A python graph library implemented in Rust

These details have not been verified by PyPI

Project links

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.

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 pydot and pillow Python libraries. This can be done either with pip install pydot 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.

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.

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, building a DAG and adding 2 nodes with an edge between them would be:

import retworkx

my_dag = retworkx.PyDAG(cycle_check=True)
# add_node(), add_child(), and add_parent() return the node index
# The sole argument here can be any python object
root_node = my_dag.add_node("MyRoot")
# The second and third arguments can be any python object
my_dag.add_child(root_node, "AChild", ["EdgeData"])

Project details

These details have not been verified by PyPI

Project links

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

0.11.0

Jan 19, 2022

0.10.2

Sep 8, 2021

0.10.1

Aug 25, 2021

0.10.0

Aug 25, 2021

This version

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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

retworkx-0.9.0.tar.gz (124.1 kB view details)

Uploaded Jun 1, 2021 Source

Built Distributions

retworkx-0.9.0-cp39-cp39-win_amd64.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 Windows x86-64

retworkx-0.9.0-cp39-cp39-win32.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 Windows x86

retworkx-0.9.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.4 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

retworkx-0.9.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (1.5 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

retworkx-0.9.0-cp39-cp39-manylinux2014_s390x.whl (2.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.9

retworkx-0.9.0-cp39-cp39-manylinux2014_ppc64le.whl (1.4 MB view details)

Uploaded Jun 2, 2021 CPython 3.9

retworkx-0.9.0-cp39-cp39-manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.9

retworkx-0.9.0-cp39-cp39-macosx_11_0_arm64.whl (1.0 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 macOS 11.0+ ARM64

retworkx-0.9.0-cp39-cp39-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 macOS 10.9+ x86-64

retworkx-0.9.0-cp39-cp39-macosx_10_9_universal2.whl (2.2 MB view details)

Uploaded Jun 1, 2021 CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

retworkx-0.9.0-cp38-cp38-win_amd64.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.8 Windows x86-64

retworkx-0.9.0-cp38-cp38-win32.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.8 Windows x86

retworkx-0.9.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.4 MB view details)

Uploaded Jun 1, 2021 CPython 3.8 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

retworkx-0.9.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (1.5 MB view details)

Uploaded Jun 1, 2021 CPython 3.8 manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

retworkx-0.9.0-cp38-cp38-manylinux2014_s390x.whl (2.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.8

retworkx-0.9.0-cp38-cp38-manylinux2014_ppc64le.whl (1.4 MB view details)

Uploaded Jun 2, 2021 CPython 3.8

retworkx-0.9.0-cp38-cp38-manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.8

retworkx-0.9.0-cp38-cp38-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded Jun 1, 2021 CPython 3.8 macOS 10.9+ x86-64

retworkx-0.9.0-cp37-cp37m-win_amd64.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m Windows x86-64

retworkx-0.9.0-cp37-cp37m-win32.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m Windows x86

retworkx-0.9.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.4 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

retworkx-0.9.0-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (1.5 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

retworkx-0.9.0-cp37-cp37m-manylinux2014_s390x.whl (2.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m

retworkx-0.9.0-cp37-cp37m-manylinux2014_ppc64le.whl (1.4 MB view details)

Uploaded Jun 2, 2021 CPython 3.7m

retworkx-0.9.0-cp37-cp37m-manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m

retworkx-0.9.0-cp37-cp37m-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded Jun 1, 2021 CPython 3.7m macOS 10.9+ x86-64

retworkx-0.9.0-cp36-cp36m-win_amd64.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m Windows x86-64

retworkx-0.9.0-cp36-cp36m-win32.whl (1.1 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m Windows x86

retworkx-0.9.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.4 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

retworkx-0.9.0-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (1.5 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

retworkx-0.9.0-cp36-cp36m-manylinux2014_s390x.whl (2.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m

retworkx-0.9.0-cp36-cp36m-manylinux2014_ppc64le.whl (1.4 MB view details)

Uploaded Jun 2, 2021 CPython 3.6m

retworkx-0.9.0-cp36-cp36m-manylinux2014_aarch64.whl (1.3 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m

retworkx-0.9.0-cp36-cp36m-macosx_10_9_x86_64.whl (1.2 MB view details)

Uploaded Jun 1, 2021 CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file retworkx-0.9.0.tar.gz.

File metadata

Download URL: retworkx-0.9.0.tar.gz
Upload date: Jun 1, 2021
Size: 124.1 kB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.4.1 importlib_metadata/4.4.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.0 CPython/3.7.10

File hashes

Hashes for retworkx-0.9.0.tar.gz
Algorithm	Hash digest
SHA256	`f32269410471b93c1504c5e43db283509513848ef0547a945135c89f906b6304`
MD5	`de9b176981caae1fff6789a65eab92bb`
BLAKE2b-256	`bcc35db19e043c7b0df58b7ce59aea39c13ed87bb620a2eb0297d966a2db0ab3`

Algorithm	Hash digest
SHA256	`4e6bba9f56fa8cacb82e2f69180446e6154951d8fea2fcbb1476e7675947f61f`
MD5	`03f800dfd47fd0dab738fc55b4612378`
BLAKE2b-256	`82a76ffc577c9926e396dd23d7e3e27df4cc2c8d89faa997b7c51604e376b2ed`

Algorithm	Hash digest
SHA256	`a98c649c44dc259e9f5b1b64c4b9738816d649126556cd9984a4d98fa136ec69`
MD5	`95d0f2d418297933d5b42b671c09f6ef`
BLAKE2b-256	`0c12de6f48ac87918966f41adc241c3d1da4a9186a9e67c31a9c3f4da2eece64`

Algorithm	Hash digest
SHA256	`b831a7ff02d96e6749e0a8da5e239529e84dc81bb7df03f739eea6922ae7ca75`
MD5	`10743bb59cf8e5d5f98f3023935d6f32`
BLAKE2b-256	`d292d1495e69bb452fc62430e69c94c150345365f2616be56b4b2142b5fb50c1`

Algorithm	Hash digest
SHA256	`0058b00f6c1f734e890e3b19fe345e0fbaae36622a321261dac8ae3ec4a9296e`
MD5	`d18434bcac4abbdbc7634e2e9820d63e`
BLAKE2b-256	`4d16c2cd01ae0fda2ff23fc767126308ae53126c262a5920d3aac543a5b45850`

Algorithm	Hash digest
SHA256	`e67debda9b194cb71073f42aa9e951e1ff18778a4286e59bd4707d1e33fce4b6`
MD5	`9d4bf83ee40eb44b66fb29c95e6ced22`
BLAKE2b-256	`4353aff34773e32fb5149873a51422757c0e90bf4d01828890477c64d4571872`

Algorithm	Hash digest
SHA256	`0a98e59c4214a2e8203b0ce9cedb7de105ffc0bde19c7840167898e9e8be1615`
MD5	`6225f796f4b6619efbd91744662f3c58`
BLAKE2b-256	`2f5100859e92aaeae2ccf85d4c5d67fb9d9510fc392decc40bacf6b7ccf2a652`

Algorithm	Hash digest
SHA256	`50d222058a7bf581e50c640b4f1c9152180573b68e54bf541eac5f562eed3f02`
MD5	`f80bdb912e6d34200b84e23a9ccda651`
BLAKE2b-256	`0e43c539cfebb23c072fca20c27e819242001d74af50b5104fceee83aee3d9e4`

Algorithm	Hash digest
SHA256	`1c334a0bbc0958b9987d52b03c329879c982b43c399ae4be670286c031e425a2`
MD5	`8e6f725c36d6383c111d0748e89248b4`
BLAKE2b-256	`b28155275534359e953ec4f7bd84bc2aac15dfaf34e6cf9c980f24b264b5ab85`

Algorithm	Hash digest
SHA256	`1b106e9440284d05449c40165c1f19bf276ee2fede59eb5d8fcc6473f90b1af0`
MD5	`6db3361926c673baa6509396d9b38805`
BLAKE2b-256	`99477465a4398e2f58e5faf6ee6b886dfef78c42c19f48c73bc58862d5f575e1`

Algorithm	Hash digest
SHA256	`1c806b508f9484dbbcde5898f9364de2dbc65be345081297ac8387f49cab0fc8`
MD5	`4f0bb0203f9360cf5295025c287e6488`
BLAKE2b-256	`64443e409869b95ed7ebbf0e9eec20dfee553fa7221ada73ef76685415ea4ba1`

Algorithm	Hash digest
SHA256	`fff30d7cc0de87b01fb98cb6006016068482fa1c9eced43f3d0a2be9525815e4`
MD5	`220718e46555c92e05abefb3ae27b9e3`
BLAKE2b-256	`24911f1cfe3b7dbe34a948b411a51e0f7d92ef94ac145a044ebc4b9ac365e53d`

Algorithm	Hash digest
SHA256	`2e626e53129aabf2b2e304e0dab4da8745eadfa7e69f7d6af78c606bba324039`
MD5	`5fe5d2b3330df930ba30342f8c115c8f`
BLAKE2b-256	`25648be0a814899d989510dbbf7309377441f0b601b1df0a6b4b71d3ed6f60bb`

Algorithm	Hash digest
SHA256	`e6bc5e57832a836765abbe01661076d77f3346d6b1f1b5468d889e8c8f1f544c`
MD5	`fcdbeb4c01f10328366208ec4c73ff89`
BLAKE2b-256	`5c66700928e00c11240ed358047d16ac964840b7ecfc19508a8c38e3e99732e0`

Algorithm	Hash digest
SHA256	`44992fb31a24bac94f7bc5d08f2aa61e4758f865a7009491cbbff2ef7a17895a`
MD5	`d762ced95ad17b865e53d99239a78820`
BLAKE2b-256	`8b2178ab7f2309b5b6b691a05d3d41460c82b7e1458701d0dae060c0fbb26260`

Algorithm	Hash digest
SHA256	`04be2e2feca1a7defa93d46eef3523c6036cecdc1506815ad9eae3cd7a79be1a`
MD5	`cfc1cd1783201b0f570e8d143c051eda`
BLAKE2b-256	`92999d011edc5dc106b979b912ce242715e832980952b4c00b2a098a34957ed2`

Algorithm	Hash digest
SHA256	`1b7a2bd016421a253b1e60948a780698eed53322d486f3678deede1f99b97359`
MD5	`f1d9d26e27bae259c506dd15923afa10`
BLAKE2b-256	`82c105b1f15f2b44c67bc6ef882ff19f47fc217760755f1cd360de92ad66d6fd`

Algorithm	Hash digest
SHA256	`b3ccee85d8fb5db54f92f30a9507cda0bb94fd4ddc387fbdbdbd904d495c5ffa`
MD5	`6b13ebf5933fbe4a7a26404bd90b53ba`
BLAKE2b-256	`36c2765209db2f0115d087bfc8acd64ba1c4fa98fb7a121b4d10e62b67cacd96`

Algorithm	Hash digest
SHA256	`6ee61253674cfabaf2c9dfa911f84d589fa0514ff310a80f5de8c8e05d2284ee`
MD5	`8f5de3080b26d316ab7dc2004dcdbdc4`
BLAKE2b-256	`7e38e9b2cd3ace4b26dc8373b043072e5e507228d394a022d013d91337e3aea7`

Algorithm	Hash digest
SHA256	`ac07e9798613461c4bfa4c48b5e4b868cb8125e31102c38f19efc9f1e2748f96`
MD5	`351ca45093b634068699134080420e6c`
BLAKE2b-256	`0da4dba0b94d68dc22dd68ba31b1943286d731fe2f6151b5f4c7c425b336b834`

Algorithm	Hash digest
SHA256	`14f61ca35afeade56684c671a3a562ef700b23e4c7ee7cf71b5c66fcdcc3ff48`
MD5	`32c642274e73a454abc4d42ec8bc2844`
BLAKE2b-256	`479922f28b9ebef093752fee06db01f6b1348372357274feb9ddf20a468823e6`

retworkx 0.9.0

Navigation

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Project description

retworkx

Installing retworkx

Installing on a platform without precompiled binaries

Optional dependencies

Building from source

Develop Mode

Using retworkx

Project details

Verified details

Maintainers

Unverified details

Project links

Meta

Classifiers

Release history Release notifications | RSS feed

Download files

Source Distribution

Built Distributions

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

File hashes

File details

File metadata

Algorithm	Hash digest
SHA256	`3d92bc350fcbdb47ced95e194569c18c5120f92d07186ad13cb05a358e5747ee`
MD5	`2687bae7130bd4b4befd3043c80c5ca2`
BLAKE2b-256	`9ecd70d436f170aa1ead2ac9e4c19c8838633355d48b530f09455eab0af2f98e`

Algorithm	Hash digest
SHA256	`c44a6a00f959010126cc5af5e778bd69c7bc77677bc442257f5eb6751dd3c7fc`
MD5	`49dd2a382ca749b41405ccb56497a180`
BLAKE2b-256	`998cd44c0c6b21bc3416ab743becc020e3b6a86a072416c558ba96d42c592bbf`

Algorithm	Hash digest
SHA256	`93ada1b8dc7a2b442e3fcab813a3ff6265501589dea873c912c79e8ea817c5af`
MD5	`b1a9d0479a957bde53d86dbf56a73f5a`
BLAKE2b-256	`60ab02e0c27eb2ec5868f960495bcbc8c49959c87e1cef43ff4a37cd7e48f7dc`

Algorithm	Hash digest
SHA256	`45b5612c0acfc159b0f57ceab9124ad3e82c4792a7ff35946c5be1f36318f367`
MD5	`22234a26121e7432786dcdf0eb2f14d3`
BLAKE2b-256	`687b169a4a4ec14ef0c54477308b0615f9f872255dfd5b95fe5cc9a2aa6091c3`

Algorithm	Hash digest
SHA256	`2c62056d0821c5227346786cffd74e94df0cef54b3aad9544150ffb4c73df3e5`
MD5	`ee65fc403a46f6139874030d82912bb4`
BLAKE2b-256	`c3ad46bfaa34bcb9d37f4e753afa557dcabe64049b2f3d4fbc44f488d1e0471b`

Algorithm	Hash digest
SHA256	`fd1888bb734a1106952138491665cbd29e068ee65ee8bb2121fb734ef8c99b2e`
MD5	`375572263329641fd0a34ee76bd19eb4`
BLAKE2b-256	`578231a2b4f98ca2ec2ddce5734ab045b8243c364979350e7cea18ba286982ed`

Algorithm	Hash digest
SHA256	`57bf3cc929d90ef364a4fd16bc2a4a59a574e591d0fca89689b8ec7b47017e9b`
MD5	`a23912e6d3282a7c45acb8cffdfa5344`
BLAKE2b-256	`217e0252fbeb22a1ec3151311b180bf87f0dbb9bf90dc0ee9cbb21fb8c8ba66d`

Algorithm	Hash digest
SHA256	`cad5db944e1bd7627ee367bec9b78bf1991286a29174a63ab7ca815f4b5e6abc`
MD5	`9fe1bc95e3fc8139eb9fa272ca467d71`
BLAKE2b-256	`77303f8d67898e4e3b5af5c6b57531831877728beb932279dd84044fe40889c7`

Algorithm	Hash digest
SHA256	`5b2a25038bc229f61a04e0d6f55927a5a89e9675cb51da9e40f8f4fe375ef209`
MD5	`7453d34d2ce39fca28464d4404ee0712`
BLAKE2b-256	`36b14da4a31520b2c35ac700304f0cb9e607b500b1c9f42b4d6a99677805b7e4`

Algorithm	Hash digest
SHA256	`0b6fc741038c37d9534babf0a77688498e082c143d5c49095045f5402a6bd719`
MD5	`d37b587a5cce49f81401ad48ce430e16`
BLAKE2b-256	`7b0bb959c438765e826ebdbebfccd3f389bbe3c5b8766ffd2edbee2607276e92`