Typing Stubs for NetworkX

3.6.1.20260408 · active · verified Sat Apr 11

Typing stubs for the `networkx` library. This package provides external type annotations, allowing static type checkers like MyPy and PyRight to analyze code that uses `networkx` for graph manipulation. It is an automatically generated component of the `typeshed` project and aims to provide accurate annotations for specific `networkx` versions. Stubs are released frequently, often daily, by typeshed's automated processes.

Warnings

gotcha Ensure the `types-networkx` version aligns with your installed `networkx` version. Mismatched versions can lead to incorrect or incomplete type checking results, as the stubs might not reflect the exact API of the `networkx` library you are using.
Fix: Install `types-networkx` with a version constraint matching your `networkx` installation, e.g., `pip install 'networkx==3.6.1' 'types-networkx==3.6.1.*'`.
gotcha Some `networkx` classes might be generic in stubs (e.g., `DiGraph[NodeT]`) but not at runtime, which can cause `TypeError: type 'DiGraph' is not subscriptable` when used with other libraries like Pydantic that inspect runtime types.
Fix: As a workaround for `TypeError` related to generic runtime types, users have reported adding `nx.DiGraph.__class_getitem__ = classmethod(lambda cls, item: cls)` after importing networkx. This makes the runtime class subscriptable for type hints without affecting behavior.
breaking While `types-networkx` provides stubs for the `networkx` API, `networkx` itself has undergone significant breaking changes between major versions (e.g., 1.x to 2.0, and 2.x to 3.0), particularly regarding iterator vs. view behavior, and the replacement of `numpy.matrix` with `numpy.ndarray`. Type stubs will reflect the target `networkx` version's API, but old code written for earlier `networkx` versions may still break at runtime even with correct stubs if not migrated.
Fix: Consult the `networkx` migration guides (e.g., from 1.x to 2.0, or 2.x to 3.0) for the underlying library. Update `networkx` code to adhere to the newer API.

Install

pip install types-networkx Install Stubs
pip install networkx Install NetworkX (required runtime library)

Imports

Graph
```
import networkx as nx
my_graph: nx.Graph[str] = nx.Graph()
```
`types-networkx` provides type information for `networkx` imports; you do not directly import from `types_networkx`.
DiGraph
```
from networkx import DiGraph
my_digraph: DiGraph[int] = DiGraph()
```
`types-networkx` provides type information for `networkx` imports; you do not directly import from `types_networkx`.

Quickstart

This example demonstrates basic `networkx` usage with type hints. When `types-networkx` is installed, a static type checker (like MyPy) will use these stubs to verify the types of variables and function signatures, catching potential errors at development time.

import networkx as nx

def create_and_analyze_graph(nodes: list[str], edges: list[tuple[str, str]]) -> tuple[nx.Graph[str], int]:
    G: nx.Graph[str] = nx.Graph()
    G.add_nodes_from(nodes)
    G.add_edges_from(edges)
    num_nodes: int = G.number_of_nodes()
    return G, num_nodes

if __name__ == '__main__':
    nodes_data = ['A', 'B', 'C', 'D']
    edges_data = [('A', 'B'), ('B', 'C'), ('C', 'D'), ('D', 'A')]
    
    graph, count = create_and_analyze_graph(nodes_data, edges_data)
    print(f"Created graph with {count} nodes and {graph.number_of_edges()} edges.")
    # Example of type checking at work: attempting to add a non-string node would be flagged by a type checker
    # graph.add_node(123) # This line would cause a type error with strict type checking

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