Helper Functions

Miscellaneous Helpers for NetworkX.

These are not imported into the base networkx namespace but can be accessed, for example, as

>>> import networkx
>>> networkx.utils.is_string_like('spam')
is_string_like(obj) Check if obj is string.
flatten(obj[, result]) Return flattened version of (possibly nested) iterable object.
iterable(obj) Return True if obj is iterable with a well-defined len().
is_list_of_ints(intlist) Return True if list is a list of ints.
make_str(x) Return the string representation of t.
generate_unique_node() Generate a unique node label.
default_opener(filename) Opens filename using system’s default program.
pairwise(iterable[, cyclic]) s -> (s0, s1), (s1, s2), (s2, s3), …
groups(many_to_one) Converts a many-to-one mapping into a one-to-many mapping.
create_random_state([random_state]) Returns a numpy.random.RandomState instance depending on input.

Data Structures and Algorithms

Union-find data structure.

UnionFind.union(*objects) Find the sets containing the objects and merge them all.

Random Sequence Generators

Utilities for generating random numbers, random sequences, and random selections.

powerlaw_sequence(n[, exponent, seed]) Return sample sequence of length n from a power law distribution.
cumulative_distribution(distribution) Return normalized cumulative distribution from discrete distribution.
discrete_sequence(n[, distribution, …]) Return sample sequence of length n from a given discrete distribution or discrete cumulative distribution.
zipf_rv(alpha[, xmin, seed]) Return a random value chosen from the Zipf distribution.
random_weighted_sample(mapping, k[, seed]) Return k items without replacement from a weighted sample.
weighted_choice(mapping[, seed]) Return a single element from a weighted sample.


open_file(path_arg[, mode]) Decorator to ensure clean opening and closing of files.
not_implemented_for(*graph_types) Decorator to mark algorithms as not implemented
nodes_or_number(which_args) Decorator to allow number of nodes or container of nodes.
preserve_random_state(func) Decorator to preserve the numpy.random state during a function.
random_state(random_state_index) Decorator to generate a numpy.random.RandomState instance.

Cuthill-Mckee Ordering

Cuthill-McKee ordering of graph nodes to produce sparse matrices

cuthill_mckee_ordering(G[, heuristic]) Generate an ordering (permutation) of the graph nodes to make a sparse matrix.
reverse_cuthill_mckee_ordering(G[, heuristic]) Generate an ordering (permutation) of the graph nodes to make a sparse matrix.

Context Managers

reversed(*args, **kwds) A context manager for temporarily reversing a directed graph in place.