A python graph library implemented in Rust

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Project description

retworkx

Build Status

You can see the full rendered docs at: https://qiskit.org/documentation/retworkx

retworkx is a general purpose graph library for python3 written in Rust to take advantage of the performance and safety that Rust provides. It was built as a replacement for qiskit's previous (and current) networkx usage (hence the name) but is designed to provide a high performance general purpose graph library for any python application. 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-terra's transpiler, but it has since grown to cover all the graph usage in Qiskit and other applications.

Installing retworkx

retworkx 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 retworkx

This will install a precompiled version of retworkx into your python environment.

Installing on a platform without precompiled binaries

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 >=1.41.1 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 retworkx

will build retworkx 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 retworkx. 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.

Optional dependencies

If you're planning to use the retworkx.visualization module you will need to install optional dependencies to use the functions. The matplotlib based drawer function retworkx.visualization.mpl_draw requires that the matplotlib library is installed. This can be installed with pip install matplotlib or when you're installing retworkx with pip install 'retworkx[mpl]'. If you're going to use the graphviz based drawer function retworkx.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 retworkx with pip install 'retworkx[graphviz]'.

If you would like to install all the optional Python dependencies when you install retworkx you can use pip install 'retworkx[all]' to do this.

Using retworkx

Once you have retworkx installed you can use it by importing retworkx. All the functions and graph classes are off the root of the package. For example, calculating the shortest path between A and C would be:

import retworkx

graph = retworkx.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
retworkx.dijkstra_shortest_paths(graph, a, c, weight_fn=float)

Building from source

The first step for building retworkx from source is to clone it locally with:

git clone https://github.com/Qiskit/retworkx.git

retworkx 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 retworkx 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 retworkx 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 retworkx 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 retworkx 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 retworkx by rerunning pip install to have any changes reflected in your python environment.

Develop Mode

If you'd like to build retworkx in debug mode and use an interactive debugger while working on a change you can use python setup.py develop to build and install retworkx in develop mode. This will build retworkx without optimizations and include debuginfo which can be handy for debugging. Do note that installing retworkx this way will be significantly slower then using pip install and should only be used for debugging/development.

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 retworkx binary. If you want to build retworkx in debug mode you have to use python setup.py develop.

Authors and Citation

retworkx is the work of many people who contribute to the project at different levels. If you use retworkx in your research, please cite our paper as per the included BibTeX file.

Project details

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Release history Release notifications | RSS feed

0.15.1

Jun 28, 2024

0.15.0

Jun 27, 2024

0.14.2

Mar 12, 2024

0.14.1

Feb 22, 2024

0.14.0

Jan 23, 2024

0.13.2

Oct 3, 2023

0.13.1

Jul 31, 2023

0.13.0

Jun 7, 2023

0.12.1

Nov 23, 2022

0.12.0

Oct 7, 2022

This version

0.11.0

Jan 19, 2022

0.10.2

Sep 8, 2021

0.10.1

Aug 25, 2021

0.10.0

Aug 25, 2021

0.9.0

Jun 1, 2021

0.8.0

Mar 2, 2021

0.7.2

Dec 14, 2020

0.7.1

Dec 3, 2020

0.7.0

Dec 3, 2020

0.6.0

Nov 12, 2020

0.5.0

Sep 18, 2020

0.4.0

Jul 17, 2020

0.3.4

Apr 27, 2020

0.3.3

Mar 18, 2020

0.3.2

Mar 13, 2020

0.3.1

Mar 6, 2020

0.3.0

Feb 20, 2020

0.2.0

Feb 10, 2020

0.1.1

Jan 31, 2020

0.1.0

Jan 27, 2020

0.0.10

Sep 18, 2019

0.0.9

May 31, 2019

0.0.8

May 22, 2019

0.0.7

May 16, 2019

0.0.6

May 15, 2019

0.0.5

May 14, 2019

0.0.3

May 13, 2019

0.0.2

May 13, 2019

0.0.1

May 11, 2019

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Algorithm	Hash digest
SHA256	`8842fcbfecde45a4562aaa5ca61f7e4d3d60a84ffd63de3af8d1b436f7bc277d`
MD5	`bf658a3159a01dfa5cf29ea33f7a4318`
BLAKE2b-256	`3f7cf72e4cc862d110efb60682b764f323109c9d5324cae8bc7599b64692f32d`

Algorithm	Hash digest
SHA256	`03d3967cc9c25c6fbee88aae99f867b1f51acedfcce7925df353f1a3ee8059f8`
MD5	`df539944880a28ffd998740ee5aa7325`
BLAKE2b-256	`7f3d4ebb2c352f3381b1a10bef2de1602ea9d43154ef0c5eb744f4a1adbb9bf6`

Algorithm	Hash digest
SHA256	`c731cf468cdc9158505687124427b3f9ddc4a72ad7dfaefbe4e80bd126c792c7`
MD5	`d8206581564b7efe633f0dd06a9c90f3`
BLAKE2b-256	`65483a9acc9393972b6e18191a24ea6d7a63a93d7c87bd9e6e3b6a4f6f93efdb`

retworkx 0.11.0

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retworkx

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Algorithm	Hash digest
SHA256	`b08484348add5eff6ddf48dc4c21aa6c085c4520287fbc11bbfdf6c44c33b387`
MD5	`dbbe1ef708fe8fa75f0a608103f1c31f`
BLAKE2b-256	`a4229c002da91a85618ed9a9cbbb0cf84e4f7e88f12c8f4ec01de77a028f3f44`

Algorithm	Hash digest
SHA256	`21f58c69fb68b2d9e1307a75dc239ccdca038a655127df5763e161b715e5ae71`
MD5	`e3e4b7438a8f26e766e5d27849704cc5`
BLAKE2b-256	`3c987b26bae577d48bc1ed2c3f94589594c9c8692a1fa9c4518f36cac6c931db`

Algorithm	Hash digest
SHA256	`adbcd034bc7acd1aa67fd95186735ce37c318b6467c054267c53dd2e8d0a1614`
MD5	`37ad9ca8213e8f5ab1f72735cdce10ce`
BLAKE2b-256	`fb469784c98b0fa7a277ff378ddad1aa2c9ed142ce95e698631a937d63bb9acd`

Algorithm	Hash digest
SHA256	`f4537cd72e12be4c7ad74b790039fc58b2383c3ef8877f60b3ebcd715960d2cd`
MD5	`1dcc13d177d5fe87fe9e97bd81a21b18`
BLAKE2b-256	`4f7335a0856179f5cdc1d9f2587c5ac66cbc92d93809babf83bd65089b84eda1`

Algorithm	Hash digest
SHA256	`c818c6034da670686f4e5c0aa424175ae95744b11d2abced3c6f0a9c7e7ab9e2`
MD5	`1d52bfe718ff2264149463c27de9a35f`
BLAKE2b-256	`01dca46b4d57bb24fb7c8e1512799e3ed7eb8497b3439ec189a5110981ff7077`

Algorithm	Hash digest
SHA256	`a199e0374036503db8c98e45e2476896fbcaf7f620f4f81206e0ee1b19a436c5`
MD5	`2dfe76d6e56dd8e44de9b7425efbfb43`
BLAKE2b-256	`06e99f7a9c10b1a6e3d32b31f2b3bab53921a11b692136ff7ad51efff2959da0`

Algorithm	Hash digest
SHA256	`4f3a2d157a8f7b2331339eca644742db2476c8c5af7846c3f22d994efcc505c2`
MD5	`0b26fe8208e65fe62ce03f8443d3d09b`
BLAKE2b-256	`5c3eae6372f4ed595ff084a0b0ad4ad7186c827475bc8b112f4d65e504f40192`

Algorithm	Hash digest
SHA256	`4b9a8f5f2c6ae01acfb8de82ae4733b2fd42d89dfa53153e5816df73c2098dd5`
MD5	`c6067d663f112394960e35dfdf8fe5c6`
BLAKE2b-256	`c0bf5584b4c2f6b62f0a326680d9a645ff3c4e4044dcc9b7c0d7540c4787b491`

Algorithm	Hash digest
SHA256	`6eecc461f5226028011192d7421c1886121c7b6760191fe1d774d8e72d9961df`
MD5	`08beba4331b8129c0fa904c008c6c05d`
BLAKE2b-256	`35e62276ef5a9b0ddc737042dd151f665250bc63a4e5457785f6472fdd8fc5f7`

Algorithm	Hash digest
SHA256	`804aa25af8898a2e0a4fbf2f94fb4d13cb7543722316a09cbed0e7c4f9b445d4`
MD5	`4ca1cf6b51204529936cd519d8dd278a`
BLAKE2b-256	`97796341de7bf5e77495fdf7f9e0fdb651a1267b11aa08a2321afcb7cf3f7d17`