, L): ...
-    def solve_inverse(self, r): ...
-    def solve(self, rhs): ...
-
-class CGInverseLaplacian(InverseLaplacian):
-    def init_solver(self, L): ...
-    def solve(self, rhs): ...
-    def solve_inverse(self, r): ...
diff --git a/stubs/networkx/algorithms/centrality/group.pyi b/stubs/networkx/algorithms/centrality/group.pyi
deleted file mode 100644
index 24435757..00000000
--- a/stubs/networkx/algorithms/centrality/group.pyi
+++ /dev/null
@@ -1,30 +0,0 @@
-from copy import deepcopy
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "group_betweenness_centrality",
-    "group_closeness_centrality",
-    "group_degree_centrality",
-    "group_in_degree_centrality",
-    "group_out_degree_centrality",
-    "prominent_group",
-]
-
-def group_betweenness_centrality(G: Graph, C, normalized=True, weight=None, endpoints=False): ...
-def prominent_group(
-    G: Graph,
-    k: int,
-    weight=None,
-    C=None,
-    endpoints=False,
-    normalized=True,
-    greedy=False,
-) -> tuple[float, ArrayLike]: ...
-def group_closeness_centrality(G: Graph, S: ArrayLike | set, weight=None) -> float: ...
-def group_degree_centrality(G: Graph, S: ArrayLike | set) -> float: ...
-def group_in_degree_centrality(G: Graph, S: ArrayLike | set) -> float: ...
-def group_out_degree_centrality(G: Graph, S: ArrayLike | set) -> float: ...
diff --git a/stubs/networkx/algorithms/centrality/harmonic.pyi b/stubs/networkx/algorithms/centrality/harmonic.pyi
deleted file mode 100644
index 4368ead2..00000000
--- a/stubs/networkx/algorithms/centrality/harmonic.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections.abc import Mapping
-from functools import partial
-
-from ...classes.graph import Graph
-
-__all__ = ["harmonic_centrality"]
-
-def harmonic_centrality(G: Graph, nbunch=None, distance=None, sources=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/katz.pyi b/stubs/networkx/algorithms/centrality/katz.pyi
deleted file mode 100644
index b35850ee..00000000
--- a/stubs/networkx/algorithms/centrality/katz.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-import math
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = ["katz_centrality", "katz_centrality_numpy"]
-
-def katz_centrality(
-    G: Graph,
-    alpha: float = 0.1,
-    beta=1.0,
-    max_iter=1000,
-    tol=1.0e-6,
-    nstart: Mapping | None = None,
-    normalized=True,
-    weight=None,
-) -> Mapping: ...
-def katz_centrality_numpy(
-    G: Graph,
-    alpha: float = 0.1,
-    beta=1.0,
-    normalized: bool = True,
-    weight: str | None = None,
-) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/load.pyi b/stubs/networkx/algorithms/centrality/load.pyi
deleted file mode 100644
index 4d9c096b..00000000
--- a/stubs/networkx/algorithms/centrality/load.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from collections.abc import Mapping
-from operator import itemgetter
-
-from ...classes.graph import Graph
-
-__all__ = ["load_centrality", "edge_load_centrality"]
-
-def newman_betweenness_centrality(G: Graph, v=None, cutoff=None, normalized=True, weight=None) -> Mapping: ...
-
-load_centrality = ...
-
-def edge_load_centrality(G: Graph, cutoff=False): ...
diff --git a/stubs/networkx/algorithms/centrality/percolation.pyi b/stubs/networkx/algorithms/centrality/percolation.pyi
deleted file mode 100644
index 5f3c3ec1..00000000
--- a/stubs/networkx/algorithms/centrality/percolation.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["percolation_centrality"]
-
-def percolation_centrality(G: Graph, attribute="percolation", states=None, weight=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/reaching.pyi b/stubs/networkx/algorithms/centrality/reaching.pyi
deleted file mode 100644
index fa3f6d9f..00000000
--- a/stubs/networkx/algorithms/centrality/reaching.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ...classes.digraph import DiGraph
-from ...classes.graph import Graph
-from ...utils import pairwise
-
-__all__ = ["global_reaching_centrality", "local_reaching_centrality"]
-
-def global_reaching_centrality(G: DiGraph, weight=None, normalized=True) -> float: ...
-def local_reaching_centrality(G: DiGraph, v, paths=None, weight=None, normalized=True) -> float: ...
diff --git a/stubs/networkx/algorithms/centrality/second_order.pyi b/stubs/networkx/algorithms/centrality/second_order.pyi
deleted file mode 100644
index 3140d0ed..00000000
--- a/stubs/networkx/algorithms/centrality/second_order.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-# Authors: Erwan Le Merrer (erwan.lemerrer@technicolor.com)
-
-__all__ = ["second_order_centrality"]
-
-def second_order_centrality(G: Graph) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/centrality/subgraph_alg.pyi b/stubs/networkx/algorithms/centrality/subgraph_alg.pyi
deleted file mode 100644
index 14d6d104..00000000
--- a/stubs/networkx/algorithms/centrality/subgraph_alg.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = [
-    "subgraph_centrality_exp",
-    "subgraph_centrality",
-    "communicability_betweenness_centrality",
-    "estrada_index",
-]
-
-def subgraph_centrality_exp(G: Graph) -> Mapping: ...
-def subgraph_centrality(G: Graph) -> Mapping: ...
-def communicability_betweenness_centrality(G: Graph) -> Mapping: ...
-def estrada_index(G: Graph) -> float: ...
diff --git a/stubs/networkx/algorithms/centrality/trophic.pyi b/stubs/networkx/algorithms/centrality/trophic.pyi
deleted file mode 100644
index a777102e..00000000
--- a/stubs/networkx/algorithms/centrality/trophic.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.digraph import DiGraph
-from ...utils import not_implemented_for
-
-__all__ = ["trophic_levels", "trophic_differences", "trophic_incoherence_parameter"]
-
-def trophic_levels(G: DiGraph, weight="weight") -> Mapping: ...
-def trophic_differences(G: DiGraph, weight="weight") -> Mapping: ...
-def trophic_incoherence_parameter(G: DiGraph, weight="weight", cannibalism: bool = False) -> float: ...
diff --git a/stubs/networkx/algorithms/centrality/voterank_alg.pyi b/stubs/networkx/algorithms/centrality/voterank_alg.pyi
deleted file mode 100644
index a9de3b73..00000000
--- a/stubs/networkx/algorithms/centrality/voterank_alg.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = ["voterank"]
-
-def voterank(G: Graph, number_of_nodes=None) -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/chains.pyi b/stubs/networkx/algorithms/chains.pyi
deleted file mode 100644
index bcd19701..00000000
--- a/stubs/networkx/algorithms/chains.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["chain_decomposition"]
-
-def chain_decomposition(G: Graph, root=None): ...
diff --git a/stubs/networkx/algorithms/chordal.pyi b/stubs/networkx/algorithms/chordal.pyi
deleted file mode 100644
index 9f0b0b35..00000000
--- a/stubs/networkx/algorithms/chordal.pyi
+++ /dev/null
@@ -1,24 +0,0 @@
-import sys
-import warnings
-
-from ..algorithms.components import connected_components
-from ..classes.graph import Graph
-from ..exception import NetworkXException
-from ..utils import arbitrary_element, not_implemented_for
-
-__all__ = [
-    "is_chordal",
-    "find_induced_nodes",
-    "chordal_graph_cliques",
-    "chordal_graph_treewidth",
-    "NetworkXTreewidthBoundExceeded",
-    "complete_to_chordal_graph",
-]
-
-class NetworkXTreewidthBoundExceeded(NetworkXException): ...
-
-def is_chordal(G: Graph) -> bool: ...
-def find_induced_nodes(G: Graph, s, t, treewidth_bound: float = ...): ...
-def chordal_graph_cliques(G: Graph): ...
-def chordal_graph_treewidth(G: Graph) -> int: ...
-def complete_to_chordal_graph(G: Graph): ...
diff --git a/stubs/networkx/algorithms/clique.pyi b/stubs/networkx/algorithms/clique.pyi
deleted file mode 100644
index 473c4109..00000000
--- a/stubs/networkx/algorithms/clique.pyi
+++ /dev/null
@@ -1,38 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "find_cliques",
-    "find_cliques_recursive",
-    "make_max_clique_graph",
-    "make_clique_bipartite",
-    "graph_clique_number",
-    "graph_number_of_cliques",
-    "node_clique_number",
-    "number_of_cliques",
-    "cliques_containing_node",
-    "enumerate_all_cliques",
-    "max_weight_clique",
-]
-
-def enumerate_all_cliques(G: Graph): ...
-def find_cliques(G: Graph, nodes=None): ...
-def find_cliques_recursive(G: Graph, nodes=None): ...
-def make_max_clique_graph(G: Graph, create_using=None): ...
-def make_clique_bipartite(G: Graph, fpos: bool | None = None, create_using=None, name=None): ...
-def graph_clique_number(G: Graph, cliques: ArrayLike | None = None) -> int: ...
-def graph_number_of_cliques(G: Graph, cliques: ArrayLike | None = None) -> int: ...
-def node_clique_number(G: Graph, nodes=None, cliques=None, separate_nodes=False) -> int | dict: ...
-def number_of_cliques(G: Graph, nodes=None, cliques=None): ...
-def cliques_containing_node(G: Graph, nodes=None, cliques=None): ...
-
-class MaxWeightClique:
-    def __init__(self, G: Graph, weight): ...
-    def update_incumbent_if_improved(self, C, C_weight): ...
-    def greedily_find_independent_set(self, P): ...
-    def find_branching_nodes(self, P, target): ...
-    def expand(self, C, C_weight, P): ...
-    def find_max_weight_clique(self): ...
-
-def max_weight_clique(G: Graph, weight="weight") -> tuple[ArrayLike, int]: ...
diff --git a/stubs/networkx/algorithms/cluster.pyi b/stubs/networkx/algorithms/cluster.pyi
deleted file mode 100644
index ce35a47a..00000000
--- a/stubs/networkx/algorithms/cluster.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from collections import Counter
-from collections.abc import Mapping
-from itertools import chain, combinations
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = [
-    "triangles",
-    "average_clustering",
-    "clustering",
-    "transitivity",
-    "square_clustering",
-    "generalized_degree",
-]
-
-def triangles(G: Graph, nodes=None) -> Mapping: ...
-def average_clustering(G: Graph, nodes=None, weight=None, count_zeros: bool = True) -> float: ...
-def clustering(G: Graph, nodes=None, weight=None) -> float | dict: ...
-def transitivity(G: Graph) -> float: ...
-def square_clustering(G: Graph, nodes=None) -> Mapping: ...
-def generalized_degree(G: Graph, nodes=None): ...
diff --git a/stubs/networkx/algorithms/coloring/__init__.pyi b/stubs/networkx/algorithms/coloring/__init__.pyi
deleted file mode 100644
index d0b7324c..00000000
--- a/stubs/networkx/algorithms/coloring/__init__.pyi
+++ /dev/null
@@ -1,2 +0,0 @@
-from .equitable_coloring import equitable_color as equitable_color
-from .greedy_coloring import greedy_color as greedy_color
diff --git a/stubs/networkx/algorithms/coloring/equitable_coloring.pyi b/stubs/networkx/algorithms/coloring/equitable_coloring.pyi
deleted file mode 100644
index 19668e3b..00000000
--- a/stubs/networkx/algorithms/coloring/equitable_coloring.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from collections import defaultdict
-
-from ...classes.graph import Graph
-
-__all__ = ["equitable_color"]
-
-def is_coloring(G: Graph, coloring): ...
-def is_equitable(G: Graph, coloring, num_colors=None): ...
-def make_C_from_F(F): ...
-def make_N_from_L_C(L, C): ...
-def make_H_from_C_N(C, N): ...
-def change_color(u, X, Y, N, H, F, C, L): ...
-def move_witnesses(src_color, dst_color, N, H, F, C, T_cal, L): ...
-def pad_graph(G: Graph, num_colors): ...
-def procedure_P(V_minus, V_plus, N, H, F, C, L, excluded_colors=None): ...
-def equitable_color(G: Graph, num_colors): ...
diff --git a/stubs/networkx/algorithms/coloring/greedy_coloring.pyi b/stubs/networkx/algorithms/coloring/greedy_coloring.pyi
deleted file mode 100644
index ea751ca7..00000000
--- a/stubs/networkx/algorithms/coloring/greedy_coloring.pyi
+++ /dev/null
@@ -1,49 +0,0 @@
-import itertools
-from collections import defaultdict, deque
-
-from ...classes.graph import Graph
-from ...utils import arbitrary_element, py_random_state
-
-__all__ = [
-    "greedy_color",
-    "strategy_connected_sequential",
-    "strategy_connected_sequential_bfs",
-    "strategy_connected_sequential_dfs",
-    "strategy_independent_set",
-    "strategy_largest_first",
-    "strategy_random_sequential",
-    "strategy_saturation_largest_first",
-    "strategy_smallest_last",
-]
-
-def strategy_largest_first(G: Graph, colors): ...
-@py_random_state(2)
-def strategy_random_sequential(G: Graph, colors, seed=None): ...
-def strategy_smallest_last(G: Graph, colors): ...
-def strategy_independent_set(G: Graph, colors): ...
-def strategy_connected_sequential_bfs(G: Graph, colors): ...
-def strategy_connected_sequential_dfs(G: Graph, colors): ...
-def strategy_connected_sequential(G: Graph, colors, traversal="bfs"): ...
-def strategy_saturation_largest_first(G: Graph, colors): ...
-
-#: Dictionary mapping name of a strategy as a string to the strategy function.
-STRATEGIES: dict = ...
-
-def greedy_color(G: Graph, strategy="largest_first", interchange: bool = False): ...
-
-# Tools for coloring with interchanges
-class _Node:
-    __slots__: list = ...
-
-    def __init__(self, node_id, n): ...
-    def __repr__(self): ...
-    def assign_color(self, adj_entry, color): ...
-    def clear_color(self, adj_entry, color): ...
-    def iter_neighbors(self): ...
-    def iter_neighbors_color(self, color): ...
-
-class _AdjEntry:
-    __slots__: list = ...
-
-    def __init__(self, node_id): ...
-    def __repr__(self): ...
diff --git a/stubs/networkx/algorithms/communicability_alg.pyi b/stubs/networkx/algorithms/communicability_alg.pyi
deleted file mode 100644
index ca3f2eba..00000000
--- a/stubs/networkx/algorithms/communicability_alg.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from collections.abc import Mapping
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["communicability", "communicability_exp"]
-
-def communicability(G: Graph) -> dict[dict, dict]: ...
-def communicability_exp(G: Graph) -> dict[dict, dict]: ...
diff --git a/stubs/networkx/algorithms/community/__init__.pyi b/stubs/networkx/algorithms/community/__init__.pyi
deleted file mode 100644
index fd1d0c64..00000000
--- a/stubs/networkx/algorithms/community/__init__.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from networkx.algorithms.community.asyn_fluid import *
-from networkx.algorithms.community.centrality import *
-from networkx.algorithms.community.community_utils import *
-from networkx.algorithms.community.divisive import *
-from networkx.algorithms.community.kclique import *
-from networkx.algorithms.community.kernighan_lin import *
-from networkx.algorithms.community.label_propagation import *
-from networkx.algorithms.community.louvain import *
-from networkx.algorithms.community.lukes import *
-from networkx.algorithms.community.modularity_max import *
-from networkx.algorithms.community.quality import *
diff --git a/stubs/networkx/algorithms/community/asyn_fluid.pyi b/stubs/networkx/algorithms/community/asyn_fluid.pyi
deleted file mode 100644
index f6da7844..00000000
--- a/stubs/networkx/algorithms/community/asyn_fluid.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from collections import Counter
-from collections.abc import Iterable
-
-from ...algorithms.components import is_connected
-from ...classes.graph import Graph
-from ...exception import NetworkXError
-from ...utils import groups, not_implemented_for, py_random_state
-
-__all__ = ["asyn_fluidc"]
-
-@py_random_state(3)
-def asyn_fluidc(G: Graph, k, max_iter=100, seed=None) -> Iterable: ...
diff --git a/stubs/networkx/algorithms/community/centrality.pyi b/stubs/networkx/algorithms/community/centrality.pyi
deleted file mode 100644
index 019bcbfe..00000000
--- a/stubs/networkx/algorithms/community/centrality.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["girvan_newman"]
-
-def girvan_newman(G: Graph, most_valuable_edge=None): ...
diff --git a/stubs/networkx/algorithms/community/community_utils.pyi b/stubs/networkx/algorithms/community/community_utils.pyi
deleted file mode 100644
index ce2aae2d..00000000
--- a/stubs/networkx/algorithms/community/community_utils.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["is_partition"]
-
-def is_partition(G: Graph, communities): ...
diff --git a/stubs/networkx/algorithms/community/divisive.pyi b/stubs/networkx/algorithms/community/divisive.pyi
deleted file mode 100644
index c39616aa..00000000
--- a/stubs/networkx/algorithms/community/divisive.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["edge_betweenness_partition", "edge_current_flow_betweenness_partition"]
-
-def edge_betweenness_partition(G: Graph, number_of_sets: int, *, weight: str | None = None) -> list: ...
-def edge_current_flow_betweenness_partition(G: Graph, number_of_sets: int, *, weight: str | None = None) -> list: ...
diff --git a/stubs/networkx/algorithms/community/kclique.pyi b/stubs/networkx/algorithms/community/kclique.pyi
deleted file mode 100644
index 4afb1fcd..00000000
--- a/stubs/networkx/algorithms/community/kclique.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from collections import defaultdict
-
-from ...classes.graph import Graph
-
-__all__ = ["k_clique_communities"]
-
-def k_clique_communities(G: Graph, k: int, cliques=None): ...
diff --git a/stubs/networkx/algorithms/community/kernighan_lin.pyi b/stubs/networkx/algorithms/community/kernighan_lin.pyi
deleted file mode 100644
index d58b6b2f..00000000
--- a/stubs/networkx/algorithms/community/kernighan_lin.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from itertools import count
-
-from ...classes.graph import Graph
-from ...utils import BinaryHeap, not_implemented_for, py_random_state
-from .community_utils import is_partition
-
-__all__ = ["kernighan_lin_bisection"]
-
-@py_random_state(4)
-def kernighan_lin_bisection(
-    G: Graph,
-    partition: tuple | None = None,
-    max_iter: int = 10,
-    weight="weight",
-    seed=None,
-) -> tuple: ...
diff --git a/stubs/networkx/algorithms/community/label_propagation.pyi b/stubs/networkx/algorithms/community/label_propagation.pyi
deleted file mode 100644
index 5ed1beac..00000000
--- a/stubs/networkx/algorithms/community/label_propagation.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections import Counter, defaultdict
-from collections.abc import Iterable
-
-from ...classes.graph import Graph
-from ...utils import groups, not_implemented_for, py_random_state
-
-__all__ = ["label_propagation_communities", "asyn_lpa_communities"]
-
-@py_random_state(2)
-def asyn_lpa_communities(G: Graph, weight: str | None = None, seed=None) -> Iterable: ...
-def label_propagation_communities(G: Graph) -> Iterable: ...
diff --git a/stubs/networkx/algorithms/community/louvain.pyi b/stubs/networkx/algorithms/community/louvain.pyi
deleted file mode 100644
index b38b90a5..00000000
--- a/stubs/networkx/algorithms/community/louvain.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from collections import defaultdict, deque
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import py_random_state
-
-__all__ = ["louvain_communities", "louvain_partitions"]
-
-@py_random_state("seed")
-def louvain_communities(G: Graph, weight="weight", resolution=1, threshold=0.0000001, seed=None) -> ArrayLike: ...
-@py_random_state("seed")
-def louvain_partitions(G: Graph, weight="weight", resolution=1, threshold=0.0000001, seed=None): ...
diff --git a/stubs/networkx/algorithms/community/lukes.pyi b/stubs/networkx/algorithms/community/lukes.pyi
deleted file mode 100644
index eec2879d..00000000
--- a/stubs/networkx/algorithms/community/lukes.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from copy import deepcopy
-from functools import lru_cache
-from random import choice
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = ["lukes_partitioning"]
-
-D_EDGE_W: str = ...
-D_EDGE_VALUE: float = ...
-D_NODE_W: str = ...
-D_NODE_VALUE: int = ...
-PKEY: str = ...
-CLUSTER_EVAL_CACHE_SIZE: int = ...
-
-def lukes_partitioning(G: Graph, max_size: int, node_weight=None, edge_weight=None) -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/community/modularity_max.pyi b/stubs/networkx/algorithms/community/modularity_max.pyi
deleted file mode 100644
index 8e758e9f..00000000
--- a/stubs/networkx/algorithms/community/modularity_max.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from collections import defaultdict
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-from ...utils.mapped_queue import MappedQueue
-from .quality import modularity
-
-__all__ = [
-    "greedy_modularity_communities",
-    "naive_greedy_modularity_communities",
-    "_naive_greedy_modularity_communities",
-]
-
-def greedy_modularity_communities(
-    G: Graph, weight=None, resolution=1, cutoff=1, best_n=None, n_communities=None
-) -> ArrayLike: ...
-def naive_greedy_modularity_communities(G: Graph, resolution=1, weight=None) -> ArrayLike: ...
-
-# old name
-_naive_greedy_modularity_communities = ...
diff --git a/stubs/networkx/algorithms/community/quality.pyi b/stubs/networkx/algorithms/community/quality.pyi
deleted file mode 100644
index fc17f91e..00000000
--- a/stubs/networkx/algorithms/community/quality.pyi
+++ /dev/null
@@ -1,28 +0,0 @@
-from collections.abc import Callable, Sequence
-from itertools import combinations
-from typing import TypeVar
-
-from networkx import NetworkXError
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-from ...utils.decorators import argmap
-from .community_utils import is_partition
-
-__all__ = ["coverage", "modularity", "performance", "partition_quality"]
-
-class NotAPartition(NetworkXError):
-    def __init__(self, G: Graph, collection): ...
-
-require_partition: argmap
-
-def intra_community_edges(G: Graph, partition): ...
-def inter_community_edges(G: Graph, partition): ...
-def inter_community_non_edges(G: Graph, partition): ...
-@require_partition
-def performance(G: Graph, partition: Sequence) -> float: ...
-@require_partition
-def coverage(G: Graph, partition: Sequence) -> float: ...
-def modularity(G: Graph, communities, weight="weight", resolution=1) -> float: ...
-@require_partition
-def partition_quality(G: Graph, partition: Sequence): ...
diff --git a/stubs/networkx/algorithms/components/__init__.pyi b/stubs/networkx/algorithms/components/__init__.pyi
deleted file mode 100644
index e093c535..00000000
--- a/stubs/networkx/algorithms/components/__init__.pyi
+++ /dev/null
@@ -1,31 +0,0 @@
-from .attracting import (
-    attracting_components as attracting_components,
-    is_attracting_component as is_attracting_component,
-    number_attracting_components as number_attracting_components,
-)
-from .biconnected import (
-    articulation_points as articulation_points,
-    biconnected_component_edges as biconnected_component_edges,
-    biconnected_components as biconnected_components,
-    is_biconnected as is_biconnected,
-)
-from .connected import (
-    connected_components as connected_components,
-    is_connected as is_connected,
-    node_connected_component as node_connected_component,
-    number_connected_components as number_connected_components,
-)
-from .semiconnected import is_semiconnected as is_semiconnected
-from .strongly_connected import (
-    condensation as condensation,
-    is_strongly_connected as is_strongly_connected,
-    kosaraju_strongly_connected_components as kosaraju_strongly_connected_components,
-    number_strongly_connected_components as number_strongly_connected_components,
-    strongly_connected_components as strongly_connected_components,
-    strongly_connected_components_recursive as strongly_connected_components_recursive,
-)
-from .weakly_connected import (
-    is_weakly_connected as is_weakly_connected,
-    number_weakly_connected_components as number_weakly_connected_components,
-    weakly_connected_components as weakly_connected_components,
-)
diff --git a/stubs/networkx/algorithms/components/attracting.pyi b/stubs/networkx/algorithms/components/attracting.pyi
deleted file mode 100644
index edb3570f..00000000
--- a/stubs/networkx/algorithms/components/attracting.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from ...classes.digraph import DiGraph
-from ...classes.multidigraph import MultiDiGraph
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "number_attracting_components",
-    "attracting_components",
-    "is_attracting_component",
-]
-
-def attracting_components(G: DiGraph | MultiDiGraph): ...
-def number_attracting_components(G: DiGraph | MultiDiGraph) -> int: ...
-def is_attracting_component(G: DiGraph | MultiDiGraph) -> bool: ...
diff --git a/stubs/networkx/algorithms/components/biconnected.pyi b/stubs/networkx/algorithms/components/biconnected.pyi
deleted file mode 100644
index 5e352749..00000000
--- a/stubs/networkx/algorithms/components/biconnected.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from itertools import chain
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "biconnected_components",
-    "biconnected_component_edges",
-    "is_biconnected",
-    "articulation_points",
-]
-
-def is_biconnected(G: Graph) -> bool: ...
-def biconnected_component_edges(G: Graph): ...
-def biconnected_components(G: Graph): ...
-def articulation_points(G: Graph): ...
diff --git a/stubs/networkx/algorithms/components/connected.pyi b/stubs/networkx/algorithms/components/connected.pyi
deleted file mode 100644
index b22156da..00000000
--- a/stubs/networkx/algorithms/components/connected.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-from ...classes.graph import Graph
-from ...utils import arbitrary_element
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "number_connected_components",
-    "connected_components",
-    "is_connected",
-    "node_connected_component",
-]
-
-def connected_components(G: Graph): ...
-def number_connected_components(G: Graph): ...
-def is_connected(G: Graph) -> bool: ...
-def node_connected_component(G: Graph, n) -> set: ...
diff --git a/stubs/networkx/algorithms/components/semiconnected.pyi b/stubs/networkx/algorithms/components/semiconnected.pyi
deleted file mode 100644
index 5f9b6588..00000000
--- a/stubs/networkx/algorithms/components/semiconnected.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, pairwise
-
-__all__ = ["is_semiconnected"]
-
-def is_semiconnected(G: Graph, topo_order: ArrayLike | tuple | None = None) -> bool: ...
diff --git a/stubs/networkx/algorithms/components/strongly_connected.pyi b/stubs/networkx/algorithms/components/strongly_connected.pyi
deleted file mode 100644
index ce5293dd..00000000
--- a/stubs/networkx/algorithms/components/strongly_connected.pyi
+++ /dev/null
@@ -1,18 +0,0 @@
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "number_strongly_connected_components",
-    "strongly_connected_components",
-    "is_strongly_connected",
-    "strongly_connected_components_recursive",
-    "kosaraju_strongly_connected_components",
-    "condensation",
-]
-
-def strongly_connected_components(G: Graph): ...
-def kosaraju_strongly_connected_components(G: Graph, source=None): ...
-def strongly_connected_components_recursive(G: Graph): ...
-def number_strongly_connected_components(G: Graph): ...
-def is_strongly_connected(G: Graph) -> bool: ...
-def condensation(G: Graph, scc=None): ...
diff --git a/stubs/networkx/algorithms/components/weakly_connected.pyi b/stubs/networkx/algorithms/components/weakly_connected.pyi
deleted file mode 100644
index 70f328c8..00000000
--- a/stubs/networkx/algorithms/components/weakly_connected.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = [
-    "number_weakly_connected_components",
-    "weakly_connected_components",
-    "is_weakly_connected",
-]
-
-def weakly_connected_components(G: Graph): ...
-def number_weakly_connected_components(G: Graph): ...
-def is_weakly_connected(G: Graph) -> bool: ...
diff --git a/stubs/networkx/algorithms/connectivity/__init__.pyi b/stubs/networkx/algorithms/connectivity/__init__.pyi
deleted file mode 100644
index 1ce81f84..00000000
--- a/stubs/networkx/algorithms/connectivity/__init__.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-from .connectivity import (
-    all_pairs_node_connectivity as all_pairs_node_connectivity,
-    average_node_connectivity as average_node_connectivity,
-    edge_connectivity as edge_connectivity,
-    local_edge_connectivity as local_edge_connectivity,
-    local_node_connectivity as local_node_connectivity,
-    node_connectivity as node_connectivity,
-)
-from .cuts import (
-    minimum_edge_cut as minimum_edge_cut,
-    minimum_node_cut as minimum_node_cut,
-    minimum_st_edge_cut as minimum_st_edge_cut,
-    minimum_st_node_cut as minimum_st_node_cut,
-)
-from .disjoint_paths import edge_disjoint_paths as edge_disjoint_paths, node_disjoint_paths as node_disjoint_paths
-from .edge_augmentation import (
-    is_k_edge_connected as is_k_edge_connected,
-    is_locally_k_edge_connected as is_locally_k_edge_connected,
-    k_edge_augmentation as k_edge_augmentation,
-)
-from .edge_kcomponents import (
-    EdgeComponentAuxGraph as EdgeComponentAuxGraph,
-    bridge_components as bridge_components,
-    k_edge_components as k_edge_components,
-    k_edge_subgraphs as k_edge_subgraphs,
-)
-from .kcomponents import k_components as k_components
-from .kcutsets import all_node_cuts as all_node_cuts
-from .stoerwagner import stoer_wagner as stoer_wagner
-from .utils import (
-    build_auxiliary_edge_connectivity as build_auxiliary_edge_connectivity,
-    build_auxiliary_node_connectivity as build_auxiliary_node_connectivity,
-)
diff --git a/stubs/networkx/algorithms/connectivity/connectivity.pyi b/stubs/networkx/algorithms/connectivity/connectivity.pyi
deleted file mode 100644
index 67f1a6a8..00000000
--- a/stubs/networkx/algorithms/connectivity/connectivity.pyi
+++ /dev/null
@@ -1,27 +0,0 @@
-import itertools
-from collections.abc import Mapping
-from operator import itemgetter
-
-# Define the default maximum flow function to use in all flow based
-# connectivity algorithms.
-from ...algorithms.flow import boykov_kolmogorov, build_residual_network, dinitz, edmonds_karp, shortest_augmenting_path
-from ...classes.graph import Graph
-from .utils import build_auxiliary_edge_connectivity, build_auxiliary_node_connectivity
-
-default_flow_func = ...
-
-__all__ = [
-    "average_node_connectivity",
-    "local_node_connectivity",
-    "node_connectivity",
-    "local_edge_connectivity",
-    "edge_connectivity",
-    "all_pairs_node_connectivity",
-]
-
-def local_node_connectivity(G: Graph, s, t, flow_func=None, auxiliary=None, residual=None, cutoff=None): ...
-def node_connectivity(G: Graph, s=None, t=None, flow_func=None): ...
-def average_node_connectivity(G: Graph, flow_func=None) -> float: ...
-def all_pairs_node_connectivity(G: Graph, nbunch=None, flow_func=None) -> Mapping: ...
-def local_edge_connectivity(G: Graph, s, t, flow_func=None, auxiliary=None, residual=None, cutoff=None): ...
-def edge_connectivity(G: Graph, s=None, t=None, flow_func=None, cutoff=None): ...
diff --git a/stubs/networkx/algorithms/connectivity/cuts.pyi b/stubs/networkx/algorithms/connectivity/cuts.pyi
deleted file mode 100644
index 1bf3dde7..00000000
--- a/stubs/networkx/algorithms/connectivity/cuts.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-import itertools
-
-# Define the default maximum flow function to use in all flow based
-# cut algorithms.
-from ...algorithms.flow import build_residual_network, edmonds_karp
-from ...classes.graph import Graph
-from .utils import build_auxiliary_edge_connectivity, build_auxiliary_node_connectivity
-
-default_flow_func = ...
-
-__all__ = [
-    "minimum_st_node_cut",
-    "minimum_node_cut",
-    "minimum_st_edge_cut",
-    "minimum_edge_cut",
-]
-
-def minimum_st_edge_cut(G: Graph, s, t, flow_func=None, auxiliary=None, residual=None) -> set: ...
-def minimum_st_node_cut(G: Graph, s, t, flow_func=None, auxiliary=None, residual=None) -> set: ...
-def minimum_node_cut(G: Graph, s=None, t=None, flow_func=None) -> set: ...
-def minimum_edge_cut(G: Graph, s=None, t=None, flow_func=None) -> set: ...
diff --git a/stubs/networkx/algorithms/connectivity/disjoint_paths.pyi b/stubs/networkx/algorithms/connectivity/disjoint_paths.pyi
deleted file mode 100644
index e51a3ce6..00000000
--- a/stubs/networkx/algorithms/connectivity/disjoint_paths.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-# Define the default maximum flow function to use for the undelying
-# maximum flow computations
-from itertools import filterfalse as _filterfalse
-
-from ...algorithms.flow import edmonds_karp, preflow_push, shortest_augmenting_path
-from ...classes.graph import Graph
-from ...exception import NetworkXNoPath
-
-# Functions to build auxiliary data structures.
-from .utils import build_auxiliary_edge_connectivity, build_auxiliary_node_connectivity
-
-default_flow_func = ...
-
-__all__ = ["edge_disjoint_paths", "node_disjoint_paths"]
-
-def edge_disjoint_paths(
-    G: Graph,
-    s,
-    t,
-    flow_func=None,
-    cutoff: int | None = None,
-    auxiliary=None,
-    residual=None,
-): ...
-def node_disjoint_paths(
-    G: Graph,
-    s,
-    t,
-    flow_func=None,
-    cutoff: int | None = None,
-    auxiliary=None,
-    residual=None,
-): ...
diff --git a/stubs/networkx/algorithms/connectivity/edge_augmentation.pyi b/stubs/networkx/algorithms/connectivity/edge_augmentation.pyi
deleted file mode 100644
index a635a33a..00000000
--- a/stubs/networkx/algorithms/connectivity/edge_augmentation.pyi
+++ /dev/null
@@ -1,28 +0,0 @@
-import itertools as it
-import math
-from collections import defaultdict, namedtuple
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for, py_random_state
-
-__all__ = ["k_edge_augmentation", "is_k_edge_connected", "is_locally_k_edge_connected"]
-
-def is_k_edge_connected(G: Graph, k) -> bool: ...
-def is_locally_k_edge_connected(G: Graph, s, t, k) -> bool: ...
-def k_edge_augmentation(G: Graph, k, avail=None, weight: str | None = None, partial: bool = False): ...
-def partial_k_edge_augmentation(G: Graph, k, avail, weight: str | None = None): ...
-def one_edge_augmentation(G: Graph, avail=None, weight: str | None = None, partial: bool = False): ...
-def bridge_augmentation(G: Graph, avail=None, weight: str | None = None): ...
-
-# --- Algorithms and Helpers ---
-
-MetaEdge = ...
-
-def unconstrained_one_edge_augmentation(G: Graph): ...
-def weighted_one_edge_augmentation(G: Graph, avail, weight: str | None = None, partial: bool = False): ...
-def unconstrained_bridge_augmentation(G: Graph): ...
-def weighted_bridge_augmentation(G: Graph, avail, weight: str | None = None): ...
-def collapse(G: Graph, grouped_nodes): ...
-def complement_edges(G: Graph): ...
-@py_random_state(4)
-def greedy_k_edge_augmentation(G: Graph, k, avail=None, weight: str | None = None, seed=None): ...
diff --git a/stubs/networkx/algorithms/connectivity/edge_kcomponents.pyi b/stubs/networkx/algorithms/connectivity/edge_kcomponents.pyi
deleted file mode 100644
index 76b85319..00000000
--- a/stubs/networkx/algorithms/connectivity/edge_kcomponents.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-import itertools as it
-from functools import partial
-
-from ...algorithms import bridges
-from ...classes.graph import Graph
-from ...utils import arbitrary_element, not_implemented_for
-
-__all__ = [
-    "k_edge_components",
-    "k_edge_subgraphs",
-    "bridge_components",
-    "EdgeComponentAuxGraph",
-]
-
-def k_edge_components(G: Graph, k): ...
-def k_edge_subgraphs(G: Graph, k): ...
-def bridge_components(G: Graph): ...
-
-class EdgeComponentAuxGraph:
-    @classmethod
-    def construct(cls, G: Graph): ...
-    def k_edge_components(self, k): ...
-    def k_edge_subgraphs(self, k): ...
-
-def general_k_edge_subgraphs(G: Graph, k): ...
diff --git a/stubs/networkx/algorithms/connectivity/kcomponents.pyi b/stubs/networkx/algorithms/connectivity/kcomponents.pyi
deleted file mode 100644
index 01751f99..00000000
--- a/stubs/networkx/algorithms/connectivity/kcomponents.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-from itertools import combinations
-from operator import itemgetter
-
-# Define the default maximum flow function.
-from ...algorithms.flow import edmonds_karp
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-default_flow_func = ...
-
-__all__ = ["k_components"]
-
-def k_components(G: Graph, flow_func=None) -> Mapping: ...
-def build_k_number_dict(kcomps): ...
diff --git a/stubs/networkx/algorithms/connectivity/kcutsets.pyi b/stubs/networkx/algorithms/connectivity/kcutsets.pyi
deleted file mode 100644
index b44fb207..00000000
--- a/stubs/networkx/algorithms/connectivity/kcutsets.pyi
+++ /dev/null
@@ -1,14 +0,0 @@
-import copy
-from collections import defaultdict
-from itertools import combinations
-from operator import itemgetter
-
-from ...algorithms.flow import build_residual_network, edmonds_karp, shortest_augmenting_path
-from ...classes.graph import Graph
-from .utils import build_auxiliary_node_connectivity
-
-default_flow_func = ...
-
-__all__ = ["all_node_cuts"]
-
-def all_node_cuts(G: Graph, k=None, flow_func=None): ...
diff --git a/stubs/networkx/algorithms/connectivity/stoerwagner.pyi b/stubs/networkx/algorithms/connectivity/stoerwagner.pyi
deleted file mode 100644
index 36eef474..00000000
--- a/stubs/networkx/algorithms/connectivity/stoerwagner.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from itertools import islice
-
-from ...classes.graph import Graph
-from ...utils import BinaryHeap, arbitrary_element, not_implemented_for
-
-__all__ = ["stoer_wagner"]
-
-def stoer_wagner(G: Graph, weight: str = "weight", heap=...): ...
diff --git a/stubs/networkx/algorithms/connectivity/utils.pyi b/stubs/networkx/algorithms/connectivity/utils.pyi
deleted file mode 100644
index cc69d6c6..00000000
--- a/stubs/networkx/algorithms/connectivity/utils.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["build_auxiliary_node_connectivity", "build_auxiliary_edge_connectivity"]
-
-def build_auxiliary_node_connectivity(G: Graph): ...
-def build_auxiliary_edge_connectivity(G: Graph): ...
diff --git a/stubs/networkx/algorithms/core.pyi b/stubs/networkx/algorithms/core.pyi
deleted file mode 100644
index dba7cfc7..00000000
--- a/stubs/networkx/algorithms/core.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-from collections.abc import Mapping
-
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..utils import not_implemented_for
-
-__all__ = [
-    "core_number",
-    "find_cores",
-    "k_core",
-    "k_shell",
-    "k_crust",
-    "k_corona",
-    "k_truss",
-    "onion_layers",
-]
-
-def core_number(G: Graph) -> Mapping: ...
-def find_cores(G: Graph): ...
-def k_core(G: Graph, k: int | None = None, core_number: Mapping | None = None): ...
-def k_shell(G: Graph, k: int | None = None, core_number: Mapping | None = None): ...
-def k_crust(G: Graph, k: int | None = None, core_number: Mapping | None = None): ...
-def k_corona(G: Graph, k: int, core_number: Mapping | None = None): ...
-def k_truss(G: Graph, k: int): ...
-def onion_layers(G: Graph) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/covering.pyi b/stubs/networkx/algorithms/covering.pyi
deleted file mode 100644
index b72c02f1..00000000
--- a/stubs/networkx/algorithms/covering.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from functools import partial
-from itertools import chain
-
-from ..classes.graph import Graph
-from ..utils import arbitrary_element, not_implemented_for
-
-__all__ = ["min_edge_cover", "is_edge_cover"]
-
-def min_edge_cover(G: Graph, matching_algorithm=None) -> set: ...
-def is_edge_cover(G: Graph, cover: set) -> bool: ...
diff --git a/stubs/networkx/algorithms/cuts.pyi b/stubs/networkx/algorithms/cuts.pyi
deleted file mode 100644
index 7e4951a4..00000000
--- a/stubs/networkx/algorithms/cuts.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from typing import Any
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "boundary_expansion",
-    "conductance",
-    "cut_size",
-    "edge_expansion",
-    "mixing_expansion",
-    "node_expansion",
-    "normalized_cut_size",
-    "volume",
-]
-
-def cut_size(G: Graph, S, T=None, weight: Any = None): ...
-def volume(G: Graph, S, weight: Any = None): ...
-def normalized_cut_size(G: Graph, S, T=None, weight: Any = None): ...
-def conductance(G: Graph, S, T=None, weight: Any = None): ...
-def edge_expansion(G: Graph, S, T=None, weight: Any = None): ...
-def mixing_expansion(G: Graph, S, T=None, weight: Any = None): ...
-def node_expansion(G: Graph, S): ...
-def boundary_expansion(G: Graph, S): ...
diff --git a/stubs/networkx/algorithms/cycles.pyi b/stubs/networkx/algorithms/cycles.pyi
deleted file mode 100644
index f663de73..00000000
--- a/stubs/networkx/algorithms/cycles.pyi
+++ /dev/null
@@ -1,18 +0,0 @@
-from collections import defaultdict
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, pairwise
-
-__all__ = [
-    "cycle_basis",
-    "simple_cycles",
-    "recursive_simple_cycles",
-    "find_cycle",
-    "minimum_cycle_basis",
-]
-
-def cycle_basis(G: Graph, root=None): ...
-def simple_cycles(G: Graph): ...
-def recursive_simple_cycles(G: Graph): ...
-def find_cycle(G: Graph, source=None, orientation=None): ...
-def minimum_cycle_basis(G: Graph, weight: str | None = None): ...
diff --git a/stubs/networkx/algorithms/d_separation.pyi b/stubs/networkx/algorithms/d_separation.pyi
deleted file mode 100644
index c9b7a774..00000000
--- a/stubs/networkx/algorithms/d_separation.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections import deque
-
-from ..classes.graph import Graph
-from ..utils import UnionFind, not_implemented_for
-
-__all__ = ["d_separated"]
-
-def d_separated(G: Graph, x: set, y: set, z: set) -> bool: ...
diff --git a/stubs/networkx/algorithms/dag.pyi b/stubs/networkx/algorithms/dag.pyi
deleted file mode 100644
index fac38ead..00000000
--- a/stubs/networkx/algorithms/dag.pyi
+++ /dev/null
@@ -1,54 +0,0 @@
-import heapq
-from collections import deque
-from functools import partial
-from itertools import chain, product, starmap
-from math import gcd
-
-from numpy.typing import ArrayLike
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..utils import arbitrary_element, not_implemented_for, pairwise
-
-__all__ = [
-    "descendants",
-    "ancestors",
-    "topological_sort",
-    "lexicographical_topological_sort",
-    "all_topological_sorts",
-    "topological_generations",
-    "is_directed_acyclic_graph",
-    "is_aperiodic",
-    "transitive_closure",
-    "transitive_closure_dag",
-    "transitive_reduction",
-    "antichains",
-    "dag_longest_path",
-    "dag_longest_path_length",
-    "dag_to_branching",
-]
-
-chaini = ...
-
-def descendants(G: Graph, source): ...
-def ancestors(G: Graph, source): ...
-def has_cycle(G: Graph): ...
-def is_directed_acyclic_graph(G: Graph) -> bool: ...
-def topological_generations(G: Graph): ...
-def topological_sort(G: Graph): ...
-def lexicographical_topological_sort(G: Graph, key=None): ...
-def all_topological_sorts(G: Graph): ...
-def is_aperiodic(G: Graph) -> bool: ...
-def transitive_closure(G: Graph, reflexive=False): ...
-def transitive_closure_dag(G: Graph, topo_order: ArrayLike | tuple | None = None): ...
-def transitive_reduction(G: Graph): ...
-def antichains(G: Graph, topo_order: ArrayLike | tuple | None = None): ...
-def dag_longest_path(
-    G: Graph,
-    weight: str = "weight",
-    default_weight: int = 1,
-    topo_order: ArrayLike | tuple | None = None,
-) -> ArrayLike: ...
-def dag_longest_path_length(G: Graph, weight: str = "weight", default_weight: int = 1) -> int: ...
-def root_to_leaf_paths(G: Graph): ...
-def dag_to_branching(G: Graph) -> DiGraph: ...
diff --git a/stubs/networkx/algorithms/distance_measures.pyi b/stubs/networkx/algorithms/distance_measures.pyi
deleted file mode 100644
index f33fe690..00000000
--- a/stubs/networkx/algorithms/distance_measures.pyi
+++ /dev/null
@@ -1,26 +0,0 @@
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = [
-    "extrema_bounding",
-    "eccentricity",
-    "diameter",
-    "radius",
-    "periphery",
-    "center",
-    "barycenter",
-    "resistance_distance",
-]
-
-def extrema_bounding(G: Graph, compute="diameter"): ...
-def eccentricity(G: Graph, v=None, sp=None) -> Mapping: ...
-def diameter(G: Graph, e=None, usebounds=False): ...
-def periphery(G: Graph, e=None, usebounds=False) -> ArrayLike: ...
-def radius(G: Graph, e=None, usebounds=False): ...
-def center(G: Graph, e=None, usebounds=False) -> ArrayLike: ...
-def barycenter(G: Graph, weight=None, attr=None, sp=None) -> ArrayLike: ...
-def resistance_distance(G: Graph, nodeA, nodeB, weight=None, invert_weight=True) -> float: ...
diff --git a/stubs/networkx/algorithms/distance_regular.pyi b/stubs/networkx/algorithms/distance_regular.pyi
deleted file mode 100644
index 6e0d25c0..00000000
--- a/stubs/networkx/algorithms/distance_regular.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections.abc import Iterable
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "is_distance_regular",
-    "is_strongly_regular",
-    "intersection_array",
-    "global_parameters",
-]
-
-def is_distance_regular(G: Graph) -> bool: ...
-def global_parameters(b: ArrayLike, c: ArrayLike) -> Iterable: ...
-def intersection_array(G: Graph): ...
-def is_strongly_regular(G: Graph) -> bool: ...
diff --git a/stubs/networkx/algorithms/dominance.pyi b/stubs/networkx/algorithms/dominance.pyi
deleted file mode 100644
index 4be6cb49..00000000
--- a/stubs/networkx/algorithms/dominance.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from functools import reduce
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["immediate_dominators", "dominance_frontiers"]
-
-def immediate_dominators(G: Graph, start): ...
-def dominance_frontiers(G: Graph, start): ...
diff --git a/stubs/networkx/algorithms/dominating.pyi b/stubs/networkx/algorithms/dominating.pyi
deleted file mode 100644
index d47abb00..00000000
--- a/stubs/networkx/algorithms/dominating.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Iterable
-from itertools import chain
-
-from ..classes.graph import Graph
-from ..utils import arbitrary_element
-
-__all__ = ["dominating_set", "is_dominating_set"]
-
-def dominating_set(G: Graph, start_with=None) -> set: ...
-def is_dominating_set(G: Graph, nbunch: Iterable): ...
diff --git a/stubs/networkx/algorithms/efficiency_measures.pyi b/stubs/networkx/algorithms/efficiency_measures.pyi
deleted file mode 100644
index df808234..00000000
--- a/stubs/networkx/algorithms/efficiency_measures.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from ..classes.graph import Graph
-from ..exception import NetworkXNoPath
-from ..utils import not_implemented_for
-
-__all__ = ["efficiency", "local_efficiency", "global_efficiency"]
-
-def efficiency(G: Graph, u, v) -> float: ...
-def global_efficiency(G: Graph) -> float: ...
-def local_efficiency(G: Graph) -> float: ...
diff --git a/stubs/networkx/algorithms/euler.pyi b/stubs/networkx/algorithms/euler.pyi
deleted file mode 100644
index cbc9f83c..00000000
--- a/stubs/networkx/algorithms/euler.pyi
+++ /dev/null
@@ -1,20 +0,0 @@
-from itertools import combinations
-
-from ..classes.graph import Graph
-from ..utils import arbitrary_element, not_implemented_for
-
-__all__ = [
-    "is_eulerian",
-    "eulerian_circuit",
-    "eulerize",
-    "is_semieulerian",
-    "has_eulerian_path",
-    "eulerian_path",
-]
-
-def is_eulerian(G: Graph): ...
-def is_semieulerian(G: Graph): ...
-def eulerian_circuit(G: Graph, source=None, keys: bool = False): ...
-def has_eulerian_path(G: Graph, source=None): ...
-def eulerian_path(G: Graph, source=None, keys=False): ...
-def eulerize(G: Graph): ...
diff --git a/stubs/networkx/algorithms/flow/__init__.pyi b/stubs/networkx/algorithms/flow/__init__.pyi
deleted file mode 100644
index 405884a8..00000000
--- a/stubs/networkx/algorithms/flow/__init__.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-from .boykovkolmogorov import boykov_kolmogorov as boykov_kolmogorov
-from .capacityscaling import capacity_scaling as capacity_scaling
-from .dinitz_alg import dinitz as dinitz
-from .edmondskarp import edmonds_karp as edmonds_karp
-from .gomory_hu import gomory_hu_tree as gomory_hu_tree
-from .maxflow import (
-    maximum_flow as maximum_flow,
-    maximum_flow_value as maximum_flow_value,
-    minimum_cut as minimum_cut,
-    minimum_cut_value as minimum_cut_value,
-)
-from .mincost import (
-    cost_of_flow as cost_of_flow,
-    max_flow_min_cost as max_flow_min_cost,
-    min_cost_flow as min_cost_flow,
-    min_cost_flow_cost as min_cost_flow_cost,
-)
-from .networksimplex import network_simplex as network_simplex
-from .preflowpush import preflow_push as preflow_push
-from .shortestaugmentingpath import shortest_augmenting_path as shortest_augmenting_path
-from .utils import build_flow_dict as build_flow_dict, build_residual_network as build_residual_network
diff --git a/stubs/networkx/algorithms/flow/boykovkolmogorov.pyi b/stubs/networkx/algorithms/flow/boykovkolmogorov.pyi
deleted file mode 100644
index dd77229f..00000000
--- a/stubs/networkx/algorithms/flow/boykovkolmogorov.pyi
+++ /dev/null
@@ -1,18 +0,0 @@
-from collections import deque
-from operator import itemgetter
-
-from ...algorithms.flow.utils import build_residual_network
-from ...classes.graph import Graph
-
-__all__ = ["boykov_kolmogorov"]
-
-def boykov_kolmogorov(
-    G: Graph,
-    s,
-    t,
-    capacity: str = "capacity",
-    residual=None,
-    value_only: bool = False,
-    cutoff=None,
-): ...
-def boykov_kolmogorov_impl(G: Graph, s, t, capacity, residual, cutoff): ...
diff --git a/stubs/networkx/algorithms/flow/capacityscaling.pyi b/stubs/networkx/algorithms/flow/capacityscaling.pyi
deleted file mode 100644
index 46a4ac90..00000000
--- a/stubs/networkx/algorithms/flow/capacityscaling.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-__all__ = ["capacity_scaling"]
-
-from itertools import chain
-from math import log
-
-from ...classes.graph import Graph
-from ...utils import BinaryHeap, arbitrary_element, not_implemented_for
-
-def capacity_scaling(
-    G: Graph,
-    demand: str = "demand",
-    capacity: str = "capacity",
-    weight: str = "weight",
-    heap=...,
-): ...
diff --git a/stubs/networkx/algorithms/flow/dinitz_alg.pyi b/stubs/networkx/algorithms/flow/dinitz_alg.pyi
deleted file mode 100644
index 5e347158..00000000
--- a/stubs/networkx/algorithms/flow/dinitz_alg.pyi
+++ /dev/null
@@ -1,18 +0,0 @@
-from collections import deque
-
-from ...algorithms.flow.utils import build_residual_network
-from ...classes.graph import Graph
-from ...utils import pairwise
-
-__all__ = ["dinitz"]
-
-def dinitz(
-    G: Graph,
-    s,
-    t,
-    capacity: str = "capacity",
-    residual=None,
-    value_only: bool = False,
-    cutoff=None,
-): ...
-def dinitz_impl(G: Graph, s, t, capacity, residual, cutoff): ...
diff --git a/stubs/networkx/algorithms/flow/edmondskarp.pyi b/stubs/networkx/algorithms/flow/edmondskarp.pyi
deleted file mode 100644
index 43e424b8..00000000
--- a/stubs/networkx/algorithms/flow/edmondskarp.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from ...algorithms.flow.utils import build_residual_network
-from ...classes.graph import Graph
-
-__all__ = ["edmonds_karp"]
-
-def edmonds_karp_core(R, s, t, cutoff): ...
-def edmonds_karp_impl(G: Graph, s, t, capacity, residual, cutoff): ...
-def edmonds_karp(
-    G: Graph,
-    s,
-    t,
-    capacity: str = "capacity",
-    residual=None,
-    value_only: bool = False,
-    cutoff=None,
-): ...
diff --git a/stubs/networkx/algorithms/flow/gomory_hu.pyi b/stubs/networkx/algorithms/flow/gomory_hu.pyi
deleted file mode 100644
index 6527385a..00000000
--- a/stubs/networkx/algorithms/flow/gomory_hu.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-from .edmondskarp import edmonds_karp
-from .utils import build_residual_network
-
-default_flow_func = ...
-
-__all__ = ["gomory_hu_tree"]
-
-def gomory_hu_tree(G: Graph, capacity: str = "capacity", flow_func=None): ...
diff --git a/stubs/networkx/algorithms/flow/maxflow.pyi b/stubs/networkx/algorithms/flow/maxflow.pyi
deleted file mode 100644
index 7fd0e379..00000000
--- a/stubs/networkx/algorithms/flow/maxflow.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from ...classes.graph import Graph
-from .boykovkolmogorov import boykov_kolmogorov
-from .dinitz_alg import dinitz
-from .edmondskarp import edmonds_karp
-from .preflowpush import preflow_push
-from .shortestaugmentingpath import shortest_augmenting_path
-from .utils import build_flow_dict
-
-# Define the default flow function for computing maximum flow.
-default_flow_func = ...
-# Functions that don't support cutoff for minimum cut computations.
-flow_funcs: list = ...
-
-__all__ = ["maximum_flow", "maximum_flow_value", "minimum_cut", "minimum_cut_value"]
-
-def maximum_flow(flowG: Graph, _s, _t, capacity: str = "capacity", flow_func=None, **kwargs): ...
-def maximum_flow_value(flowG: Graph, _s, _t, capacity: str = "capacity", flow_func=None, **kwargs): ...
-def minimum_cut(flowG: Graph, _s, _t, capacity: str = "capacity", flow_func=None, **kwargs): ...
-def minimum_cut_value(flowG: Graph, _s, _t, capacity: str = "capacity", flow_func=None, **kwargs): ...
diff --git a/stubs/networkx/algorithms/flow/mincost.pyi b/stubs/networkx/algorithms/flow/mincost.pyi
deleted file mode 100644
index 87453fa6..00000000
--- a/stubs/networkx/algorithms/flow/mincost.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["min_cost_flow_cost", "min_cost_flow", "cost_of_flow", "max_flow_min_cost"]
-
-def min_cost_flow_cost(G: Graph, demand: str = "demand", capacity: str = "capacity", weight: str = "weight"): ...
-def min_cost_flow(G: Graph, demand: str = "demand", capacity: str = "capacity", weight: str = "weight") -> Mapping: ...
-def cost_of_flow(G: Graph, flowDict: Mapping, weight: str = "weight"): ...
-def max_flow_min_cost(G: Graph, s, t, capacity: str = "capacity", weight: str = "weight") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/flow/networksimplex.pyi b/stubs/networkx/algorithms/flow/networksimplex.pyi
deleted file mode 100644
index 09c55f43..00000000
--- a/stubs/networkx/algorithms/flow/networksimplex.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-__all__ = ["network_simplex"]
-
-from itertools import chain, islice, repeat
-from math import ceil, sqrt
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-class _DataEssentialsAndFunctions:
-    def __init__(
-        self,
-        G: Graph,
-        multigraph,
-        demand="demand",
-        capacity="capacity",
-        weight="weight",
-    ): ...
-    def initialize_spanning_tree(self, n, faux_inf): ...
-    def find_apex(self, p, q): ...
-    def trace_path(self, p, w): ...
-    def find_cycle(self, i, p, q): ...
-    def augment_flow(self, Wn, We, f): ...
-    def trace_subtree(self, p): ...
-    def remove_edge(self, s, t): ...
-    def make_root(self, q): ...
-    def add_edge(self, i, p, q): ...
-    def update_potentials(self, i, p, q): ...
-    def reduced_cost(self, i): ...
-    def find_entering_edges(self): ...
-    def residual_capacity(self, i, p): ...
-    def find_leaving_edge(self, Wn, We): ...
-
-def network_simplex(G: Graph, demand: str = "demand", capacity: str = "capacity", weight: str = "weight"): ...
diff --git a/stubs/networkx/algorithms/flow/preflowpush.pyi b/stubs/networkx/algorithms/flow/preflowpush.pyi
deleted file mode 100644
index 5e1844e8..00000000
--- a/stubs/networkx/algorithms/flow/preflowpush.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from collections import deque
-from itertools import islice
-
-from ...classes.graph import Graph
-from ...utils import arbitrary_element
-from .utils import CurrentEdge, GlobalRelabelThreshold, Level, build_residual_network, detect_unboundedness
-
-__all__ = ["preflow_push"]
-
-def preflow_push_impl(G: Graph, s, t, capacity, residual, global_relabel_freq, value_only): ...
-def preflow_push(
-    G: Graph,
-    s,
-    t,
-    capacity: str = "capacity",
-    residual=None,
-    global_relabel_freq=1,
-    value_only: bool = False,
-): ...
diff --git a/stubs/networkx/algorithms/flow/shortestaugmentingpath.pyi b/stubs/networkx/algorithms/flow/shortestaugmentingpath.pyi
deleted file mode 100644
index abf9da7f..00000000
--- a/stubs/networkx/algorithms/flow/shortestaugmentingpath.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from collections import deque
-
-from ...classes.graph import Graph
-from .edmondskarp import edmonds_karp_core
-from .utils import CurrentEdge, build_residual_network
-
-__all__ = ["shortest_augmenting_path"]
-
-def shortest_augmenting_path_impl(G: Graph, s, t, capacity, residual, two_phase, cutoff): ...
-def shortest_augmenting_path(
-    G: Graph,
-    s,
-    t,
-    capacity: str = "capacity",
-    residual=None,
-    value_only: bool = False,
-    two_phase: bool = False,
-    cutoff=None,
-): ...
diff --git a/stubs/networkx/algorithms/flow/utils.pyi b/stubs/networkx/algorithms/flow/utils.pyi
deleted file mode 100644
index 5a94581c..00000000
--- a/stubs/networkx/algorithms/flow/utils.pyi
+++ /dev/null
@@ -1,35 +0,0 @@
-from collections import deque
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "CurrentEdge",
-    "Level",
-    "GlobalRelabelThreshold",
-    "build_residual_network",
-    "detect_unboundedness",
-    "build_flow_dict",
-]
-
-class CurrentEdge:
-    __slots__ = ...
-
-    def __init__(self, edges): ...
-    def get(self): ...
-    def move_to_next(self): ...
-    def _rewind(self): ...
-
-class Level:
-    __slots__ = ...
-
-    def __init__(self): ...
-
-class GlobalRelabelThreshold:
-    def __init__(self, n, m, freq): ...
-    def add_work(self, work): ...
-    def is_reached(self): ...
-    def clear_work(self): ...
-
-def build_residual_network(G: Graph, capacity): ...
-def detect_unboundedness(R, s, t): ...
-def build_flow_dict(G: Graph, R): ...
diff --git a/stubs/networkx/algorithms/graph_hashing.pyi b/stubs/networkx/algorithms/graph_hashing.pyi
deleted file mode 100644
index 7777170c..00000000
--- a/stubs/networkx/algorithms/graph_hashing.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from collections import Counter, defaultdict
-from collections.abc import Mapping
-from hashlib import blake2b
-
-from ..classes.graph import Graph
-
-__all__ = ["weisfeiler_lehman_graph_hash", "weisfeiler_lehman_subgraph_hashes"]
-
-def weisfeiler_lehman_graph_hash(
-    G: Graph,
-    edge_attr: str | None = None,
-    node_attr: str | None = None,
-    iterations: int = 3,
-    digest_size: int = 16,
-) -> str: ...
-def weisfeiler_lehman_subgraph_hashes(
-    G: Graph,
-    edge_attr: str | None = None,
-    node_attr: str | None = None,
-    iterations: int = 3,
-    digest_size: int = 16,
-) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/graphical.pyi b/stubs/networkx/algorithms/graphical.pyi
deleted file mode 100644
index a9a3e2be..00000000
--- a/stubs/networkx/algorithms/graphical.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-import heapq
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "is_graphical",
-    "is_multigraphical",
-    "is_pseudographical",
-    "is_digraphical",
-    "is_valid_degree_sequence_erdos_gallai",
-    "is_valid_degree_sequence_havel_hakimi",
-]
-
-def is_graphical(sequence, method="eg") -> bool: ...
-def is_valid_degree_sequence_havel_hakimi(deg_sequence: ArrayLike) -> bool: ...
-def is_valid_degree_sequence_erdos_gallai(deg_sequence: ArrayLike) -> bool: ...
-def is_multigraphical(sequence: ArrayLike) -> bool: ...
-def is_pseudographical(sequence) -> bool: ...
-def is_digraphical(in_sequence, out_sequence) -> bool: ...
diff --git a/stubs/networkx/algorithms/hierarchy.pyi b/stubs/networkx/algorithms/hierarchy.pyi
deleted file mode 100644
index 57824cd9..00000000
--- a/stubs/networkx/algorithms/hierarchy.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ..classes.digraph import DiGraph
-from ..classes.multidigraph import MultiDiGraph
-
-__all__ = ["flow_hierarchy"]
-
-def flow_hierarchy(G: DiGraph | MultiDiGraph, weight=None) -> float: ...
diff --git a/stubs/networkx/algorithms/hybrid.pyi b/stubs/networkx/algorithms/hybrid.pyi
deleted file mode 100644
index efb95950..00000000
--- a/stubs/networkx/algorithms/hybrid.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-import copy
-
-from ..classes.graph import Graph
-
-__all__ = ["kl_connected_subgraph", "is_kl_connected"]
-
-def kl_connected_subgraph(G: Graph, k, l, low_memory: bool = False, same_as_graph: bool = False): ...
-def is_kl_connected(G: Graph, k, l, low_memory: bool = False) -> bool: ...
diff --git a/stubs/networkx/algorithms/isolate.pyi b/stubs/networkx/algorithms/isolate.pyi
deleted file mode 100644
index 60db475a..00000000
--- a/stubs/networkx/algorithms/isolate.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes.graph import Graph
-
-__all__ = ["is_isolate", "isolates", "number_of_isolates"]
-
-def is_isolate(G: Graph, n) -> bool: ...
-def isolates(G: Graph): ...
-def number_of_isolates(G: Graph) -> int: ...
diff --git a/stubs/networkx/algorithms/isomorphism/__init__.pyi b/stubs/networkx/algorithms/isomorphism/__init__.pyi
deleted file mode 100644
index 83ccfe41..00000000
--- a/stubs/networkx/algorithms/isomorphism/__init__.pyi
+++ /dev/null
@@ -1,29 +0,0 @@
-from .ismags import ISMAGS as ISMAGS
-from .isomorph import (
-    could_be_isomorphic as could_be_isomorphic,
-    fast_could_be_isomorphic as fast_could_be_isomorphic,
-    faster_could_be_isomorphic as faster_could_be_isomorphic,
-    is_isomorphic as is_isomorphic,
-)
-from .matchhelpers import (
-    categorical_edge_match as categorical_edge_match,
-    categorical_multiedge_match as categorical_multiedge_match,
-    categorical_node_match as categorical_node_match,
-    generic_edge_match as generic_edge_match,
-    generic_multiedge_match as generic_multiedge_match,
-    generic_node_match as generic_node_match,
-    numerical_edge_match as numerical_edge_match,
-    numerical_multiedge_match as numerical_multiedge_match,
-    numerical_node_match as numerical_node_match,
-)
-from .temporalisomorphvf2 import (
-    TimeRespectingDiGraphMatcher as TimeRespectingDiGraphMatcher,
-    TimeRespectingGraphMatcher as TimeRespectingGraphMatcher,
-)
-from .tree_isomorphism import rooted_tree_isomorphism as rooted_tree_isomorphism, tree_isomorphism as tree_isomorphism
-from .vf2userfunc import (
-    DiGraphMatcher as DiGraphMatcher,
-    GraphMatcher as GraphMatcher,
-    MultiDiGraphMatcher as MultiDiGraphMatcher,
-    MultiGraphMatcher as MultiGraphMatcher,
-)
diff --git a/stubs/networkx/algorithms/isomorphism/ismags.pyi b/stubs/networkx/algorithms/isomorphism/ismags.pyi
deleted file mode 100644
index af69cdac..00000000
--- a/stubs/networkx/algorithms/isomorphism/ismags.pyi
+++ /dev/null
@@ -1,95 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["ISMAGS"]
-
-import itertools
-from collections import Counter, defaultdict
-from functools import reduce, wraps
-
-def are_all_equal(iterable) -> bool: ...
-def make_partitions(items, test): ...
-def partition_to_color(partitions) -> Mapping: ...
-def intersect(collection_of_sets) -> set: ...
-
-class ISMAGS:
-    def __init__(
-        self,
-        graph: Graph,
-        subgraph: Graph,
-        node_match=None,
-        edge_match=None,
-        cache=None,
-    ): ...
-    @property
-    def _sgn_partitions(self): ...
-    @property
-    def _sge_partitions(self): ...
-    @property
-    def _gn_partitions(self): ...
-    @property
-    def _ge_partitions(self): ...
-    @property
-    def _sgn_colors(self): ...
-    @property
-    def _sge_colors(self): ...
-    @property
-    def _gn_colors(self): ...
-    @property
-    def _ge_colors(self): ...
-    @property
-    def _node_compatibility(self): ...
-    @property
-    def _edge_compatibility(self): ...
-    @staticmethod
-    def _node_match_maker(cmp): ...
-    @staticmethod
-    def _edge_match_maker(cmp): ...
-    def find_isomorphisms(self, symmetry: bool = True): ...
-    @staticmethod
-    def _find_neighbor_color_count(graph, node, node_color, edge_color): ...
-    def _get_lookahead_candidates(self): ...
-    def largest_common_subgraph(self, symmetry: bool = True): ...
-    def analyze_symmetry(self, graph: Graph, node_partitions, edge_colors): ...
-    def is_isomorphic(self, symmetry=False) -> bool: ...
-    def subgraph_is_isomorphic(self, symmetry=False) -> bool: ...
-    def isomorphisms_iter(self, symmetry=True): ...
-    def subgraph_isomorphisms_iter(self, symmetry=True): ...
-    def _find_nodecolor_candidates(self): ...
-    @staticmethod
-    def _make_constraints(cosets): ...
-    @staticmethod
-    def _find_node_edge_color(graph, node_colors, edge_colors): ...
-    @staticmethod
-    def _get_permutations_by_length(items): ...
-    @classmethod
-    def _refine_node_partitions(cls, graph, node_partitions, edge_colors, branch=False): ...
-    def _edges_of_same_color(self, sgn1, sgn2): ...
-    def _map_nodes(self, sgn, candidates, constraints, mapping=None, to_be_mapped=None): ...
-    def _largest_common_subgraph(self, candidates, constraints, to_be_mapped=None): ...
-    @staticmethod
-    def _remove_node(node, nodes, constraints): ...
-    @staticmethod
-    def _find_permutations(top_partitions, bottom_partitions): ...
-    @staticmethod
-    def _update_orbits(orbits, permutations): ...
-    def _couple_nodes(
-        self,
-        top_partitions,
-        bottom_partitions,
-        pair_idx,
-        t_node,
-        b_node,
-        graph,
-        edge_colors,
-    ): ...
-    def _process_ordered_pair_partitions(
-        self,
-        graph,
-        top_partitions,
-        bottom_partitions,
-        edge_colors,
-        orbits=None,
-        cosets=None,
-    ): ...
diff --git a/stubs/networkx/algorithms/isomorphism/isomorph.pyi b/stubs/networkx/algorithms/isomorphism/isomorph.pyi
deleted file mode 100644
index b4f51af3..00000000
--- a/stubs/networkx/algorithms/isomorphism/isomorph.pyi
+++ /dev/null
@@ -1,30 +0,0 @@
-from typing import Callable
-
-from ...classes.graph import Graph
-from ...exception import NetworkXError
-
-__all__ = [
-    "could_be_isomorphic",
-    "fast_could_be_isomorphic",
-    "faster_could_be_isomorphic",
-    "is_isomorphic",
-]
-
-def could_be_isomorphic(G1: Graph, G2: Graph): ...
-
-graph_could_be_isomorphic = ...
-
-def fast_could_be_isomorphic(G1: Graph, G2: Graph): ...
-
-fast_graph_could_be_isomorphic = ...
-
-def faster_could_be_isomorphic(G1: Graph, G2: Graph): ...
-
-faster_graph_could_be_isomorphic = ...
-
-def is_isomorphic(
-    G1: Graph,
-    G2: Graph,
-    node_match: Callable | None = None,
-    edge_match: Callable | None = None,
-): ...
diff --git a/stubs/networkx/algorithms/isomorphism/isomorphvf2.pyi b/stubs/networkx/algorithms/isomorphism/isomorphvf2.pyi
deleted file mode 100644
index d6e8752a..00000000
--- a/stubs/networkx/algorithms/isomorphism/isomorphvf2.pyi
+++ /dev/null
@@ -1,45 +0,0 @@
-# This work was originally coded by Christopher Ellison
-# as part of the Computational Mechanics Python (CMPy) project.
-# James P. Crutchfield, principal investigator.
-# Complexity Sciences Center and Physics Department, UC Davis.
-
-import sys
-
-from ...classes.graph import Graph
-
-__all__ = ["GraphMatcher", "DiGraphMatcher"]
-
-class GraphMatcher:
-    def __init__(self, G1: Graph, G2: Graph): ...
-    def reset_recursion_limit(self): ...
-    def candidate_pairs_iter(self): ...
-    def initialize(self): ...
-    def is_isomorphic(self): ...
-    def isomorphisms_iter(self): ...
-    def match(self): ...
-    def semantic_feasibility(self, G1_node, G2_node): ...
-    def subgraph_is_isomorphic(self): ...
-    def subgraph_is_monomorphic(self): ...
-
-    #    subgraph_is_isomorphic.__doc__ += "\n" + subgraph.replace('\n','\n'+indent)
-
-    def subgraph_isomorphisms_iter(self): ...
-    def subgraph_monomorphisms_iter(self): ...
-
-    #    subgraph_isomorphisms_iter.__doc__ += "\n" + subgraph.replace('\n','\n'+indent)
-
-    def syntactic_feasibility(self, G1_node, G2_node): ...
-
-class DiGraphMatcher(GraphMatcher):
-    def __init__(self, G1: Graph, G2: Graph): ...
-    def candidate_pairs_iter(self): ...
-    def initialize(self): ...
-    def syntactic_feasibility(self, G1_node, G2_node): ...
-
-class GMState:
-    def __init__(self, GM, G1_node=None, G2_node=None): ...
-    def restore(self): ...
-
-class DiGMState:
-    def __init__(self, GM, G1_node=None, G2_node=None): ...
-    def restore(self): ...
diff --git a/stubs/networkx/algorithms/isomorphism/matchhelpers.pyi b/stubs/networkx/algorithms/isomorphism/matchhelpers.pyi
deleted file mode 100644
index 5a2cbe08..00000000
--- a/stubs/networkx/algorithms/isomorphism/matchhelpers.pyi
+++ /dev/null
@@ -1,63 +0,0 @@
-import math
-import types
-from itertools import permutations
-from typing import Callable
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "categorical_node_match",
-    "categorical_edge_match",
-    "categorical_multiedge_match",
-    "numerical_node_match",
-    "numerical_edge_match",
-    "numerical_multiedge_match",
-    "generic_node_match",
-    "generic_edge_match",
-    "generic_multiedge_match",
-]
-
-def copyfunc(f, name=None): ...
-def allclose(x, y, rtol: float = ..., atol: float = 1e-08): ...
-
-categorical_doc: str = ...
-
-def categorical_node_match(attr: str | ArrayLike, default): ...
-
-categorical_edge_match = ...
-
-def categorical_multiedge_match(attr: str | ArrayLike, default): ...
-
-# Docstrings for categorical functions.
-tmpdoc = ...
-
-numerical_doc: str = ...
-
-def numerical_node_match(
-    attr: str | ArrayLike,
-    default,
-    rtol: float = ...,
-    atol: float = 1e-08,
-): ...
-
-numerical_edge_match = ...
-
-def numerical_multiedge_match(
-    attr: str | ArrayLike,
-    default,
-    rtol: float = ...,
-    atol: float = 1e-08,
-): ...
-
-# Docstrings for numerical functions.
-tmpdoc = ...
-
-generic_doc: str = ...
-
-def generic_node_match(attr: str | ArrayLike, default, op: ArrayLike | Callable): ...
-
-generic_edge_match = ...
-
-def generic_multiedge_match(attr: str | ArrayLike, default, op: ArrayLike | Callable): ...
diff --git a/stubs/networkx/algorithms/isomorphism/temporalisomorphvf2.pyi b/stubs/networkx/algorithms/isomorphism/temporalisomorphvf2.pyi
deleted file mode 100644
index 969e35de..00000000
--- a/stubs/networkx/algorithms/isomorphism/temporalisomorphvf2.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from ...classes.graph import Graph
-from .isomorphvf2 import DiGraphMatcher, GraphMatcher
-
-__all__ = ["TimeRespectingGraphMatcher", "TimeRespectingDiGraphMatcher"]
-
-class TimeRespectingGraphMatcher(GraphMatcher):
-    def __init__(self, G1: Graph, G2: Graph, temporal_attribute_name, delta): ...
-    def one_hop(self, Gx, Gx_node, neighbors): ...
-    def two_hop(self, Gx, core_x, Gx_node, neighbors): ...
-    def semantic_feasibility(self, G1_node, G2_node): ...
-
-class TimeRespectingDiGraphMatcher(DiGraphMatcher):
-    def __init__(self, G1: Graph, G2: Graph, temporal_attribute_name, delta): ...
-    def get_pred_dates(self, Gx, Gx_node, core_x, pred): ...
-    def get_succ_dates(self, Gx, Gx_node, core_x, succ): ...
-    def one_hop(self, Gx, Gx_node, core_x, pred, succ): ...
-    def two_hop_pred(self, Gx, Gx_node, core_x, pred): ...
-    def two_hop_succ(self, Gx, Gx_node, core_x, succ): ...
-    def preds(self, Gx, core_x, v, Gx_node=None): ...
-    def succs(self, Gx, core_x, v, Gx_node=None): ...
-    def test_one(self, pred_dates, succ_dates): ...
-    def test_two(self, pred_dates, succ_dates): ...
-    def semantic_feasibility(self, G1_node, G2_node): ...
diff --git a/stubs/networkx/algorithms/isomorphism/tree_isomorphism.pyi b/stubs/networkx/algorithms/isomorphism/tree_isomorphism.pyi
deleted file mode 100644
index bf754a1f..00000000
--- a/stubs/networkx/algorithms/isomorphism/tree_isomorphism.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["rooted_tree_isomorphism", "tree_isomorphism"]
-
-def root_trees(t1, root1, t2, root2): ...
-
-# figure out the level of each node, with 0 at root
-def assign_levels(G: Graph, root): ...
-
-# now group the nodes at each level
-def group_by_levels(levels): ...
-
-# now lets get the isomorphism by walking the ordered_children
-def generate_isomorphism(v, w, M, ordered_children): ...
-def rooted_tree_isomorphism(t1, root1, t2, root2) -> ArrayLike: ...
-def tree_isomorphism(t1, t2) -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/isomorphism/vf2userfunc.pyi b/stubs/networkx/algorithms/isomorphism/vf2userfunc.pyi
deleted file mode 100644
index 69552a04..00000000
--- a/stubs/networkx/algorithms/isomorphism/vf2userfunc.pyi
+++ /dev/null
@@ -1,34 +0,0 @@
-from typing import Callable
-
-from ...classes.graph import Graph
-from . import isomorphvf2 as vf2
-
-__all__ = ["GraphMatcher", "DiGraphMatcher", "MultiGraphMatcher", "MultiDiGraphMatcher"]
-
-class GraphMatcher(vf2.GraphMatcher):
-    def __init__(
-        self,
-        G1: Graph,
-        G2: Graph,
-        node_match: Callable | None = None,
-        edge_match: Callable | None = None,
-    ): ...
-
-    semantic_feasibility = ...
-
-class DiGraphMatcher(vf2.DiGraphMatcher):
-    def __init__(
-        self,
-        G1: Graph,
-        G2: Graph,
-        node_match: Callable | None = None,
-        edge_match: Callable | None = None,
-    ): ...
-    def semantic_feasibility(self, G1_node, G2_node): ...
-
-# The "semantics" of edge_match are different for multi(di)graphs, but
-# the implementation is the same.  So, technically we do not need to
-# provide "multi" versions, but we do so to match NetworkX's base classes.
-
-class MultiGraphMatcher(GraphMatcher): ...
-class MultiDiGraphMatcher(DiGraphMatcher): ...
diff --git a/stubs/networkx/algorithms/link_analysis/__init__.pyi b/stubs/networkx/algorithms/link_analysis/__init__.pyi
deleted file mode 100644
index ff7c4952..00000000
--- a/stubs/networkx/algorithms/link_analysis/__init__.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from ...algorithms.link_analysis.hits_alg import (
-    authority_matrix as authority_matrix,
-    hits as hits,
-    hits_numpy as hits_numpy,
-    hits_scipy as hits_scipy,
-    hub_matrix as hub_matrix,
-)
-from ...algorithms.link_analysis.pagerank_alg import (
-    google_matrix as google_matrix,
-    pagerank as pagerank,
-    pagerank_numpy as pagerank_numpy,
-    pagerank_scipy as pagerank_scipy,
-)
diff --git a/stubs/networkx/algorithms/link_analysis/hits_alg.pyi b/stubs/networkx/algorithms/link_analysis/hits_alg.pyi
deleted file mode 100644
index ae1b7344..00000000
--- a/stubs/networkx/algorithms/link_analysis/hits_alg.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["hits", "hits_numpy", "hits_scipy", "authority_matrix", "hub_matrix"]
-
-def hits(
-    G: Graph,
-    max_iter=100,
-    tol: float = 1.0e-8,
-    nstart: Mapping | None = None,
-    normalized=True,
-): ...
-def authority_matrix(G: Graph, nodelist=None): ...
-def hub_matrix(G: Graph, nodelist=None): ...
-def hits_numpy(G: Graph, normalized=True): ...
-def hits_scipy(
-    G: Graph,
-    max_iter=100,
-    tol: float = 1.0e-6,
-    nstart: Mapping | None = None,
-    normalized=True,
-): ...
diff --git a/stubs/networkx/algorithms/link_analysis/pagerank_alg.pyi b/stubs/networkx/algorithms/link_analysis/pagerank_alg.pyi
deleted file mode 100644
index 65ff7cca..00000000
--- a/stubs/networkx/algorithms/link_analysis/pagerank_alg.pyi
+++ /dev/null
@@ -1,44 +0,0 @@
-from collections.abc import Mapping
-from warnings import warn
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = ["pagerank", "pagerank_numpy", "pagerank_scipy", "google_matrix"]
-
-def pagerank(
-    G: Graph,
-    alpha: float = 0.85,
-    personalization: Mapping | None = None,
-    max_iter=100,
-    tol: float = 1.0e-6,
-    nstart: Mapping | None = None,
-    weight="weight",
-    dangling: Mapping | None = None,
-) -> Mapping: ...
-def google_matrix(
-    G: Graph,
-    alpha: float = 0.85,
-    personalization: Mapping | None = None,
-    nodelist: ArrayLike | None = None,
-    weight="weight",
-    dangling: Mapping | None = None,
-): ...
-def pagerank_numpy(
-    G: Graph,
-    alpha: float = 0.85,
-    personalization: Mapping | None = None,
-    weight="weight",
-    dangling: Mapping | None = None,
-) -> Mapping: ...
-def pagerank_scipy(
-    G: Graph,
-    alpha: float = 0.85,
-    personalization: Mapping | None = None,
-    max_iter=100,
-    tol: float = 1.0e-6,
-    nstart: Mapping | None = None,
-    weight="weight",
-    dangling: Mapping | None = None,
-) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/link_prediction.pyi b/stubs/networkx/algorithms/link_prediction.pyi
deleted file mode 100644
index 1f0e01e3..00000000
--- a/stubs/networkx/algorithms/link_prediction.pyi
+++ /dev/null
@@ -1,24 +0,0 @@
-from math import log
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = [
-    "resource_allocation_index",
-    "jaccard_coefficient",
-    "adamic_adar_index",
-    "preferential_attachment",
-    "cn_soundarajan_hopcroft",
-    "ra_index_soundarajan_hopcroft",
-    "within_inter_cluster",
-    "common_neighbor_centrality",
-]
-
-def resource_allocation_index(G: Graph, ebunch=None): ...
-def jaccard_coefficient(G: Graph, ebunch=None): ...
-def adamic_adar_index(G: Graph, ebunch=None): ...
-def common_neighbor_centrality(G: Graph, ebunch=None, alpha=0.8): ...
-def preferential_attachment(G: Graph, ebunch=None): ...
-def cn_soundarajan_hopcroft(G: Graph, ebunch=None, community="community"): ...
-def ra_index_soundarajan_hopcroft(G: Graph, ebunch=None, community="community"): ...
-def within_inter_cluster(G: Graph, ebunch=None, delta=0.001, community="community"): ...
diff --git a/stubs/networkx/algorithms/lowest_common_ancestors.pyi b/stubs/networkx/algorithms/lowest_common_ancestors.pyi
deleted file mode 100644
index 840e6729..00000000
--- a/stubs/networkx/algorithms/lowest_common_ancestors.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping, Set as AbstractSet
-from itertools import combinations_with_replacement
-from typing import Any
-
-from ..classes.graph import Graph
-from ..utils import UnionFind, arbitrary_element, not_implemented_for
-
-__all__ = [
-    "all_pairs_lowest_common_ancestor",
-    "tree_all_pairs_lowest_common_ancestor",
-    "lowest_common_ancestor",
-]
-
-def all_pairs_lowest_common_ancestor(G: Graph, pairs=None): ...
-def lowest_common_ancestor(G: Graph, node1, node2, default: Any = None): ...
-def tree_all_pairs_lowest_common_ancestor(G: Graph, root=None, pairs=None): ...
diff --git a/stubs/networkx/algorithms/matching.pyi b/stubs/networkx/algorithms/matching.pyi
deleted file mode 100644
index 795a0965..00000000
--- a/stubs/networkx/algorithms/matching.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from collections import Counter
-from collections.abc import Mapping
-from itertools import combinations, repeat
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = [
-    "is_matching",
-    "is_maximal_matching",
-    "is_perfect_matching",
-    "max_weight_matching",
-    "min_weight_matching",
-    "maximal_matching",
-]
-
-def maximal_matching(G: Graph) -> set: ...
-def matching_dict_to_set(matching): ...
-def is_matching(G: Graph, matching: Mapping | set) -> bool: ...
-def is_maximal_matching(G: Graph, matching: Mapping | set) -> bool: ...
-def is_perfect_matching(G: Graph, matching: Mapping | set) -> bool: ...
-def min_weight_matching(G: Graph, maxcardinality: bool | None = None, weight="weight") -> set: ...
-def max_weight_matching(G: Graph, maxcardinality=False, weight="weight") -> set: ...
diff --git a/stubs/networkx/algorithms/minors/__init__.pyi b/stubs/networkx/algorithms/minors/__init__.pyi
deleted file mode 100644
index 5ea777b3..00000000
--- a/stubs/networkx/algorithms/minors/__init__.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ...algorithms.minors.contraction import (
-    contracted_edge as contracted_edge,
-    contracted_nodes as contracted_nodes,
-    equivalence_classes as equivalence_classes,
-    identified_nodes as identified_nodes,
-    quotient_graph as quotient_graph,
-)
diff --git a/stubs/networkx/algorithms/minors/contraction.pyi b/stubs/networkx/algorithms/minors/contraction.pyi
deleted file mode 100644
index 0099f884..00000000
--- a/stubs/networkx/algorithms/minors/contraction.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-from itertools import chain, combinations, permutations, product
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...exception import NetworkXException
-from ...utils import arbitrary_element
-
-__all__ = [
-    "contracted_edge",
-    "contracted_nodes",
-    "equivalence_classes",
-    "identified_nodes",
-    "quotient_graph",
-]
-
-chaini = ...
-
-def equivalence_classes(iterable: ArrayLike | tuple | set, relation): ...
-def quotient_graph(
-    G: Graph,
-    partition,
-    edge_relation=None,
-    node_data=None,
-    edge_data=None,
-    relabel: bool = False,
-    create_using=None,
-): ...
-def contracted_nodes(G: Graph, u, v, self_loops: bool = True, copy: bool = True): ...
-
-identified_nodes = ...
-
-def contracted_edge(G: Graph, edge: tuple, self_loops: bool = True, copy=True): ...
diff --git a/stubs/networkx/algorithms/mis.pyi b/stubs/networkx/algorithms/mis.pyi
deleted file mode 100644
index 66e15c9c..00000000
--- a/stubs/networkx/algorithms/mis.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections.abc import Iterable
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, py_random_state
-
-__all__ = ["maximal_independent_set"]
-
-@py_random_state(2)
-def maximal_independent_set(G: Graph, nodes: ArrayLike | Iterable | None = None, seed=None) -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/moral.pyi b/stubs/networkx/algorithms/moral.pyi
deleted file mode 100644
index bc8b7e18..00000000
--- a/stubs/networkx/algorithms/moral.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-import itertools
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["moral_graph"]
-
-def moral_graph(G: Graph): ...
diff --git a/stubs/networkx/algorithms/node_classification/__init__.pyi b/stubs/networkx/algorithms/node_classification/__init__.pyi
deleted file mode 100644
index 3dda347a..00000000
--- a/stubs/networkx/algorithms/node_classification/__init__.pyi
+++ /dev/null
@@ -1,2 +0,0 @@
-from .hmn import harmonic_function as harmonic_function
-from .lgc import local_and_global_consistency as local_and_global_consistency
diff --git a/stubs/networkx/algorithms/node_classification/hmn.pyi b/stubs/networkx/algorithms/node_classification/hmn.pyi
deleted file mode 100644
index c0c483ba..00000000
--- a/stubs/networkx/algorithms/node_classification/hmn.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["harmonic_function"]
-
-def harmonic_function(G: Graph, max_iter: int = 30, label_name: str = "label") -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/node_classification/lgc.pyi b/stubs/networkx/algorithms/node_classification/lgc.pyi
deleted file mode 100644
index 34ab3fea..00000000
--- a/stubs/networkx/algorithms/node_classification/lgc.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["local_and_global_consistency"]
-
-def local_and_global_consistency(G: Graph, alpha: float = 0.99, max_iter: int = 30, label_name: str = "label") -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/node_classification/utils.pyi b/stubs/networkx/algorithms/node_classification/utils.pyi
deleted file mode 100644
index 38d8c0f0..00000000
--- a/stubs/networkx/algorithms/node_classification/utils.pyi
+++ /dev/null
@@ -1 +0,0 @@
-from ...classes.graph import Graph
diff --git a/stubs/networkx/algorithms/non_randomness.pyi b/stubs/networkx/algorithms/non_randomness.pyi
deleted file mode 100644
index 8f84a93f..00000000
--- a/stubs/networkx/algorithms/non_randomness.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-import math
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["non_randomness"]
-
-def non_randomness(G: Graph, k: int | None = None, weight="weight"): ...
diff --git a/stubs/networkx/algorithms/operators/__init__.pyi b/stubs/networkx/algorithms/operators/__init__.pyi
deleted file mode 100644
index fd5db7bc..00000000
--- a/stubs/networkx/algorithms/operators/__init__.pyi
+++ /dev/null
@@ -1,24 +0,0 @@
-from .all import (
-    compose_all as compose_all,
-    disjoint_union_all as disjoint_union_all,
-    intersection_all as intersection_all,
-    union_all as union_all,
-)
-from .binary import (
-    compose as compose,
-    difference as difference,
-    disjoint_union as disjoint_union,
-    full_join as full_join,
-    intersection as intersection,
-    symmetric_difference as symmetric_difference,
-    union as union,
-)
-from .product import (
-    cartesian_product as cartesian_product,
-    lexicographic_product as lexicographic_product,
-    power as power,
-    rooted_product as rooted_product,
-    strong_product as strong_product,
-    tensor_product as tensor_product,
-)
-from .unary import complement as complement, reverse as reverse
diff --git a/stubs/networkx/algorithms/operators/all.pyi b/stubs/networkx/algorithms/operators/all.pyi
deleted file mode 100644
index be40d292..00000000
--- a/stubs/networkx/algorithms/operators/all.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from itertools import zip_longest
-
-from numpy.typing import ArrayLike
-
-__all__ = ["union_all", "compose_all", "disjoint_union_all", "intersection_all"]
-
-def union_all(graphs, rename: bool = ...): ...
-def disjoint_union_all(graphs: ArrayLike): ...
-def compose_all(graphs: ArrayLike): ...
-def intersection_all(graphs: ArrayLike): ...
diff --git a/stubs/networkx/algorithms/operators/binary.pyi b/stubs/networkx/algorithms/operators/binary.pyi
deleted file mode 100644
index 31d25f48..00000000
--- a/stubs/networkx/algorithms/operators/binary.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = [
-    "union",
-    "compose",
-    "disjoint_union",
-    "intersection",
-    "difference",
-    "symmetric_difference",
-    "full_join",
-]
-
-def union(G: Graph, H, rename: tuple = ..., name: str | None = None): ...
-def disjoint_union(G: Graph, H): ...
-def intersection(G: Graph, H): ...
-def difference(G: Graph, H): ...
-def symmetric_difference(G: Graph, H): ...
-def compose(G: Graph, H): ...
-def full_join(G: Graph, H, rename: tuple = ...): ...
diff --git a/stubs/networkx/algorithms/operators/product.pyi b/stubs/networkx/algorithms/operators/product.pyi
deleted file mode 100644
index 7e426e72..00000000
--- a/stubs/networkx/algorithms/operators/product.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from itertools import product
-
-from ...classes.graph import Graph
-from ...utils import not_implemented_for
-
-__all__ = [
-    "tensor_product",
-    "cartesian_product",
-    "lexicographic_product",
-    "strong_product",
-    "power",
-    "rooted_product",
-]
-
-# Generators for producting graph products
-
-def tensor_product(G: Graph, H): ...
-def cartesian_product(G: Graph, H): ...
-def lexicographic_product(G: Graph, H): ...
-def strong_product(G: Graph, H): ...
-def power(G: Graph, k): ...
-def rooted_product(G: Graph, H, root): ...
diff --git a/stubs/networkx/algorithms/operators/unary.pyi b/stubs/networkx/algorithms/operators/unary.pyi
deleted file mode 100644
index d1e265c2..00000000
--- a/stubs/networkx/algorithms/operators/unary.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["complement", "reverse"]
-
-def complement(G: Graph): ...
-def reverse(G: Graph, copy: bool = True): ...
diff --git a/stubs/networkx/algorithms/planar_drawing.pyi b/stubs/networkx/algorithms/planar_drawing.pyi
deleted file mode 100644
index 9af7f867..00000000
--- a/stubs/networkx/algorithms/planar_drawing.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = ["combinatorial_embedding_to_pos"]
-
-def combinatorial_embedding_to_pos(embedding, fully_triangulate: bool = False) -> Mapping: ...
-def set_position(parent, tree, remaining_nodes, delta_x, y_coordinate, pos): ...
-def get_canonical_ordering(embedding, outer_face: ArrayLike) -> ArrayLike: ...
-def triangulate_face(embedding, v1, v2): ...
-def triangulate_embedding(embedding, fully_triangulate: bool = True): ...
-def make_bi_connected(embedding, starting_node, outgoing_node, edges_counted: set) -> ArrayLike: ...
diff --git a/stubs/networkx/algorithms/planarity.pyi b/stubs/networkx/algorithms/planarity.pyi
deleted file mode 100644
index b1d05e0e..00000000
--- a/stubs/networkx/algorithms/planarity.pyi
+++ /dev/null
@@ -1,58 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-
-__all__ = ["check_planarity", "is_planar", "PlanarEmbedding"]
-
-def is_planar(G: Graph) -> bool: ...
-def check_planarity(G: Graph, counterexample: bool = False): ...
-def check_planarity_recursive(G: Graph, counterexample=False): ...
-def get_counterexample(G: Graph): ...
-def get_counterexample_recursive(G: Graph): ...
-
-class Interval:
-    def __init__(self, low=None, high=None): ...
-    def empty(self): ...
-    def copy(self): ...
-    def conflicting(self, b, planarity_state): ...
-
-class ConflictPair:
-    def __init__(self, left=..., right=...): ...
-    def swap(self): ...
-    def lowest(self, planarity_state): ...
-
-def top_of_stack(l): ...
-
-class LRPlanarity:
-    __slots__: list = ...
-
-    def __init__(self, G): ...
-    def lr_planarity(self) -> Mapping: ...
-    def lr_planarity_recursive(self): ...
-    def dfs_orientation(self, v): ...
-    def dfs_orientation_recursive(self, v): ...
-    def dfs_testing(self, v): ...
-    def dfs_testing_recursive(self, v): ...
-    def add_constraints(self, ei, e): ...
-    def remove_back_edges(self, e): ...
-    def dfs_embedding(self, v): ...
-    def dfs_embedding_recursive(self, v): ...
-    def sign(self, e): ...
-    def sign_recursive(self, e): ...
-
-class PlanarEmbedding(DiGraph):
-    def get_data(self) -> Mapping: ...
-    def set_data(self, data: Mapping): ...
-    def neighbors_cw_order(self, v): ...
-    def check_structure(self): ...
-    def add_half_edge_ccw(self, start_node, end_node, reference_neighbor): ...
-    def add_half_edge_cw(self, start_node, end_node, reference_neighbor): ...
-    def connect_components(self, v, w): ...
-    def add_half_edge_first(self, start_node, end_node): ...
-    def next_face_half_edge(self, v, w) -> tuple: ...
-    def traverse_face(self, v, w, mark_half_edges: set | None = None) -> ArrayLike: ...
-    def is_directed(self): ...
diff --git a/stubs/networkx/algorithms/polynomials.pyi b/stubs/networkx/algorithms/polynomials.pyi
deleted file mode 100644
index 24e4a7ba..00000000
--- a/stubs/networkx/algorithms/polynomials.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from collections import deque
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["tutte_polynomial", "chromatic_polynomial"]
-
-def tutte_polynomial(G: Graph): ...
-def chromatic_polynomial(G: Graph): ...
diff --git a/stubs/networkx/algorithms/reciprocity.pyi b/stubs/networkx/algorithms/reciprocity.pyi
deleted file mode 100644
index 3966f04c..00000000
--- a/stubs/networkx/algorithms/reciprocity.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections.abc import Mapping
-
-from networkx import NetworkXError
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["reciprocity", "overall_reciprocity"]
-
-def reciprocity(G: Graph, nodes=None) -> Mapping: ...
-def overall_reciprocity(G: Graph): ...
diff --git a/stubs/networkx/algorithms/regular.pyi b/stubs/networkx/algorithms/regular.pyi
deleted file mode 100644
index 71c9b657..00000000
--- a/stubs/networkx/algorithms/regular.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["is_regular", "is_k_regular", "k_factor"]
-
-def is_regular(G: Graph) -> bool: ...
-def is_k_regular(G: Graph, k) -> bool: ...
-def k_factor(G: Graph, k, matching_weight="weight"): ...
diff --git a/stubs/networkx/algorithms/richclub.pyi b/stubs/networkx/algorithms/richclub.pyi
deleted file mode 100644
index 957209e3..00000000
--- a/stubs/networkx/algorithms/richclub.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from collections.abc import Mapping
-from itertools import accumulate
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["rich_club_coefficient"]
-
-def rich_club_coefficient(G: Graph, normalized=True, Q=100, seed=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/shortest_paths/__init__.pyi b/stubs/networkx/algorithms/shortest_paths/__init__.pyi
deleted file mode 100644
index 293fe213..00000000
--- a/stubs/networkx/algorithms/shortest_paths/__init__.pyi
+++ /dev/null
@@ -1,51 +0,0 @@
-from .astar import astar_path as astar_path, astar_path_length as astar_path_length
-from .dense import (
-    floyd_warshall as floyd_warshall,
-    floyd_warshall_numpy as floyd_warshall_numpy,
-    floyd_warshall_predecessor_and_distance as floyd_warshall_predecessor_and_distance,
-    reconstruct_path as reconstruct_path,
-)
-from .generic import (
-    all_shortest_paths as all_shortest_paths,
-    average_shortest_path_length as average_shortest_path_length,
-    has_path as has_path,
-    shortest_path as shortest_path,
-    shortest_path_length as shortest_path_length,
-)
-from .unweighted import (
-    all_pairs_shortest_path as all_pairs_shortest_path,
-    all_pairs_shortest_path_length as all_pairs_shortest_path_length,
-    bidirectional_shortest_path as bidirectional_shortest_path,
-    predecessor as predecessor,
-    single_source_shortest_path as single_source_shortest_path,
-    single_source_shortest_path_length as single_source_shortest_path_length,
-    single_target_shortest_path as single_target_shortest_path,
-    single_target_shortest_path_length as single_target_shortest_path_length,
-)
-from .weighted import (
-    all_pairs_bellman_ford_path as all_pairs_bellman_ford_path,
-    all_pairs_bellman_ford_path_length as all_pairs_bellman_ford_path_length,
-    all_pairs_dijkstra as all_pairs_dijkstra,
-    all_pairs_dijkstra_path as all_pairs_dijkstra_path,
-    all_pairs_dijkstra_path_length as all_pairs_dijkstra_path_length,
-    bellman_ford_path as bellman_ford_path,
-    bellman_ford_path_length as bellman_ford_path_length,
-    bellman_ford_predecessor_and_distance as bellman_ford_predecessor_and_distance,
-    bidirectional_dijkstra as bidirectional_dijkstra,
-    dijkstra_path as dijkstra_path,
-    dijkstra_path_length as dijkstra_path_length,
-    dijkstra_predecessor_and_distance as dijkstra_predecessor_and_distance,
-    find_negative_cycle as find_negative_cycle,
-    goldberg_radzik as goldberg_radzik,
-    johnson as johnson,
-    multi_source_dijkstra as multi_source_dijkstra,
-    multi_source_dijkstra_path as multi_source_dijkstra_path,
-    multi_source_dijkstra_path_length as multi_source_dijkstra_path_length,
-    negative_edge_cycle as negative_edge_cycle,
-    single_source_bellman_ford as single_source_bellman_ford,
-    single_source_bellman_ford_path as single_source_bellman_ford_path,
-    single_source_bellman_ford_path_length as single_source_bellman_ford_path_length,
-    single_source_dijkstra as single_source_dijkstra,
-    single_source_dijkstra_path as single_source_dijkstra_path,
-    single_source_dijkstra_path_length as single_source_dijkstra_path_length,
-)
diff --git a/stubs/networkx/algorithms/shortest_paths/astar.pyi b/stubs/networkx/algorithms/shortest_paths/astar.pyi
deleted file mode 100644
index c22932db..00000000
--- a/stubs/networkx/algorithms/shortest_paths/astar.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-from heapq import heappop, heappush
-from itertools import count
-
-from ...classes.graph import Graph
-
-__all__ = ["astar_path", "astar_path_length"]
-
-def astar_path(G: Graph, source, target, heuristic=None, weight="weight"): ...
-def astar_path_length(G: Graph, source, target, heuristic=None, weight="weight"): ...
diff --git a/stubs/networkx/algorithms/shortest_paths/dense.pyi b/stubs/networkx/algorithms/shortest_paths/dense.pyi
deleted file mode 100644
index 84ee24cd..00000000
--- a/stubs/networkx/algorithms/shortest_paths/dense.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "floyd_warshall",
-    "floyd_warshall_predecessor_and_distance",
-    "reconstruct_path",
-    "floyd_warshall_numpy",
-]
-
-def floyd_warshall_numpy(G: Graph, nodelist=None, weight="weight"): ...
-def floyd_warshall_predecessor_and_distance(G: Graph, weight="weight") -> dict: ...
-def reconstruct_path(source, target, predecessors: Mapping) -> ArrayLike: ...
-def floyd_warshall(G: Graph, weight="weight") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/shortest_paths/generic.pyi b/stubs/networkx/algorithms/shortest_paths/generic.pyi
deleted file mode 100644
index 2784fe4d..00000000
--- a/stubs/networkx/algorithms/shortest_paths/generic.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = [
-    "shortest_path",
-    "all_shortest_paths",
-    "shortest_path_length",
-    "average_shortest_path_length",
-    "has_path",
-]
-
-def has_path(G: Graph, source, target): ...
-def shortest_path(G: Graph, source=None, target=None, weight=None, method="dijkstra") -> list | dict: ...
-def shortest_path_length(G: Graph, source=None, target=None, weight=None, method="dijkstra"): ...
-def average_shortest_path_length(G: Graph, weight=None, method=None): ...
-def all_shortest_paths(G: Graph, source, target, weight=None, method="dijkstra"): ...
diff --git a/stubs/networkx/algorithms/shortest_paths/unweighted.pyi b/stubs/networkx/algorithms/shortest_paths/unweighted.pyi
deleted file mode 100644
index bd40b033..00000000
--- a/stubs/networkx/algorithms/shortest_paths/unweighted.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "bidirectional_shortest_path",
-    "single_source_shortest_path",
-    "single_source_shortest_path_length",
-    "single_target_shortest_path",
-    "single_target_shortest_path_length",
-    "all_pairs_shortest_path",
-    "all_pairs_shortest_path_length",
-    "predecessor",
-]
-
-def single_source_shortest_path_length(G: Graph, source, cutoff=None) -> Mapping: ...
-def single_target_shortest_path_length(G: Graph, target, cutoff=None): ...
-def all_pairs_shortest_path_length(G: Graph, cutoff=None): ...
-def bidirectional_shortest_path(G: Graph, source, target) -> ArrayLike: ...
-def single_source_shortest_path(G: Graph, source, cutoff=None) -> Mapping: ...
-def single_target_shortest_path(G: Graph, target, cutoff=None) -> Mapping: ...
-def all_pairs_shortest_path(G: Graph, cutoff=None) -> Mapping: ...
-def predecessor(G: Graph, source, target=None, cutoff=None, return_seen=None) -> Mapping: ...
diff --git a/stubs/networkx/algorithms/shortest_paths/weighted.pyi b/stubs/networkx/algorithms/shortest_paths/weighted.pyi
deleted file mode 100644
index 7e758d2d..00000000
--- a/stubs/networkx/algorithms/shortest_paths/weighted.pyi
+++ /dev/null
@@ -1,62 +0,0 @@
-from collections import deque
-from collections.abc import Mapping
-from heapq import heappop, heappush
-from itertools import count
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "dijkstra_path",
-    "dijkstra_path_length",
-    "bidirectional_dijkstra",
-    "single_source_dijkstra",
-    "single_source_dijkstra_path",
-    "single_source_dijkstra_path_length",
-    "multi_source_dijkstra",
-    "multi_source_dijkstra_path",
-    "multi_source_dijkstra_path_length",
-    "all_pairs_dijkstra",
-    "all_pairs_dijkstra_path",
-    "all_pairs_dijkstra_path_length",
-    "dijkstra_predecessor_and_distance",
-    "bellman_ford_path",
-    "bellman_ford_path_length",
-    "single_source_bellman_ford",
-    "single_source_bellman_ford_path",
-    "single_source_bellman_ford_path_length",
-    "all_pairs_bellman_ford_path",
-    "all_pairs_bellman_ford_path_length",
-    "bellman_ford_predecessor_and_distance",
-    "negative_edge_cycle",
-    "find_negative_cycle",
-    "goldberg_radzik",
-    "johnson",
-]
-
-def dijkstra_path(G: Graph, source, target, weight="weight") -> ArrayLike: ...
-def dijkstra_path_length(G: Graph, source, target, weight="weight"): ...
-def single_source_dijkstra_path(G: Graph, source, cutoff=None, weight="weight") -> Mapping: ...
-def single_source_dijkstra_path_length(G: Graph, source, cutoff=None, weight="weight") -> Mapping: ...
-def single_source_dijkstra(G: Graph, source, target=None, cutoff=None, weight="weight"): ...
-def multi_source_dijkstra_path(G: Graph, sources, cutoff=None, weight="weight") -> Mapping: ...
-def multi_source_dijkstra_path_length(G: Graph, sources, cutoff=None, weight="weight") -> Mapping: ...
-def multi_source_dijkstra(G: Graph, sources, target=None, cutoff=None, weight="weight"): ...
-def dijkstra_predecessor_and_distance(G: Graph, source, cutoff=None, weight="weight") -> dict: ...
-def all_pairs_dijkstra(G: Graph, cutoff=None, weight="weight"): ...
-def all_pairs_dijkstra_path_length(G: Graph, cutoff=None, weight="weight"): ...
-def all_pairs_dijkstra_path(G: Graph, cutoff=None, weight="weight") -> Mapping: ...
-def bellman_ford_predecessor_and_distance(G: Graph, source, target=None, weight="weight", heuristic: bool = False) -> dict: ...
-def bellman_ford_path(G: Graph, source, target, weight="weight") -> ArrayLike: ...
-def bellman_ford_path_length(G: Graph, source, target, weight="weight"): ...
-def single_source_bellman_ford_path(G: Graph, source, weight="weight") -> Mapping: ...
-def single_source_bellman_ford_path_length(G: Graph, source, weight="weight"): ...
-def single_source_bellman_ford(G: Graph, source, target=None, weight="weight"): ...
-def all_pairs_bellman_ford_path_length(G: Graph, weight="weight"): ...
-def all_pairs_bellman_ford_path(G: Graph, weight="weight") -> Mapping: ...
-def goldberg_radzik(G: Graph, source, weight="weight") -> dict: ...
-def negative_edge_cycle(G: Graph, weight="weight", heuristic: bool = True) -> bool: ...
-def find_negative_cycle(G: Graph, source, weight="weight") -> ArrayLike: ...
-def bidirectional_dijkstra(G: Graph, source, target, weight="weight"): ...
-def johnson(G: Graph, weight="weight") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/similarity.pyi b/stubs/networkx/algorithms/similarity.pyi
deleted file mode 100644
index a0f28002..00000000
--- a/stubs/networkx/algorithms/similarity.pyi
+++ /dev/null
@@ -1,98 +0,0 @@
-import math
-import time
-import warnings
-from collections.abc import Mapping
-from functools import reduce
-from itertools import product
-from operator import mul
-from typing import Callable
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "graph_edit_distance",
-    "optimal_edit_paths",
-    "optimize_graph_edit_distance",
-    "optimize_edit_paths",
-    "simrank_similarity",
-    "simrank_similarity_numpy",
-    "panther_similarity",
-    "generate_random_paths",
-]
-
-def debug_print(*args, **kwargs): ...
-def graph_edit_distance(
-    G1,
-    G2,
-    node_match: Callable | None = None,
-    edge_match: Callable | None = None,
-    node_subst_cost: Callable | None = None,
-    node_del_cost: Callable | None = None,
-    node_ins_cost: Callable | None = None,
-    edge_subst_cost: Callable | None = None,
-    edge_del_cost: Callable | None = None,
-    edge_ins_cost: Callable | None = None,
-    roots=None,
-    upper_bound=None,
-    timeout=None,
-): ...
-def optimal_edit_paths(
-    G1,
-    G2,
-    node_match: Callable | None = None,
-    edge_match: Callable | None = None,
-    node_subst_cost: Callable | None = None,
-    node_del_cost: Callable | None = None,
-    node_ins_cost: Callable | None = None,
-    edge_subst_cost: Callable | None = None,
-    edge_del_cost: Callable | None = None,
-    edge_ins_cost: Callable | None = None,
-    upper_bound=None,
-): ...
-def optimize_graph_edit_distance(
-    G1,
-    G2,
-    node_match: Callable | None = None,
-    edge_match: Callable | None = None,
-    node_subst_cost: Callable | None = None,
-    node_del_cost: Callable | None = None,
-    node_ins_cost: Callable | None = None,
-    edge_subst_cost: Callable | None = None,
-    edge_del_cost: Callable | None = None,
-    edge_ins_cost: Callable | None = None,
-    upper_bound=None,
-): ...
-def optimize_edit_paths(
-    G1,
-    G2,
-    node_match: Callable | None = None,
-    edge_match: Callable | None = None,
-    node_subst_cost: Callable | None = None,
-    node_del_cost: Callable | None = None,
-    node_ins_cost: Callable | None = None,
-    edge_subst_cost: Callable | None = None,
-    edge_del_cost: Callable | None = None,
-    edge_ins_cost: Callable | None = None,
-    upper_bound=None,
-    strictly_decreasing: bool = True,
-    roots=None,
-    timeout=None,
-): ...
-def simrank_similarity(
-    G: Graph,
-    source=None,
-    target=None,
-    importance_factor: float = 0.9,
-    max_iterations=1000,
-    tolerance: float = 1e-4,
-) -> dict | float: ...
-def simrank_similarity_numpy(
-    G: Graph,
-    source=None,
-    target=None,
-    importance_factor=0.9,
-    max_iterations=100,
-    tolerance=1e-4,
-): ...
-def panther_similarity(G: Graph, source, k=5, path_length=5, c=0.5, delta=0.1, eps=None) -> Mapping: ...
-def generate_random_paths(G: Graph, sample_size, path_length=5, index_map: Mapping | None = None): ...
diff --git a/stubs/networkx/algorithms/simple_paths.pyi b/stubs/networkx/algorithms/simple_paths.pyi
deleted file mode 100644
index 7d9b8ca2..00000000
--- a/stubs/networkx/algorithms/simple_paths.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-from heapq import heappop, heappush
-from itertools import count
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, pairwise
-
-__all__ = [
-    "all_simple_paths",
-    "is_simple_path",
-    "shortest_simple_paths",
-    "all_simple_edge_paths",
-]
-
-def is_simple_path(G: Graph, nodes: ArrayLike) -> bool: ...
-def all_simple_paths(G: Graph, source, target, cutoff=None): ...
-def all_simple_edge_paths(G: Graph, source, target, cutoff=None): ...
-def shortest_simple_paths(G: Graph, source, target, weight=None): ...
-
-class PathBuffer:
-    def __init__(self): ...
-    def __len__(self): ...
-    def push(self, cost, path): ...
-    def pop(self): ...
diff --git a/stubs/networkx/algorithms/smallworld.pyi b/stubs/networkx/algorithms/smallworld.pyi
deleted file mode 100644
index efba650d..00000000
--- a/stubs/networkx/algorithms/smallworld.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, py_random_state
-
-__all__ = ["random_reference", "lattice_reference", "sigma", "omega"]
-
-@py_random_state(3)
-def random_reference(G: Graph, niter=1, connectivity=True, seed=None): ...
-@py_random_state(4)
-def lattice_reference(G: Graph, niter=5, D=None, connectivity=True, seed=None): ...
-@py_random_state(3)
-def sigma(G: Graph, niter=100, nrand=10, seed=None) -> float: ...
-@py_random_state(3)
-def omega(G: Graph, niter=5, nrand=10, seed=None) -> float: ...
diff --git a/stubs/networkx/algorithms/smetric.pyi b/stubs/networkx/algorithms/smetric.pyi
deleted file mode 100644
index 3b48dcfd..00000000
--- a/stubs/networkx/algorithms/smetric.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-from ..classes.graph import Graph
-
-__all__ = ["s_metric"]
-
-def s_metric(G: Graph, normalized=True) -> float: ...
diff --git a/stubs/networkx/algorithms/sparsifiers.pyi b/stubs/networkx/algorithms/sparsifiers.pyi
deleted file mode 100644
index 6006431c..00000000
--- a/stubs/networkx/algorithms/sparsifiers.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-import math
-from typing import Any
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, py_random_state
-
-__all__ = ["spanner"]
-
-@py_random_state(3)
-def spanner(G: Graph, stretch: float, weight: Any = None, seed=None): ...
diff --git a/stubs/networkx/algorithms/structuralholes.pyi b/stubs/networkx/algorithms/structuralholes.pyi
deleted file mode 100644
index 15a0e933..00000000
--- a/stubs/networkx/algorithms/structuralholes.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections.abc import Mapping
-
-from ..classes.graph import Graph
-
-__all__ = ["constraint", "local_constraint", "effective_size"]
-
-def mutual_weight(G: Graph, u, v, weight=None): ...
-def normalized_mutual_weight(G: Graph, u, v, norm=..., weight=None): ...
-def effective_size(G: Graph, nodes=None, weight: str | None = None) -> Mapping: ...
-def constraint(G: Graph, nodes=None, weight: str | None = None) -> Mapping: ...
-def local_constraint(G: Graph, u, v, weight: str | None = None) -> float: ...
diff --git a/stubs/networkx/algorithms/summarization.pyi b/stubs/networkx/algorithms/summarization.pyi
deleted file mode 100644
index c148fd2e..00000000
--- a/stubs/networkx/algorithms/summarization.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from collections import Counter, defaultdict
-from collections.abc import Iterable
-
-from ..classes.graph import Graph
-
-__all__ = ["dedensify", "snap_aggregation"]
-
-def dedensify(G: Graph, threshold: int, prefix=None, copy=True): ...
-def snap_aggregation(
-    G: Graph,
-    node_attributes,
-    edge_attributes: Iterable = ...,
-    prefix: str = "Supernode-",
-    supernode_attribute: str = "group",
-    superedge_attribute: str = "types",
-): ...
diff --git a/stubs/networkx/algorithms/swap.pyi b/stubs/networkx/algorithms/swap.pyi
deleted file mode 100644
index 0cfd84ba..00000000
--- a/stubs/networkx/algorithms/swap.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-import math
-
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = ["double_edge_swap", "connected_double_edge_swap"]
-
-@py_random_state(3)
-def double_edge_swap(G: Graph, nswap=1, max_tries=100, seed=None): ...
-@py_random_state(3)
-def connected_double_edge_swap(G: Graph, nswap=1, _window_threshold=3, seed=None) -> int: ...
diff --git a/stubs/networkx/algorithms/threshold.pyi b/stubs/networkx/algorithms/threshold.pyi
deleted file mode 100644
index 3bd1d743..00000000
--- a/stubs/networkx/algorithms/threshold.pyi
+++ /dev/null
@@ -1,47 +0,0 @@
-from math import sqrt
-
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = ["is_threshold_graph", "find_threshold_graph"]
-
-def is_threshold_graph(G: Graph) -> bool: ...
-def is_threshold_sequence(degree_sequence): ...
-def creation_sequence(degree_sequence, with_labels=False, compact=False): ...
-def make_compact(creation_sequence): ...
-def uncompact(creation_sequence): ...
-def creation_sequence_to_weights(creation_sequence): ...
-def weights_to_creation_sequence(weights, threshold=1, with_labels=False, compact=False): ...
-
-# Manipulating NetworkX.Graphs in context of threshold graphs
-def threshold_graph(creation_sequence, create_using=None): ...
-def find_alternating_4_cycle(G: Graph): ...
-def find_threshold_graph(G: Graph, create_using=None): ...
-def find_creation_sequence(G: Graph): ...
-
-# Properties of Threshold Graphs
-def triangles(creation_sequence): ...
-def triangle_sequence(creation_sequence): ...
-def cluster_sequence(creation_sequence): ...
-def degree_sequence(creation_sequence): ...
-def density(creation_sequence): ...
-def degree_correlation(creation_sequence): ...
-def shortest_path(creation_sequence, u, v): ...
-def shortest_path_length(creation_sequence, i): ...
-def betweenness_sequence(creation_sequence, normalized=True): ...
-def eigenvectors(creation_sequence): ...
-def spectral_projection(u, eigenpairs): ...
-def eigenvalues(creation_sequence): ...
-
-# Threshold graph creation routines
-
-@py_random_state(2)
-def random_threshold_sequence(n, p, seed=None): ...
-
-# maybe *_d_threshold_sequence routines should
-# be (or be called from) a single routine with a more descriptive name
-# and a keyword parameter?
-def right_d_threshold_sequence(n, m): ...
-def left_d_threshold_sequence(n, m): ...
-@py_random_state(3)
-def swap_d(cs, p_split=1.0, p_combine=1.0, seed=None): ...
diff --git a/stubs/networkx/algorithms/tournament.pyi b/stubs/networkx/algorithms/tournament.pyi
deleted file mode 100644
index d9459ac0..00000000
--- a/stubs/networkx/algorithms/tournament.pyi
+++ /dev/null
@@ -1,27 +0,0 @@
-from itertools import combinations
-
-from numpy.typing import ArrayLike
-
-from ..algorithms.simple_paths import is_simple_path as is_path
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..utils import arbitrary_element, not_implemented_for, py_random_state
-
-__all__ = [
-    "hamiltonian_path",
-    "is_reachable",
-    "is_strongly_connected",
-    "is_tournament",
-    "random_tournament",
-    "score_sequence",
-]
-
-def index_satisfying(iterable, condition): ...
-def is_tournament(G: Graph) -> bool: ...
-def hamiltonian_path(G: Graph) -> ArrayLike: ...
-@py_random_state(1)
-def random_tournament(n: int, seed=None) -> DiGraph: ...
-def score_sequence(G: Graph) -> ArrayLike: ...
-def tournament_matrix(G: Graph): ...
-def is_reachable(G: Graph, s, t) -> bool: ...
-def is_strongly_connected(G: Graph) -> bool: ...
diff --git a/stubs/networkx/algorithms/traversal/__init__.pyi b/stubs/networkx/algorithms/traversal/__init__.pyi
deleted file mode 100644
index 0f0b8503..00000000
--- a/stubs/networkx/algorithms/traversal/__init__.pyi
+++ /dev/null
@@ -1,20 +0,0 @@
-from .beamsearch import bfs_beam_edges as bfs_beam_edges
-from .breadth_first_search import (
-    bfs_edges as bfs_edges,
-    bfs_layers as bfs_layers,
-    bfs_predecessors as bfs_predecessors,
-    bfs_successors as bfs_successors,
-    bfs_tree as bfs_tree,
-    descendants_at_distance as descendants_at_distance,
-)
-from .depth_first_search import (
-    dfs_edges as dfs_edges,
-    dfs_labeled_edges as dfs_labeled_edges,
-    dfs_postorder_nodes as dfs_postorder_nodes,
-    dfs_predecessors as dfs_predecessors,
-    dfs_preorder_nodes as dfs_preorder_nodes,
-    dfs_successors as dfs_successors,
-    dfs_tree as dfs_tree,
-)
-from .edgebfs import edge_bfs as edge_bfs
-from .edgedfs import edge_dfs as edge_dfs
diff --git a/stubs/networkx/algorithms/traversal/beamsearch.pyi b/stubs/networkx/algorithms/traversal/beamsearch.pyi
deleted file mode 100644
index c89ceb84..00000000
--- a/stubs/networkx/algorithms/traversal/beamsearch.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ...classes.graph import Graph
-from .breadth_first_search import generic_bfs_edges
-
-__all__ = ["bfs_beam_edges"]
-
-def bfs_beam_edges(G: Graph, source, value, width=None): ...
diff --git a/stubs/networkx/algorithms/traversal/breadth_first_search.pyi b/stubs/networkx/algorithms/traversal/breadth_first_search.pyi
deleted file mode 100644
index 9af0193c..00000000
--- a/stubs/networkx/algorithms/traversal/breadth_first_search.pyi
+++ /dev/null
@@ -1,20 +0,0 @@
-from collections import deque
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "bfs_edges",
-    "bfs_tree",
-    "bfs_predecessors",
-    "bfs_successors",
-    "descendants_at_distance",
-    "bfs_layers",
-]
-
-def generic_bfs_edges(G: Graph, source, neighbors=None, depth_limit=None, sort_neighbors=None): ...
-def bfs_edges(G: Graph, source, reverse: bool = False, depth_limit=None, sort_neighbors=None): ...
-def bfs_tree(G: Graph, source, reverse: bool = False, depth_limit=None, sort_neighbors=None): ...
-def bfs_predecessors(G: Graph, source, depth_limit=None, sort_neighbors=None): ...
-def bfs_successors(G: Graph, source, depth_limit=None, sort_neighbors=None): ...
-def bfs_layers(G: Graph, sources): ...
-def descendants_at_distance(G: Graph, source, distance): ...
diff --git a/stubs/networkx/algorithms/traversal/depth_first_search.pyi b/stubs/networkx/algorithms/traversal/depth_first_search.pyi
deleted file mode 100644
index ccbb5736..00000000
--- a/stubs/networkx/algorithms/traversal/depth_first_search.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = [
-    "dfs_edges",
-    "dfs_tree",
-    "dfs_predecessors",
-    "dfs_successors",
-    "dfs_preorder_nodes",
-    "dfs_postorder_nodes",
-    "dfs_labeled_edges",
-]
-
-def dfs_edges(G: Graph, source=None, depth_limit=None): ...
-def dfs_tree(G: Graph, source=None, depth_limit=None): ...
-def dfs_predecessors(G: Graph, source=None, depth_limit=None) -> Mapping: ...
-def dfs_successors(G: Graph, source=None, depth_limit=None) -> Mapping: ...
-def dfs_postorder_nodes(G: Graph, source=None, depth_limit=None): ...
-def dfs_preorder_nodes(G: Graph, source=None, depth_limit=None): ...
-def dfs_labeled_edges(G: Graph, source=None, depth_limit=None): ...
diff --git a/stubs/networkx/algorithms/traversal/edgebfs.pyi b/stubs/networkx/algorithms/traversal/edgebfs.pyi
deleted file mode 100644
index d32f50fa..00000000
--- a/stubs/networkx/algorithms/traversal/edgebfs.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from collections import deque
-
-from ...classes.graph import Graph
-
-FORWARD: str = ...
-REVERSE: str = ...
-
-__all__ = ["edge_bfs"]
-
-def edge_bfs(G: Graph, source=None, orientation=None): ...
diff --git a/stubs/networkx/algorithms/traversal/edgedfs.pyi b/stubs/networkx/algorithms/traversal/edgedfs.pyi
deleted file mode 100644
index 3b9686c0..00000000
--- a/stubs/networkx/algorithms/traversal/edgedfs.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ...classes.graph import Graph
-
-FORWARD: str = ...
-REVERSE: str = ...
-
-__all__ = ["edge_dfs"]
-
-def edge_dfs(G: Graph, source=None, orientation=None): ...
diff --git a/stubs/networkx/algorithms/tree/__init__.pyi b/stubs/networkx/algorithms/tree/__init__.pyi
deleted file mode 100644
index c5eae234..00000000
--- a/stubs/networkx/algorithms/tree/__init__.pyi
+++ /dev/null
@@ -1,35 +0,0 @@
-from .branchings import (
-    ArborescenceIterator as ArborescenceIterator,
-    Edmonds as Edmonds,
-    branching_weight as branching_weight,
-    greedy_branching as greedy_branching,
-    maximum_branching as maximum_branching,
-    maximum_spanning_arborescence as maximum_spanning_arborescence,
-    minimum_branching as minimum_branching,
-    minimum_spanning_arborescence as minimum_spanning_arborescence,
-)
-from .coding import (
-    NotATree as NotATree,
-    from_nested_tuple as from_nested_tuple,
-    from_prufer_sequence as from_prufer_sequence,
-    to_nested_tuple as to_nested_tuple,
-    to_prufer_sequence as to_prufer_sequence,
-)
-from .decomposition import junction_tree as junction_tree
-from .mst import (
-    EdgePartition as EdgePartition,
-    SpanningTreeIterator as SpanningTreeIterator,
-    maximum_spanning_edges as maximum_spanning_edges,
-    maximum_spanning_tree as maximum_spanning_tree,
-    minimum_spanning_edges as minimum_spanning_edges,
-    minimum_spanning_tree as minimum_spanning_tree,
-    partition_spanning_tree as partition_spanning_tree,
-    random_spanning_tree as random_spanning_tree,
-)
-from .operations import join as join
-from .recognition import (
-    is_arborescence as is_arborescence,
-    is_branching as is_branching,
-    is_forest as is_forest,
-    is_tree as is_tree,
-)
diff --git a/stubs/networkx/algorithms/tree/branchings.pyi b/stubs/networkx/algorithms/tree/branchings.pyi
deleted file mode 100644
index b11a5712..00000000
--- a/stubs/networkx/algorithms/tree/branchings.pyi
+++ /dev/null
@@ -1,102 +0,0 @@
-from typing import Literal
-
-from ...classes.digraph import DiGraph
-from ...classes.graph import Graph
-from ...classes.multidigraph import MultiDiGraph
-from ...utils import py_random_state
-from .recognition import is_arborescence, is_branching
-
-__all__ = [
-    "branching_weight",
-    "greedy_branching",
-    "maximum_branching",
-    "minimum_branching",
-    "maximum_spanning_arborescence",
-    "minimum_spanning_arborescence",
-    "ArborescenceIterator",
-    "Edmonds",
-]
-
-KINDS: set = ...
-
-STYLES: dict = ...
-
-INF = ...
-
-@py_random_state(1)
-def random_string(L=15, seed=None): ...
-def branching_weight(G: DiGraph, attr: str = "weight", default: float = 1) -> int | float: ...
-@py_random_state(4)
-def greedy_branching(G: DiGraph, attr: str = "weight", default: float = 1, kind: str = "max", seed=None): ...
-
-class MultiDiGraph_EdgeKey(MultiDiGraph):
-    def __init__(self, incoming_graph_data=None, **attr): ...
-    def remove_node(self, n): ...
-    def remove_nodes_from(self, nbunch): ...
-    def add_edge(self, u_for_edge, v_for_edge, key_for_edge, **attr): ...
-    def add_edges_from(self, ebunch_to_add, **attr): ...
-    def remove_edge_with_key(self, key): ...
-    def remove_edges_from(self, ebunch): ...
-
-def get_path(G: Graph, u, v): ...
-
-class Edmonds:
-    def __init__(self, G: Graph, seed=None): ...
-    def _init(self, attr, default, kind, style, preserve_attrs, seed, partition): ...
-    def find_optimum(
-        self,
-        attr: str = "weight",
-        default: float = 1,
-        kind: Literal["min", "max"] = "max",
-        style: Literal["branching", "arborescence"] = "branching",
-        preserve_attrs: bool = False,
-        partition: str | None = None,
-        seed=None,
-    ): ...
-
-def maximum_branching(
-    G: Graph,
-    attr: str = "weight",
-    default: float = 1,
-    preserve_attrs: bool = False,
-    partition: str | None = None,
-): ...
-def minimum_branching(
-    G: Graph,
-    attr: str = "weight",
-    default: float = 1,
-    preserve_attrs: bool = False,
-    partition: str | None = None,
-): ...
-def maximum_spanning_arborescence(
-    G: Graph,
-    attr: str = "weight",
-    default: float = 1,
-    preserve_attrs: bool = False,
-    partition: str | None = None,
-): ...
-def minimum_spanning_arborescence(
-    G: Graph,
-    attr: str = "weight",
-    default: float = 1,
-    preserve_attrs: bool = False,
-    partition: str | None = None,
-): ...
-
-docstring_branching: str = ...
-
-docstring_arborescence = ...
-
-class ArborescenceIterator:
-    def __init__(
-        self,
-        G: Graph,
-        weight: str = "weight",
-        minimum: bool = True,
-        init_partition: tuple | None = None,
-    ): ...
-    def __iter__(self) -> ArborescenceIterator: ...
-    def __next__(self): ...
-    def _partition(self, partition, partition_arborescence): ...
-    def _write_partition(self, partition): ...
-    def _clear_partition(self, G): ...
diff --git a/stubs/networkx/algorithms/tree/coding.pyi b/stubs/networkx/algorithms/tree/coding.pyi
deleted file mode 100644
index fa66886f..00000000
--- a/stubs/networkx/algorithms/tree/coding.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from collections import Counter
-from itertools import chain
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-from ...exception import NetworkXException
-from ...utils import not_implemented_for
-
-__all__ = [
-    "from_nested_tuple",
-    "from_prufer_sequence",
-    "NotATree",
-    "to_nested_tuple",
-    "to_prufer_sequence",
-]
-
-class NotATree(NetworkXException): ...
-
-def to_nested_tuple(T, root, canonical_form: bool = False) -> tuple: ...
-def from_nested_tuple(sequence: tuple, sensible_relabeling: bool = False): ...
-def to_prufer_sequence(T) -> ArrayLike: ...
-def from_prufer_sequence(sequence: ArrayLike): ...
diff --git a/stubs/networkx/algorithms/tree/decomposition.pyi b/stubs/networkx/algorithms/tree/decomposition.pyi
deleted file mode 100644
index fd5b62a0..00000000
--- a/stubs/networkx/algorithms/tree/decomposition.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from itertools import combinations
-
-from networkx import Graph
-
-from ...algorithms import chordal_graph_cliques, complete_to_chordal_graph, moral
-from ...utils import not_implemented_for
-
-__all__ = ["junction_tree"]
-
-def junction_tree(G: Graph) -> Graph: ...
diff --git a/stubs/networkx/algorithms/tree/mst.pyi b/stubs/networkx/algorithms/tree/mst.pyi
deleted file mode 100644
index e9ad1104..00000000
--- a/stubs/networkx/algorithms/tree/mst.pyi
+++ /dev/null
@@ -1,82 +0,0 @@
-from dataclasses import dataclass, field
-from enum import Enum
-from heapq import heappop, heappush
-from itertools import count
-from math import isnan
-from operator import itemgetter
-from queue import PriorityQueue
-
-from ...classes.graph import Graph
-from ...utils import UnionFind, not_implemented_for, py_random_state
-
-__all__ = [
-    "minimum_spanning_edges",
-    "maximum_spanning_edges",
-    "minimum_spanning_tree",
-    "maximum_spanning_tree",
-    "random_spanning_tree",
-    "partition_spanning_tree",
-    "EdgePartition",
-    "SpanningTreeIterator",
-]
-
-class EdgePartition(Enum):
-    OPEN = ...
-    INCLUDED = ...
-    EXCLUDED = ...
-
-def boruvka_mst_edges(G: Graph, minimum=True, weight="weight", keys=False, data=True, ignore_nan=False): ...
-def kruskal_mst_edges(
-    G: Graph,
-    minimum,
-    weight="weight",
-    keys=True,
-    data=True,
-    ignore_nan=False,
-    partition=None,
-): ...
-def prim_mst_edges(G: Graph, minimum, weight="weight", keys=True, data=True, ignore_nan=False): ...
-
-ALGORITHMS: dict = ...
-
-def minimum_spanning_edges(
-    G: Graph,
-    algorithm: str = "kruskal",
-    weight: str = "weight",
-    keys: bool = True,
-    data: bool = True,
-    ignore_nan=False,
-): ...
-def maximum_spanning_edges(
-    G: Graph,
-    algorithm: str = "kruskal",
-    weight: str = "weight",
-    keys: bool = True,
-    data: bool = True,
-    ignore_nan=False,
-): ...
-def minimum_spanning_tree(G: Graph, weight: str = "weight", algorithm: str = "kruskal", ignore_nan=False): ...
-def partition_spanning_tree(
-    G: Graph,
-    minimum=True,
-    weight: str = "weight",
-    partition: str = "partition",
-    ignore_nan=False,
-): ...
-def maximum_spanning_tree(G: Graph, weight: str = "weight", algorithm: str = "kruskal", ignore_nan=False): ...
-@py_random_state(3)
-def random_spanning_tree(G: Graph, weight: str | None = None, *, multiplicative: bool = True, seed=None): ...
-
-class SpanningTreeIterator:
-    def __init__(
-        self,
-        G: Graph,
-        weight: str = "weight",
-        minimum: bool = True,
-        ignore_nan: bool = False,
-    ): ...
-    def __iter__(self) -> SpanningTreeIterator: ...
-    def __next__(self): ...
-    def _partition(self, partition, partition_tree): ...
-    def _write_partition(self, partition): ...
-    def _clear_partition(self, G): ...
diff --git a/stubs/networkx/algorithms/tree/operations.pyi b/stubs/networkx/algorithms/tree/operations.pyi
deleted file mode 100644
index 09cd3d2c..00000000
--- a/stubs/networkx/algorithms/tree/operations.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from functools import partial
-from itertools import accumulate, chain
-
-from numpy.typing import ArrayLike
-
-from ...classes.graph import Graph
-
-__all__ = ["join"]
-
-def join(rooted_trees: ArrayLike, label_attribute: str | None = None): ...
diff --git a/stubs/networkx/algorithms/tree/recognition.pyi b/stubs/networkx/algorithms/tree/recognition.pyi
deleted file mode 100644
index 4a6ac6c7..00000000
--- a/stubs/networkx/algorithms/tree/recognition.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ...classes.graph import Graph
-
-__all__ = ["is_arborescence", "is_branching", "is_forest", "is_tree"]
-
-def is_arborescence(G: Graph) -> bool: ...
-def is_branching(G: Graph) -> bool: ...
-def is_forest(G: Graph) -> bool: ...
-def is_tree(G: Graph) -> bool: ...
diff --git a/stubs/networkx/algorithms/triads.pyi b/stubs/networkx/algorithms/triads.pyi
deleted file mode 100644
index b7c489a2..00000000
--- a/stubs/networkx/algorithms/triads.pyi
+++ /dev/null
@@ -1,44 +0,0 @@
-from collections import defaultdict
-from collections.abc import Mapping
-from itertools import combinations, permutations
-from random import sample
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-# See https://github.com/networkx/networkx/pull/1474
-# Copyright 2011 Reya Group <http://www.reyagroup.com>
-# Copyright 2011 Alex Levenson <alex@isnotinvain.com>
-# Copyright 2011 Diederik van Liere <diederik.vanliere@rotman.utoronto.ca>
-
-__all__ = [
-    "triadic_census",
-    "is_triad",
-    "all_triplets",
-    "all_triads",
-    "triads_by_type",
-    "triad_type",
-    "random_triad",
-]
-
-#: The integer codes representing each type of triad.
-#:
-#: Triads that are the same up to symmetry have the same code.
-TRICODES = ...
-
-#: The names of each type of triad. The order of the elements is
-#: important: it corresponds to the tricodes given in :data:`TRICODES`.
-TRIAD_NAMES = ...
-
-#: A dictionary mapping triad code to triad name.
-TRICODE_TO_NAME: dict = ...
-
-def triadic_census(G: Graph, nodelist: ArrayLike | None = None) -> Mapping: ...
-def is_triad(G: Graph) -> bool: ...
-def all_triplets(G: Graph): ...
-def all_triads(G: Graph): ...
-def triads_by_type(G: Graph) -> Mapping: ...
-def triad_type(G: Graph) -> str: ...
-def random_triad(G: Graph): ...
diff --git a/stubs/networkx/algorithms/vitality.pyi b/stubs/networkx/algorithms/vitality.pyi
deleted file mode 100644
index 053849ec..00000000
--- a/stubs/networkx/algorithms/vitality.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from functools import partial
-from typing import Any
-
-from ..classes.graph import Graph
-
-__all__ = ["closeness_vitality"]
-
-def closeness_vitality(G: Graph, node: Any = None, weight: str | None = None, wiener_index=None) -> dict | float: ...
diff --git a/stubs/networkx/algorithms/voronoi.pyi b/stubs/networkx/algorithms/voronoi.pyi
deleted file mode 100644
index 821d1eda..00000000
--- a/stubs/networkx/algorithms/voronoi.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections.abc import Mapping
-
-from ..classes.graph import Graph
-from ..utils import groups
-
-__all__ = ["voronoi_cells"]
-
-def voronoi_cells(G: Graph, center_nodes: set, weight="weight") -> Mapping: ...
diff --git a/stubs/networkx/algorithms/wiener.pyi b/stubs/networkx/algorithms/wiener.pyi
deleted file mode 100644
index 60ff51c9..00000000
--- a/stubs/networkx/algorithms/wiener.pyi
+++ /dev/null
@@ -1,14 +0,0 @@
-from itertools import chain
-from typing import Any
-
-from ..classes.graph import Graph
-from .components import is_connected, is_strongly_connected
-from .shortest_paths import shortest_path_length as spl
-
-__all__ = ["wiener_index"]
-
-#: Rename the :func:`chain.from_iterable` function for the sake of
-#: brevity.
-chaini = ...
-
-def wiener_index(G: Graph, weight: Any = None) -> float: ...
diff --git a/stubs/networkx/classes/__init__.pyi b/stubs/networkx/classes/__init__.pyi
deleted file mode 100644
index aee69427..00000000
--- a/stubs/networkx/classes/__init__.pyi
+++ /dev/null
@@ -1,48 +0,0 @@
-from . import coreviews as coreviews, filters as filters, graphviews as graphviews, reportviews as reportviews
-from .digraph import DiGraph as DiGraph
-from .function import (
-    add_cycle as add_cycle,
-    add_path as add_path,
-    add_star as add_star,
-    all_neighbors as all_neighbors,
-    common_neighbors as common_neighbors,
-    create_empty_copy as create_empty_copy,
-    degree as degree,
-    degree_histogram as degree_histogram,
-    density as density,
-    edge_subgraph as edge_subgraph,
-    edges as edges,
-    freeze as freeze,
-    get_edge_attributes as get_edge_attributes,
-    get_node_attributes as get_node_attributes,
-    induced_subgraph as induced_subgraph,
-    info as info,
-    is_directed as is_directed,
-    is_empty as is_empty,
-    is_frozen as is_frozen,
-    is_negatively_weighted as is_negatively_weighted,
-    is_path as is_path,
-    is_weighted as is_weighted,
-    neighbors as neighbors,
-    nodes as nodes,
-    nodes_with_selfloops as nodes_with_selfloops,
-    non_edges as non_edges,
-    non_neighbors as non_neighbors,
-    number_of_edges as number_of_edges,
-    number_of_nodes as number_of_nodes,
-    number_of_selfloops as number_of_selfloops,
-    path_weight as path_weight,
-    restricted_view as restricted_view,
-    reverse_view as reverse_view,
-    selfloop_edges as selfloop_edges,
-    set_edge_attributes as set_edge_attributes,
-    set_node_attributes as set_node_attributes,
-    subgraph as subgraph,
-    subgraph_view as subgraph_view,
-    to_directed as to_directed,
-    to_undirected as to_undirected,
-)
-from .graph import Graph as Graph
-from .multidigraph import MultiDiGraph as MultiDiGraph
-from .multigraph import MultiGraph as MultiGraph
-from .ordered import *
diff --git a/stubs/networkx/classes/coreviews.pyi b/stubs/networkx/classes/coreviews.pyi
deleted file mode 100644
index 9bc00ce1..00000000
--- a/stubs/networkx/classes/coreviews.pyi
+++ /dev/null
@@ -1,101 +0,0 @@
-import warnings
-from collections.abc import Mapping
-
-__all__ = [
-    "AtlasView",
-    "AdjacencyView",
-    "MultiAdjacencyView",
-    "UnionAtlas",
-    "UnionAdjacency",
-    "UnionMultiInner",
-    "UnionMultiAdjacency",
-    "FilterAtlas",
-    "FilterAdjacency",
-    "FilterMultiInner",
-    "FilterMultiAdjacency",
-]
-
-class AtlasView(Mapping):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, d): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, key): ...
-    def copy(self): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class AdjacencyView(AtlasView):
-    __slots__ = ...  # Still uses AtlasView slots names _atlas
-
-    def __getitem__(self, name): ...
-    def copy(self): ...
-
-class MultiAdjacencyView(AdjacencyView):
-    __slots__ = ...  # Still uses AtlasView slots names _atlas
-
-    def __getitem__(self, name): ...
-    def copy(self): ...
-
-class UnionAtlas(Mapping):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, succ, pred): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, key): ...
-    def copy(self): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class UnionAdjacency(Mapping):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, succ, pred): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, nbr): ...
-    def copy(self): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class UnionMultiInner(UnionAtlas):
-    __slots__ = ...  # Still uses UnionAtlas slots names _succ, _pred
-
-    def __getitem__(self, node): ...
-    def copy(self): ...
-
-class UnionMultiAdjacency(UnionAdjacency):
-    __slots__ = ...  # Still uses UnionAdjacency slots names _succ, _pred
-
-    def __getitem__(self, node): ...
-
-class FilterAtlas(Mapping):  # nodedict, nbrdict, keydict
-    def __init__(self, d, NODE_OK): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, key): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class FilterAdjacency(Mapping):  # edgedict
-    def __init__(self, d, NODE_OK, EDGE_OK): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, node): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class FilterMultiInner(FilterAdjacency):  # muliedge_seconddict
-    def __iter__(self): ...
-    def __getitem__(self, nbr): ...
-
-class FilterMultiAdjacency(FilterAdjacency):  # multiedgedict
-    def __getitem__(self, node): ...
diff --git a/stubs/networkx/classes/digraph.pyi b/stubs/networkx/classes/digraph.pyi
deleted file mode 100644
index 826b3a8f..00000000
--- a/stubs/networkx/classes/digraph.pyi
+++ /dev/null
@@ -1,62 +0,0 @@
-from functools import cached_property
-
-from ..classes.graph import Graph
-from ..classes.reportviews import DiDegreeView, InEdgeView, OutEdgeView
-
-__all__ = ["DiGraph"]
-
-class _CachedPropertyResetterAdjAndSucc:
-    def __set__(self, obj, value): ...
-
-class _CachedPropertyResetterPred:
-    def __set__(self, obj, value): ...
-
-class DiGraph(Graph):
-    graph = ...
-    _adj = ...
-    _succ = ...
-    _pred = ...
-
-    def __init__(self, incoming_graph_data=None, **attr): ...
-    @cached_property
-    def adj(self): ...
-    @cached_property
-    def succ(self): ...
-    @cached_property
-    def pred(self): ...
-    def add_node(self, node_for_adding, **attr): ...
-    def add_nodes_from(self, nodes_for_adding, **attr): ...
-    def remove_node(self, n): ...
-    def remove_nodes_from(self, nodes): ...
-    def add_edge(self, u_of_edge, v_of_edge, **attr): ...
-    def add_edges_from(self, ebunch_to_add, **attr): ...
-    def remove_edge(self, u, v): ...
-    def remove_edges_from(self, ebunch): ...
-    def has_successor(self, u, v): ...
-    def has_predecessor(self, u, v): ...
-    def successors(self, n): ...
-
-    # digraph definitions
-    neighbors = successors
-
-    def predecessors(self, n): ...
-    @cached_property
-    def edges(self) -> OutEdgeView: ...
-
-    # alias out_edges to edges
-    @cached_property
-    def out_edges(self) -> OutEdgeView: ...
-    @cached_property
-    def in_edges(self) -> InEdgeView: ...
-    @cached_property
-    def degree(self) -> DiDegreeView | int: ...
-    @cached_property
-    def in_degree(self): ...
-    @cached_property
-    def out_degree(self): ...
-    def clear(self): ...
-    def clear_edges(self): ...
-    def is_multigraph(self): ...
-    def is_directed(self): ...
-    def to_undirected(self, reciprocal=False, as_view=False) -> Graph: ...
-    def reverse(self, copy=True): ...
diff --git a/stubs/networkx/classes/filters.pyi b/stubs/networkx/classes/filters.pyi
deleted file mode 100644
index 61ababe4..00000000
--- a/stubs/networkx/classes/filters.pyi
+++ /dev/null
@@ -1,30 +0,0 @@
-__all__ = [
-    "no_filter",
-    "hide_nodes",
-    "hide_edges",
-    "hide_multiedges",
-    "hide_diedges",
-    "hide_multidiedges",
-    "show_nodes",
-    "show_edges",
-    "show_multiedges",
-    "show_diedges",
-    "show_multidiedges",
-]
-
-def no_filter(*items): ...
-def hide_nodes(nodes): ...
-def hide_diedges(edges): ...
-def hide_edges(edges): ...
-def hide_multidiedges(edges): ...
-def hide_multiedges(edges): ...
-
-# write show_nodes as a class to make SubGraph pickleable
-class show_nodes:
-    def __init__(self, nodes): ...
-    def __call__(self, node): ...
-
-def show_diedges(edges): ...
-def show_edges(edges): ...
-def show_multidiedges(edges): ...
-def show_multiedges(edges): ...
diff --git a/stubs/networkx/classes/function.pyi b/stubs/networkx/classes/function.pyi
deleted file mode 100644
index 2fbdafc3..00000000
--- a/stubs/networkx/classes/function.pyi
+++ /dev/null
@@ -1,92 +0,0 @@
-from collections import Counter
-from collections.abc import Iterable
-from itertools import chain
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..classes.graphviews import reverse_view, subgraph_view
-from ..utils import not_implemented_for, pairwise
-
-__all__ = [
-    "nodes",
-    "edges",
-    "degree",
-    "degree_histogram",
-    "neighbors",
-    "number_of_nodes",
-    "number_of_edges",
-    "density",
-    "is_directed",
-    "info",
-    "freeze",
-    "is_frozen",
-    "subgraph",
-    "subgraph_view",
-    "induced_subgraph",
-    "reverse_view",
-    "edge_subgraph",
-    "restricted_view",
-    "to_directed",
-    "to_undirected",
-    "add_star",
-    "add_path",
-    "add_cycle",
-    "create_empty_copy",
-    "set_node_attributes",
-    "get_node_attributes",
-    "set_edge_attributes",
-    "get_edge_attributes",
-    "all_neighbors",
-    "non_neighbors",
-    "non_edges",
-    "common_neighbors",
-    "is_weighted",
-    "is_negatively_weighted",
-    "is_empty",
-    "selfloop_edges",
-    "nodes_with_selfloops",
-    "number_of_selfloops",
-    "path_weight",
-    "is_path",
-]
-
-def nodes(G: Graph): ...
-def edges(G: Graph, nbunch=None): ...
-def degree(G: Graph, nbunch=None, weight=None): ...
-def neighbors(G: Graph, n): ...
-def number_of_nodes(G: Graph): ...
-def number_of_edges(G: Graph): ...
-def density(G: Graph): ...
-def degree_histogram(G: Graph) -> ArrayLike: ...
-def is_directed(G: Graph): ...
-def frozen(*args, **kwargs): ...
-def freeze(G: Graph): ...
-def is_frozen(G: Graph): ...
-def add_star(G_to_add_to, nodes_for_star, **attr): ...
-def add_path(G_to_add_to, nodes_for_path, **attr): ...
-def add_cycle(G_to_add_to, nodes_for_cycle, **attr): ...
-def subgraph(G: Graph, nbunch: ArrayLike | Iterable): ...
-def induced_subgraph(G: Graph, nbunch): ...
-def edge_subgraph(G: Graph, edges: Iterable): ...
-def restricted_view(G: Graph, nodes: Iterable, edges: Iterable): ...
-def to_directed(graph): ...
-def to_undirected(graph): ...
-def create_empty_copy(G: Graph, with_data=True): ...
-def info(G: Graph, n=None) -> str: ...
-def set_node_attributes(G: Graph, values, name=None): ...
-def get_node_attributes(G: Graph, name: str): ...
-def set_edge_attributes(G: Graph, values, name=None): ...
-def get_edge_attributes(G: Graph, name: str): ...
-def all_neighbors(graph, node): ...
-def non_neighbors(graph, node): ...
-def non_edges(graph): ...
-def common_neighbors(G: Graph, u, v): ...
-def is_weighted(G: Graph, edge: tuple | None = None, weight: str = "weight") -> bool: ...
-def is_negatively_weighted(G: Graph, edge: tuple | None = None, weight: str = "weight") -> bool: ...
-def is_empty(G: Graph) -> bool: ...
-def nodes_with_selfloops(G: Graph): ...
-def selfloop_edges(G: Graph, data=False, keys=False, default=None): ...
-def number_of_selfloops(G: Graph) -> int: ...
-def is_path(G: Graph, path: ArrayLike) -> bool: ...
-def path_weight(G: Graph, path: ArrayLike, weight: str) -> int | float: ...
diff --git a/stubs/networkx/classes/graph.pyi b/stubs/networkx/classes/graph.pyi
deleted file mode 100644
index 81c08846..00000000
--- a/stubs/networkx/classes/graph.pyi
+++ /dev/null
@@ -1,80 +0,0 @@
-from collections.abc import Iterable, Mapping
-from copy import deepcopy
-from functools import cached_property
-
-import networkx.convert as convert
-from numpy.typing import ArrayLike
-
-from ..classes.coreviews import AdjacencyView
-from ..classes.digraph import DiGraph
-from ..classes.reportviews import DegreeView, EdgeView, NodeView
-from ..exception import NetworkXError
-
-__all__ = ["Graph"]
-
-class _CachedPropertyResetterAdj:
-    def __set__(self, obj, value): ...
-
-class _CachedPropertyResetterNode:
-    def __set__(self, obj, value): ...
-
-class Graph:
-    graph = ...
-    _adj = ...
-    _node = ...
-
-    node_dict_factory = ...
-    node_attr_dict_factory = ...
-    adjlist_outer_dict_factory = ...
-    adjlist_inner_dict_factory = ...
-    edge_attr_dict_factory = ...
-    graph_attr_dict_factory = ...
-
-    def to_directed_class(self): ...
-    def to_undirected_class(self): ...
-    def __init__(self, incoming_graph_data=None, **attr): ...
-    @cached_property
-    def adj(self): ...
-    @property
-    def name(self): ...
-    @name.setter
-    def name(self, s): ...
-    def __iter__(self): ...
-    def __contains__(self, n): ...
-    def __len__(self) -> int: ...
-    def __getitem__(self, n) -> Mapping: ...
-    def add_node(self, node_for_adding, **attr): ...
-    def add_nodes_from(self, nodes_for_adding, **attr): ...
-    def remove_node(self, n): ...
-    def remove_nodes_from(self, nodes): ...
-    @cached_property
-    def nodes(self) -> NodeView: ...
-    def number_of_nodes(self) -> int: ...
-    def order(self) -> int: ...
-    def has_node(self, n): ...
-    def add_edge(self, u_of_edge, v_of_edge, **attr): ...
-    def add_edges_from(self, ebunch_to_add, **attr): ...
-    def add_weighted_edges_from(self, ebunch_to_add, weight="weight", **attr): ...
-    def remove_edge(self, u, v): ...
-    def remove_edges_from(self, ebunch): ...
-    def update(self, edges=None, nodes=None): ...
-    def has_edge(self, u, v) -> bool: ...
-    def neighbors(self, n): ...
-    @cached_property
-    def edges(self) -> EdgeView: ...
-    def get_edge_data(self, u, v, default=None) -> Mapping: ...
-    def adjacency(self): ...
-    @cached_property
-    def degree(self) -> DegreeView | int: ...
-    def clear(self): ...
-    def clear_edges(self): ...
-    def is_multigraph(self): ...
-    def is_directed(self): ...
-    def copy(self, as_view=False) -> Graph: ...
-    def to_directed(self, as_view=False) -> DiGraph: ...
-    def to_undirected(self, as_view=False): ...
-    def subgraph(self, nodes: ArrayLike | Iterable): ...
-    def edge_subgraph(self, edges: Iterable) -> Graph: ...
-    def size(self, weight=None): ...
-    def number_of_edges(self, u=None, v=None) -> int: ...
-    def nbunch_iter(self, nbunch=None): ...
diff --git a/stubs/networkx/classes/graphviews.pyi b/stubs/networkx/classes/graphviews.pyi
deleted file mode 100644
index ffd62a6f..00000000
--- a/stubs/networkx/classes/graphviews.pyi
+++ /dev/null
@@ -1,14 +0,0 @@
-from typing import Callable
-
-from networkx import DiGraph, Graph
-
-from ..classes.coreviews import FilterAdjacency, FilterAtlas, FilterMultiAdjacency, UnionAdjacency, UnionMultiAdjacency
-from ..classes.filters import no_filter
-from ..exception import NetworkXError
-from ..utils import not_implemented_for
-
-__all__ = ["generic_graph_view", "subgraph_view", "reverse_view"]
-
-def generic_graph_view(G: Graph, create_using=None): ...
-def subgraph_view(G: Graph, filter_node: Callable = ..., filter_edge: Callable = ...) -> Graph: ...
-def reverse_view(G: DiGraph) -> DiGraph: ...
diff --git a/stubs/networkx/classes/multidigraph.pyi b/stubs/networkx/classes/multidigraph.pyi
deleted file mode 100644
index 353a09a9..00000000
--- a/stubs/networkx/classes/multidigraph.pyi
+++ /dev/null
@@ -1,47 +0,0 @@
-from copy import deepcopy
-from functools import cached_property
-
-import networkx.convert as convert
-
-from ..classes.coreviews import MultiAdjacencyView
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..classes.multigraph import MultiGraph
-from ..classes.reportviews import DiMultiDegreeView, InMultiDegreeView, InMultiEdgeView, OutMultiDegreeView, OutMultiEdgeView
-from ..exception import NetworkXError
-
-__all__ = ["MultiDiGraph"]
-
-class MultiDiGraph(MultiGraph, DiGraph):
-    # node_dict_factory = dict    # already assigned in Graph
-    # adjlist_outer_dict_factory = dict
-    # adjlist_inner_dict_factory = dict
-    edge_key_dict_factory = ...
-    # edge_attr_dict_factory = dict
-    def __init__(self, incoming_graph_data=None, multigraph_input=None, **attr): ...
-    @cached_property
-    def adj(self): ...
-    @cached_property
-    def succ(self): ...
-    @cached_property
-    def pred(self): ...
-    def add_edge(self, u_for_edge, v_for_edge, key=None, **attr): ...
-    def remove_edge(self, u, v, key=None): ...
-    @cached_property
-    def edges(self) -> OutMultiEdgeView: ...
-
-    # alias out_edges to edges
-    @cached_property
-    def out_edges(self) -> OutMultiEdgeView: ...
-    @cached_property
-    def in_edges(self) -> InMultiEdgeView: ...
-    @cached_property
-    def degree(self) -> DiMultiDegreeView | int: ...
-    @cached_property
-    def in_degree(self): ...
-    @cached_property
-    def out_degree(self): ...
-    def is_multigraph(self): ...
-    def is_directed(self): ...
-    def to_undirected(self, reciprocal=False, as_view=False) -> MultiGraph: ...
-    def reverse(self, copy=True): ...
diff --git a/stubs/networkx/classes/multigraph.pyi b/stubs/networkx/classes/multigraph.pyi
deleted file mode 100644
index 58ed6804..00000000
--- a/stubs/networkx/classes/multigraph.pyi
+++ /dev/null
@@ -1,42 +0,0 @@
-from collections.abc import Mapping
-from copy import deepcopy
-from functools import cached_property
-
-import networkx.convert as convert
-from networkx import NetworkXError
-
-from ..classes.coreviews import MultiAdjacencyView
-from ..classes.graph import Graph
-from ..classes.multidigraph import MultiDiGraph
-from ..classes.reportviews import MultiDegreeView, MultiEdgeView
-
-__all__ = ["MultiGraph"]
-
-class MultiGraph(Graph):
-    # node_dict_factory = dict    # already assigned in Graph
-    # adjlist_outer_dict_factory = dict
-    # adjlist_inner_dict_factory = dict
-    edge_key_dict_factory = ...
-    # edge_attr_dict_factory = dict
-    def to_directed_class(self): ...
-    def to_undirected_class(self): ...
-    def __init__(self, incoming_graph_data=None, multigraph_input=None, **attr): ...
-    @cached_property
-    def adj(self): ...
-    def new_edge_key(self, u, v) -> int: ...
-    def add_edge(self, u_for_edge, v_for_edge, key=None, **attr): ...
-    def add_edges_from(self, ebunch_to_add, **attr): ...
-    def remove_edge(self, u, v, key=None): ...
-    def remove_edges_from(self, ebunch): ...
-    def has_edge(self, u, v, key=None) -> bool: ...
-    @cached_property
-    def edges(self) -> MultiEdgeView: ...
-    def get_edge_data(self, u, v, key=None, default=None) -> Mapping: ...
-    @cached_property
-    def degree(self) -> MultiDegreeView | int: ...
-    def is_multigraph(self): ...
-    def is_directed(self): ...
-    def copy(self, as_view=False) -> Graph: ...
-    def to_directed(self, as_view=False) -> MultiDiGraph: ...
-    def to_undirected(self, as_view=False): ...
-    def number_of_edges(self, u=None, v=None) -> int: ...
diff --git a/stubs/networkx/classes/ordered.pyi b/stubs/networkx/classes/ordered.pyi
deleted file mode 100644
index ecc0e3ee..00000000
--- a/stubs/networkx/classes/ordered.pyi
+++ /dev/null
@@ -1,43 +0,0 @@
-import warnings
-from collections import OrderedDict
-
-from .digraph import DiGraph
-from .graph import Graph
-from .multidigraph import MultiDiGraph
-from .multigraph import MultiGraph
-
-__all__: list[str] = []
-
-class OrderedGraph(Graph):
-    node_dict_factory = ...
-    adjlist_outer_dict_factory = ...
-    adjlist_inner_dict_factory = ...
-    edge_attr_dict_factory = ...
-
-    def __init__(self, incoming_graph_data=None, **attr): ...
-
-class OrderedDiGraph(DiGraph):
-    node_dict_factory = ...
-    adjlist_outer_dict_factory = ...
-    adjlist_inner_dict_factory = ...
-    edge_attr_dict_factory = ...
-
-    def __init__(self, incoming_graph_data=None, **attr): ...
-
-class OrderedMultiGraph(MultiGraph):
-    node_dict_factory = ...
-    adjlist_outer_dict_factory = ...
-    adjlist_inner_dict_factory = ...
-    edge_key_dict_factory = ...
-    edge_attr_dict_factory = ...
-
-    def __init__(self, incoming_graph_data=None, **attr): ...
-
-class OrderedMultiDiGraph(MultiDiGraph):
-    node_dict_factory = ...
-    adjlist_outer_dict_factory = ...
-    adjlist_inner_dict_factory = ...
-    edge_key_dict_factory = ...
-    edge_attr_dict_factory = ...
-
-    def __init__(self, incoming_graph_data=None, **attr): ...
diff --git a/stubs/networkx/classes/reportviews.pyi b/stubs/networkx/classes/reportviews.pyi
deleted file mode 100644
index 9c1843b9..00000000
--- a/stubs/networkx/classes/reportviews.pyi
+++ /dev/null
@@ -1,236 +0,0 @@
-from collections.abc import Mapping, Set as AbstractSet
-from typing import Any
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "NodeView",
-    "NodeDataView",
-    "EdgeView",
-    "OutEdgeView",
-    "InEdgeView",
-    "EdgeDataView",
-    "OutEdgeDataView",
-    "InEdgeDataView",
-    "MultiEdgeView",
-    "OutMultiEdgeView",
-    "InMultiEdgeView",
-    "MultiEdgeDataView",
-    "OutMultiEdgeDataView",
-    "InMultiEdgeDataView",
-    "DegreeView",
-    "DiDegreeView",
-    "InDegreeView",
-    "OutDegreeView",
-    "MultiDegreeView",
-    "DiMultiDegreeView",
-    "InMultiDegreeView",
-    "OutMultiDegreeView",
-]
-
-# NodeViews
-class NodeView(Mapping, AbstractSet):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, graph): ...
-
-    # Mapping methods
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __getitem__(self, n): ...
-
-    # Set methods
-    def __contains__(self, n): ...
-    @classmethod
-    def _from_iterable(cls, it): ...
-
-    # DataView method
-    def __call__(self, data=False, default=None): ...
-    def data(self, data=True, default: Any = None) -> NodeDataView: ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class NodeDataView(AbstractSet):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, nodedict, data=False, default=None): ...
-    @classmethod
-    def _from_iterable(cls, it): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, n): ...
-    def __getitem__(self, n): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-# DegreeViews
-class DiDegreeView:
-    def __init__(self, G: Graph, nbunch=None, weight=None): ...
-    def __call__(self, nbunch=None, weight=None): ...
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-    def __len__(self): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class DegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class OutDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class InDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class MultiDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class DiMultiDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class InMultiDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-class OutMultiDegreeView(DiDegreeView):
-    def __getitem__(self, n): ...
-    def __iter__(self): ...
-
-# EdgeDataViews
-class OutEdgeDataView:
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, viewer, nbunch=None, data=False, default=None): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class EdgeDataView(OutEdgeDataView):
-    __slots__ = ...
-
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-class InEdgeDataView(OutEdgeDataView):
-    __slots__ = ...
-
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-class OutMultiEdgeDataView(OutEdgeDataView):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    def __init__(self, viewer, nbunch=None, data=False, keys=False, default=None): ...
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-class MultiEdgeDataView(OutMultiEdgeDataView):
-    __slots__ = ...
-
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-class InMultiEdgeDataView(OutMultiEdgeDataView):
-    __slots__ = ...
-
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-# EdgeViews    have set operations and no data reported
-class OutEdgeView(AbstractSet, Mapping):
-    __slots__ = ...
-
-    def __getstate__(self): ...
-    def __setstate__(self, state): ...
-    @classmethod
-    def _from_iterable(cls, it): ...
-
-    dataview = ...
-
-    def __init__(self, G): ...
-
-    # Set methods
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-    # Mapping Methods
-    def __getitem__(self, e): ...
-
-    # EdgeDataView methods
-    def __call__(self, nbunch=None, data=False, default=None): ...
-    def data(self, data=True, default: Any = None, nbunch=None): ...
-
-    # String Methods
-    def __str__(self): ...
-    def __repr__(self): ...
-
-class EdgeView(OutEdgeView):
-    __slots__ = ...
-
-    dataview = ...
-
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-
-class InEdgeView(OutEdgeView):
-    __slots__ = ...
-
-    def __setstate__(self, state): ...
-
-    dataview = ...
-
-    def __init__(self, G): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-    def __getitem__(self, e): ...
-
-class OutMultiEdgeView(OutEdgeView):
-    __slots__ = ...
-
-    dataview = ...
-
-    def __len__(self): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-    def __getitem__(self, e): ...
-    def __call__(self, nbunch=None, data=False, keys=False, default=None): ...
-    def data(self, data=True, keys=False, default: Any = None, nbunch=None): ...
-
-class MultiEdgeView(OutMultiEdgeView):
-    __slots__ = ...
-
-    dataview = ...
-
-    def __len__(self): ...
-    def __iter__(self): ...
-
-class InMultiEdgeView(OutMultiEdgeView):
-    __slots__ = ...
-
-    def __setstate__(self, state): ...
-
-    dataview = ...
-
-    def __init__(self, G): ...
-    def __iter__(self): ...
-    def __contains__(self, e): ...
-    def __getitem__(self, e): ...
diff --git a/stubs/networkx/conftest.pyi b/stubs/networkx/conftest.pyi
deleted file mode 100644
index 2f6b8d35..00000000
--- a/stubs/networkx/conftest.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-import pytest
-
-def pytest_addoption(parser): ...
-def pytest_configure(config): ...
-def pytest_collection_modifyitems(config, items): ...
-@pytest.fixture(autouse=True)
-def set_warnings(): ...
-@pytest.fixture(autouse=True)
-def add_nx(doctest_namespace): ...
-
-# List of files that pytest should ignore
-
-collect_ignore: list = ...
-
-needs_numpy: list = ...
-needs_scipy: list = ...
-needs_matplotlib: list = ...
-needs_pandas: list = ...
-needs_yaml: list = ...
-needs_pygraphviz: list = ...
-needs_pydot: list = ...
-needs_ogr: list = ...
-needs_sympy: list = ...
diff --git a/stubs/networkx/convert.pyi b/stubs/networkx/convert.pyi
deleted file mode 100644
index ec398e3a..00000000
--- a/stubs/networkx/convert.pyi
+++ /dev/null
@@ -1,25 +0,0 @@
-import warnings
-from collections.abc import Collection, Generator, Iterator, Mapping
-
-from numpy.typing import ArrayLike
-
-from ._typing import Scalar
-from .classes.graph import Graph
-
-__all__ = [
-    "to_networkx_graph",
-    "from_dict_of_dicts",
-    "to_dict_of_dicts",
-    "from_dict_of_lists",
-    "to_dict_of_lists",
-    "from_edgelist",
-    "to_edgelist",
-]
-
-def to_networkx_graph(data, create_using=None, multigraph_input=False): ...
-def to_dict_of_lists(G: Graph, nodelist: ArrayLike | None = None): ...
-def from_dict_of_lists(d, create_using=None): ...
-def to_dict_of_dicts(G: Graph, nodelist: ArrayLike | None = None, edge_data: Scalar | None = None) -> Mapping: ...
-def from_dict_of_dicts(d: dict[dict, dict], create_using=None, multigraph_input=False): ...
-def to_edgelist(G: Graph, nodelist: ArrayLike | None = None): ...
-def from_edgelist(edgelist, create_using=None): ...
diff --git a/stubs/networkx/convert_matrix.pyi b/stubs/networkx/convert_matrix.pyi
deleted file mode 100644
index 0cd0fd54..00000000
--- a/stubs/networkx/convert_matrix.pyi
+++ /dev/null
@@ -1,95 +0,0 @@
-import itertools
-import warnings
-from collections import defaultdict
-from typing import Callable, Literal
-
-from numpy.typing import ArrayLike
-
-from .classes.graph import Graph
-from .utils import not_implemented_for
-
-__all__ = [
-    "from_numpy_matrix",
-    "to_numpy_matrix",
-    "from_pandas_adjacency",
-    "to_pandas_adjacency",
-    "from_pandas_edgelist",
-    "to_pandas_edgelist",
-    "to_numpy_recarray",
-    "from_scipy_sparse_array",
-    "from_scipy_sparse_matrix",
-    "to_scipy_sparse_array",
-    "to_scipy_sparse_matrix",
-    "from_numpy_array",
-    "to_numpy_array",
-]
-
-def to_pandas_adjacency(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    order=None,
-    multigraph_weight=...,
-    weight: str | None = "weight",
-    nonedge: float = 0.0,
-): ...
-def from_pandas_adjacency(df, create_using=None): ...
-def to_pandas_edgelist(
-    G: Graph,
-    source: str | int = "source",
-    target: str | int = "target",
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    order=None,
-    edge_key=None,
-): ...
-def from_pandas_edgelist(
-    df,
-    source: str | int = "source",
-    target: str | int = "target",
-    edge_attr=None,
-    create_using=None,
-    edge_key=None,
-): ...
-def to_numpy_matrix(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    order: Literal["C", "F"] | None = None,
-    multigraph_weight=...,
-    weight="weight",
-    nonedge=0.0,
-): ...
-def from_numpy_matrix(A, parallel_edges: bool = False, create_using=None): ...
-def to_numpy_recarray(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    order: Literal["C", "F"] | None = None,
-): ...
-def to_scipy_sparse_array(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    weight="weight",
-    format="csr",
-): ...
-def to_scipy_sparse_matrix(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    weight="weight",
-    format="csr",
-): ...
-def from_scipy_sparse_matrix(A, parallel_edges: bool = False, create_using=None, edge_attribute: str = "weight"): ...
-def from_scipy_sparse_array(A, parallel_edges: bool = False, create_using=None, edge_attribute: str = "weight"): ...
-def to_numpy_array(
-    G: Graph,
-    nodelist: ArrayLike | None = None,
-    dtype=None,
-    order: Literal["C", "F"] | None = None,
-    multigraph_weight: Callable = ...,
-    weight="weight",
-    nonedge=0.0,
-): ...
-def from_numpy_array(A, parallel_edges: bool = False, create_using=None): ...
diff --git a/stubs/networkx/drawing/__init__.pyi b/stubs/networkx/drawing/__init__.pyi
deleted file mode 100644
index 641d1e57..00000000
--- a/stubs/networkx/drawing/__init__.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-# graph drawing and interface to graphviz
-
-from . import nx_agraph as nx_agraph, nx_pydot as nx_pydot
-from .layout import (
-    bipartite_layout as bipartite_layout,
-    circular_layout as circular_layout,
-    fruchterman_reingold_layout as fruchterman_reingold_layout,
-    kamada_kawai_layout as kamada_kawai_layout,
-    multipartite_layout as multipartite_layout,
-    planar_layout as planar_layout,
-    random_layout as random_layout,
-    rescale_layout as rescale_layout,
-    rescale_layout_dict as rescale_layout_dict,
-    shell_layout as shell_layout,
-    spectral_layout as spectral_layout,
-    spiral_layout as spiral_layout,
-    spring_layout as spring_layout,
-)
-from .nx_pylab import (
-    draw as draw,
-    draw_circular as draw_circular,
-    draw_kamada_kawai as draw_kamada_kawai,
-    draw_networkx as draw_networkx,
-    draw_networkx_edge_labels as draw_networkx_edge_labels,
-    draw_networkx_edges as draw_networkx_edges,
-    draw_networkx_labels as draw_networkx_labels,
-    draw_networkx_nodes as draw_networkx_nodes,
-    draw_planar as draw_planar,
-    draw_random as draw_random,
-    draw_shell as draw_shell,
-    draw_spectral as draw_spectral,
-    draw_spring as draw_spring,
-)
diff --git a/stubs/networkx/drawing/layout.pyi b/stubs/networkx/drawing/layout.pyi
deleted file mode 100644
index 8b4dfecb..00000000
--- a/stubs/networkx/drawing/layout.pyi
+++ /dev/null
@@ -1,87 +0,0 @@
-from collections.abc import Mapping
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import np_random_state
-
-__all__ = [
-    "bipartite_layout",
-    "circular_layout",
-    "kamada_kawai_layout",
-    "random_layout",
-    "rescale_layout",
-    "rescale_layout_dict",
-    "shell_layout",
-    "spring_layout",
-    "spectral_layout",
-    "planar_layout",
-    "fruchterman_reingold_layout",
-    "spiral_layout",
-    "multipartite_layout",
-]
-
-@np_random_state(3)
-def random_layout(G: Graph, center: ArrayLike | None = None, dim: int = 2, seed=None) -> Mapping: ...
-def circular_layout(G: Graph, scale=1, center: ArrayLike | None = None, dim: int = 2) -> Mapping: ...
-def shell_layout(
-    G: Graph,
-    nlist=None,
-    rotate=None,
-    scale=1,
-    center: ArrayLike | None = None,
-    dim: int = 2,
-) -> Mapping: ...
-def bipartite_layout(
-    G: Graph,
-    nodes,
-    align="vertical",
-    scale=1,
-    center: ArrayLike | None = None,
-    aspect_ratio=...,
-) -> Mapping: ...
-@np_random_state(10)
-def spring_layout(
-    G: Graph,
-    k=None,
-    pos=None,
-    fixed=None,
-    iterations=50,
-    threshold=1e-4,
-    weight="weight",
-    scale=1,
-    center: ArrayLike | None = None,
-    dim: int = 2,
-    seed=None,
-) -> Mapping: ...
-
-fruchterman_reingold_layout = ...
-
-def kamada_kawai_layout(
-    G: Graph,
-    dist=None,
-    pos=None,
-    weight="weight",
-    scale=1,
-    center: ArrayLike | None = None,
-    dim: int = 2,
-) -> Mapping: ...
-def spectral_layout(G: Graph, weight="weight", scale=1, center: ArrayLike | None = None, dim: int = 2) -> Mapping: ...
-def planar_layout(G: Graph, scale=1, center: ArrayLike | None = None, dim: int = 2) -> Mapping: ...
-def spiral_layout(
-    G: Graph,
-    scale=1,
-    center: ArrayLike | None = None,
-    dim: int = 2,
-    resolution: float = 0.35,
-    equidistant: bool = False,
-) -> Mapping: ...
-def multipartite_layout(
-    G: Graph,
-    subset_key="subset",
-    align="vertical",
-    scale=1,
-    center: ArrayLike | None = None,
-) -> Mapping: ...
-def rescale_layout(pos, scale=1): ...
-def rescale_layout_dict(pos, scale=1): ...
diff --git a/stubs/networkx/drawing/nx_agraph.pyi b/stubs/networkx/drawing/nx_agraph.pyi
deleted file mode 100644
index 1ccd1f83..00000000
--- a/stubs/networkx/drawing/nx_agraph.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-import os
-import tempfile
-from collections.abc import Mapping
-from typing import Callable
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "from_agraph",
-    "to_agraph",
-    "write_dot",
-    "read_dot",
-    "graphviz_layout",
-    "pygraphviz_layout",
-    "view_pygraphviz",
-]
-
-def from_agraph(A, create_using=None): ...
-def to_agraph(N): ...
-def write_dot(G: Graph, path): ...
-def read_dot(path): ...
-def graphviz_layout(G: Graph, prog: str = "neato", root: str | None = None, args: str = ""): ...
-def pygraphviz_layout(G: Graph, prog: str = "neato", root: str | None = None, args: str = "") -> Mapping: ...
-def view_pygraphviz(
-    G: Graph,
-    edgelabel: str | Callable | None = None,
-    prog: str = "dot",
-    args: str = "",
-    suffix: str = "",
-    path: str | None = None,
-    show: bool = True,
-): ...
-def display_pygraphviz(graph, path, format: str | None = None, prog: str | None = None, args: str = ""): ...
diff --git a/stubs/networkx/drawing/nx_pydot.pyi b/stubs/networkx/drawing/nx_pydot.pyi
deleted file mode 100644
index f792a014..00000000
--- a/stubs/networkx/drawing/nx_pydot.pyi
+++ /dev/null
@@ -1,24 +0,0 @@
-import warnings
-from collections.abc import Mapping
-from locale import getpreferredencoding
-
-from ..classes.graph import Graph
-from ..classes.multidigraph import MultiDiGraph
-from ..classes.multigraph import MultiGraph
-from ..utils import open_file
-
-__all__ = [
-    "write_dot",
-    "read_dot",
-    "graphviz_layout",
-    "pydot_layout",
-    "to_pydot",
-    "from_pydot",
-]
-
-def write_dot(G: Graph, path): ...
-def read_dot(path) -> MultiGraph | MultiDiGraph: ...
-def from_pydot(P): ...
-def to_pydot(N): ...
-def graphviz_layout(G: Graph, prog="neato", root=None): ...
-def pydot_layout(G: Graph, prog="neato", root=None) -> Mapping: ...
diff --git a/stubs/networkx/drawing/nx_pylab.pyi b/stubs/networkx/drawing/nx_pylab.pyi
deleted file mode 100644
index 3545ae53..00000000
--- a/stubs/networkx/drawing/nx_pylab.pyi
+++ /dev/null
@@ -1,121 +0,0 @@
-from collections.abc import Mapping
-from numbers import Number
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..drawing.layout import (
-    circular_layout,
-    kamada_kawai_layout,
-    planar_layout,
-    random_layout,
-    shell_layout,
-    spectral_layout,
-    spring_layout,
-)
-
-__all__ = [
-    "draw",
-    "draw_networkx",
-    "draw_networkx_nodes",
-    "draw_networkx_edges",
-    "draw_networkx_labels",
-    "draw_networkx_edge_labels",
-    "draw_circular",
-    "draw_kamada_kawai",
-    "draw_random",
-    "draw_spectral",
-    "draw_spring",
-    "draw_planar",
-    "draw_shell",
-]
-
-def draw(G: Graph, pos: Mapping | None = None, ax=None, **kwds): ...
-def draw_networkx(G: Graph, pos: Mapping | None = None, arrows=None, with_labels=True, **kwds): ...
-def draw_networkx_nodes(
-    G: Graph,
-    pos: Mapping,
-    nodelist=None,
-    node_size=300,
-    node_color="#1f78b4",
-    node_shape="o",
-    alpha=None,
-    cmap=None,
-    vmin=None,
-    vmax=None,
-    ax=None,
-    linewidths=None,
-    edgecolors=None,
-    label=None,
-    margins=None,
-): ...
-def draw_networkx_edges(
-    G: Graph,
-    pos: Mapping,
-    edgelist=None,
-    width=1.0,
-    edge_color="k",
-    style="solid",
-    alpha=None,
-    arrowstyle=None,
-    arrowsize=10,
-    edge_cmap=None,
-    edge_vmin: float | None = None,
-    edge_vmax: float | None = None,
-    ax=None,
-    arrows=None,
-    label: str | None = None,
-    node_size=300,
-    nodelist=None,
-    node_shape="o",
-    connectionstyle="arc3",
-    min_source_margin=0,
-    min_target_margin=0,
-): ...
-def draw_networkx_labels(
-    G: Graph,
-    pos: Mapping,
-    labels=None,
-    font_size=12,
-    font_color="k",
-    font_family="sans-serif",
-    font_weight="normal",
-    alpha=None,
-    bbox=None,
-    horizontalalignment="center",
-    verticalalignment="center",
-    ax=None,
-    clip_on=True,
-) -> Mapping: ...
-def draw_networkx_edge_labels(
-    G: Graph,
-    pos: Mapping,
-    edge_labels=None,
-    label_pos=0.5,
-    font_size=10,
-    font_color="k",
-    font_family="sans-serif",
-    font_weight="normal",
-    alpha=None,
-    bbox=None,
-    horizontalalignment="center",
-    verticalalignment="center",
-    ax=None,
-    rotate=True,
-    clip_on=True,
-) -> Mapping: ...
-def draw_circular(G: Graph, **kwargs): ...
-def draw_kamada_kawai(G: Graph, **kwargs): ...
-def draw_random(G: Graph, **kwargs): ...
-def draw_spectral(G: Graph, **kwargs): ...
-def draw_spring(G: Graph, **kwargs): ...
-def draw_shell(G: Graph, nlist=None, **kwargs): ...
-def draw_planar(G: Graph, **kwargs): ...
-def apply_alpha(
-    colors,
-    alpha: float | ArrayLike,
-    elem_list,
-    cmap=None,
-    vmin: float | None = None,
-    vmax: float | None = None,
-): ...
diff --git a/stubs/networkx/exception.pyi b/stubs/networkx/exception.pyi
deleted file mode 100644
index 73e7a089..00000000
--- a/stubs/networkx/exception.pyi
+++ /dev/null
@@ -1,33 +0,0 @@
-__all__ = [
-    "HasACycle",
-    "NodeNotFound",
-    "PowerIterationFailedConvergence",
-    "ExceededMaxIterations",
-    "AmbiguousSolution",
-    "NetworkXAlgorithmError",
-    "NetworkXException",
-    "NetworkXError",
-    "NetworkXNoCycle",
-    "NetworkXNoPath",
-    "NetworkXNotImplemented",
-    "NetworkXPointlessConcept",
-    "NetworkXUnbounded",
-    "NetworkXUnfeasible",
-]
-
-class NetworkXException(Exception): ...
-class NetworkXError(NetworkXException): ...
-class NetworkXPointlessConcept(NetworkXException): ...
-class NetworkXAlgorithmError(NetworkXException): ...
-class NetworkXUnfeasible(NetworkXAlgorithmError): ...
-class NetworkXNoPath(NetworkXUnfeasible): ...
-class NetworkXNoCycle(NetworkXUnfeasible): ...
-class HasACycle(NetworkXException): ...
-class NetworkXUnbounded(NetworkXAlgorithmError): ...
-class NetworkXNotImplemented(NetworkXException): ...
-class NodeNotFound(NetworkXException): ...
-class AmbiguousSolution(NetworkXException): ...
-class ExceededMaxIterations(NetworkXException): ...
-
-class PowerIterationFailedConvergence(ExceededMaxIterations):
-    def __init__(self, num_iterations, *args, **kw): ...
diff --git a/stubs/networkx/generators/__init__.pyi b/stubs/networkx/generators/__init__.pyi
deleted file mode 100644
index a3a00fe8..00000000
--- a/stubs/networkx/generators/__init__.pyi
+++ /dev/null
@@ -1,155 +0,0 @@
-from .atlas import graph_atlas as graph_atlas, graph_atlas_g as graph_atlas_g
-from .classic import (
-    balanced_tree as balanced_tree,
-    barbell_graph as barbell_graph,
-    binomial_tree as binomial_tree,
-    circulant_graph as circulant_graph,
-    circular_ladder_graph as circular_ladder_graph,
-    complete_graph as complete_graph,
-    complete_multipartite_graph as complete_multipartite_graph,
-    cycle_graph as cycle_graph,
-    dorogovtsev_goltsev_mendes_graph as dorogovtsev_goltsev_mendes_graph,
-    empty_graph as empty_graph,
-    full_rary_tree as full_rary_tree,
-    ladder_graph as ladder_graph,
-    lollipop_graph as lollipop_graph,
-    null_graph as null_graph,
-    path_graph as path_graph,
-    star_graph as star_graph,
-    trivial_graph as trivial_graph,
-    turan_graph as turan_graph,
-    wheel_graph as wheel_graph,
-)
-from .cographs import random_cograph as random_cograph
-from .community import (
-    LFR_benchmark_graph as LFR_benchmark_graph,
-    caveman_graph as caveman_graph,
-    connected_caveman_graph as connected_caveman_graph,
-    gaussian_random_partition_graph as gaussian_random_partition_graph,
-    planted_partition_graph as planted_partition_graph,
-    random_partition_graph as random_partition_graph,
-    relaxed_caveman_graph as relaxed_caveman_graph,
-    ring_of_cliques as ring_of_cliques,
-    stochastic_block_model as stochastic_block_model,
-    windmill_graph as windmill_graph,
-)
-from .degree_seq import (
-    configuration_model as configuration_model,
-    degree_sequence_tree as degree_sequence_tree,
-    directed_configuration_model as directed_configuration_model,
-    directed_havel_hakimi_graph as directed_havel_hakimi_graph,
-    expected_degree_graph as expected_degree_graph,
-    havel_hakimi_graph as havel_hakimi_graph,
-    random_degree_sequence_graph as random_degree_sequence_graph,
-)
-from .directed import (
-    gn_graph as gn_graph,
-    gnc_graph as gnc_graph,
-    gnr_graph as gnr_graph,
-    random_k_out_graph as random_k_out_graph,
-    scale_free_graph as scale_free_graph,
-)
-from .duplication import (
-    duplication_divergence_graph as duplication_divergence_graph,
-    partial_duplication_graph as partial_duplication_graph,
-)
-from .ego import ego_graph as ego_graph
-from .expanders import (
-    chordal_cycle_graph as chordal_cycle_graph,
-    margulis_gabber_galil_graph as margulis_gabber_galil_graph,
-    paley_graph as paley_graph,
-)
-from .geometric import (
-    geographical_threshold_graph as geographical_threshold_graph,
-    geometric_edges as geometric_edges,
-    navigable_small_world_graph as navigable_small_world_graph,
-    random_geometric_graph as random_geometric_graph,
-    soft_random_geometric_graph as soft_random_geometric_graph,
-    thresholded_random_geometric_graph as thresholded_random_geometric_graph,
-    waxman_graph as waxman_graph,
-)
-from .internet_as_graphs import random_internet_as_graph as random_internet_as_graph
-from .intersection import (
-    general_random_intersection_graph as general_random_intersection_graph,
-    k_random_intersection_graph as k_random_intersection_graph,
-    uniform_random_intersection_graph as uniform_random_intersection_graph,
-)
-from .interval_graph import interval_graph as interval_graph
-from .joint_degree_seq import (
-    directed_joint_degree_graph as directed_joint_degree_graph,
-    is_valid_directed_joint_degree as is_valid_directed_joint_degree,
-    is_valid_joint_degree as is_valid_joint_degree,
-    joint_degree_graph as joint_degree_graph,
-)
-from .lattice import (
-    grid_2d_graph as grid_2d_graph,
-    grid_graph as grid_graph,
-    hexagonal_lattice_graph as hexagonal_lattice_graph,
-    hypercube_graph as hypercube_graph,
-    triangular_lattice_graph as triangular_lattice_graph,
-)
-from .line import inverse_line_graph as inverse_line_graph, line_graph as line_graph
-from .mycielski import mycielski_graph as mycielski_graph, mycielskian as mycielskian
-from .nonisomorphic_trees import (
-    nonisomorphic_trees as nonisomorphic_trees,
-    number_of_nonisomorphic_trees as number_of_nonisomorphic_trees,
-)
-from .random_clustered import random_clustered_graph as random_clustered_graph
-from .random_graphs import (
-    barabasi_albert_graph as barabasi_albert_graph,
-    binomial_graph as binomial_graph,
-    connected_watts_strogatz_graph as connected_watts_strogatz_graph,
-    dense_gnm_random_graph as dense_gnm_random_graph,
-    dual_barabasi_albert_graph as dual_barabasi_albert_graph,
-    erdos_renyi_graph as erdos_renyi_graph,
-    extended_barabasi_albert_graph as extended_barabasi_albert_graph,
-    fast_gnp_random_graph as fast_gnp_random_graph,
-    gnm_random_graph as gnm_random_graph,
-    gnp_random_graph as gnp_random_graph,
-    newman_watts_strogatz_graph as newman_watts_strogatz_graph,
-    powerlaw_cluster_graph as powerlaw_cluster_graph,
-    random_kernel_graph as random_kernel_graph,
-    random_lobster as random_lobster,
-    random_powerlaw_tree as random_powerlaw_tree,
-    random_powerlaw_tree_sequence as random_powerlaw_tree_sequence,
-    random_regular_graph as random_regular_graph,
-    random_shell_graph as random_shell_graph,
-    watts_strogatz_graph as watts_strogatz_graph,
-)
-from .small import (
-    LCF_graph as LCF_graph,
-    bull_graph as bull_graph,
-    chvatal_graph as chvatal_graph,
-    cubical_graph as cubical_graph,
-    desargues_graph as desargues_graph,
-    diamond_graph as diamond_graph,
-    dodecahedral_graph as dodecahedral_graph,
-    frucht_graph as frucht_graph,
-    heawood_graph as heawood_graph,
-    hoffman_singleton_graph as hoffman_singleton_graph,
-    house_graph as house_graph,
-    house_x_graph as house_x_graph,
-    icosahedral_graph as icosahedral_graph,
-    krackhardt_kite_graph as krackhardt_kite_graph,
-    make_small_graph as make_small_graph,
-    moebius_kantor_graph as moebius_kantor_graph,
-    octahedral_graph as octahedral_graph,
-    pappus_graph as pappus_graph,
-    petersen_graph as petersen_graph,
-    sedgewick_maze_graph as sedgewick_maze_graph,
-    tetrahedral_graph as tetrahedral_graph,
-    truncated_cube_graph as truncated_cube_graph,
-    truncated_tetrahedron_graph as truncated_tetrahedron_graph,
-    tutte_graph as tutte_graph,
-)
-from .social import (
-    davis_southern_women_graph as davis_southern_women_graph,
-    florentine_families_graph as florentine_families_graph,
-    karate_club_graph as karate_club_graph,
-    les_miserables_graph as les_miserables_graph,
-)
-from .spectral_graph_forge import spectral_graph_forge as spectral_graph_forge
-from .stochastic import stochastic_graph as stochastic_graph
-from .sudoku import sudoku_graph as sudoku_graph
-from .trees import prefix_tree as prefix_tree, prefix_tree_recursive as prefix_tree_recursive, random_tree as random_tree
-from .triads import triad_graph as triad_graph
diff --git a/stubs/networkx/generators/atlas.pyi b/stubs/networkx/generators/atlas.pyi
deleted file mode 100644
index 62820a93..00000000
--- a/stubs/networkx/generators/atlas.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from importlib.abc import Traversable
-from typing import Final
-
-from numpy.typing import ArrayLike
-
-__all__ = ["graph_atlas", "graph_atlas_g"]
-
-NUM_GRAPHS: Final = 1253
-ATLAS_FILE: Traversable
-
-def graph_atlas(i: int) -> ArrayLike: ...
-def graph_atlas_g() -> ArrayLike: ...
diff --git a/stubs/networkx/generators/classic.pyi b/stubs/networkx/generators/classic.pyi
deleted file mode 100644
index e0e7c52a..00000000
--- a/stubs/networkx/generators/classic.pyi
+++ /dev/null
@@ -1,59 +0,0 @@
-import itertools
-import numbers
-from collections.abc import Iterable
-
-from ..classes import Graph
-from ..exception import NetworkXError
-from ..utils import nodes_or_number, pairwise
-
-__all__ = [
-    "balanced_tree",
-    "barbell_graph",
-    "binomial_tree",
-    "complete_graph",
-    "complete_multipartite_graph",
-    "circular_ladder_graph",
-    "circulant_graph",
-    "cycle_graph",
-    "dorogovtsev_goltsev_mendes_graph",
-    "empty_graph",
-    "full_rary_tree",
-    "ladder_graph",
-    "lollipop_graph",
-    "null_graph",
-    "path_graph",
-    "star_graph",
-    "trivial_graph",
-    "turan_graph",
-    "wheel_graph",
-]
-
-# -------------------------------------------------------------------
-#   Some Classic Graphs
-# -------------------------------------------------------------------
-
-def full_rary_tree(r: int, n: int, create_using=None): ...
-def balanced_tree(r: int, h: int, create_using=None): ...
-def barbell_graph(m1, m2, create_using=None): ...
-def binomial_tree(n: int, create_using=None): ...
-@nodes_or_number(0)
-def complete_graph(n, create_using=None): ...
-def circular_ladder_graph(n, create_using=None): ...
-def circulant_graph(n, offsets, create_using=None): ...
-@nodes_or_number(0)
-def cycle_graph(n, create_using=None): ...
-def dorogovtsev_goltsev_mendes_graph(n, create_using=None): ...
-@nodes_or_number(0)
-def empty_graph(n=0, create_using=None, default=...): ...
-def ladder_graph(n, create_using=None): ...
-def lollipop_graph(m, n, create_using=None): ...
-def null_graph(create_using=None): ...
-@nodes_or_number(0)
-def path_graph(n: int | Iterable, create_using=None): ...
-@nodes_or_number(0)
-def star_graph(n: int | Iterable, create_using=None): ...
-def trivial_graph(create_using=None): ...
-def turan_graph(n: int, r: int): ...
-@nodes_or_number(0)
-def wheel_graph(n: int | Iterable, create_using=None): ...
-def complete_multipartite_graph(*subset_sizes): ...
diff --git a/stubs/networkx/generators/cographs.pyi b/stubs/networkx/generators/cographs.pyi
deleted file mode 100644
index 983d4473..00000000
--- a/stubs/networkx/generators/cographs.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = ["random_cograph"]
-
-@py_random_state(1)
-def random_cograph(n: int, seed=None): ...
diff --git a/stubs/networkx/generators/community.pyi b/stubs/networkx/generators/community.pyi
deleted file mode 100644
index e12cfe6f..00000000
--- a/stubs/networkx/generators/community.pyi
+++ /dev/null
@@ -1,58 +0,0 @@
-import itertools
-import math
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = [
-    "caveman_graph",
-    "connected_caveman_graph",
-    "relaxed_caveman_graph",
-    "random_partition_graph",
-    "planted_partition_graph",
-    "gaussian_random_partition_graph",
-    "ring_of_cliques",
-    "windmill_graph",
-    "stochastic_block_model",
-    "LFR_benchmark_graph",
-]
-
-def caveman_graph(l: int, k: int): ...
-def connected_caveman_graph(l: int, k: int): ...
-@py_random_state(3)
-def relaxed_caveman_graph(l: int, k: int, p: float, seed=None): ...
-@py_random_state(3)
-def random_partition_graph(sizes: ArrayLike, p_in: float, p_out: float, seed=None, directed=False): ...
-@py_random_state(4)
-def planted_partition_graph(l: int, k: int, p_in: float, p_out: float, seed=None, directed=False): ...
-@py_random_state(6)
-def gaussian_random_partition_graph(n: int, s: float, v: float, p_in: float, p_out: float, directed=False, seed=None): ...
-def ring_of_cliques(num_cliques: int, clique_size: int): ...
-def windmill_graph(n: int, k: int): ...
-@py_random_state(3)
-def stochastic_block_model(
-    sizes: ArrayLike,
-    p,
-    nodelist: ArrayLike | None = None,
-    seed=None,
-    directed=False,
-    selfloops=False,
-    sparse=True,
-): ...
-@py_random_state(11)
-def LFR_benchmark_graph(
-    n: int,
-    tau1: float,
-    tau2: float,
-    mu: float,
-    average_degree: float | None = None,
-    min_degree: int | None = None,
-    max_degree: int | None = None,
-    min_community: int | None = None,
-    max_community: int | None = None,
-    tol: float = 1.0e-7,
-    max_iters: int = 500,
-    seed=None,
-): ...
diff --git a/stubs/networkx/generators/degree_seq.pyi b/stubs/networkx/generators/degree_seq.pyi
deleted file mode 100644
index fa7bb9a5..00000000
--- a/stubs/networkx/generators/degree_seq.pyi
+++ /dev/null
@@ -1,49 +0,0 @@
-import heapq
-import math
-from itertools import chain, combinations, zip_longest
-from operator import itemgetter
-
-from numpy.typing import ArrayLike
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..classes.multidigraph import MultiDiGraph
-from ..classes.multigraph import MultiGraph
-from ..utils import py_random_state, random_weighted_sample
-
-__all__ = [
-    "configuration_model",
-    "directed_configuration_model",
-    "expected_degree_graph",
-    "havel_hakimi_graph",
-    "directed_havel_hakimi_graph",
-    "degree_sequence_tree",
-    "random_degree_sequence_graph",
-]
-
-chaini = ...
-
-@py_random_state(2)
-def configuration_model(deg_sequence, create_using=None, seed=None) -> MultiGraph: ...
-@py_random_state(3)
-def directed_configuration_model(in_degree_sequence, out_degree_sequence, create_using=None, seed=None) -> MultiDiGraph: ...
-@py_random_state(1)
-def expected_degree_graph(w: ArrayLike, seed=None, selfloops=True) -> Graph: ...
-def havel_hakimi_graph(deg_sequence, create_using=None): ...
-def directed_havel_hakimi_graph(in_deg_sequence, out_deg_sequence, create_using=None) -> DiGraph: ...
-def degree_sequence_tree(deg_sequence, create_using=None): ...
-@py_random_state(1)
-def random_degree_sequence_graph(sequence, seed=None, tries: int = 10) -> Graph: ...
-
-class DegreeSequenceRandomGraph:
-    # class to generate random graphs with a given degree sequence
-    # use random_degree_sequence_graph()
-    def __init__(self, degree, rng): ...
-    def generate(self): ...
-    def update_remaining(self, u, v, aux_graph=None): ...
-    def p(self, u, v): ...
-    def q(self, u, v): ...
-    def suitable_edge(self): ...
-    def phase1(self): ...
-    def phase2(self): ...
-    def phase3(self): ...
diff --git a/stubs/networkx/generators/directed.pyi b/stubs/networkx/generators/directed.pyi
deleted file mode 100644
index 1f7a5120..00000000
--- a/stubs/networkx/generators/directed.pyi
+++ /dev/null
@@ -1,38 +0,0 @@
-import numbers
-from collections import Counter
-
-from ..classes import MultiDiGraph
-from ..classes.graph import Graph
-from ..generators.classic import empty_graph
-from ..utils import discrete_sequence, py_random_state, weighted_choice
-
-__all__ = [
-    "gn_graph",
-    "gnc_graph",
-    "gnr_graph",
-    "random_k_out_graph",
-    "scale_free_graph",
-]
-
-@py_random_state(3)
-def gn_graph(n: int, kernel=None, create_using=None, seed=None): ...
-@py_random_state(3)
-def gnr_graph(n: int, p: float, create_using=None, seed=None): ...
-@py_random_state(2)
-def gnc_graph(n: int, create_using=None, seed=None): ...
-@py_random_state(7)
-def scale_free_graph(
-    n,
-    alpha: float = 0.41,
-    beta: float = 0.54,
-    gamma: float = 0.05,
-    delta_in: float = 0.2,
-    delta_out: float = 0,
-    create_using=None,
-    seed=None,
-    initial_graph=None,
-) -> MultiDiGraph: ...
-@py_random_state(4)
-def random_uniform_k_out_graph(n: int, k: int, self_loops: bool = True, with_replacement: bool = True, seed=None): ...
-@py_random_state(4)
-def random_k_out_graph(n: int, k: int, alpha: float, self_loops: bool = True, seed=None) -> MultiDiGraph: ...
diff --git a/stubs/networkx/generators/duplication.pyi b/stubs/networkx/generators/duplication.pyi
deleted file mode 100644
index 84189998..00000000
--- a/stubs/networkx/generators/duplication.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..utils import py_random_state
-
-__all__ = ["partial_duplication_graph", "duplication_divergence_graph"]
-
-@py_random_state(4)
-def partial_duplication_graph(N: int, n: int, p: float, q: float, seed=None): ...
-@py_random_state(2)
-def duplication_divergence_graph(n: int, p: float, seed=None) -> Graph: ...
diff --git a/stubs/networkx/generators/ego.pyi b/stubs/networkx/generators/ego.pyi
deleted file mode 100644
index 3f603002..00000000
--- a/stubs/networkx/generators/ego.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-__all__ = ["ego_graph"]
-
-from ..classes.graph import Graph
-
-def ego_graph(G: Graph, n, radius=1, center: bool = True, undirected: bool = False, distance=None): ...
diff --git a/stubs/networkx/generators/expanders.pyi b/stubs/networkx/generators/expanders.pyi
deleted file mode 100644
index ab0f75da..00000000
--- a/stubs/networkx/generators/expanders.pyi
+++ /dev/null
@@ -1,41 +0,0 @@
-import itertools
-
-from ..classes.graph import Graph
-
-__all__ = ["margulis_gabber_galil_graph", "chordal_cycle_graph", "paley_graph"]
-
-# Other discrete torus expanders can be constructed by using the following edge
-# sets. For more information, see Chapter 4, "Expander Graphs", in
-# "Pseudorandomness", by Salil Vadhan.
-#
-# For a directed expander, add edges from (x, y) to:
-#
-#     (x, y),
-#     ((x + 1) % n, y),
-#     (x, (y + 1) % n),
-#     (x, (x + y) % n),
-#     (-y % n, x)
-#
-# For an undirected expander, add the reverse edges.
-#
-# Also appearing in the paper of Gabber and Galil:
-#
-#     (x, y),
-#     (x, (x + y) % n),
-#     (x, (x + y + 1) % n),
-#     ((x + y) % n, y),
-#     ((x + y + 1) % n, y)
-#
-# and:
-#
-#     (x, y),
-#     ((x + 2*y) % n, y),
-#     ((x + (2*y + 1)) % n, y),
-#     ((x + (2*y + 2)) % n, y),
-#     (x, (y + 2*x) % n),
-#     (x, (y + (2*x + 1)) % n),
-#     (x, (y + (2*x + 2)) % n),
-#
-def margulis_gabber_galil_graph(n: int, create_using=None): ...
-def chordal_cycle_graph(p, create_using=None): ...
-def paley_graph(p, create_using=None): ...
diff --git a/stubs/networkx/generators/geometric.pyi b/stubs/networkx/generators/geometric.pyi
deleted file mode 100644
index ba2432ac..00000000
--- a/stubs/networkx/generators/geometric.pyi
+++ /dev/null
@@ -1,76 +0,0 @@
-import math
-from bisect import bisect_left
-from collections.abc import Iterable, Mapping
-from itertools import accumulate, combinations, product
-
-from numpy.typing import ArrayLike
-
-from .._typing import Scalar
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = [
-    "geometric_edges",
-    "geographical_threshold_graph",
-    "navigable_small_world_graph",
-    "random_geometric_graph",
-    "soft_random_geometric_graph",
-    "thresholded_random_geometric_graph",
-    "waxman_graph",
-]
-
-def euclidean(x, y): ...
-def geometric_edges(G: Graph, radius: Scalar, p: Scalar = 2) -> ArrayLike: ...
-@py_random_state(5)
-def random_geometric_graph(
-    n: int | Iterable,
-    radius: float,
-    dim: int = 2,
-    pos: Mapping | None = None,
-    p: float = 2,
-    seed=None,
-) -> Graph: ...
-@py_random_state(6)
-def soft_random_geometric_graph(
-    n: int | Iterable,
-    radius: float,
-    dim: int = 2,
-    pos: Mapping | None = None,
-    p: float = 2,
-    p_dist=None,
-    seed=None,
-) -> Graph: ...
-@py_random_state(7)
-def geographical_threshold_graph(
-    n: int | Iterable,
-    theta: float,
-    dim: int = 2,
-    pos: Mapping | None = None,
-    weight: Mapping | None = None,
-    metric=None,
-    p_dist=None,
-    seed=None,
-) -> Graph: ...
-@py_random_state(6)
-def waxman_graph(
-    n: int | Iterable,
-    beta: float = 0.4,
-    alpha: float = 0.1,
-    L: float | None = None,
-    domain=...,
-    metric=None,
-    seed=None,
-) -> Graph: ...
-@py_random_state(5)
-def navigable_small_world_graph(n: int, p: int = 1, q: int = 1, r: float = 2, dim: int = 2, seed=None): ...
-@py_random_state(7)
-def thresholded_random_geometric_graph(
-    n: int | Iterable,
-    radius: float,
-    theta: float,
-    dim: int = 2,
-    pos: Mapping | None = None,
-    weight: Mapping | None = None,
-    p=2,
-    seed=None,
-) -> Graph: ...
diff --git a/stubs/networkx/generators/harary_graph.pyi b/stubs/networkx/generators/harary_graph.pyi
deleted file mode 100644
index 056bd8f6..00000000
--- a/stubs/networkx/generators/harary_graph.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-
-__all__ = ["hnm_harary_graph", "hkn_harary_graph"]
-
-def hnm_harary_graph(n, m, create_using=None): ...
-def hkn_harary_graph(k, n, create_using=None): ...
diff --git a/stubs/networkx/generators/internet_as_graphs.pyi b/stubs/networkx/generators/internet_as_graphs.pyi
deleted file mode 100644
index 9a917700..00000000
--- a/stubs/networkx/generators/internet_as_graphs.pyi
+++ /dev/null
@@ -1,27 +0,0 @@
-from collections.abc import Mapping
-from typing import Any
-
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = ["random_internet_as_graph"]
-
-def uniform_int_from_avg(a, m, seed): ...
-def choose_pref_attach(degs: Mapping, seed) -> Any: ...
-
-class AS_graph_generator:
-    def __init__(self, n, seed): ...
-    def t_graph(self): ...
-    def add_edge(self, i, j, kind): ...
-    def choose_peer_pref_attach(self, node_list): ...
-    def choose_node_pref_attach(self, node_list): ...
-    def add_customer(self, i, j): ...
-    def add_node(self, i: Any, kind: str, reg2prob: float, avg_deg: float, t_edge_prob: float) -> Any: ...
-    def add_m_peering_link(self, m: Any, to_kind: str) -> bool: ...
-    def add_cp_peering_link(self, cp: Any, to_kind: str) -> bool: ...
-    def graph_regions(self, rn): ...
-    def add_peering_links(self, from_kind, to_kind): ...
-    def generate(self): ...
-
-@py_random_state(1)
-def random_internet_as_graph(n, seed=None): ...
diff --git a/stubs/networkx/generators/intersection.pyi b/stubs/networkx/generators/intersection.pyi
deleted file mode 100644
index 465fe46e..00000000
--- a/stubs/networkx/generators/intersection.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = [
-    "uniform_random_intersection_graph",
-    "k_random_intersection_graph",
-    "general_random_intersection_graph",
-]
-
-@py_random_state(3)
-def uniform_random_intersection_graph(n: int, m: int, p: float, seed=None): ...
-@py_random_state(3)
-def k_random_intersection_graph(n: int, m: int, k: float, seed=None): ...
-@py_random_state(3)
-def general_random_intersection_graph(n: int, m: int, p, seed=None): ...
diff --git a/stubs/networkx/generators/interval_graph.pyi b/stubs/networkx/generators/interval_graph.pyi
deleted file mode 100644
index 03706b2a..00000000
--- a/stubs/networkx/generators/interval_graph.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from collections.abc import Sequence
-
-from ..classes.graph import Graph
-
-__all__ = ["interval_graph"]
-
-def interval_graph(intervals): ...
diff --git a/stubs/networkx/generators/joint_degree_seq.pyi b/stubs/networkx/generators/joint_degree_seq.pyi
deleted file mode 100644
index 9f54f6c3..00000000
--- a/stubs/networkx/generators/joint_degree_seq.pyi
+++ /dev/null
@@ -1,16 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = [
-    "is_valid_joint_degree",
-    "is_valid_directed_joint_degree",
-    "joint_degree_graph",
-    "directed_joint_degree_graph",
-]
-
-def is_valid_joint_degree(joint_degrees) -> bool: ...
-@py_random_state(1)
-def joint_degree_graph(joint_degrees, seed=None) -> Graph: ...
-def is_valid_directed_joint_degree(in_degrees, out_degrees, nkk) -> bool: ...
-@py_random_state(3)
-def directed_joint_degree_graph(in_degrees, out_degrees, nkk, seed=None) -> Graph: ...
diff --git a/stubs/networkx/generators/lattice.pyi b/stubs/networkx/generators/lattice.pyi
deleted file mode 100644
index d652b655..00000000
--- a/stubs/networkx/generators/lattice.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from collections.abc import Iterable
-from itertools import repeat
-from math import sqrt
-
-from ..classes import set_node_attributes
-from ..exception import NetworkXError
-from ..generators.classic import cycle_graph, empty_graph, path_graph
-from ..relabel import relabel_nodes
-from ..utils import flatten, nodes_or_number, pairwise
-
-__all__ = [
-    "grid_2d_graph",
-    "grid_graph",
-    "hypercube_graph",
-    "triangular_lattice_graph",
-    "hexagonal_lattice_graph",
-]
-
-def grid_2d_graph(m, n, periodic: bool | Iterable = False, create_using=None): ...
-def grid_graph(dim, periodic: bool | Iterable = False): ...
-def hypercube_graph(n: int): ...
-def triangular_lattice_graph(m: int, n: int, periodic=False, with_positions=True, create_using=None): ...
-def hexagonal_lattice_graph(m: int, n: int, periodic: bool = False, with_positions=True, create_using=None): ...
diff --git a/stubs/networkx/generators/line.pyi b/stubs/networkx/generators/line.pyi
deleted file mode 100644
index 0806dc39..00000000
--- a/stubs/networkx/generators/line.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from collections import defaultdict
-from functools import partial
-from itertools import combinations
-
-from ..classes.graph import Graph
-from ..utils import arbitrary_element
-from ..utils.decorators import not_implemented_for
-
-__all__ = ["line_graph", "inverse_line_graph"]
-
-def line_graph(G: Graph, create_using=None): ...
-def inverse_line_graph(G: Graph): ...
diff --git a/stubs/networkx/generators/mycielski.pyi b/stubs/networkx/generators/mycielski.pyi
deleted file mode 100644
index 5f2a507c..00000000
--- a/stubs/networkx/generators/mycielski.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["mycielskian", "mycielski_graph"]
-
-def mycielskian(G: Graph, iterations: int = 1): ...
-def mycielski_graph(n: int): ...
diff --git a/stubs/networkx/generators/nonisomorphic_trees.pyi b/stubs/networkx/generators/nonisomorphic_trees.pyi
deleted file mode 100644
index 458943af..00000000
--- a/stubs/networkx/generators/nonisomorphic_trees.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-__all__ = ["nonisomorphic_trees", "number_of_nonisomorphic_trees"]
-
-from ..classes.graph import Graph
-
-def nonisomorphic_trees(order: int, create="graph"): ...
-def number_of_nonisomorphic_trees(order: int): ...
diff --git a/stubs/networkx/generators/random_clustered.pyi b/stubs/networkx/generators/random_clustered.pyi
deleted file mode 100644
index f1dc966b..00000000
--- a/stubs/networkx/generators/random_clustered.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ..classes.graph import Graph
-from ..classes.multigraph import MultiGraph
-from ..utils import py_random_state
-
-__all__ = ["random_clustered_graph"]
-
-@py_random_state(2)
-def random_clustered_graph(joint_degree_sequence, create_using=None, seed=None) -> MultiGraph: ...
diff --git a/stubs/networkx/generators/random_graphs.pyi b/stubs/networkx/generators/random_graphs.pyi
deleted file mode 100644
index 4b93dc1a..00000000
--- a/stubs/networkx/generators/random_graphs.pyi
+++ /dev/null
@@ -1,70 +0,0 @@
-import itertools
-import math
-from collections import defaultdict
-
-from ..classes.graph import Graph
-from ..utils import py_random_state
-from .classic import complete_graph, empty_graph, path_graph, star_graph
-from .degree_seq import degree_sequence_tree
-
-__all__ = [
-    "fast_gnp_random_graph",
-    "gnp_random_graph",
-    "dense_gnm_random_graph",
-    "gnm_random_graph",
-    "erdos_renyi_graph",
-    "binomial_graph",
-    "newman_watts_strogatz_graph",
-    "watts_strogatz_graph",
-    "connected_watts_strogatz_graph",
-    "random_regular_graph",
-    "barabasi_albert_graph",
-    "dual_barabasi_albert_graph",
-    "extended_barabasi_albert_graph",
-    "powerlaw_cluster_graph",
-    "random_lobster",
-    "random_shell_graph",
-    "random_powerlaw_tree",
-    "random_powerlaw_tree_sequence",
-    "random_kernel_graph",
-]
-
-@py_random_state(2)
-def fast_gnp_random_graph(n: int, p: float, seed=None, directed=False): ...
-@py_random_state(2)
-def gnp_random_graph(n: int, p: float, seed=None, directed=False): ...
-
-# add some aliases to common names
-binomial_graph = ...
-erdos_renyi_graph = ...
-
-@py_random_state(2)
-def dense_gnm_random_graph(n: int, m: int, seed=None): ...
-@py_random_state(2)
-def gnm_random_graph(n: int, m: int, seed=None, directed=False): ...
-@py_random_state(3)
-def newman_watts_strogatz_graph(n: int, k: int, p: float, seed=None): ...
-@py_random_state(3)
-def watts_strogatz_graph(n: int, k: int, p: float, seed=None): ...
-@py_random_state(4)
-def connected_watts_strogatz_graph(n: int, k: int, p: float, tries: int = 100, seed=None): ...
-@py_random_state(2)
-def random_regular_graph(d: int, n, seed=None): ...
-@py_random_state(2)
-def barabasi_albert_graph(n: int, m: int, seed=None, initial_graph: Graph | None = None) -> Graph: ...
-@py_random_state(4)
-def dual_barabasi_albert_graph(n: int, m1: int, m2: int, p: float, seed=None, initial_graph: Graph | None = None) -> Graph: ...
-@py_random_state(4)
-def extended_barabasi_albert_graph(n: int, m: int, p: float, q: float, seed=None) -> Graph: ...
-@py_random_state(3)
-def powerlaw_cluster_graph(n: int, m: int, p: float, seed=None): ...
-@py_random_state(3)
-def random_lobster(n: int, p1: float, p2: float, seed=None): ...
-@py_random_state(1)
-def random_shell_graph(constructor, seed=None): ...
-@py_random_state(2)
-def random_powerlaw_tree(n: int, gamma: float = 3, seed=None, tries: int = 100): ...
-@py_random_state(2)
-def random_powerlaw_tree_sequence(n: int, gamma: float = 3, seed=None, tries: int = 100): ...
-@py_random_state(3)
-def random_kernel_graph(n: int, kernel_integral, kernel_root=None, seed=None): ...
diff --git a/stubs/networkx/generators/small.pyi b/stubs/networkx/generators/small.pyi
deleted file mode 100644
index 259b66ba..00000000
--- a/stubs/networkx/generators/small.pyi
+++ /dev/null
@@ -1,63 +0,0 @@
-__all__ = [
-    "make_small_graph",
-    "LCF_graph",
-    "bull_graph",
-    "chvatal_graph",
-    "cubical_graph",
-    "desargues_graph",
-    "diamond_graph",
-    "dodecahedral_graph",
-    "frucht_graph",
-    "heawood_graph",
-    "hoffman_singleton_graph",
-    "house_graph",
-    "house_x_graph",
-    "icosahedral_graph",
-    "krackhardt_kite_graph",
-    "moebius_kantor_graph",
-    "octahedral_graph",
-    "pappus_graph",
-    "petersen_graph",
-    "sedgewick_maze_graph",
-    "tetrahedral_graph",
-    "truncated_cube_graph",
-    "truncated_tetrahedron_graph",
-    "tutte_graph",
-]
-
-from functools import wraps
-
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..generators.classic import complete_graph, cycle_graph, empty_graph, path_graph
-
-def make_small_undirected_graph(graph_description, create_using=None): ...
-def make_small_graph(graph_description, create_using=None): ...
-def LCF_graph(n, shift_list, repeats, create_using=None): ...
-
-# -------------------------------------------------------------------------------
-#   Various small and named graphs
-# -------------------------------------------------------------------------------
-
-def bull_graph(create_using=None): ...
-def chvatal_graph(create_using=None): ...
-def cubical_graph(create_using=None): ...
-def desargues_graph(create_using=None): ...
-def diamond_graph(create_using=None): ...
-def dodecahedral_graph(create_using=None): ...
-def frucht_graph(create_using=None): ...
-def heawood_graph(create_using=None): ...
-def hoffman_singleton_graph(): ...
-def house_graph(create_using=None): ...
-def house_x_graph(create_using=None): ...
-def icosahedral_graph(create_using=None): ...
-def krackhardt_kite_graph(create_using=None): ...
-def moebius_kantor_graph(create_using=None): ...
-def octahedral_graph(create_using=None): ...
-def pappus_graph(): ...
-def petersen_graph(create_using=None): ...
-def sedgewick_maze_graph(create_using=None): ...
-def tetrahedral_graph(create_using=None): ...
-def truncated_cube_graph(create_using=None): ...
-def truncated_tetrahedron_graph(create_using=None): ...
-def tutte_graph(create_using=None): ...
diff --git a/stubs/networkx/generators/social.pyi b/stubs/networkx/generators/social.pyi
deleted file mode 100644
index 328249ff..00000000
--- a/stubs/networkx/generators/social.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from ..classes.graph import Graph
-
-__all__ = [
-    "karate_club_graph",
-    "davis_southern_women_graph",
-    "florentine_families_graph",
-    "les_miserables_graph",
-]
-
-def karate_club_graph(): ...
-def davis_southern_women_graph(): ...
-def florentine_families_graph(): ...
-def les_miserables_graph(): ...
diff --git a/stubs/networkx/generators/spectral_graph_forge.pyi b/stubs/networkx/generators/spectral_graph_forge.pyi
deleted file mode 100644
index 117f2878..00000000
--- a/stubs/networkx/generators/spectral_graph_forge.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import np_random_state
-
-__all__ = ["spectral_graph_forge"]
-
-@np_random_state(3)
-def spectral_graph_forge(G: Graph, alpha: float, transformation: str = "identity", seed=None) -> Graph: ...
diff --git a/stubs/networkx/generators/stochastic.pyi b/stubs/networkx/generators/stochastic.pyi
deleted file mode 100644
index 99c93644..00000000
--- a/stubs/networkx/generators/stochastic.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from ..classes import DiGraph, MultiDiGraph
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["stochastic_graph"]
-
-def stochastic_graph(G: Graph, copy: bool = True, weight="weight"): ...
diff --git a/stubs/networkx/generators/sudoku.pyi b/stubs/networkx/generators/sudoku.pyi
deleted file mode 100644
index fd55ec2d..00000000
--- a/stubs/networkx/generators/sudoku.pyi
+++ /dev/null
@@ -1,6 +0,0 @@
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-
-__all__ = ["sudoku_graph"]
-
-def sudoku_graph(n=3): ...
diff --git a/stubs/networkx/generators/trees.pyi b/stubs/networkx/generators/trees.pyi
deleted file mode 100644
index de7beb4d..00000000
--- a/stubs/networkx/generators/trees.pyi
+++ /dev/null
@@ -1,19 +0,0 @@
-from collections import defaultdict
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = ["prefix_tree", "random_tree", "prefix_tree_recursive"]
-
-def prefix_tree(paths) -> DiGraph: ...
-def prefix_tree_recursive(paths) -> DiGraph: ...
-
-# From the Wikipedia article on Prüfer sequences:
-#
-# > Generating uniformly distributed random Prüfer sequences and
-# > converting them into the corresponding trees is a straightforward
-# > method of generating uniformly distributed random labelled trees.
-#
-@py_random_state(1)
-def random_tree(n: int, seed=None, create_using=None): ...
diff --git a/stubs/networkx/generators/triads.pyi b/stubs/networkx/generators/triads.pyi
deleted file mode 100644
index f781863f..00000000
--- a/stubs/networkx/generators/triads.pyi
+++ /dev/null
@@ -1,14 +0,0 @@
-from networkx import DiGraph
-
-# See https://github.com/networkx/networkx/pull/1474
-# Copyright 2011 Reya Group <http://www.reyagroup.com>
-# Copyright 2011 Alex Levenson <alex@isnotinvain.com>
-# Copyright 2011 Diederik van Liere <diederik.vanliere@rotman.utoronto.ca>
-
-__all__ = ["triad_graph"]
-
-#: Dictionary mapping triad name to list of directed edges in the
-#: digraph representation of that triad (with nodes 'a', 'b', and 'c').
-TRIAD_EDGES: dict = ...
-
-def triad_graph(triad_name: str) -> DiGraph: ...
diff --git a/stubs/networkx/lazy_imports.pyi b/stubs/networkx/lazy_imports.pyi
deleted file mode 100644
index a091fabe..00000000
--- a/stubs/networkx/lazy_imports.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-import importlib
-import importlib.util
-import inspect
-import os
-import sys
-import types
-from collections.abc import Mapping
-
-__all__ = ["attach"]
-
-def attach(module_name: str, submodules: set | None = None, submod_attrs: Mapping | None = None): ...
-
-class DelayedImportErrorModule(types.ModuleType):
-    def __init__(self, frame_data, *args, **kwargs): ...
-    def __getattr__(self, x): ...
diff --git a/stubs/networkx/linalg/__init__.pyi b/stubs/networkx/linalg/__init__.pyi
deleted file mode 100644
index 633f26e9..00000000
--- a/stubs/networkx/linalg/__init__.pyi
+++ /dev/null
@@ -1,31 +0,0 @@
-from . import (
-    attrmatrix as attrmatrix,
-    bethehessianmatrix as bethehessianmatrix,
-    graphmatrix as graphmatrix,
-    laplacianmatrix as laplacianmatrix,
-    modularitymatrix as modularitymatrix,
-    spectrum as spectrum,
-)
-from .algebraicconnectivity import (
-    algebraic_connectivity as algebraic_connectivity,
-    fiedler_vector as fiedler_vector,
-    spectral_ordering as spectral_ordering,
-)
-from .attrmatrix import attr_matrix as attr_matrix, attr_sparse_matrix as attr_sparse_matrix
-from .bethehessianmatrix import bethe_hessian_matrix as bethe_hessian_matrix
-from .graphmatrix import adj_matrix as adj_matrix, adjacency_matrix as adjacency_matrix, incidence_matrix as incidence_matrix
-from .laplacianmatrix import (
-    directed_combinatorial_laplacian_matrix as directed_combinatorial_laplacian_matrix,
-    directed_laplacian_matrix as directed_laplacian_matrix,
-    laplacian_matrix as laplacian_matrix,
-    normalized_laplacian_matrix as normalized_laplacian_matrix,
-    total_spanning_tree_weight as total_spanning_tree_weight,
-)
-from .modularitymatrix import directed_modularity_matrix as directed_modularity_matrix, modularity_matrix as modularity_matrix
-from .spectrum import (
-    adjacency_spectrum as adjacency_spectrum,
-    bethe_hessian_spectrum as bethe_hessian_spectrum,
-    laplacian_spectrum as laplacian_spectrum,
-    modularity_spectrum as modularity_spectrum,
-    normalized_laplacian_spectrum as normalized_laplacian_spectrum,
-)
diff --git a/stubs/networkx/linalg/algebraicconnectivity.pyi b/stubs/networkx/linalg/algebraicconnectivity.pyi
deleted file mode 100644
index 3b8d61f4..00000000
--- a/stubs/networkx/linalg/algebraicconnectivity.pyi
+++ /dev/null
@@ -1,43 +0,0 @@
-from functools import partial
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for, np_random_state, reverse_cuthill_mckee_ordering
-
-__all__ = ["algebraic_connectivity", "fiedler_vector", "spectral_ordering"]
-
-class _PCGSolver:
-    def __init__(self, A, M): ...
-    def solve(self, B, tol): ...
-    def _solve(self, b, tol): ...
-
-class _LUSolver:
-    def __init__(self, A): ...
-    def solve(self, B, tol=None): ...
-
-@np_random_state(5)
-def algebraic_connectivity(
-    G: Graph,
-    weight="weight",
-    normalized=False,
-    tol=1e-8,
-    method="tracemin_pcg",
-    seed=None,
-) -> float: ...
-@np_random_state(5)
-def fiedler_vector(
-    G: Graph,
-    weight="weight",
-    normalized=False,
-    tol=1e-8,
-    method="tracemin_pcg",
-    seed=None,
-): ...
-@np_random_state(5)
-def spectral_ordering(
-    G: Graph,
-    weight="weight",
-    normalized=False,
-    tol=1e-8,
-    method="tracemin_pcg",
-    seed=None,
-): ...
diff --git a/stubs/networkx/linalg/attrmatrix.pyi b/stubs/networkx/linalg/attrmatrix.pyi
deleted file mode 100644
index 66f5a401..00000000
--- a/stubs/networkx/linalg/attrmatrix.pyi
+++ /dev/null
@@ -1,23 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = ["attr_matrix", "attr_sparse_matrix"]
-
-def attr_matrix(
-    G: Graph,
-    edge_attr: str | None = None,
-    node_attr: str | None = None,
-    normalized: bool = False,
-    rc_order: ArrayLike | None = None,
-    dtype=None,
-    order=None,
-): ...
-def attr_sparse_matrix(
-    G: Graph,
-    edge_attr: str | None = None,
-    node_attr: str | None = None,
-    normalized: bool = False,
-    rc_order: ArrayLike | None = None,
-    dtype=None,
-): ...
diff --git a/stubs/networkx/linalg/bethehessianmatrix.pyi b/stubs/networkx/linalg/bethehessianmatrix.pyi
deleted file mode 100644
index 01abf4c8..00000000
--- a/stubs/networkx/linalg/bethehessianmatrix.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["bethe_hessian_matrix"]
-
-def bethe_hessian_matrix(G: Graph, r: float | None = None, nodelist: ArrayLike | None = None): ...
diff --git a/stubs/networkx/linalg/graphmatrix.pyi b/stubs/networkx/linalg/graphmatrix.pyi
deleted file mode 100644
index 04f597d6..00000000
--- a/stubs/networkx/linalg/graphmatrix.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-
-__all__ = ["incidence_matrix", "adj_matrix", "adjacency_matrix"]
-
-def incidence_matrix(G: Graph, nodelist=None, edgelist=None, oriented=False, weight=None): ...
-def adjacency_matrix(G: Graph, nodelist: ArrayLike | None = None, dtype=None, weight="weight"): ...
-
-adj_matrix = ...
diff --git a/stubs/networkx/linalg/laplacianmatrix.pyi b/stubs/networkx/linalg/laplacianmatrix.pyi
deleted file mode 100644
index ca3a2a7a..00000000
--- a/stubs/networkx/linalg/laplacianmatrix.pyi
+++ /dev/null
@@ -1,35 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = [
-    "laplacian_matrix",
-    "normalized_laplacian_matrix",
-    "total_spanning_tree_weight",
-    "directed_laplacian_matrix",
-    "directed_combinatorial_laplacian_matrix",
-]
-
-def laplacian_matrix(G: Graph, nodelist: ArrayLike | None = None, weight="weight"): ...
-def normalized_laplacian_matrix(G: Graph, nodelist: ArrayLike | None = None, weight="weight"): ...
-def total_spanning_tree_weight(G: Graph, weight: str | None = None) -> float: ...
-
-###############################################################################
-# Code based on work from https://github.com/bjedwards
-
-def directed_laplacian_matrix(
-    G: DiGraph,
-    nodelist: ArrayLike | None = None,
-    weight="weight",
-    walk_type=None,
-    alpha=0.95,
-): ...
-def directed_combinatorial_laplacian_matrix(
-    G: DiGraph,
-    nodelist: ArrayLike | None = None,
-    weight="weight",
-    walk_type=None,
-    alpha=0.95,
-): ...
diff --git a/stubs/networkx/linalg/modularitymatrix.pyi b/stubs/networkx/linalg/modularitymatrix.pyi
deleted file mode 100644
index cd75f9e2..00000000
--- a/stubs/networkx/linalg/modularitymatrix.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-from numpy.typing import ArrayLike
-
-from ..classes.digraph import DiGraph
-from ..classes.graph import Graph
-from ..utils import not_implemented_for
-
-__all__ = ["modularity_matrix", "directed_modularity_matrix"]
-
-def modularity_matrix(G: Graph, nodelist: ArrayLike | None = None, weight=None): ...
-def directed_modularity_matrix(G: DiGraph, nodelist: ArrayLike | None = None, weight=None): ...
diff --git a/stubs/networkx/linalg/spectrum.pyi b/stubs/networkx/linalg/spectrum.pyi
deleted file mode 100644
index 9c0329ed..00000000
--- a/stubs/networkx/linalg/spectrum.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-from ..classes.graph import Graph
-
-__all__ = [
-    "laplacian_spectrum",
-    "adjacency_spectrum",
-    "modularity_spectrum",
-    "normalized_laplacian_spectrum",
-    "bethe_hessian_spectrum",
-]
-
-def laplacian_spectrum(G: Graph, weight="weight"): ...
-def normalized_laplacian_spectrum(G: Graph, weight="weight"): ...
-def adjacency_spectrum(G: Graph, weight="weight"): ...
-def modularity_spectrum(G: Graph): ...
-def bethe_hessian_spectrum(G: Graph, r: float | None = None): ...
diff --git a/stubs/networkx/readwrite/__init__.pyi b/stubs/networkx/readwrite/__init__.pyi
deleted file mode 100644
index a0617464..00000000
--- a/stubs/networkx/readwrite/__init__.pyi
+++ /dev/null
@@ -1,60 +0,0 @@
-from .adjlist import (
-    generate_adjlist as generate_adjlist,
-    parse_adjlist as parse_adjlist,
-    read_adjlist as read_adjlist,
-    write_adjlist as write_adjlist,
-)
-from .edgelist import (
-    generate_edgelist as generate_edgelist,
-    parse_edgelist as parse_edgelist,
-    read_edgelist as read_edgelist,
-    read_weighted_edgelist as read_weighted_edgelist,
-    write_edgelist as write_edgelist,
-    write_weighted_edgelist as write_weighted_edgelist,
-)
-from .gexf import (
-    generate_gexf as generate_gexf,
-    read_gexf as read_gexf,
-    relabel_gexf_graph as relabel_gexf_graph,
-    write_gexf as write_gexf,
-)
-from .gml import generate_gml as generate_gml, parse_gml as parse_gml, read_gml as read_gml, write_gml as write_gml
-from .gpickle import read_gpickle as read_gpickle, write_gpickle as write_gpickle
-from .graph6 import (
-    from_graph6_bytes as from_graph6_bytes,
-    read_graph6 as read_graph6,
-    to_graph6_bytes as to_graph6_bytes,
-    write_graph6 as write_graph6,
-)
-from .graphml import (
-    GraphMLReader as GraphMLReader,
-    GraphMLWriter as GraphMLWriter,
-    generate_graphml as generate_graphml,
-    parse_graphml as parse_graphml,
-    read_graphml as read_graphml,
-    write_graphml as write_graphml,
-    write_graphml_lxml as write_graphml_lxml,
-    write_graphml_xml as write_graphml_xml,
-)
-from .json_graph import *
-from .leda import parse_leda as parse_leda, read_leda as read_leda
-from .multiline_adjlist import (
-    generate_multiline_adjlist as generate_multiline_adjlist,
-    parse_multiline_adjlist as parse_multiline_adjlist,
-    read_multiline_adjlist as read_multiline_adjlist,
-    write_multiline_adjlist as write_multiline_adjlist,
-)
-from .nx_shp import read_shp as read_shp, write_shp as write_shp
-from .pajek import (
-    generate_pajek as generate_pajek,
-    parse_pajek as parse_pajek,
-    read_pajek as read_pajek,
-    write_pajek as write_pajek,
-)
-from .sparse6 import (
-    from_sparse6_bytes as from_sparse6_bytes,
-    read_sparse6 as read_sparse6,
-    to_sparse6_bytes as to_sparse6_bytes,
-    write_sparse6 as write_sparse6,
-)
-from .text import forest_str as forest_str
diff --git a/stubs/networkx/readwrite/adjlist.pyi b/stubs/networkx/readwrite/adjlist.pyi
deleted file mode 100644
index 959a9b24..00000000
--- a/stubs/networkx/readwrite/adjlist.pyi
+++ /dev/null
@@ -1,22 +0,0 @@
-__all__ = ["generate_adjlist", "write_adjlist", "parse_adjlist", "read_adjlist"]
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-def generate_adjlist(G: Graph, delimiter: str = " ") -> str: ...
-def write_adjlist(G: Graph, path, comments: str = "#", delimiter: str = " ", encoding: str = "utf-8"): ...
-def parse_adjlist(
-    lines,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-): ...
-def read_adjlist(
-    path,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    encoding="utf-8",
-): ...
diff --git a/stubs/networkx/readwrite/edgelist.pyi b/stubs/networkx/readwrite/edgelist.pyi
deleted file mode 100644
index d95f49b1..00000000
--- a/stubs/networkx/readwrite/edgelist.pyi
+++ /dev/null
@@ -1,50 +0,0 @@
-from numpy.typing import ArrayLike
-
-__all__ = [
-    "generate_edgelist",
-    "write_edgelist",
-    "parse_edgelist",
-    "read_edgelist",
-    "read_weighted_edgelist",
-    "write_weighted_edgelist",
-]
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-def generate_edgelist(G: Graph, delimiter: str = " ", data=True) -> str: ...
-def write_edgelist(
-    G: Graph,
-    path,
-    comments: str = "#",
-    delimiter: str = " ",
-    data: bool | ArrayLike = True,
-    encoding: str = "utf-8",
-): ...
-def parse_edgelist(
-    lines,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    data=True,
-): ...
-def read_edgelist(
-    path,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    data=True,
-    edgetype=None,
-    encoding: str = "utf-8",
-): ...
-def write_weighted_edgelist(G: Graph, path, comments: str = "#", delimiter: str = " ", encoding: str = "utf-8"): ...
-def read_weighted_edgelist(
-    path,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    encoding: str = "utf-8",
-): ...
diff --git a/stubs/networkx/readwrite/gexf.pyi b/stubs/networkx/readwrite/gexf.pyi
deleted file mode 100644
index 639d881f..00000000
--- a/stubs/networkx/readwrite/gexf.pyi
+++ /dev/null
@@ -1,58 +0,0 @@
-import itertools
-import time
-from xml.etree.ElementTree import Element, ElementTree, SubElement, register_namespace, tostring
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-__all__ = ["write_gexf", "read_gexf", "relabel_gexf_graph", "generate_gexf"]
-
-def write_gexf(G: Graph, path, encoding="utf-8", prettyprint=True, version="1.2draft"): ...
-def generate_gexf(G: Graph, encoding="utf-8", prettyprint=True, version="1.2draft"): ...
-def read_gexf(path, node_type=None, relabel=False, version="1.2draft"): ...
-
-class GEXF:
-    versions: dict
-
-    def construct_types(self): ...
-
-    # http://www.w3.org/TR/xmlschema-2/#boolean
-    convert_bool: dict = ...
-
-    def set_version(self, version): ...
-
-class GEXFWriter(GEXF):
-    # class for writing GEXF format files
-    # use write_gexf() function
-    def __init__(self, graph=None, encoding="utf-8", prettyprint=True, version="1.2draft"): ...
-    def __str__(self): ...
-    def add_graph(self, G): ...
-    def add_nodes(self, G: Graph, graph_element): ...
-    def add_edges(self, G: Graph, graph_element): ...
-    def add_attributes(self, node_or_edge, xml_obj, data, default): ...
-    def get_attr_id(self, title, attr_type, edge_or_node, default, mode): ...
-    def add_viz(self, element, node_data): ...
-    def add_parents(self, node_element, node_data): ...
-    def add_slices(self, node_or_edge_element, node_or_edge_data): ...
-    def add_spells(self, node_or_edge_element, node_or_edge_data): ...
-    def alter_graph_mode_timeformat(self, start_or_end): ...
-    def write(self, fh): ...
-    def indent(self, elem, level=0): ...
-
-class GEXFReader(GEXF):
-    # Class to read GEXF format files
-    # use read_gexf() function
-    def __init__(self, node_type=None, version="1.2draft"): ...
-    def __call__(self, stream): ...
-    def make_graph(self, graph_xml): ...
-    def add_node(self, G: Graph, node_xml, node_attr, node_pid=None): ...
-    def add_start_end(self, data, xml): ...
-    def add_viz(self, data, node_xml): ...
-    def add_parents(self, data, node_xml): ...
-    def add_slices(self, data, node_or_edge_xml): ...
-    def add_spells(self, data, node_or_edge_xml): ...
-    def add_edge(self, G: Graph, edge_element, edge_attr): ...
-    def decode_attr_elements(self, gexf_keys, obj_xml): ...
-    def find_gexf_attributes(self, attributes_element): ...
-
-def relabel_gexf_graph(G: Graph): ...
diff --git a/stubs/networkx/readwrite/gml.pyi b/stubs/networkx/readwrite/gml.pyi
deleted file mode 100644
index 961f1c9d..00000000
--- a/stubs/networkx/readwrite/gml.pyi
+++ /dev/null
@@ -1,47 +0,0 @@
-import html.entities as htmlentitydefs
-import re
-import warnings
-from ast import literal_eval
-from collections import defaultdict
-from collections.abc import Iterable
-from enum import Enum
-from io import StringIO
-from typing import Any, Callable, NamedTuple
-
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..utils import open_file
-
-__all__ = ["read_gml", "parse_gml", "generate_gml", "write_gml"]
-
-def escape(text): ...
-def unescape(text): ...
-def literal_destringizer(rep: str) -> Any: ...
-def read_gml(path, label: str = "label", destringizer: Callable | None = None): ...
-def parse_gml(
-    lines: str | Iterable[str],
-    label: str = "label",
-    destringizer: Callable | None = None,
-): ...
-
-class Pattern(Enum):
-    KEYS = ...
-    REALS = ...
-    INTS = ...
-    STRINGS = ...
-    DICT_START = ...
-    DICT_END = ...
-    COMMENT_WHITESPACE = ...
-
-class Token(NamedTuple):
-    category: Pattern = ...
-    value: Any = ...
-    line: int = ...
-    position: int = ...
-
-LIST_START_VALUE: str = ...
-
-def parse_gml_lines(lines, label, destringizer): ...
-def literal_stringizer(value: Any) -> str: ...
-def generate_gml(G: Graph, stringizer: Callable | None = None): ...
-def write_gml(G: Graph, path, stringizer: Callable | None = None): ...
diff --git a/stubs/networkx/readwrite/gpickle.pyi b/stubs/networkx/readwrite/gpickle.pyi
deleted file mode 100644
index 21e8e37d..00000000
--- a/stubs/networkx/readwrite/gpickle.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-__all__ = ["read_gpickle", "write_gpickle"]
-
-import pickle
-import warnings
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-def write_gpickle(G: Graph, path, protocol=...): ...
-def read_gpickle(path): ...
diff --git a/stubs/networkx/readwrite/graph6.pyi b/stubs/networkx/readwrite/graph6.pyi
deleted file mode 100644
index 84efab5f..00000000
--- a/stubs/networkx/readwrite/graph6.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-from collections.abc import Iterable
-
-# Original author: D. Eppstein, UC Irvine, August 12, 2003.
-# The original code at http://www.ics.uci.edu/~eppstein/PADS/ is public domain.
-from itertools import islice
-
-from numpy.typing import ArrayLike
-
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..utils import not_implemented_for, open_file
-
-__all__ = ["from_graph6_bytes", "read_graph6", "to_graph6_bytes", "write_graph6"]
-
-def from_graph6_bytes(bytes_in) -> Graph: ...
-def to_graph6_bytes(G: Graph, nodes: ArrayLike | Iterable | None = None, header: bool = True): ...
-def read_graph6(path): ...
-def write_graph6(G: Graph, path: str, nodes: ArrayLike | Iterable | None = None, header: bool = True): ...
-def write_graph6_file(G: Graph, f, nodes: ArrayLike | Iterable | None = None, header: bool = True): ...
-def data_to_n(data): ...
-def n_to_data(n): ...
diff --git a/stubs/networkx/readwrite/graphml.pyi b/stubs/networkx/readwrite/graphml.pyi
deleted file mode 100644
index 81e6c0af..00000000
--- a/stubs/networkx/readwrite/graphml.pyi
+++ /dev/null
@@ -1,115 +0,0 @@
-import warnings
-from collections import defaultdict
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-__all__ = [
-    "write_graphml",
-    "read_graphml",
-    "generate_graphml",
-    "write_graphml_xml",
-    "write_graphml_lxml",
-    "parse_graphml",
-    "GraphMLWriter",
-    "GraphMLReader",
-]
-
-def write_graphml_xml(
-    G: Graph,
-    path,
-    encoding="utf-8",
-    prettyprint=True,
-    infer_numeric_types: bool = False,
-    named_key_ids=False,
-    edge_id_from_attribute=None,
-): ...
-def write_graphml_lxml(
-    G: Graph,
-    path,
-    encoding="utf-8",
-    prettyprint=True,
-    infer_numeric_types: bool = False,
-    named_key_ids=False,
-    edge_id_from_attribute=None,
-): ...
-def generate_graphml(
-    G: Graph,
-    encoding="utf-8",
-    prettyprint=True,
-    named_key_ids=False,
-    edge_id_from_attribute=None,
-): ...
-def read_graphml(path, node_type=..., edge_key_type=..., force_multigraph=False): ...
-def parse_graphml(graphml_string: str, node_type=..., edge_key_type=..., force_multigraph=False): ...
-
-class GraphML:
-    NS_GRAPHML: str = ...
-    NS_XSI: str = ...
-    # xmlns:y="http://www.yworks.com/xml/graphml"
-    NS_Y: str = ...
-    SCHEMALOCATION = ...
-
-    def construct_types(self): ...
-
-    # This page says that data types in GraphML follow Java(TM).
-    #  http://graphml.graphdrawing.org/primer/graphml-primer.html#AttributesDefinition
-    # true and false are the only boolean literals:
-    #  http://en.wikibooks.org/wiki/Java_Programming/Literals#Boolean_Literals
-    convert_bool: dict = ...
-
-    def get_xml_type(self, key): ...
-
-class GraphMLWriter(GraphML):
-    def __init__(
-        self,
-        graph=None,
-        encoding="utf-8",
-        prettyprint=True,
-        infer_numeric_types=False,
-        named_key_ids=False,
-        edge_id_from_attribute=None,
-    ): ...
-    def __str__(self): ...
-    def attr_type(self, name, scope, value): ...
-    def get_key(self, name, attr_type, scope, default): ...
-    def add_data(self, name, element_type, value, scope="all", default=None): ...
-    def add_attributes(self, scope, xml_obj, data, default): ...
-    def add_nodes(self, G: Graph, graph_element): ...
-    def add_edges(self, G: Graph, graph_element): ...
-    def add_graph_element(self, G): ...
-    def add_graphs(self, graph_list): ...
-    def dump(self, stream): ...
-    def indent(self, elem, level=0): ...
-
-class IncrementalElement:
-    def __init__(self, xml, prettyprint): ...
-    def append(self, element): ...
-
-class GraphMLWriterLxml(GraphMLWriter):
-    def __init__(
-        self,
-        path,
-        graph=None,
-        encoding="utf-8",
-        prettyprint=True,
-        infer_numeric_types=False,
-        named_key_ids=False,
-        edge_id_from_attribute=None,
-    ): ...
-    def add_graph_element(self, G): ...
-    def add_attributes(self, scope, xml_obj, data, default): ...
-    def __str__(self): ...
-    def dump(self): ...
-
-# default is lxml is present.
-write_graphml = ...
-
-class GraphMLReader(GraphML):
-    def __init__(self, node_type=..., edge_key_type=..., force_multigraph=False): ...
-    def __call__(self, path=None, string=None): ...
-    def make_graph(self, graph_xml, graphml_keys, defaults, G=None): ...
-    def add_node(self, G: Graph, node_xml, graphml_keys, defaults): ...
-    def add_edge(self, G: Graph, edge_element, graphml_keys): ...
-    def decode_data_elements(self, graphml_keys, obj_xml): ...
-    def find_graphml_keys(self, graph_element): ...
diff --git a/stubs/networkx/readwrite/json_graph/__init__.pyi b/stubs/networkx/readwrite/json_graph/__init__.pyi
deleted file mode 100644
index 34ff4dca..00000000
--- a/stubs/networkx/readwrite/json_graph/__init__.pyi
+++ /dev/null
@@ -1,5 +0,0 @@
-from .adjacency import adjacency_data as adjacency_data, adjacency_graph as adjacency_graph
-from .cytoscape import cytoscape_data as cytoscape_data, cytoscape_graph as cytoscape_graph
-from .jit import jit_data as jit_data, jit_graph as jit_graph
-from .node_link import node_link_data as node_link_data, node_link_graph as node_link_graph
-from .tree import tree_data as tree_data, tree_graph as tree_graph
diff --git a/stubs/networkx/readwrite/json_graph/adjacency.pyi b/stubs/networkx/readwrite/json_graph/adjacency.pyi
deleted file mode 100644
index ab450016..00000000
--- a/stubs/networkx/readwrite/json_graph/adjacency.pyi
+++ /dev/null
@@ -1,11 +0,0 @@
-from collections.abc import Mapping
-from itertools import chain
-
-from ...classes.graph import Graph
-
-__all__ = ["adjacency_data", "adjacency_graph"]
-
-_attrs = ...
-
-def adjacency_data(G: Graph, attrs: Mapping = ...) -> Mapping: ...
-def adjacency_graph(data: Mapping, directed: bool = False, multigraph: bool = True, attrs: Mapping = ...): ...
diff --git a/stubs/networkx/readwrite/json_graph/cytoscape.pyi b/stubs/networkx/readwrite/json_graph/cytoscape.pyi
deleted file mode 100644
index 32722248..00000000
--- a/stubs/networkx/readwrite/json_graph/cytoscape.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections.abc import Mapping
-
-from ...classes.graph import Graph
-
-__all__ = ["cytoscape_data", "cytoscape_graph"]
-
-def cytoscape_data(G: Graph, attrs=None, name: str = "name", ident: str = "id") -> Mapping: ...
-def cytoscape_graph(data: Mapping, attrs=None, name: str = "name", ident: str = "id"): ...
diff --git a/stubs/networkx/readwrite/json_graph/jit.pyi b/stubs/networkx/readwrite/json_graph/jit.pyi
deleted file mode 100644
index 604abd0b..00000000
--- a/stubs/networkx/readwrite/json_graph/jit.pyi
+++ /dev/null
@@ -1,10 +0,0 @@
-import json
-import warnings
-
-from ...classes.graph import Graph
-from ...utils.decorators import not_implemented_for
-
-__all__ = ["jit_graph", "jit_data"]
-
-def jit_graph(data, create_using=None): ...
-def jit_data(G: Graph, indent=None, default=None): ...
diff --git a/stubs/networkx/readwrite/json_graph/node_link.pyi b/stubs/networkx/readwrite/json_graph/node_link.pyi
deleted file mode 100644
index c774da72..00000000
--- a/stubs/networkx/readwrite/json_graph/node_link.pyi
+++ /dev/null
@@ -1,31 +0,0 @@
-from collections.abc import Mapping
-from itertools import chain, count
-
-from ...classes.graph import Graph
-
-__all__ = ["node_link_data", "node_link_graph"]
-
-_attrs = ...
-
-def node_link_data(
-    G: Graph,
-    attrs: Mapping | None = None,
-    *,
-    source: str = "source",
-    target: str = "target",
-    name: str = "id",
-    key: str = "key",
-    link: str = "links",
-) -> Mapping: ...
-def node_link_graph(
-    data: Mapping,
-    directed: bool = False,
-    multigraph: bool = True,
-    attrs: Mapping | None = None,
-    *,
-    source: str = "source",
-    target: str = "target",
-    name: str = "id",
-    key: str = "key",
-    link: str = "links",
-): ...
diff --git a/stubs/networkx/readwrite/json_graph/tree.pyi b/stubs/networkx/readwrite/json_graph/tree.pyi
deleted file mode 100644
index c8ac60a9..00000000
--- a/stubs/networkx/readwrite/json_graph/tree.pyi
+++ /dev/null
@@ -1,21 +0,0 @@
-from collections.abc import Mapping
-from itertools import chain
-
-from ...classes.graph import Graph
-
-__all__ = ["tree_data", "tree_graph"]
-
-# NOTE: Remove attrs from signature in 3.0
-def tree_data(
-    G: Graph,
-    root,
-    attrs: Mapping | None = None,
-    ident: str = "id",
-    children: str = "children",
-) -> Mapping: ...
-def tree_graph(
-    data: Mapping,
-    attrs: Mapping | None = None,
-    ident: str = "id",
-    children: str = "children",
-): ...
diff --git a/stubs/networkx/readwrite/leda.pyi b/stubs/networkx/readwrite/leda.pyi
deleted file mode 100644
index 8465714f..00000000
--- a/stubs/networkx/readwrite/leda.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from collections.abc import Iterable
-
-# Original author: D. Eppstein, UC Irvine, August 12, 2003.
-# The original code at http://www.ics.uci.edu/~eppstein/PADS/ is public domain.
-
-__all__ = ["read_leda", "parse_leda"]
-
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..utils import open_file
-
-def read_leda(path, encoding="UTF-8"): ...
-def parse_leda(lines: str | Iterable): ...
diff --git a/stubs/networkx/readwrite/multiline_adjlist.pyi b/stubs/networkx/readwrite/multiline_adjlist.pyi
deleted file mode 100644
index c6ee18ae..00000000
--- a/stubs/networkx/readwrite/multiline_adjlist.pyi
+++ /dev/null
@@ -1,29 +0,0 @@
-__all__ = [
-    "generate_multiline_adjlist",
-    "write_multiline_adjlist",
-    "parse_multiline_adjlist",
-    "read_multiline_adjlist",
-]
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-def generate_multiline_adjlist(G: Graph, delimiter: str = " ") -> str: ...
-def write_multiline_adjlist(G: Graph, path, delimiter: str = " ", comments: str = "#", encoding: str = "utf-8"): ...
-def parse_multiline_adjlist(
-    lines,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    edgetype=None,
-): ...
-def read_multiline_adjlist(
-    path,
-    comments: str = "#",
-    delimiter: str | None = None,
-    create_using=None,
-    nodetype=None,
-    edgetype=None,
-    encoding="utf-8",
-): ...
diff --git a/stubs/networkx/readwrite/nx_shp.pyi b/stubs/networkx/readwrite/nx_shp.pyi
deleted file mode 100644
index 36cbcf46..00000000
--- a/stubs/networkx/readwrite/nx_shp.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-import warnings
-
-from ..classes.graph import Graph
-
-__all__ = ["read_shp", "write_shp"]
-
-def read_shp(path, simplify: bool = True, geom_attrs: bool = True, strict: bool = True): ...
-def edges_from_line(geom, attrs, simplify=True, geom_attrs=True): ...
-def write_shp(G: Graph, outdir): ...
diff --git a/stubs/networkx/readwrite/nx_yaml.pyi b/stubs/networkx/readwrite/nx_yaml.pyi
deleted file mode 100644
index 8b137891..00000000
--- a/stubs/networkx/readwrite/nx_yaml.pyi
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/stubs/networkx/readwrite/p2g.pyi b/stubs/networkx/readwrite/p2g.pyi
deleted file mode 100644
index 54b9141d..00000000
--- a/stubs/networkx/readwrite/p2g.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-import networkx
-
-from ..classes.graph import Graph
-from ..classes.multidigraph import MultiDiGraph
-from ..utils import open_file
-
-def write_p2g(G: Graph, path, encoding="utf-8"): ...
-def read_p2g(path, encoding="utf-8") -> MultiDiGraph: ...
-def parse_p2g(lines) -> MultiDiGraph: ...
diff --git a/stubs/networkx/readwrite/pajek.pyi b/stubs/networkx/readwrite/pajek.pyi
deleted file mode 100644
index b4636035..00000000
--- a/stubs/networkx/readwrite/pajek.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-import warnings
-from collections.abc import Iterable
-
-from ..classes.graph import Graph
-from ..utils import open_file
-
-__all__ = ["read_pajek", "parse_pajek", "generate_pajek", "write_pajek"]
-
-def generate_pajek(G: Graph): ...
-def write_pajek(G: Graph, path, encoding="UTF-8"): ...
-def read_pajek(path, encoding="UTF-8"): ...
-def parse_pajek(lines: str | Iterable): ...
-def make_qstr(t): ...
diff --git a/stubs/networkx/readwrite/sparse6.pyi b/stubs/networkx/readwrite/sparse6.pyi
deleted file mode 100644
index 1efae49c..00000000
--- a/stubs/networkx/readwrite/sparse6.pyi
+++ /dev/null
@@ -1,17 +0,0 @@
-from collections.abc import Iterable
-
-from numpy.typing import ArrayLike
-
-# Original author: D. Eppstein, UC Irvine, August 12, 2003.
-# The original code at https://www.ics.uci.edu/~eppstein/PADS/ is public domain.
-from ..classes.graph import Graph
-from ..exception import NetworkXError
-from ..readwrite.graph6 import data_to_n, n_to_data
-from ..utils import not_implemented_for, open_file
-
-__all__ = ["from_sparse6_bytes", "read_sparse6", "to_sparse6_bytes", "write_sparse6"]
-
-def from_sparse6_bytes(string: str) -> Graph: ...
-def to_sparse6_bytes(G: Graph, nodes: ArrayLike | Iterable | None = None, header: bool = True): ...
-def read_sparse6(path): ...
-def write_sparse6(G: Graph, path, nodes: ArrayLike | Iterable | None = None, header: bool = True): ...
diff --git a/stubs/networkx/readwrite/text.pyi b/stubs/networkx/readwrite/text.pyi
deleted file mode 100644
index a13d3661..00000000
--- a/stubs/networkx/readwrite/text.pyi
+++ /dev/null
@@ -1,13 +0,0 @@
-from typing import Callable
-
-from numpy.typing import ArrayLike
-
-__all__ = ["forest_str"]
-
-def forest_str(
-    graph,
-    with_labels: bool = True,
-    sources: ArrayLike | None = None,
-    write: Callable | None = None,
-    ascii_only: bool = False,
-): ...
diff --git a/stubs/networkx/relabel.pyi b/stubs/networkx/relabel.pyi
deleted file mode 100644
index 9fc84ed5..00000000
--- a/stubs/networkx/relabel.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from collections.abc import Mapping
-
-from .classes.graph import Graph
-
-__all__ = ["convert_node_labels_to_integers", "relabel_nodes"]
-
-def relabel_nodes(G: Graph, mapping: Mapping, copy=True): ...
-def convert_node_labels_to_integers(G: Graph, first_label=0, ordering: str = "default", label_attribute=None): ...
diff --git a/stubs/networkx/testing/__init__.pyi b/stubs/networkx/testing/__init__.pyi
deleted file mode 100644
index ecaa565f..00000000
--- a/stubs/networkx/testing/__init__.pyi
+++ /dev/null
@@ -1,7 +0,0 @@
-from .test import run as run
-from .utils import (
-    almost_equal as almost_equal,
-    assert_edges_equal as assert_edges_equal,
-    assert_graphs_equal as assert_graphs_equal,
-    assert_nodes_equal as assert_nodes_equal,
-)
diff --git a/stubs/networkx/testing/test.pyi b/stubs/networkx/testing/test.pyi
deleted file mode 100644
index 13702b01..00000000
--- a/stubs/networkx/testing/test.pyi
+++ /dev/null
@@ -1,3 +0,0 @@
-import warnings
-
-def run(verbosity=1, doctest: bool = False): ...
diff --git a/stubs/networkx/testing/utils.pyi b/stubs/networkx/testing/utils.pyi
deleted file mode 100644
index a0d47669..00000000
--- a/stubs/networkx/testing/utils.pyi
+++ /dev/null
@@ -1,15 +0,0 @@
-import warnings
-
-from ..utils import edges_equal, graphs_equal, nodes_equal
-
-__all__ = [
-    "assert_nodes_equal",
-    "assert_edges_equal",
-    "assert_graphs_equal",
-    "almost_equal",
-]
-
-def almost_equal(x, y, places=7): ...
-def assert_nodes_equal(nodes1, nodes2): ...
-def assert_edges_equal(edges1, edges2): ...
-def assert_graphs_equal(graph1, graph2): ...
diff --git a/stubs/networkx/utils/__init__.pyi b/stubs/networkx/utils/__init__.pyi
deleted file mode 100644
index 65990e53..00000000
--- a/stubs/networkx/utils/__init__.pyi
+++ /dev/null
@@ -1,51 +0,0 @@
-from .contextmanagers import reversed as reversed
-from .decorators import (
-    argmap as argmap,
-    nodes_or_number as nodes_or_number,
-    not_implemented_for as not_implemented_for,
-    np_random_state as np_random_state,
-    open_file as open_file,
-    preserve_random_state as preserve_random_state,
-    py_random_state as py_random_state,
-    random_state as random_state,
-)
-from .heaps import BinaryHeap as BinaryHeap, MinHeap as MinHeap, PairingHeap as PairingHeap
-from .misc import (
-    PythonRandomInterface as PythonRandomInterface,
-    arbitrary_element as arbitrary_element,
-    consume as consume,
-    create_py_random_state as create_py_random_state,
-    create_random_state as create_random_state,
-    default_opener as default_opener,
-    dict_to_numpy_array as dict_to_numpy_array,
-    dict_to_numpy_array1 as dict_to_numpy_array1,
-    dict_to_numpy_array2 as dict_to_numpy_array2,
-    edges_equal as edges_equal,
-    empty_generator as empty_generator,
-    flatten as flatten,
-    generate_unique_node as generate_unique_node,
-    graphs_equal as graphs_equal,
-    groups as groups,
-    is_iterator as is_iterator,
-    is_list_of_ints as is_list_of_ints,
-    is_string_like as is_string_like,
-    iterable as iterable,
-    make_list_of_ints as make_list_of_ints,
-    make_str as make_str,
-    nodes_equal as nodes_equal,
-    pairwise as pairwise,
-    to_tuple as to_tuple,
-)
-from .random_sequence import (
-    cumulative_distribution as cumulative_distribution,
-    discrete_sequence as discrete_sequence,
-    powerlaw_sequence as powerlaw_sequence,
-    random_weighted_sample as random_weighted_sample,
-    weighted_choice as weighted_choice,
-    zipf_rv as zipf_rv,
-)
-from .rcm import (
-    cuthill_mckee_ordering as cuthill_mckee_ordering,
-    reverse_cuthill_mckee_ordering as reverse_cuthill_mckee_ordering,
-)
-from .union_find import *
diff --git a/stubs/networkx/utils/contextmanagers.pyi b/stubs/networkx/utils/contextmanagers.pyi
deleted file mode 100644
index 48a55096..00000000
--- a/stubs/networkx/utils/contextmanagers.pyi
+++ /dev/null
@@ -1,9 +0,0 @@
-import warnings
-from contextlib import contextmanager
-
-from ..classes.graph import Graph
-
-__all__ = ["reversed"]
-
-@contextmanager
-def reversed(G: Graph): ...
diff --git a/stubs/networkx/utils/decorators.pyi b/stubs/networkx/utils/decorators.pyi
deleted file mode 100644
index c5563db7..00000000
--- a/stubs/networkx/utils/decorators.pyi
+++ /dev/null
@@ -1,57 +0,0 @@
-from collections.abc import Sequence
-from typing import Callable
-
-__all__ = [
-    "not_implemented_for",
-    "open_file",
-    "nodes_or_number",
-    "preserve_random_state",
-    "random_state",
-    "np_random_state",
-    "py_random_state",
-    "argmap",
-]
-
-def not_implemented_for(*graph_types): ...
-
-# To handle new extensions, define a function accepting a `path` and `mode`.
-# Then add the extension to _dispatch_dict.
-fopeners: dict = ...
-_dispatch_dict = ...
-
-def open_file(path_arg: str | int, mode: str = "r"): ...
-def nodes_or_number(which_args: str | int | Sequence[str]): ...
-def preserve_random_state(func): ...
-def np_random_state(random_state_argument: str | int): ...
-def random_state(random_state_argument): ...
-def py_random_state(random_state_argument: str | int): ...
-
-class argmap:
-    def __init__(self, func: Callable, *args, try_finally=False): ...
-    @staticmethod
-    def _lazy_compile(func): ...
-    def __call__(self, f: Callable) -> Callable: ...
-
-    __count: int = ...
-
-    @classmethod
-    def _count(cls): ...
-
-    _bad_chars = ...
-
-    @classmethod
-    def _name(cls, f): ...
-    def compile(self, f: Callable) -> Callable: ...
-    def assemble(self, f: Callable): ...
-    @classmethod
-    def signature(cls, f: Callable): ...
-
-    Signature = ...
-
-    @staticmethod
-    def _flatten(nestlist, visited): ...
-
-    _tabs = ...
-
-    @staticmethod
-    def _indent(*lines): ...
diff --git a/stubs/networkx/utils/heaps.pyi b/stubs/networkx/utils/heaps.pyi
deleted file mode 100644
index fa3ca7c7..00000000
--- a/stubs/networkx/utils/heaps.pyi
+++ /dev/null
@@ -1,35 +0,0 @@
-from heapq import heappop, heappush
-from itertools import count
-from typing import Any
-
-from ..classes.graph import Graph
-
-__all__ = ["MinHeap", "PairingHeap", "BinaryHeap"]
-
-class MinHeap:
-    def __init__(self): ...
-    def min(self) -> tuple: ...
-    def pop(self) -> tuple: ...
-    def get(self, key, default: Any = None): ...
-    def insert(self, key, value, allow_increase: bool = False) -> bool: ...
-    def __nonzero__(self): ...
-    def __bool__(self): ...
-    def __len__(self): ...
-    def __contains__(self, key): ...
-
-class PairingHeap(MinHeap):
-    def __init__(self): ...
-    def min(self) -> tuple: ...
-    def pop(self) -> tuple: ...
-    def get(self, key, default: Any = None): ...
-    def insert(self, key, value, allow_increase: bool = False) -> bool: ...
-    def _link(self, root, other): ...
-    def _merge_children(self, root): ...
-    def _cut(self, node): ...
-
-class BinaryHeap(MinHeap):
-    def __init__(self): ...
-    def min(self) -> tuple: ...
-    def pop(self) -> tuple: ...
-    def get(self, key, default: Any = None): ...
-    def insert(self, key, value, allow_increase: bool = False) -> bool: ...
diff --git a/stubs/networkx/utils/mapped_queue.pyi b/stubs/networkx/utils/mapped_queue.pyi
deleted file mode 100644
index 6bfe95ba..00000000
--- a/stubs/networkx/utils/mapped_queue.pyi
+++ /dev/null
@@ -1,26 +0,0 @@
-import heapq
-
-__all__ = ["MappedQueue"]
-
-class _HeapElement:
-    __slots__: list = ...
-
-    def __init__(self, priority, element): ...
-    def __lt__(self, other): ...
-    def __gt__(self, other): ...
-    def __eq__(self, other): ...
-    def __hash__(self): ...
-    def __getitem__(self, indx): ...
-    def __iter__(self): ...
-    def __repr__(self): ...
-
-class MappedQueue:
-    def __init__(self, data=[]): ...
-    def _heapify(self): ...
-    def __len__(self): ...
-    def push(self, elt, priority=None): ...
-    def pop(self): ...
-    def update(self, elt, new, priority=None): ...
-    def remove(self, elt): ...
-    def _siftup(self, pos): ...
-    def _siftdown(self, start_pos, pos): ...
diff --git a/stubs/networkx/utils/misc.pyi b/stubs/networkx/utils/misc.pyi
deleted file mode 100644
index 9cb666fa..00000000
--- a/stubs/networkx/utils/misc.pyi
+++ /dev/null
@@ -1,102 +0,0 @@
-import sys
-import uuid
-import warnings
-from collections import defaultdict, deque
-from collections.abc import Iterable, Iterator, Sized
-from itertools import chain, tee
-
-from ..classes.graph import Graph
-
-__all__ = [
-    "is_string_like",
-    "iterable",
-    "empty_generator",
-    "flatten",
-    "make_list_of_ints",
-    "is_list_of_ints",
-    "make_str",
-    "generate_unique_node",
-    "default_opener",
-    "dict_to_numpy_array",
-    "dict_to_numpy_array1",
-    "dict_to_numpy_array2",
-    "is_iterator",
-    "arbitrary_element",
-    "consume",
-    "pairwise",
-    "groups",
-    "to_tuple",
-    "create_random_state",
-    "create_py_random_state",
-    "PythonRandomInterface",
-    "nodes_equal",
-    "edges_equal",
-    "graphs_equal",
-]
-
-# some cookbook stuff
-# used in deciding whether something is a bunch of nodes, edges, etc.
-# see G.add_nodes and others in Graph Class in networkx/base.py
-
-def is_string_like(obj): ...
-def iterable(obj): ...
-def empty_generator(): ...
-def flatten(obj, result=None): ...
-def make_list_of_ints(sequence): ...
-def is_list_of_ints(intlist): ...
-def make_str(x): ...
-def generate_unique_node(): ...
-def default_opener(filename: str): ...
-def dict_to_numpy_array(d, mapping=None): ...
-def dict_to_numpy_array2(d, mapping=None): ...
-def dict_to_numpy_array1(d, mapping=None): ...
-def is_iterator(obj): ...
-def arbitrary_element(iterable): ...
-
-# Recipe from the itertools documentation.
-def consume(iterator): ...
-
-# Recipe from the itertools documentation.
-def pairwise(iterable, cyclic=False): ...
-def groups(many_to_one): ...
-def to_tuple(x): ...
-def create_random_state(random_state=None): ...
-
-class PythonRandomInterface:
-    def __init__(self, rng=None): ...
-    def random(self): ...
-    def uniform(self, a, b): ...
-    def randrange(self, a, b=None): ...
-
-    # NOTE: the numpy implementations of `choice` don't support strings, so
-    # this cannot be replaced with self._rng.choice
-    def choice(self, seq): ...
-    def gauss(self, mu, sigma): ...
-    def shuffle(self, seq): ...
-
-    #    Some methods don't match API for numpy RandomState.
-    #    Commented out versions are not used by NetworkX
-
-    def sample(self, seq, k): ...
-    def randint(self, a, b): ...
-
-    #    exponential as expovariate with 1/argument,
-    def expovariate(self, scale): ...
-
-    #    pareto as paretovariate with 1/argument,
-    def paretovariate(self, shape): ...
-
-#    weibull as weibullvariate multiplied by beta,
-#    def weibullvariate(self, alpha, beta):
-#        return self._rng.weibull(alpha) * beta
-#
-#    def triangular(self, low, high, mode):
-#        return self._rng.triangular(low, mode, high)
-#
-#    def choices(self, seq, weights=None, cum_weights=None, k=1):
-#        return self._rng.choice(seq
-
-def create_py_random_state(random_state=None): ...
-def nodes_equal(nodes1, nodes2) -> bool: ...
-def edges_equal(edges1, edges2) -> bool: ...
-def graphs_equal(graph1, graph2) -> bool: ...
diff --git a/stubs/networkx/utils/random_sequence.pyi b/stubs/networkx/utils/random_sequence.pyi
deleted file mode 100644
index 98ce4a88..00000000
--- a/stubs/networkx/utils/random_sequence.pyi
+++ /dev/null
@@ -1,27 +0,0 @@
-from ..classes.graph import Graph
-from ..utils import py_random_state
-
-__all__ = [
-    "powerlaw_sequence",
-    "zipf_rv",
-    "cumulative_distribution",
-    "discrete_sequence",
-    "random_weighted_sample",
-    "weighted_choice",
-]
-
-# The same helpers for choosing random sequences from distributions
-# uses Python's random module
-# https://docs.python.org/3/library/random.html
-
-@py_random_state(2)
-def powerlaw_sequence(n, exponent=2.0, seed=None): ...
-@py_random_state(2)
-def zipf_rv(alpha: float, xmin: int = 1, seed=None) -> int: ...
-def cumulative_distribution(distribution): ...
-@py_random_state(3)
-def discrete_sequence(n, distribution=None, cdistribution=None, seed=None): ...
-@py_random_state(2)
-def random_weighted_sample(mapping, k, seed=None): ...
-@py_random_state(1)
-def weighted_choice(mapping, seed=None): ...
diff --git a/stubs/networkx/utils/rcm.pyi b/stubs/networkx/utils/rcm.pyi
deleted file mode 100644
index e60a44bd..00000000
--- a/stubs/networkx/utils/rcm.pyi
+++ /dev/null
@@ -1,12 +0,0 @@
-from collections import deque
-from operator import itemgetter
-
-from ..classes.graph import Graph
-from ..utils import arbitrary_element
-
-__all__ = ["cuthill_mckee_ordering", "reverse_cuthill_mckee_ordering"]
-
-def cuthill_mckee_ordering(G: Graph, heuristic=None): ...
-def reverse_cuthill_mckee_ordering(G: Graph, heuristic=None): ...
-def connected_cuthill_mckee_ordering(G: Graph, heuristic=None): ...
-def pseudo_peripheral_node(G: Graph): ...
diff --git a/stubs/networkx/utils/union_find.pyi b/stubs/networkx/utils/union_find.pyi
deleted file mode 100644
index 68d753e1..00000000
--- a/stubs/networkx/utils/union_find.pyi
+++ /dev/null
@@ -1,8 +0,0 @@
-from ..utils import groups
-
-class UnionFind:
-    def __init__(self, elements=None): ...
-    def __getitem__(self, object): ...
-    def __iter__(self): ...
-    def to_sets(self): ...
-    def union(self, *objects): ...
diff --git a/stubs/skimage/future/graph/graph_cut.pyi b/stubs/skimage/future/graph/graph_cut.pyi
index 5b10a39b..61fcc14e 100644
--- a/stubs/skimage/future/graph/graph_cut.pyi
+++ b/stubs/skimage/future/graph/graph_cut.pyi
@@ -1,9 +1,5 @@
-import networkx as nx
-import numpy as np
 from numpy.typing import ArrayLike, NDArray
-from scipy.sparse import linalg
 
-from . import _ncut
 from .rag import RAG
 
 def cut_threshold(labels: NDArray, rag: RAG, thresh: float, in_place: bool = True) -> NDArray: ...
diff --git a/tests/run_stubtest.py b/tests/run_stubtest.py
index f460aa71..efc2209d 100644
--- a/tests/run_stubtest.py
+++ b/tests/run_stubtest.py
@@ -11,6 +11,11 @@
 root = Path(__file__).parent.parent
 stubs_path = root / "stubs"
 PARTIAL_STUBS_MARKER = "-stubs"
+SKIP_PACKAGES = {
+    # This stub has been upstreamed and is only kept for backwards compatibility
+    # The version that is stubbed does not match the one we install for type testing
+    "matplotlib",
+}
 
 
 def run_stubtest(module: str) -> CompletedProcess[bytes]:
@@ -40,19 +45,12 @@ def run_stubtest(module: str) -> CompletedProcess[bytes]:
         return run((sys.executable, "-m", *args), cwd=stubs_path)
 
 
-def main(modules: Collection[str]) -> int:
+def main(packages: Collection[str]) -> int:
     returncode = 0
-    if not modules:
-        modules = os.listdir(stubs_path)
-    for stub_module in modules:
-        if stub_module in {
-            # This stub has been upstreamed and is only kept for backwards compatibility
-            # The version that is stubbed does not match the one we install for type testing
-            "matplotlib",
-            # This stub is being upstreamed to typeshed and not worth fixing all issues.
-            # networkx 3.5 also isn't available on Python 3.10
-            "networkx",
-        }:
+    if not packages:
+        packages = os.listdir(stubs_path)
+    for stub_module in packages:
+        if stub_module in SKIP_PACKAGES:
             print(f"\nSkipped {stub_module}", flush=True)
             continue
         if stub_module.startswith("."):