Install¶
NetworkX requires Python 3.6, 3.7, or 3.8. If you do not already have a Python environment configured on your computer, please see the instructions for installing the full scientific Python stack.
Below we assume you have the default Python environment already configured on
your computer and you intend to install networkx inside of it. If you want
to create and work with Python virtual environments, please follow instructions
on venv and virtual
environments.
First, make sure you have the latest version of pip (the Python package manager)
installed. If you do not, refer to the Pip documentation and install pip first.
Install the released version¶
Install the current release of networkx with pip:
$ pip install networkx
To upgrade to a newer release use the --upgrade flag:
$ pip install --upgrade networkx
If you do not have permission to install software systemwide, you can
install into your user directory using the --user flag:
$ pip install --user networkx
Alternatively, you can manually download networkx from
GitHub or
PyPI.
To install one of these versions, unpack it and run the following from the
top-level source directory using the Terminal:
$ pip install .
Install the development version¶
If you have Git installed on your system, it is also
possible to install the development version of networkx.
Before installing the development version, you may need to uninstall the
standard version of networkx using pip:
$ pip uninstall networkx
Then do:
$ git clone https://github.com/networkx/networkx.git
$ cd networkx
$ pip install -e .
The pip install -e . command allows you to follow the development branch as
it changes by creating links in the right places and installing the command
line scripts to the appropriate locations.
Then, if you want to update networkx at any time, in the same directory do:
$ git pull
Optional packages¶
Note
Some optional packages (e.g., gdal) may require compiling
C or C++ code. If you have difficulty installing these packages
with pip, please review the instructions for installing
the full scientific Python stack.
The following optional packages provide additional functionality. See the
files in the requirements/ directory for information about specific
version requirements.
NumPy provides array-based dense matrix representations of graphs and high-performance array math and linear algebra which is used in some graph algorithms.
SciPy provides sparse matrix representation of graphs and many numerical scientific tools.
pandas provides a DataFrame, which is a tabular data structure with labeled axes.
Matplotlib provides flexible drawing of graphs.
PyGraphviz and pydot provide graph drawing and graph layout algorithms via GraphViz.
PyYAML provides YAML format reading and writing.
gdal provides shapefile format reading and writing.
lxml used for GraphML XML format.
To install networkx and all optional packages, do:
$ pip install networkx[all]
To explicitly install all optional packages, do:
$ pip install numpy scipy pandas matplotlib pygraphviz pydot pyyaml gdal
Or, install any optional package (e.g., numpy) individually:
$ pip install numpy
Testing¶
NetworkX uses the Python pytest testing package. You can learn more
about pytest on their homepage.
Test a source distribution¶
You can test the complete package from the unpacked source directory with:
pytest networkx
Test an installed package¶
From a shell command prompt you can test the installed package with:
pytest --pyargs networkx
If you have a file-based (not a Python egg) installation you can test the installed package with:
>>> import networkx as nx
>>> nx.test()
or:
python -c "import networkx as nx; nx.test()"
-
test(verbosity=1, doctest=False)¶ Run NetworkX tests.
- Parameters
verbosity (integer, optional) – Level of detail in test reports. Higher numbers provide more detail.
doctest (bool, optional) – True to run doctests in code modules