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Update most test/lint dependencies (#15582)

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This commit is contained in:
renovate[bot]
2026-04-01 17:54:51 +02:00
committed by GitHub
parent 8ffc43610f
commit 8b31f2639e
142 changed files with 310 additions and 357 deletions
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stubs/networkx/networkx/algorithms/assortativity/pairs.pyi
+2 -4
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@@ -7,10 +7,8 @@ from networkx.utils.backends import _dispatchable
__all__ = ["node_attribute_xy", "node_degree_xy"]
@_dispatchable
def node_attribute_xy(
G: Graph[_Node], attribute, nodes: Iterable[Incomplete] | None = None
) -> Generator[Incomplete, None, None]: ...
def node_attribute_xy(G: Graph[_Node], attribute, nodes: Iterable[Incomplete] | None = None) -> Generator[Incomplete]: ...
@_dispatchable
def node_degree_xy(
G: Graph[_Node], x: str = "out", y: str = "in", weight: str | None = None, nodes: Iterable[Incomplete] | None = None
) -> Generator[Incomplete, None, None]: ...
) -> Generator[Incomplete]: ...
stubs/networkx/networkx/algorithms/boundary.pyi
+11 -11
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@@ -16,7 +16,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node], None, None]: ...
) -> Generator[tuple[_Node, _Node]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -25,7 +25,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -34,7 +34,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -43,7 +43,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default: _U | None = None,
) -> Generator[tuple[_Node, _Node, dict[str, _U]], None, None]: ...
) -> Generator[tuple[_Node, _Node, dict[str, _U]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -52,7 +52,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default: _U | None = None,
) -> Generator[tuple[_Node, _Node, dict[str, _U]], None, None]: ...
) -> Generator[tuple[_Node, _Node, dict[str, _U]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -61,7 +61,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, int], None, None]: ...
) -> Generator[tuple[_Node, _Node, int]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -70,7 +70,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, int], None, None]: ...
) -> Generator[tuple[_Node, _Node, int]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -79,7 +79,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -88,7 +88,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default=None,
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -97,7 +97,7 @@ def edge_boundary(
data=False,
keys: bool = False,
default: _U | None = None,
) -> Generator[tuple[_Node, _Node, int, dict[str, _U]], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, dict[str, _U]]]: ...
@overload
def edge_boundary(
G: Graph[_Node],
@@ -106,6 +106,6 @@ def edge_boundary(
data=False,
keys: bool = False,
default: _U | None = None,
) -> Generator[tuple[_Node, _Node, int, dict[str, _U]], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, dict[str, _U]]]: ...
@_dispatchable
def node_boundary(G: Graph[_Node], nbunch1: Iterable[Incomplete], nbunch2: Iterable[Incomplete] | None = None) -> set[_Node]: ...
stubs/networkx/networkx/algorithms/bridges.pyi
+3 -7
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@@ -7,14 +7,10 @@ from networkx.utils.backends import _dispatchable
__all__ = ["bridges", "has_bridges", "local_bridges"]
@_dispatchable
def bridges(G: Graph[_Node], root: _Node | None = None) -> Generator[_Node, None, None]: ...
def bridges(G: Graph[_Node], root: _Node | None = None) -> Generator[_Node]: ...
@_dispatchable
def has_bridges(G: Graph[_Node], root: _Node | None = None) -> bool: ...
@overload
def local_bridges(
G: Graph[_Node], with_span: bool = True, weight: str | None = None
) -> Generator[tuple[_Node, _Node], None, None]: ...
def local_bridges(G: Graph[_Node], with_span: bool = True, weight: str | None = None) -> Generator[tuple[_Node, _Node]]: ...
@overload
def local_bridges(
G: Graph[_Node], with_span: bool = True, weight: str | None = None
) -> Generator[tuple[_Node, _Node, int], None, None]: ...
def local_bridges(G: Graph[_Node], with_span: bool = True, weight: str | None = None) -> Generator[tuple[_Node, _Node, int]]: ...
stubs/networkx/networkx/algorithms/centrality/flow_matrix.pyi
+1 -1
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@@ -5,7 +5,7 @@ from networkx.classes.graph import Graph, _Node
from networkx.utils.backends import _dispatchable
@_dispatchable
def flow_matrix_row(G: Graph[_Node], weight=None, dtype=..., solver: str = "lu") -> Generator[Incomplete, None, None]: ...
def flow_matrix_row(G: Graph[_Node], weight=None, dtype=..., solver: str = "lu") -> Generator[Incomplete]: ...
class InverseLaplacian:
dtype: Incomplete
stubs/networkx/networkx/algorithms/chains.pyi
+1 -1
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@@ -6,4 +6,4 @@ from networkx.utils.backends import _dispatchable
__all__ = ["chain_decomposition"]
@_dispatchable
def chain_decomposition(G: Graph[_Node], root: _Node | None = None) -> Generator[list[tuple[_Node, _Node]], None, None]: ...
def chain_decomposition(G: Graph[_Node], root: _Node | None = None) -> Generator[list[tuple[_Node, _Node]]]: ...
stubs/networkx/networkx/algorithms/chordal.pyi
+1 -1
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@@ -22,7 +22,7 @@ def is_chordal(G: Graph[_Node]) -> bool: ...
@_dispatchable
def find_induced_nodes(G: Graph[_Node], s: _Node, t: _Node, treewidth_bound: float = sys.maxsize) -> set[_Node]: ...
@_dispatchable
def chordal_graph_cliques(G: Graph[_Node]) -> Generator[frozenset[_Node], None, None]: ...
def chordal_graph_cliques(G: Graph[_Node]) -> Generator[frozenset[_Node]]: ...
@_dispatchable
def chordal_graph_treewidth(G: Graph[_Node]) -> int: ...
@_dispatchable
stubs/networkx/networkx/algorithms/clique.pyi
+2 -2
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@@ -17,9 +17,9 @@ __all__ = [
]
@_dispatchable
def enumerate_all_cliques(G: Graph[_Node]) -> Generator[list[_Node], None, None]: ...
def enumerate_all_cliques(G: Graph[_Node]) -> Generator[list[_Node]]: ...
@_dispatchable
def find_cliques(G: Graph[_Node], nodes: Iterable[Incomplete] | None = None) -> Generator[list[_Node], None, None]: ...
def find_cliques(G: Graph[_Node], nodes: Iterable[Incomplete] | None = None) -> Generator[list[_Node]]: ...
@_dispatchable
def find_cliques_recursive(G: Graph[_Node], nodes: Iterable[Incomplete] | None = None) -> Iterator[list[_Node]]: ...
@_dispatchable
stubs/networkx/networkx/algorithms/coloring/greedy_coloring.pyi
+2 -4
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@@ -24,15 +24,13 @@ def strategy_random_sequential(G: Graph[_Node], colors: Unused, seed=None): ...
@_dispatchable
def strategy_smallest_last(G: Graph[_Node], colors: Unused): ...
@_dispatchable
def strategy_independent_set(G: Graph[_Node], colors: Unused) -> Generator[Incomplete, Incomplete, None]: ...
def strategy_independent_set(G: Graph[_Node], colors: Unused) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def strategy_connected_sequential_bfs(G: Graph[_Node], colors): ...
@_dispatchable
def strategy_connected_sequential_dfs(G: Graph[_Node], colors): ...
@_dispatchable
def strategy_connected_sequential(
G: Graph[_Node], colors: Unused, traversal: str = "bfs"
) -> Generator[Incomplete, None, None]: ...
def strategy_connected_sequential(G: Graph[_Node], colors: Unused, traversal: str = "bfs") -> Generator[Incomplete]: ...
@_dispatchable
def strategy_saturation_largest_first(G: Graph[_Node], colors) -> Generator[Incomplete, None, Incomplete]: ...
stubs/networkx/networkx/algorithms/community/kclique.pyi
+1 -1
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@@ -7,4 +7,4 @@ from networkx.utils.backends import _dispatchable
__all__ = ["k_clique_communities"]
@_dispatchable
def k_clique_communities(G: Graph[_Node], k: int, cliques=None) -> Generator[Incomplete, None, None]: ...
def k_clique_communities(G: Graph[_Node], k: int, cliques=None) -> Generator[Incomplete]: ...
stubs/networkx/networkx/algorithms/community/label_propagation.pyi
+1 -1
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@@ -13,6 +13,6 @@ def fast_label_propagation_communities(G: Graph[_Node], *, weight=None, seed=Non
@_dispatchable
def asyn_lpa_communities(
G: Graph[_Node], weight: str | None = None, seed: int | RandomState | None = None
) -> Generator[Incomplete, Incomplete, None]: ...
) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def label_propagation_communities(G: Graph[_Node]) -> dict_values[Incomplete, set[Incomplete]]: ...
stubs/networkx/networkx/algorithms/community/louvain.pyi
+1 -1
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@@ -23,4 +23,4 @@ def louvain_partitions(
resolution: float | None = 1,
threshold: float | None = 1e-07,
seed: int | RandomState | None = None,
) -> Generator[list[set[Incomplete]], None, None]: ...
) -> Generator[list[set[Incomplete]]]: ...
stubs/networkx/networkx/algorithms/connectivity/disjoint_paths.pyi
+2 -2
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@@ -18,7 +18,7 @@ def edge_disjoint_paths(
cutoff: int | None = None,
auxiliary: DiGraph[_Node] | None = None,
residual: DiGraph[_Node] | None = None,
) -> Generator[Incomplete, None, None]: ...
) -> Generator[Incomplete]: ...
@_dispatchable
def node_disjoint_paths(
G: Graph[_Node],
@@ -28,4 +28,4 @@ def node_disjoint_paths(
cutoff: int | None = None,
auxiliary: DiGraph[_Node] | None = None,
residual: DiGraph[_Node] | None = None,
) -> Generator[Incomplete, None, None]: ...
) -> Generator[Incomplete]: ...
stubs/networkx/networkx/algorithms/connectivity/edge_augmentation.pyi
+1 -1
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@@ -18,7 +18,7 @@ def k_edge_augmentation(
avail: set[tuple[int, int]] | set[tuple[int, int, float]] | SupportsGetItem[tuple[int, int], float] | None = None,
weight: str | None = None,
partial: bool = False,
) -> Generator[tuple[_Node, _Node], None, None]: ...
) -> Generator[tuple[_Node, _Node]]: ...
@_dispatchable
def partial_k_edge_augmentation(G: Graph[_Node], k, avail, weight: str | None = None): ...
@_dispatchable
stubs/networkx/networkx/algorithms/connectivity/edge_kcomponents.pyi
+3 -3
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@@ -11,7 +11,7 @@ def k_edge_components(G: Graph[_Node], k: int): ...
@_dispatchable
def k_edge_subgraphs(G: Graph[_Node], k: int): ...
@_dispatchable
def bridge_components(G: Graph[_Node]) -> Generator[Incomplete, Incomplete, None]: ...
def bridge_components(G: Graph[_Node]) -> Generator[Incomplete, Incomplete]: ...
class EdgeComponentAuxGraph:
A: Incomplete
@@ -19,8 +19,8 @@ class EdgeComponentAuxGraph:
@classmethod
def construct(cls, G: Graph[_Node]): ...
def k_edge_components(self, k: int) -> Generator[Incomplete, Incomplete, None]: ...
def k_edge_subgraphs(self, k: int) -> Generator[Incomplete, Incomplete, None]: ...
def k_edge_components(self, k: int) -> Generator[Incomplete, Incomplete]: ...
def k_edge_subgraphs(self, k: int) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def general_k_edge_subgraphs(G: Graph[_Node], k): ...
stubs/networkx/networkx/algorithms/connectivity/kcutsets.pyi
+1 -1
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@@ -11,4 +11,4 @@ default_flow_func = edmonds_karp
@_dispatchable
def all_node_cuts(
G: Graph[_Node], k: int | None = None, flow_func: Callable[..., Incomplete] | None = None
) -> Generator[Incomplete, None, None]: ...
) -> Generator[Incomplete]: ...
stubs/networkx/networkx/algorithms/dag.pyi
+5 -7
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@@ -30,15 +30,13 @@ def ancestors(G: Graph[_Node], source) -> set[_Node]: ...
@_dispatchable
def is_directed_acyclic_graph(G: Graph[_Node]) -> bool: ...
@_dispatchable
def topological_generations(G: DiGraph[_Node]) -> Generator[list[_Node], None, None]: ...
def topological_generations(G: DiGraph[_Node]) -> Generator[list[_Node]]: ...
@_dispatchable
def topological_sort(G: DiGraph[_Node]) -> Generator[_Node, None, None]: ...
def topological_sort(G: DiGraph[_Node]) -> Generator[_Node]: ...
@_dispatchable
def lexicographical_topological_sort(
G: DiGraph[_Node], key: Callable[..., Incomplete] | None = None
) -> Generator[_Node, None, None]: ...
def lexicographical_topological_sort(G: DiGraph[_Node], key: Callable[..., Incomplete] | None = None) -> Generator[_Node]: ...
@_dispatchable
def all_topological_sorts(G: DiGraph[_Node]) -> Generator[list[_Node], None, None]: ...
def all_topological_sorts(G: DiGraph[_Node]) -> Generator[list[_Node]]: ...
@_dispatchable
def is_aperiodic(G: DiGraph[_Node]) -> bool: ...
@_dispatchable
@@ -48,7 +46,7 @@ def transitive_closure_dag(G: DiGraph[_Node], topo_order: Iterable[Incomplete] |
@_dispatchable
def transitive_reduction(G: DiGraph[_Node]) -> DiGraph[_Node]: ...
@_dispatchable
def antichains(G: DiGraph[_Node], topo_order: Iterable[Incomplete] | None = None) -> Generator[list[_Node], None, None]: ...
def antichains(G: DiGraph[_Node], topo_order: Iterable[Incomplete] | None = None) -> Generator[list[_Node]]: ...
@_dispatchable
def dag_longest_path(
G: DiGraph[_Node],
stubs/networkx/networkx/algorithms/euler.pyi
+2 -4
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@@ -11,12 +11,10 @@ def is_eulerian(G: Graph[_Node]) -> bool: ...
@_dispatchable
def is_semieulerian(G: Graph[_Node]) -> bool: ...
@_dispatchable
def eulerian_circuit(
G: Graph[_Node], source: _Node | None = None, keys: bool = False
) -> Generator[Incomplete, Incomplete, None]: ...
def eulerian_circuit(G: Graph[_Node], source: _Node | None = None, keys: bool = False) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def has_eulerian_path(G: Graph[_Node], source: _Node | None = None) -> bool: ...
@_dispatchable
def eulerian_path(G: Graph[_Node], source=None, keys: bool = False) -> Generator[Incomplete, Incomplete, None]: ...
def eulerian_path(G: Graph[_Node], source=None, keys: bool = False) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def eulerize(G: Graph[_Node]): ...
stubs/networkx/networkx/algorithms/flow/networksimplex.pyi
+2 -2
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@@ -34,13 +34,13 @@ class _DataEssentialsAndFunctions:
def trace_path(self, p, w): ...
def find_cycle(self, i, p, q): ...
def augment_flow(self, Wn, We, f) -> None: ...
def trace_subtree(self, p) -> Generator[Incomplete, None, None]: ...
def trace_subtree(self, p) -> Generator[Incomplete]: ...
def remove_edge(self, s, t) -> None: ...
def make_root(self, q) -> None: ...
def add_edge(self, i, p, q) -> None: ...
def update_potentials(self, i, p, q) -> None: ...
def reduced_cost(self, i): ...
def find_entering_edges(self) -> Generator[Incomplete, None, None]: ...
def find_entering_edges(self) -> Generator[Incomplete]: ...
def residual_capacity(self, i, p): ...
def find_leaving_edge(self, Wn, We): ...
stubs/networkx/networkx/algorithms/isomorphism/ismags.pyi
+2 -2
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@@ -24,9 +24,9 @@ class ISMAGS:
def __init__(self, graph, subgraph, node_match=None, edge_match=None, cache=None) -> None: ...
def create_aligned_partitions(self, thing_matcher, sg_things, g_things): ...
def find_isomorphisms(self, symmetry: bool = True) -> Generator[Incomplete, Incomplete, Incomplete]: ...
def largest_common_subgraph(self, symmetry: bool = True) -> Generator[Incomplete, Incomplete, None]: ...
def largest_common_subgraph(self, symmetry: bool = True) -> Generator[Incomplete, Incomplete]: ...
def analyze_subgraph_symmetry(self) -> dict[Hashable, set[Hashable]]: ...
def is_isomorphic(self, symmetry: bool = False) -> bool: ...
def subgraph_is_isomorphic(self, symmetry: bool = False) -> bool: ...
def isomorphisms_iter(self, symmetry: bool = True) -> Generator[Incomplete, Incomplete, None]: ...
def isomorphisms_iter(self, symmetry: bool = True) -> Generator[Incomplete, Incomplete]: ...
def subgraph_isomorphisms_iter(self, symmetry: bool = True): ...
stubs/networkx/networkx/algorithms/isomorphism/isomorphvf2.pyi
+6 -6
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@@ -14,7 +14,7 @@ class GraphMatcher:
def __init__(self, G1, G2) -> None: ...
def reset_recursion_limit(self) -> None: ...
def candidate_pairs_iter(self) -> Generator[Incomplete, None, None]: ...
def candidate_pairs_iter(self) -> Generator[Incomplete]: ...
core_1: Incomplete
core_2: Incomplete
inout_1: Incomplete
@@ -24,18 +24,18 @@ class GraphMatcher:
def initialize(self) -> None: ...
def is_isomorphic(self) -> bool: ...
def isomorphisms_iter(self) -> Generator[Incomplete, Incomplete, None]: ...
def match(self) -> Generator[Incomplete, Incomplete, None]: ...
def isomorphisms_iter(self) -> Generator[Incomplete, Incomplete]: ...
def match(self) -> Generator[Incomplete, Incomplete]: ...
def semantic_feasibility(self, G1_node, G2_node): ...
def subgraph_is_isomorphic(self): ...
def subgraph_is_monomorphic(self): ...
def subgraph_isomorphisms_iter(self) -> Generator[Incomplete, Incomplete, None]: ...
def subgraph_monomorphisms_iter(self) -> Generator[Incomplete, Incomplete, None]: ...
def subgraph_isomorphisms_iter(self) -> Generator[Incomplete, Incomplete]: ...
def subgraph_monomorphisms_iter(self) -> Generator[Incomplete, Incomplete]: ...
def syntactic_feasibility(self, G1_node, G2_node): ...
class DiGraphMatcher(GraphMatcher):
def __init__(self, G1, G2) -> None: ...
def candidate_pairs_iter(self) -> Generator[Incomplete, None, None]: ...
def candidate_pairs_iter(self) -> Generator[Incomplete]: ...
core_1: Incomplete
core_2: Incomplete
in_1: Incomplete
stubs/networkx/networkx/algorithms/lowest_common_ancestors.pyi
+1 -3
View File
@@ -12,6 +12,4 @@ def all_pairs_lowest_common_ancestor(G: DiGraph[_Node], pairs=None): ...
@_dispatchable
def lowest_common_ancestor(G: DiGraph[_Node], node1, node2, default=None): ...
@_dispatchable
def tree_all_pairs_lowest_common_ancestor(
G: DiGraph[_Node], root: _Node | None = None, pairs=None
) -> Generator[Incomplete, None, None]: ...
def tree_all_pairs_lowest_common_ancestor(G: DiGraph[_Node], root: _Node | None = None, pairs=None) -> Generator[Incomplete]: ...
stubs/networkx/networkx/algorithms/planarity.pyi
+1 -1
View File
@@ -95,7 +95,7 @@ class LRPlanarity:
class PlanarEmbedding(DiGraph[_Node]):
def get_data(self) -> dict[_Node, list[_Node]]: ...
def set_data(self, data: Mapping[_Node, Reversible[_Node]]) -> None: ...
def neighbors_cw_order(self, v: _Node) -> Generator[_Node, None, None]: ...
def neighbors_cw_order(self, v: _Node) -> Generator[_Node]: ...
def add_half_edge(self, start_node: _Node, end_node: _Node, *, cw: _Node | None = None, ccw: _Node | None = None): ...
def check_structure(self) -> None: ...
def add_half_edge_ccw(self, start_node: _Node, end_node: _Node, reference_neighbor: _Node) -> None: ...
stubs/networkx/networkx/algorithms/shortest_paths/unweighted.pyi
+1 -1
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@@ -20,7 +20,7 @@ def single_source_shortest_path_length(G: Graph[_Node], source: _Node, cutoff: i
@_dispatchable
def single_target_shortest_path_length(G: Graph[_Node], target: _Node, cutoff: int | None = None): ...
@_dispatchable
def all_pairs_shortest_path_length(G: Graph[_Node], cutoff: int | None = None) -> Generator[Incomplete, None, None]: ...
def all_pairs_shortest_path_length(G: Graph[_Node], cutoff: int | None = None) -> Generator[Incomplete]: ...
@_dispatchable
def bidirectional_shortest_path(G: Graph[_Node], source: _Node, target: _Node) -> list[Incomplete]: ...
@_dispatchable
stubs/networkx/networkx/algorithms/similarity.pyi
+1 -1
View File
@@ -59,7 +59,7 @@ def optimize_graph_edit_distance(
edge_del_cost: Callable[..., Incomplete] | None = None,
edge_ins_cost: Callable[..., Incomplete] | None = None,
upper_bound: float | None = None,
) -> Generator[Incomplete, None, None]: ...
) -> Generator[Incomplete]: ...
@_dispatchable
def optimize_edit_paths(
G1: Graph[_Node],
stubs/networkx/networkx/algorithms/simple_paths.pyi
+1 -1
View File
@@ -23,7 +23,7 @@ def shortest_simple_paths(
source: _Node,
target: _Node,
weight: str | Callable[[Any, Any, SupportsGetItem[str, Any]], float | None] | None = None,
) -> Generator[list[_Node], None, None]: ...
) -> Generator[list[_Node]]: ...
class PathBuffer:
paths: Incomplete
stubs/networkx/networkx/algorithms/triads.pyi
+1 -1
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@@ -18,7 +18,7 @@ def triadic_census(G: DiGraph[_Node], nodelist: Collection[_Node] | None = None)
@_dispatchable
def is_triad(G: Graph[_Node]) -> bool: ...
@_dispatchable
def all_triads(G: DiGraph[_Node]) -> Generator[Incomplete, None, None]: ...
def all_triads(G: DiGraph[_Node]) -> Generator[Incomplete]: ...
@_dispatchable
def triads_by_type(G: DiGraph[_Node]) -> defaultdict[Incomplete, list[Incomplete]]: ...
@_dispatchable
stubs/networkx/networkx/classes/function.pyi
+11 -11
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@@ -130,44 +130,44 @@ def get_edge_attributes(G: Graph[_Node], name: str, default=None) -> dict[tuple[
@_dispatchable
def remove_edge_attributes(G: Graph[_Node], *attr_names, ebunch=None) -> None: ...
def all_neighbors(graph: Graph[_Node], node: _Node) -> Iterator[_Node]: ...
def non_neighbors(graph: Graph[_Node], node: _Node) -> Generator[_Node, None, None]: ...
def non_edges(graph: Graph[_Node]) -> Generator[tuple[_Node, _Node], None, None]: ...
def common_neighbors(G: Graph[_Node], u: _Node, v: _Node) -> Generator[_Node, None, None]: ...
def non_neighbors(graph: Graph[_Node], node: _Node) -> Generator[_Node]: ...
def non_edges(graph: Graph[_Node]) -> Generator[tuple[_Node, _Node]]: ...
def common_neighbors(G: Graph[_Node], u: _Node, v: _Node) -> Generator[_Node]: ...
@_dispatchable
def is_weighted(G: Graph[_Node], edge: tuple[_Node, _Node] | None = None, weight: str = "weight") -> bool: ...
@_dispatchable
def is_negatively_weighted(G: Graph[_Node], edge: tuple[_Node, _Node] | None = None, weight: str = "weight") -> bool: ...
@_dispatchable
def is_empty(G: Graph[Hashable]) -> bool: ...
def nodes_with_selfloops(G: Graph[_Node]) -> Generator[_Node, None, None]: ...
def nodes_with_selfloops(G: Graph[_Node]) -> Generator[_Node]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: Literal[False] = False, keys: Literal[False] = False, default=None
) -> Generator[tuple[_Node, _Node], None, None]: ...
) -> Generator[tuple[_Node, _Node]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: Literal[True], keys: Literal[False] = False, default=None
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, dict[str, Incomplete]]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: str, keys: Literal[False] = False, default: _U | None = None
) -> Generator[tuple[_Node, _Node, _U], None, None]: ...
) -> Generator[tuple[_Node, _Node, _U]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: Literal[False], keys: Literal[True], default=None
) -> Generator[tuple[_Node, _Node, int], None, None]: ...
) -> Generator[tuple[_Node, _Node, int]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: Literal[False] = False, *, keys: Literal[True], default=None
) -> Generator[tuple[_Node, _Node, int], None, None]: ...
) -> Generator[tuple[_Node, _Node, int]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: Literal[True], keys: Literal[True], default=None
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, dict[str, Incomplete]]]: ...
@overload
def selfloop_edges(
G: Graph[_Node], data: str, keys: Literal[True], default: _U | None = None
) -> Generator[tuple[_Node, _Node, int, _U], None, None]: ...
) -> Generator[tuple[_Node, _Node, int, _U]]: ...
@_dispatchable
def number_of_selfloops(G: Graph[Hashable]) -> int: ...
def is_path(G: Graph[_Node], path: Iterable[Incomplete]) -> bool: ...
stubs/networkx/networkx/readwrite/adjlist.pyi
+1 -1
View File
@@ -5,7 +5,7 @@ from networkx.utils.backends import _dispatchable
__all__ = ["generate_adjlist", "write_adjlist", "parse_adjlist", "read_adjlist"]
def generate_adjlist(G: Graph[_Node], delimiter: str = " ") -> Generator[str, None, None]: ...
def generate_adjlist(G: Graph[_Node], delimiter: str = " ") -> Generator[str]: ...
def write_adjlist(G: Graph[_Node], path, comments: str = "#", delimiter: str = " ", encoding: str = "utf-8") -> None: ...
@_dispatchable
def parse_adjlist(lines, comments: str = "#", delimiter=None, create_using=None, nodetype=None): ...
stubs/networkx/networkx/readwrite/edgelist.pyi
+1 -1
View File
@@ -13,7 +13,7 @@ __all__ = [
"write_weighted_edgelist",
]
def generate_edgelist(G: Graph[_Node], delimiter: str = " ", data: bool = True) -> Generator[Incomplete, None, None]: ...
def generate_edgelist(G: Graph[_Node], delimiter: str = " ", data: bool = True) -> Generator[Incomplete]: ...
def write_edgelist(
G: Graph[_Node], path, comments: str = "#", delimiter: str = " ", data: bool = True, encoding: str = "utf-8"
) -> None: ...
stubs/networkx/networkx/readwrite/gexf.pyi
+1 -1
View File
@@ -10,7 +10,7 @@ __all__ = ["write_gexf", "read_gexf", "relabel_gexf_graph", "generate_gexf"]
def write_gexf(G: Graph[_Node], path, encoding: str = "utf-8", prettyprint: bool = True, version: str = "1.2draft") -> None: ...
def generate_gexf(
G: Graph[_Node], encoding: str = "utf-8", prettyprint: bool = True, version: str = "1.2draft"
) -> Generator[Incomplete, Incomplete, None]: ...
) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def read_gexf(path, node_type=None, relabel: bool = False, version: str = "1.2draft"): ...
stubs/networkx/networkx/readwrite/gml.pyi
+1 -1
View File
@@ -37,5 +37,5 @@ LIST_START_VALUE: Final = "_networkx_list_start"
def parse_gml_lines(lines, label, destringizer): ...
def literal_stringizer(value) -> str: ...
def generate_gml(G: Graph[_Node], stringizer=None) -> Generator[Incomplete, Incomplete, None]: ...
def generate_gml(G: Graph[_Node], stringizer=None) -> Generator[Incomplete, Incomplete]: ...
def write_gml(G: Graph[_Node], path, stringizer=None) -> None: ...
stubs/networkx/networkx/readwrite/graphml.pyi
+2 -2
View File
@@ -36,7 +36,7 @@ def write_graphml_lxml(
): ...
def generate_graphml(
G: Graph[_Node], encoding: str = "utf-8", prettyprint: bool = True, named_key_ids: bool = False, edge_id_from_attribute=None
) -> Generator[Incomplete, Incomplete, None]: ...
) -> Generator[Incomplete, Incomplete]: ...
@_dispatchable
def read_graphml(path, node_type=..., edge_key_type=..., force_multigraph: bool = False): ...
@_dispatchable
@@ -121,7 +121,7 @@ class GraphMLReader(GraphML):
edge_ids: Incomplete
def __init__(self, node_type=..., edge_key_type=..., force_multigraph: bool = False) -> None: ...
xml: Incomplete
def __call__(self, path=None, string=None) -> Generator[Incomplete, None, None]: ...
def __call__(self, path=None, string=None) -> Generator[Incomplete]: ...
def make_graph(self, graph_xml, graphml_keys, defaults, G=None): ...
def add_node(self, G: Graph[_Node], node_xml, graphml_keys, defaults) -> None: ...
def add_edge(self, G: Graph[_Node], edge_element, graphml_keys) -> None: ...
stubs/networkx/networkx/readwrite/multiline_adjlist.pyi
+1 -1
View File
@@ -5,7 +5,7 @@ from networkx.utils.backends import _dispatchable
__all__ = ["generate_multiline_adjlist", "write_multiline_adjlist", "parse_multiline_adjlist", "read_multiline_adjlist"]
def generate_multiline_adjlist(G: Graph[_Node], delimiter: str = " ") -> Generator[str, None, None]: ...
def generate_multiline_adjlist(G: Graph[_Node], delimiter: str = " ") -> Generator[str]: ...
def write_multiline_adjlist(G: Graph[_Node], path, delimiter=" ", comments="#", encoding="utf-8") -> None: ...
@_dispatchable
def parse_multiline_adjlist(lines, comments: str = "#", delimiter=None, create_using=None, nodetype=None, edgetype=None): ...
stubs/networkx/networkx/readwrite/pajek.pyi
+1 -1
View File
@@ -6,7 +6,7 @@ from networkx.utils.backends import _dispatchable
__all__ = ["read_pajek", "parse_pajek", "generate_pajek", "write_pajek"]
def generate_pajek(G: Graph[_Node]) -> Generator[Incomplete, None, None]: ...
def generate_pajek(G: Graph[_Node]) -> Generator[Incomplete]: ...
def write_pajek(G: Graph[_Node], path, encoding: str = "UTF-8") -> None: ...
@_dispatchable
def read_pajek(path, encoding: str = "UTF-8"): ...
stubs/networkx/networkx/utils/rcm.pyi
+1 -1
View File
@@ -5,7 +5,7 @@ from networkx.classes.graph import Graph, _Node
__all__ = ["cuthill_mckee_ordering", "reverse_cuthill_mckee_ordering"]
def cuthill_mckee_ordering(G: Graph[_Node], heuristic=None) -> Generator[Incomplete, Incomplete, None]: ...
def cuthill_mckee_ordering(G: Graph[_Node], heuristic=None) -> Generator[Incomplete, Incomplete]: ...
def reverse_cuthill_mckee_ordering(G: Graph[_Node], heuristic=None): ...
def connected_cuthill_mckee_ordering(G: Graph[_Node], heuristic=None): ...
def pseudo_peripheral_node(G: Graph[_Node]): ...