/py-networkx, Python package for creating and manipulating graphs and networks
1.11, Package name:
py27-networkx-1.11, Maintainer: pkgsrc-users
NetworkX (NX) is a Python package for the creation, manipulation, and
study of the structure, dynamics, and functions of complex networks.
- Includes standard graph-theoretic and statistical physics functions
- Easy exchange of network algorithms between applications,
disciplines, and platforms
- Includes many classic graphs and synthetic networks
- Nodes and edges can be "anything"
(e.g. time-series, text, images, XML records)
- Exploits existing code from high-quality legacy software in C,
C++, Fortran, etc.
- Open source (encourages community input)
Required to run:
] Required to build:
Master sites: SHA1:
Version history: (Expand)
- (2016-08-12) Updated to version: py27-networkx-1.11
- (2015-11-01) Updated to version: py27-networkx-1.10
- (2014-07-31) Updated to version: py27-networkx-1.9
- (2014-06-10) Updated to version: py27-networkx-1.8.1
- (2012-10-04) Updated to version: py27-networkx-1.7nb1
- (2012-07-13) Updated to version: py27-networkx-1.7
CVS history: (Expand)
| 2016-09-11 18:55:17 by Thomas Klausner | Files touched by this commit (1) |
This package does in fact support python-3.x.
| 2016-08-12 15:38:22 by Wen Heping | Files touched by this commit (3) | |
Update to 1.11
Based on PR/51271 from email@example.com
[#1930] No longer import nx_agraph and nx_pydot into the top-level \
namespace. They can be accessed within networkx as e.g. nx.nx_agraph.write_dot \
or imported as from networkx.drawing.nx_agraph import write_dot.
[#1750] Arguments center and scale are now available for all layout \
functions. The defaul values revert to the v1.9 values (center is the origin for \
circular layouts and domain is [0, scale) for others.
[#1924] Replace pydot with pydotplus for drawing with the pydot interface.
[#1888] Replace support for Python3.2 with support for Python 3.5.
[#1763] Set up appveyor to automatically test installation on Windows \
machines. Remove symbolic links in examples to help such istallation.
Change many doc_string typos to allow sphinx to build the docs without errors or \
Enable the docs to be automatically built on readthedocs.org by changing \
| 2016-07-09 15:04:18 by Thomas Klausner | Files touched by this commit (599) |
Remove python33: adapt all packages that refer to it.
| 2016-06-10 11:06:54 by Thomas Klausner | Files touched by this commit (1) |
| 2016-06-08 19:43:49 by Thomas Klausner | Files touched by this commit (356) |
Switch to MASTER_SITES_PYPI.
| 2015-12-05 22:26:09 by Adam Ciarcinski | Files touched by this commit (578) |
Extend PYTHON_VERSIONS_INCOMPATIBLE to 35
| 2015-11-01 10:58:28 by Thomas Klausner | Files touched by this commit (3) | |
Update py-networkx to 1.10, based on PR 50383 by Derouiche.
[#1501] connected_components, weakly_connected_components, and \
strongly_connected_components return now a generator of sets of nodes. \
Previously the generator was of lists of nodes. This PR also refactored the \
connected_components and weakly_connected_components implementations making them \
faster, especially for large graphs.
[#1547] The func_iter functions in Di/Multi/Graphs classes are slated for \
removal in NetworkX 2.0 release. func will behave like func_iter and return an \
iterator instead of list. These functions are deprecated in NetworkX 1.10 \
[#823] A enumerate_all_cliques function is added in the clique package \
(networkx.algorithms.clique) for enumerating all cliques (including nonmaximal \
ones) of undirected graphs.
[#1105] A coloring package (networkx.algorithms.coloring) is created for \
graph coloring algorithms. Initially, a greedy_color function is provided for \
coloring graphs using various greedy heuristics.
[#1193] A new generator edge_dfs, added to networkx.algorithms.traversal, \
implements a depth-first traversal of the edges in a graph. This complements \
functionality provided by a depth-first traversal of the nodes in a graph. For \
multigraphs, it allows the user to know precisely which edges were followed in a \
traversal. All NetworkX graph types are supported. A traversal can also reverse \
edge orientations or ignore them.
[#1194] A find_cycle function is added to the networkx.algorithms.cycles \
package to find a cycle in a graph. Edge orientations can be optionally reversed \
[#1210] Add a random generator for the duplication-divergence model.
[#1241] A new networkx.algorithms.dominance package is added for \
dominance/dominator algorithms on directed graphs. It contains a \
immediate_dominators function for computing immediate dominators/dominator trees \
and a dominance_frontiers function for computing dominance frontiers.
[#1269] The GML reader/parser and writer/generator are rewritten to remove \
the dependence on pyparsing and enable handling of arbitrary graph data.
[#1280] The network simplex method in the networkx.algorithms.flow package \
is rewritten to improve its performance and support multi- and disconnected \
networks. For some cases, the new implementation is two or three orders of \
magnitude faster than the old implementation.
[#1286] Added the Margulis–Gabber–Galil graph to networkx.generators.
[#1306] Added the chordal p-cycle graph, a mildly explicit algebraic \
construction of a family of 3-regular expander graphs. Also, moves both the \
existing expander graph generator function (for the Margulis-Gabber-Galil \
expander) and the new chordal cycle graph function to a new module, \
[#1314] Allow overwriting of base class dict with dict-like: OrderedGraph, \
ThinGraph, LogGraph, etc.
[#1321] Added to_pandas_dataframe and from_pandas_dataframe.
[#1322] Added the Hopcroft–Karp algorithm for finding a maximum \
cardinality matching in bipartite graphs.
[#1336] Expanded data keyword in G.edges and added default keyword.
[#1338] Added support for finding optimum branchings and arborescences.
[#1340] Added a from_pandas_dataframe function that accepts Pandas \
DataFrames and returns a new graph object. At a minimum, the DataFrame must have \
two columns, which define the nodes that make up an edge. However, the function \
can also process an arbitrary number of additional columns as edge attributes, \
such as ‘weight’.
[#1354] Expanded layout functions to add flexibility for drawing subsets of \
nodes with distinct layouts and for centering each layout around given \
[#1356] Added ordered variants of default graph class.
[#1360] Added harmonic centrality to network.algorithms.centrality.
[#1390] The generators.bipartite have been moved to \
algorithms.bipartite.generators. The functions are not imported in the main \
namespace, so to use it, the bipartite package has to be imported.
[#1391] Added Kanevsky’s algorithm for finding all minimum-size separating \
node sets in an undirected graph. It is implemented as a generator of node cut \
[#1399] Added power function for simple graphs
[#1405] Added fast approximation for node connectivity based on White and \
Newman’s approximation algorithm for finding node independent paths between \
[#1413] Added transitive closure and antichains function for directed \
acyclic graphs in algorithms.dag. The antichains function was contributed by \
Peter Jipsen and Franco Saliola and originally developed for the SAGE project.
[#1425] Added generator function for the complete multipartite graph.
[#1427] Added nonisomorphic trees generator.
[#1436] Added a generator function for circulant graphs to the \
[#1437] Added function for computing quotient graphs; also created a new \
[#1438] Added longest_path and longest_path_length for DAG.
[#1439] Added node and edge contraction functions to networkx.algorithms.minors.
[#1445] Added a new modularity matrix module to networkx.linalg, and \
associated spectrum functions to the networkx.linalg.spectrum module.
[#1447] Added function to generate all simple paths starting with the \
shortest ones based on Yen’s algorithm for finding k shortest paths at \
[#1455] Added the directed modularity matrix to the \
[#1474] Adds triadic_census function; also creates a new module, \
[#1476] Adds functions for testing if a graph has weighted or negatively \
weighted edges. Also adds a function for testing if a graph is empty. These are \
is_weighted, is_negatively_weighted, and is_empty.
[#1481] Added Johnson’s algorithm; one more algorithm for shortest paths. \
It solves all pairs shortest path problem. This is johnson at \
[#1414] Added Moody and White algorithm for identifying k_components in a \
graph, which is based on Kanevsky’s algorithm for finding all minimum-size \
node cut-sets (implemented in all_node_cuts #1391).
[#1415] Added fast approximation for k_components to the \
networkx.approximation package. This is based on White and Newman approximation \
algorithm for finding node independent paths between two nodes (see #1405).
[#1236] The legacy ford_fulkerson maximum flow function is removed. Use \
[#1192] Support for Python 2.6 is dropped.
| 2014-07-28 14:16:23 by Wen Heping | Files touched by this commit (3) | |
Update to 1.9
Add missing DEPENDS
Release date: 21 June 2014
Support for Python 3.1 is dropped in this release.
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