Warning

This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

# Utilities¶

## 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')
True

 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.

## 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.

 create_degree_sequence(n[, sfunction, max_tries]) pareto_sequence(n[, exponent]) Return sample sequence of length n from a Pareto distribution. powerlaw_sequence(n[, exponent]) Return sample sequence of length n from a power law distribution. uniform_sequence(n) Return sample sequence of length n from a uniform 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_sequence(n[, alpha, xmin]) Return a sample sequence of length n from a Zipf distribution with exponent parameter alpha and minimum value xmin. zipf_rv(alpha[, xmin, seed]) Return a random value chosen from the Zipf distribution. random_weighted_sample(mapping, k) Return k items without replacement from a weighted sample. weighted_choice(mapping) Return a single element from a weighted sample.

## Decorators¶

 open_file(path_arg[, mode]) Decorator to ensure clean opening and closing of files.

## 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.