Warning

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

# Release Log¶

## NetworkX 1.9.1¶

Release date: 13 September 2014

Bugfix release for minor installation and documentation issues.

https://github.com/networkx/networkx/milestones/networkx-1.9.1

## NetworkX 1.9¶

Release date: 21 June 2014

Support for Python 3.1 is dropped in this release.

### Highlights¶

- Completely rewritten maximum flow and flow-based connectivity algorithms with backwards incompatible interfaces
- Community graph generators
- Stoer–Wagner minimum cut algorithm
- Linear-time Eulerian circuit algorithm
- Linear algebra package changed to use SciPy sparse matrices
- Algebraic connectivity, Fiedler vector, spectral ordering algorithms
- Link prediction algorithms
- Goldberg–Radzik shortest path algorithm
- Semiconnected graph and tree recognition algorithms

### API changes¶

## NetworkX 1.8¶

Release date: 28 July 2013

### Highlights¶

- Faster (linear-time) graphicality tests and Havel-Hakimi graph generators
- Directed Laplacian matrix generator
- Katz centrality algorithm
- Functions to generate all simple paths
- Improved shapefile reader
- More flexible weighted projection of bipartite graphs
- Faster topological sort, decendents and ancestors of DAGs
- Scaling parameter for force-directed layout

### Bug fixes¶

- Error with average weighted connectivity for digraphs, correct normalized laplacian with self-loops, load betweenness for single node graphs, isolated nodes missing from dfs/bfs trees, normalize HITS using l1, handle density of graphs with self loops
- Cleaner handling of current figure status with Matplotlib, Pajek files now don’t write troublesome header line, default alpha value for GEXF files, read curved edges from yEd GraphML

For full details of the issues closed for this release (added features and bug fixes) see: https://github.com/networkx/networkx/issues?milestone=1&page=1&state=closed

### API changes¶

## NetworkX 1.7¶

Release date: 4 July 2012

### Highlights¶

- New functions for k-clique community finding, flow hierarchy, union, disjoint union, compose, and intersection operators that work on lists of graphs, and creating the biadjacency matrix of a bipartite graph.
- New approximation algorithms for dominating set, edge dominating set, independent set, max clique, and min-weighted vertex cover.
- Many bug fixes and other improvements.

For full details of the tickets closed for this release (added features and bug fixes) see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.7

### API changes¶

## NetworkX 1.6¶

Release date: 20 November 2011

### Highlights¶

New functions for finding articulation points, generating random bipartite graphs, constructing adjacency matrix representations, forming graph products, computing assortativity coefficients, measuring subgraph centrality and communicability, finding k-clique communities, and writing JSON format output.

New examples for drawing with D3 Javascript library, and ordering matrices with the Cuthill-McKee algorithm.

More memory efficient implementation of current-flow betweenness and new approximation algorithms for current-flow betweenness and shortest-path betweenness.

Simplified handling of “weight” attributes for algorithms that use weights/costs/values. See *Version 1.6 notes and API changes*.

Updated all code to work with the PyPy Python implementation http://pypy.org which produces faster performance on many algorithms.

For full details of the tickets closed for this release (added features and bug fixes) see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.6

### API changes¶

## NetworkX 1.5¶

Release date: 4 June 2011

For full details of the tickets closed for this release see: https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.5

### Highlights¶

### New features¶

- Algorithms for
`generating`

and`analyzing`

bipartite graphs`Maximal independent set`

algorithm`Erdős-Gallai graphical degree sequence test`

`Negative edge cycle test`

- More memory efficient
`Dijkstra path length`

with cutoff parameter`Weighted clustering coefficient`

- Read and write version 1.2 of
`GEXF reader`

format`Neighbor degree correlation`

that handle subsets of nodes`In-place node relabeling`

- Many ‘weighted’ graph algorithms now take optional parameter to use specified edge attribute (default=’weight’) (
`ticket 509`

)- Test for
`distance regular`

graphs- Fast
`directed Erdős-Renyi graph`

generator- Fast
`expected degree graph`

generator`Navigable small world`

generator`Waxman model`

generator`Geographical threshold graph`

generator`Karate Club, Florentine Families, and Davis' Women's Club`

graphs

### API changes¶

### Bug fixes¶

- Fix edge handling for multigraphs in networkx/graphviz interface (
`ticket 507`

)- Update networkx/pydot interface for new versions of pydot (
`ticket 506`

), (`ticket 535`

)- Fix negative cycle handling in Bellman-Ford (
`ticket 502`

)- Write more attributes with GraphML and GML formats (
`ticket 480`

)- Handle white space better in read_edgelist (
`ticket 513`

)- Better parsing of Pajek format files (
`ticket 524`

) (`ticket 542`

)- Isolates functions work with directed graphs (
`ticket 526`

)- Faster conversion to numpy matrices (
`ticket 529`

)- Add graph[‘name’] and use properties to access Graph.name (
`ticket 544`

)- Topological sort confused None and 0 (
`ticket 546`

)- GEXF writer mishandled weight=0 (
`ticket 550`

)- Speedup in SciPy version of PageRank (
`ticket 554`

)- Numpy PageRank node order incorrect + speedups (
`ticket 555`

)

## NetworkX 1.4¶

Release date: 23 January 2011

### New features¶

`k-shell,k-crust,k-corona`

`read GraphML files from yEd`

`read/write GEXF format files`

`find cycles in a directed graph`

`DFS`

and`BFS`

algorithms`chordal graph functions`

`Prim's algorithm for minimum spanning tree`

`r-ary tree generator`

`rich club coefficient`

- NumPy matrix version of
`Floyd's algorithm for all-pairs shortest path`

`read GIS shapefiles`

`functions to get and set node and edge attributes`

- and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.4

### API changes¶

`gnp_random_graph()`

now takes a directed=True|False keyword instead of create_using`gnm_random_graph()`

now takes a directed=True|False keyword instead of create_using

## NetworkX 1.3¶

Release date: 28 August 2010

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- Works with Python versions 2.6, 2.7, 3.1, and 3.2 (but not 2.4 and 2.5).
`Minimum cost flow algorithms`

`Bellman-Ford shortest paths`

`GraphML reader and writer`

`More exception/error types`

- Updated many tests to unittest style. Run with: “import networkx; networkx.test()” (requires nose testing package)
- and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.3

## NetworkX 1.2¶

Release date: 28 July 2010

See: https://networkx.lanl.gov/trac/timeline

### New features¶

`Ford-Fulkerson max flow and min cut`

`Closeness vitality`

`Eulerian circuits`

`Functions for isolates`

`Simpler s_max generator`

- Compatible with IronPython-2.6
- Improved testing functionality: import networkx; networkx.test() tests entire package and skips tests with missing optional packages
- All tests work with Python-2.4
- and more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.2

## NetworkX 1.1¶

Release date: 21 April 2010

See: https://networkx.lanl.gov/trac/timeline

### New features¶

`Algorithm for finding a basis for graph cycles`

`Blockmodeling`

`Assortativity and mixing matrices`

`in-degree and out-degree centrality`

`Attracting components`

and`condensation`

.`Weakly connected components`

`Simpler interface to shortest path algorithms`

`Edgelist format to read and write data with attributes`

`Attribute matrices`

`GML reader for nested attributes`

- Current-flow (random walk)
`betweenness`

and`closeness`

.`Directed configuration model`

, and`directed random graph model`

.- Improved documentation of drawing, shortest paths, and other algorithms
- Many more tests, can be run with “import networkx; networkx.test()”
- and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.1

### API changes¶

#### Returning dictionaries¶

Several of the algorithms and the degree() method now return dictionaries keyed by node instead of lists. In some cases there was a with_labels keyword which is no longer necessary. For example,

```
>>> G=nx.Graph()
>>> G.add_edge('a','b')
>>> G.degree() # returns dictionary of degree keyed by node
{'a': 1, 'b': 1}
```

Asking for the degree of a single node still returns a single number

```
>>> G.degree('a')
1
```

The following now return dictionaries by default (instead of lists) and the with_labels keyword has been removed:

`Graph.degree()`

,`MultiGraph.degree()`

,`DiGraph.degree()`

,`DiGraph.in_degree()`

,`DiGraph.out_degree()`

,`MultiDiGraph.degree()`

,`MultiDiGraph.in_degree()`

,`MultiDiGraph.out_degree()`

.`clustering()`

,`triangles()`

`node_clique_number()`

,`number_of_cliques()`

,`cliques_containing_node()`

`eccentricity()`

The following now return dictionaries by default (instead of lists)

`pagerank()`

`hits()`

#### Adding nodes¶

add_nodes_from now accepts (node,attrdict) two-tuples

```
>>> G=nx.Graph()
>>> G.add_nodes_from([(1,{'color':'red'})])
```

### Bug fixes¶

- Support graph attributes with union, intersection, and other graph operations
- Improve subgraph speed (and related algorithms such as connected_components_subgraphs())
- Handle multigraphs in more operators (e.g. union)
- Handle double-quoted labels with pydot
- Normalize betweenness_centrality for undirected graphs correctly
- Normalize eigenvector_centrality by l2 norm
`read_gml()`

now returns multigraphs

## NetworkX 1.0.1¶

Release date: 11 Jan 2010

See: https://networkx.lanl.gov/trac/timeline

Bug fix release for missing setup.py in manifest.

## NetworkX 1.0¶

Release date: 8 Jan 2010

See: https://networkx.lanl.gov/trac/timeline

### New features¶

This release has significant changes to parts of the graph API to allow graph, node, and edge attributes. See http://networkx.lanl.gov//reference/api_changes.html

- Update Graph, DiGraph, and MultiGraph classes to allow attributes.
- Default edge data is now an empty dictionary (was the integer 1)
- Difference and intersection operators
- Average shortest path
- A* (A-Star) algorithm
- PageRank, HITS, and eigenvector centrality
- Read Pajek files
- Line graphs
- Minimum spanning tree (Kruskal’s algorithm)
- Dense and sparse Fruchterman-Reingold layout
- Random clustered graph generator
- Directed scale-free graph generator
- Faster random regular graph generator
- Improved edge color and label drawing with Matplotlib
- and much more, see https://networkx.lanl.gov/trac/query?status=closed&group=milestone&milestone=networkx-1.0

### Examples¶

- Update to work with networkx-1.0 API
- Graph subclass example

## NetworkX 0.99¶

Release date: 18 November 2008

See: https://networkx.lanl.gov/trac/timeline

### New features¶

This release has significant changes to parts of the graph API. See http://networkx.lanl.gov//reference/api_changes.html

- Update Graph and DiGraph classes to use weighted graphs as default Change in API for performance and code simplicity.
- New MultiGraph and MultiDiGraph classes (replace XGraph and XDiGraph)
- Update to use Sphinx documentation system http://networkx.lanl.gov/
- Developer site at https://networkx.lanl.gov/trac/
- Experimental LabeledGraph and LabeledDiGraph
- Moved package and file layout to subdirectories.

### Bug fixes¶

- handle root= option to draw_graphviz correctly

### Examples¶

- Update to work with networkx-0.99 API
- Drawing examples now use matplotlib.pyplot interface
- Improved drawings in many examples
- New examples - see http://networkx.lanl.gov/examples/

## NetworkX 0.37¶

Release date: 17 August 2008

See: https://networkx.lanl.gov/trac/timeline

NetworkX now requires Python 2.4 or later for full functionality.

### New features¶

- Edge coloring and node line widths with Matplotlib drawings
- Update pydot functions to work with pydot-1.0.2
- Maximum-weight matching algorithm
- Ubigraph interface for 3D OpenGL layout and drawing
- Pajek graph file format reader and writer
- p2g graph file format reader and writer
- Secondary sort in topological sort

### Bug fixes¶

- Better edge data handling with GML writer
- Edge betweenness fix for XGraph with default data of None
- Handle Matplotlib version strings (allow “pre”)
- Interface to PyGraphviz (to_agraph()) now handles parallel edges
- Fix bug in copy from XGraph to XGraph with multiedges
- Use SciPy sparse lil matrix format instead of coo format
- Clear up ambiguous cases for Barabasi-Albert model
- Better care of color maps with Matplotlib when drawing colored nodes and edges
- Fix error handling in layout.py

### Examples¶

- Ubigraph examples showing 3D drawing

## NetworkX 0.36¶

Release date: 13 January 2008

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- GML format graph reader, tests, and example (football.py)
- edge_betweenness() and load_betweenness()

### Bug fixes¶

- remove obsolete parts of pygraphviz interface
- improve handling of Matplotlib version strings
- write_dot() now writes parallel edges and self loops
- is_bipartite() and bipartite_color() fixes
- configuration model speedup using random.shuffle()
- convert with specified nodelist now works correctly
- vf2 isomorphism checker updates

## NetworkX 0.35.1¶

Release date: 27 July 2007

See: https://networkx.lanl.gov/trac/timeline

Small update to fix import readwrite problem and maintain Python2.3 compatibility.

## NetworkX 0.35¶

Release date: 22 July 2007

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- algorithms for strongly connected components.
- Brandes betweenness centrality algorithm (weighted and unweighted versions)
- closeness centrality for weighted graphs
- dfs_preorder, dfs_postorder, dfs_tree, dfs_successor, dfs_predecessor
- readers for GraphML, LEDA, sparse6, and graph6 formats.
- allow arguments in graphviz_layout to be passed directly to graphviz

### Bug fixes¶

- more detailed installation instructions
- replaced dfs_preorder,dfs_postorder (see search.py)
- allow initial node positions in spectral_layout
- report no error on attempting to draw empty graph
- report errors correctly when using tuples as nodes #114
- handle conversions from incomplete dict-of-dict data

## NetworkX 0.34¶

Release date: 12 April 2007

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- benchmarks for graph classes
- Brandes betweenness centrality algorithm
- Dijkstra predecessor and distance algorithm
- xslt to convert DIA graphs to NetworkX
- number_of_edges(u,v) counts edges between nodes u and v
- run tests with python setup_egg.py test (needs setuptools) else use python -c “import networkx; networkx.test()”
- is_isomorphic() that uses vf2 algorithm

### Bug fixes¶

- speedups of neighbors()
- simplified Dijkstra’s algorithm code
- better exception handling for shortest paths
- get_edge(u,v) returns None (instead of exception) if no edge u-v
- floyd_warshall_array fixes for negative weights
- bad G467, docs, and unittest fixes for graph atlas
- don’t put nans in numpy or scipy sparse adjacency matrix
- handle get_edge() exception (return None if no edge)
- remove extra kwds arguments in many places
- no multi counting edges in conversion to dict of lists for multigraphs
- allow passing tuple to get_edge()
- bad parameter order in node/edge betweenness
- edge betweenness doesn’t fail with XGraph
- don’t throw exceptions for nodes not in graph (silently ignore instead) in edges_* and degree_*

## NetworkX 0.33¶

Release date: 27 November 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

draw edges with specified colormap

more efficient version of Floyd’s algorithm for all pairs shortest path

use numpy only, Numeric is deprecated

include tests in source package (networkx/tests)

include documentation in source package (doc)

- tests can now be run with
>>> import networkx >>> networkx.test()

### Bug fixes¶

- read_gpickle now works correctly with Windows
- refactored large modules into smaller code files
- degree(nbunch) now returns degrees in same order as nbunch
- degree() now works for multiedges=True
- update node_boundary and edge_boundary for efficiency
- edited documentation for graph classes, now mostly in info.py

### Examples¶

- Draw edges with colormap

## NetworkX 0.32¶

Release date: 29 September 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- Update to work with numpy-1.0x
- Make egg usage optional: use python setup_egg.py bdist_egg to build egg
- Generators and functions for bipartite graphs
- Experimental classes for trees and forests
- Support for new pygraphviz update (in nx_agraph.py) , see http://networkx.lanl.gov/pygraphviz/ for pygraphviz details

### Bug fixes¶

- Handle special cases correctly in triangles function
- Typos in documentation
- Handle special cases in shortest_path and shortest_path_length, allow cutoff parameter for maximum depth to search
- Update examples: erdos_renyi.py, miles.py, roget,py, eigenvalues.py

### Examples¶

- Expected degree sequence
- New pygraphviz interface

## NetworkX 0.31¶

Release date: 20 July 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- arbitrary node relabeling (use relabel_nodes)
- conversion of NetworkX graphs to/from Python dict/list types, numpy matrix or array types, and scipy_sparse_matrix types
- generator for random graphs with given expected degree sequence

### Bug fixes¶

- Allow drawing graphs with no edges using pylab
- Use faster heapq in dijkstra
- Don’t complain if X windows is not available

### Examples¶

- update drawing examples

## NetworkX 0.30¶

Release date: 23 June 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- update to work with Python 2.5
- bidirectional version of shortest_path and Dijkstra
- single_source_shortest_path and all_pairs_shortest_path
- s-metric and experimental code to generate maximal s-metric graph
- double_edge_swap and connected_double_edge_swap
- Floyd’s algorithm for all pairs shortest path
- read and write unicode graph data to text files
- read and write YAML format text files, http://yaml.org

### Bug fixes¶

- speed improvements (faster version of subgraph, is_connected)
- added cumulative distribution and modified discrete distribution utilities
- report error if DiGraphs are sent to connected_components routines
- removed with_labels keywords for many functions where it was causing confusion
- function name changes in shortest_path routines
- saner internal handling of nbunch (node bunches), raise an exception if an nbunch isn’t a node or iterable
- better keyword handling in io.py allows reading multiple graphs
- don’t mix Numeric and numpy arrays in graph layouts and drawing
- avoid automatically rescaling matplotlib axes when redrawing graph layout

### Examples¶

- unicode node labels

## NetworkX 0.29¶

Release date: 28 April 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- Algorithms for betweenness, eigenvalues, eigenvectors, and spectral projection for threshold graphs
- Use numpy when available
- dense_gnm_random_graph generator
- Generators for some directed graphs: GN, GNR, and GNC by Krapivsky and Redner
- Grid graph generators now label by index tuples. Helper functions for manipulating labels.
- relabel_nodes_with_function

### Bug fixes¶

- Betweenness centrality now correctly uses Brandes definition and has normalization option outside main loop
- Empty graph now labeled as empty_graph(n)
- shortest_path_length used python2.4 generator feature
- degree_sequence_tree off by one error caused nonconsecutive labeling
- periodic_grid_2d_graph removed in favor of grid_2d_graph with periodic=True

## NetworkX 0.28¶

Release date: 13 March 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- Option to construct Laplacian with rows and columns in specified order
- Option in convert_node_labels_to_integers to use sorted order
- predecessor(G,n) function that returns dictionary of nodes with predecessors from breadth-first search of G starting at node n. https://networkx.lanl.gov/trac/ticket/26

### Examples¶

- Formation of giant component in binomial_graph:
- Chess masters matches:
- Gallery https://networkx.lanl.gov/gallery.html

### Bug fixes¶

- Adjusted names for random graphs.

- erdos_renyi_graph=binomial_graph=gnp_graph: n nodes with edge probability p
- gnm_graph: n nodes and m edges
- fast_gnp_random_graph: gnp for sparse graphs (small p)
Documentation contains correct spelling of Barabási, Bollobás, Erdős, and Rényi in UTF-8 encoding

Increased speed of connected_components and related functions by using faster BFS algorithm in networkx.paths https://networkx.lanl.gov/trac/ticket/27

XGraph and XDiGraph with multiedges=True produced error on delete_edge

Cleaned up docstring errors

Normalize names of some graphs to produce strings that represent calling sequence

## NetworkX 0.27¶

Release date: 5 February 2006

See: https://networkx.lanl.gov/trac/timeline

### New features¶

- sparse_binomial_graph: faster graph generator for sparse random graphs
- read/write routines in io.py now handle XGraph() type and gzip and bzip2 files
- optional mapping of type for read/write routine to allow on-the-fly conversion of node and edge datatype on read
- Substantial changes related to digraphs and definitions of neighbors() and edges(). For digraphs edges=out_edges. Neighbors now returns a list of neighboring nodes with possible duplicates for graphs with parallel edges See https://networkx.lanl.gov/trac/ticket/24
- Addition of out_edges, in_edges and corresponding out_neighbors and in_neighbors for digraphs. For digraphs edges=out_edges.

### Examples¶

- Minard’s data for Napoleon’s Russian campaign

### Bug fixes¶

- XGraph(multiedges=True) returns a copy of the list of edges for get_edge()

## NetworkX 0.26¶

Release date: 6 January 2006

### New features¶

- Simpler interface to drawing with pylab
- G.info(node=None) function returns short information about graph or node
- adj_matrix now takes optional nodelist to force ordering of rows/columns in matrix
- optional pygraphviz and pydot interface to graphviz is now callable as “graphviz” with pygraphviz preferred. Use draw_graphviz(G).

### Examples¶

- Several new examples showing how draw to graphs with various properties of nodes, edges, and labels

### Bug fixes¶

- Default data type for all graphs is now None (was the integer 1)
- add_nodes_from now won’t delete edges if nodes added already exist
- Added missing names to generated graphs
- Indexes for nodes in graphs start at zero by default (was 1)

## NetworkX 0.25¶

Release date: 5 December 2005

### New features¶

- Uses setuptools for installation http://peak.telecommunity.com/DevCenter/setuptools
- Improved testing infrastructure, can now run python setup.py test
- Added interface to draw graphs with pygraphviz https://networkx.lanl.gov/pygraphviz/
- is_directed() function call

### Examples¶

- Email example shows how to use XDiGraph with Python objects as edge data

### Documentation¶

- Reformat menu, minor changes to Readme, better stylesheet

### Bug fixes¶

- use create_using= instead of result= keywords for graph types in all cases
- missing weights for degree 0 and 1 nodes in clustering
- configuration model now uses XGraph, returns graph with identical degree sequence as input sequence
- fixed Dijkstra priority queue
- fixed non-recursive toposort and is_directed_acyclic graph

## NetworkX 0.24¶

Release date: 20 August 2005

### Bug fixes¶

- Update of Dijkstra algorithm code
- dfs_successor now calls proper search method
- Changed to list comprehension in DiGraph.reverse() for python2.3 compatibility
- Barabasi-Albert graph generator fixed
- Attempt to add self loop should add node even if parallel edges not allowed

## NetworkX 0.23¶

Release date: 14 July 2005

The NetworkX web locations have changed:

http://networkx.lanl.gov/ - main documentation site http://networkx.lanl.gov/svn/ - subversion source code repository https://networkx.lanl.gov/trac/ - bug tracking and info

### Important Change¶

The naming conventions in NetworkX have changed. The package name “NX” is now “networkx”.

The suggested ways to import the NetworkX package are

- import networkx
- import networkx as NX
- from networkx import *

### New features¶

DiGraph reverse

- Graph generators

- watts_strogatz_graph now does rewiring method
- old watts_strogatz_graph->newman_watts_strogatz_graph

### Examples¶

### Documentation¶

- Changed to reflect NX-networkx change
- main site is now https://networkx.lanl.gov/

### Bug fixes¶

- Fixed logic in io.py for reading DiGraphs.
- Path based centrality measures (betweenness, closeness) modified so they work on graphs that are not connected and produce the same result as if each connected component were considered separately.

## NetworkX 0.22¶

Release date: 17 June 2005

### New features¶

Topological sort, testing for directed acyclic graphs (DAGs)

Dijkstra’s algorithm for shortest paths in weighted graphs

Multidimensional layout with dim=n for drawing

3d rendering demonstration with vtk

- Graph generators

- random_powerlaw_tree
- dorogovtsev_goltsev_mendes_graph

### Examples¶

- Kevin Bacon movie actor graph: Examples/kevin_bacon.py
- Compute eigenvalues of graph Laplacian: Examples/eigenvalues.py
- Atlas of small graphs: Examples/atlas.py

### Documentation¶

- Rewrite of setup scripts to install documentation and tests in documentation directory specified

### Bug fixes¶

- Handle calls to edges() with non-node, non-iterable items.
- truncated_tetrahedral_graph was just plain wrong
- Speedup of betweenness_centrality code
- bfs_path_length now returns correct lengths
- Catch error if target of search not in connected component of source
- Code cleanup to label internal functions with _name
- Changed import statement lines to always use “import NX” to protect name-spaces
- Other minor bug-fixes and testing added