- You can see the full rendered docs at: https://www.rustworkx.org/
A high-performance, general-purpose graph library for Python, written in Rust.
Once installed, simply import rustworkx
.
All graph classes and top-level functions are accessible with a single import.
To illustrate this, the following example calculates the shortest path
between two nodes A
and C
in an undirected graph.
import rustworkx
# Rustworkx's undirected graph type.
graph = rustworkx.PyGraph()
# Each time add node is called, it returns a new node index
a = graph.add_node("A")
b = graph.add_node("B")
c = graph.add_node("C")
# add_edges_from takes tuples of node indices and weights,
# and returns edge indices
graph.add_edges_from([(a, b, 1.5), (a, c, 5.0), (b, c, 2.5)])
# Returns the path A -> B -> C
rustworkx.dijkstra_shortest_paths(graph, a, c, weight_fn=float)
rustworkx is published on PyPI so on x86_64, i686, ppc64le, s390x, and aarch64 Linux systems, x86_64 on Mac OSX, and 32 and 64 bit Windows installing is as simple as running:
pip install rustworkx
This will install a precompiled version of rustworkx into your Python environment.
If there are no precompiled binaries published for your system you'll have to
build the package from source. However, to be able able to build the package
from the published source package you need to have Rust >= 1.70 installed (and
also cargo which is normally included with
rust) You can use rustup (a cross platform installer for
rust) to make this simpler, or rely on
other installation methods.
A source package is also published on pypi, so you still can also run the above
pip
command to install it. Once you have rust properly installed, running:
pip install rustworkx
will build rustworkx for your local system from the source package and install it just as it would if there was a prebuilt binary available.
Note
To build from source you will need to ensure you have pip >=19.0.0
installed, which supports PEP-517, or that you have manually installed
setuptools-rust
prior to running pip install rustworkx
. If you recieve an
error about setuptools-rust
not being found you should upgrade pip with
pip install -U pip
or manually install setuptools-rust
with
pip install setuptools-rust
and try again.
If you're planning to use the rustworkx.visualization
module you will need to
install optional dependencies to use the functions. The matplotlib based drawer
function rustworkx.visualization.mpl_draw
requires that the
matplotlib library is installed. This can be
installed with pip install matplotlib
or when you're installing rustworkx with
pip install 'rustworkx[mpl]'
. If you're going to use the graphviz based drawer
function rustworkx.visualization.graphviz_drawer
first you will need to install
graphviz, instructions for this can be found here:
https://graphviz.org/download/#executable-packages. Then you
will need to install the pillow Python library.
This can be done either with pip install pillow
or when installing rustworkx
with pip install 'rustworkx[graphviz]'
.
If you would like to install all the optional Python dependencies when you
install rustworkx you can use pip install 'rustworkx[all]'
to do this.
rustworkx is the work of many people who contribute to the project at different levels. If you use rustworkx in your research, please cite our paper as per the included BibTeX file.
Besides Github interactions (such as opening issues) there are two locations
available to talk to other rustworkx users and developers. The first is a
public Slack channel in the Qiskit workspace,
#rustworkx. You can join the
Qiskit Slack workspace here. Additionally,
there is an IRC channel #rustworkx
on the OFTC IRC network
The first step for building rustworkx from source is to clone it locally with:
git clone https://github.com/Qiskit/rustworkx.git
rustworkx uses PyO3 and
setuptools-rust to build the
python interface, which enables using standard python tooling to work. So,
assuming you have rust installed, you can easily install rustworkx into your
python environment using pip
. Once you have a local clone of the repo, change
your current working directory to the root of the repo. Then, you can install
rustworkx into your python env with:
pip install .
Assuming your current working directory is still the root of the repo. Otherwise you can run:
pip install $PATH_TO_REPO_ROOT
which will install it the same way. Then rustworkx is installed in your
local python environment. There are 2 things to note when doing this
though, first if you try to run python from the repo root using this
method it will not work as you expect. There is a name conflict in the
repo root because of the local python package shim used in building the
package. Simply run your python scripts or programs using rustworkx
outside of the repo root. The second issue is that any local changes you
make to the rust code will not be reflected live in your python environment,
you'll need to recompile rustworkx by rerunning pip install
to have any
changes reflected in your python environment.
If you'd like to build rustworkx in debug mode and use an interactive debugger
while working on a change you can use python setup.py develop
to build
and install rustworkx in develop mode. This will build rustworkx without
optimizations and include debuginfo which can be handy for debugging. Do note
that installing rustworkx this way will be significantly slower then using
pip install
and should only be used for debugging/development.
Tip
It's worth noting that pip install -e
does not work, as it will link the python
packaging shim to your python environment but not build the rustworkx binary. If
you want to build rustworkx in debug mode you have to use
python setup.py develop
.
Rustworkx was originally called retworkx and was created initially to be a replacement for Qiskit's previous (and current) NetworkX usage (hence the original name). The project was originally started to build a faster directed graph to use as the underlying data structure for the DAG at the center of qiskit's transpiler. However, since it's initial introduction the project has grown substantially and now covers all applications that need to work with graphs which includes Qiskit.