Skip to main content

Vehicle routing open-source optimization machine (VROOM)

Project description

Python Vehicle Routing Open-source Optimization Machine

gh_action codecov pypi

Good solution, fast… in Python.

Pyvroom is an Python wrapper to the excellent VROOM optimization engine for solving vehicle routing problems.

The library aims to solve several well-known types of vehicle routing problems, including:

  • Travelling salesman.

  • Capacitated vehicle routing.

  • Routing with time windows.

  • Multi-depot heterogeneous vehicle.

  • Pickup-and-delivery.

VROOM can also solve any mix of the above problem types.

Basic usage

>>> import vroom

>>> problem_instance = vroom.Input()

>>> problem_instance.set_durations_matrix(
...     profile="car",
...     matrix_input=[[0, 2104, 197, 1299],
...                   [2103, 0, 2255, 3152],
...                   [197, 2256, 0, 1102],
...                   [1299, 3153, 1102, 0]],
... )

>>> problem_instance.add_vehicle([vroom.Vehicle(47, start=0, end=0),
...                               vroom.Vehicle(48, start=2, end=2)])

>>> problem_instance.add_job([vroom.Job(1414, location=0),
...                           vroom.Job(1515, location=1),
...                           vroom.Job(1616, location=2),
...                           vroom.Job(1717, location=3)])

>>> solution = problem_instance.solve(exploration_level=5, nb_threads=4)

>>> solution.summary.cost
6411

>>> solution.routes.columns
Index(['vehicle_id', 'type', 'arrival', 'duration', 'setup', 'service',
       'waiting_time', 'location_index', 'id', 'description'],
      dtype='object')

>>> groups = solution.routes[solution.routes.type == "job"].groupby("vehicle_id")["id"].apply(lambda x: set(x.dropna().astype(int)))
>>> groups[47] == {1414, 1515} and groups[48] == {1616, 1717}
True

Usage with a routing engine

>>> import vroom

>>> problem_instance = vroom.Input(
...     servers={"auto": "valhalla1.openstreetmap.de:443"},
...     router=vroom._vroom.ROUTER.VALHALLA
... )

>>> problem_instance.add_vehicle(vroom.Vehicle(1, start=(2.44, 48.81), profile="auto"))

>>> problem_instance.add_job([
...     vroom.Job(1, location=(2.44, 48.81)),
...     vroom.Job(2, location=(2.46, 48.7)),
...     vroom.Job(3, location=(2.42, 48.6)),
... ])

>>> sol = problem_instance.solve(exploration_level=5, nb_threads=4)
>>> 3800 < sol.summary.duration < 4200
True

Installation

Pyvroom currently makes binaries for on macOS and Linux. There is also a Windows build that can be used, but it is somewhat experimental.

Installation of the pre-compiled releases should be as simple as:

pip install pyvroom

The current minimal requirements are as follows:

  • Python at least version 3.10.

  • Intel MacOS (or Rosetta2) at least version 15.0.

  • Apple Silicon MacOS at least version 15.0.

  • Windows on AMD64.

  • Linux on x86_64 and Aarch64 given glibc at least version 2.34.

Outside this it might be possible to build your own binaries.

Building from source

Building the source distributions requires:

  • Download the Pyvroom repository on you local machine:

    git clone --recurse-submodules https://github.com/VROOM-Project/pyvroom
  • Install the Python dependencies:

    pip install -r pyvroom/build-requirements.txt
  • Install asio headers, and openssl and crypto libraries and headers. For mac, this would be:

    brew install openssl@1.1
    brew install asio

    For RHEL:

    yum module enable mariadb-devel:10.3
    yum install -y openssl-devel asio

    For Musllinux:

    apk add asio-dev
    apk add openssl-dev
  • The installation can then be done with:

    pip install pyvroom/

Alternatively it is also possible to install the package from source using Conan. This is also likely the only option if installing on Windows.

To install using Conan, do the following:

cd pyvroom/
conan install --build=openssl --install-folder conan_build .

Documentation

The code is currently only documented with Pydoc. This means that the best way to learn Pyvroom for now is to either look at the source code or use dir() and help() to navigate the interface.

It is also useful to take a look at the VROOM API documentation. The interface there is mostly the same.

Project details


Download files

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

Source Distribution

pyvroom-1.15.0.tar.gz (25.6 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyvroom-1.15.0-cp314-cp314-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.14Windows x86-64

pyvroom-1.15.0-cp314-cp314-manylinux_2_34_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.34+ x86-64

pyvroom-1.15.0-cp314-cp314-manylinux_2_34_aarch64.whl (4.3 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.34+ ARM64

pyvroom-1.15.0-cp314-cp314-macosx_15_0_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.14macOS 15.0+ x86-64

pyvroom-1.15.0-cp314-cp314-macosx_15_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.14macOS 15.0+ ARM64

pyvroom-1.15.0-cp313-cp313-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.13Windows x86-64

pyvroom-1.15.0-cp313-cp313-manylinux_2_34_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ x86-64

pyvroom-1.15.0-cp313-cp313-manylinux_2_34_aarch64.whl (4.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.34+ ARM64

pyvroom-1.15.0-cp313-cp313-macosx_15_0_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.13macOS 15.0+ x86-64

pyvroom-1.15.0-cp313-cp313-macosx_15_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.13macOS 15.0+ ARM64

pyvroom-1.15.0-cp312-cp312-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.12Windows x86-64

pyvroom-1.15.0-cp312-cp312-manylinux_2_34_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ x86-64

pyvroom-1.15.0-cp312-cp312-manylinux_2_34_aarch64.whl (4.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.34+ ARM64

pyvroom-1.15.0-cp312-cp312-macosx_15_0_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.12macOS 15.0+ x86-64

pyvroom-1.15.0-cp312-cp312-macosx_15_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.12macOS 15.0+ ARM64

pyvroom-1.15.0-cp311-cp311-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.11Windows x86-64

pyvroom-1.15.0-cp311-cp311-manylinux_2_34_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.34+ x86-64

pyvroom-1.15.0-cp311-cp311-manylinux_2_34_aarch64.whl (4.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.34+ ARM64

pyvroom-1.15.0-cp311-cp311-macosx_15_0_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.11macOS 15.0+ x86-64

pyvroom-1.15.0-cp311-cp311-macosx_15_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.11macOS 15.0+ ARM64

pyvroom-1.15.0-cp310-cp310-win_amd64.whl (2.1 MB view details)

Uploaded CPython 3.10Windows x86-64

pyvroom-1.15.0-cp310-cp310-manylinux_2_34_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.34+ x86-64

pyvroom-1.15.0-cp310-cp310-manylinux_2_34_aarch64.whl (4.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.34+ ARM64

pyvroom-1.15.0-cp310-cp310-macosx_15_0_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10macOS 15.0+ x86-64

pyvroom-1.15.0-cp310-cp310-macosx_15_0_arm64.whl (3.9 MB view details)

Uploaded CPython 3.10macOS 15.0+ ARM64

File details

Details for the file pyvroom-1.15.0.tar.gz.

File metadata

  • Download URL: pyvroom-1.15.0.tar.gz
  • Upload date:
  • Size: 25.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0.tar.gz
Algorithm Hash digest
SHA256 43572c57bd9ffa3682a714377fb91825e0b1aa189dac8b84a92b32d368d88e27
MD5 25437ac7ac09e4b8f6b395a5e3c4b3d4
BLAKE2b-256 4b669507b16c77c2c9d97772c869a896aa0e0eb6a742b3dd765666499f90dbca

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: pyvroom-1.15.0-cp314-cp314-win_amd64.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.14, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 f80013cb778d3fd6d0c6b33e84cff6615a195af103b551b8225f7b1694732eea
MD5 3fbb4a850f4b52aadf392f741469b627
BLAKE2b-256 084fa2800c9055b766e4c218df93086b5b55b6f8b515d39327e3f8b550d5495e

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp314-cp314-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp314-cp314-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 e873213f3fdf10fdb3b3c51f230a64857321cdde65719c1704438d03d8c78437
MD5 a7173b5ff04fa77926b9638d0ed61e78
BLAKE2b-256 0f816cde5ebfcbd9f7bb123cbc6c24116df85e68183e888faa8ac00cdbd71af7

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp314-cp314-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp314-cp314-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 8844855777014173e610cc27967bc10053bc7dbed9192140d9d3f79a136c40fb
MD5 3881cc8c6e42193f4c15b3d716403b5d
BLAKE2b-256 11b7f02df77224350d6b4a69573b6b0c32e6cfa498a204e6febf9ecf49361e3d

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp314-cp314-macosx_15_0_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp314-cp314-macosx_15_0_x86_64.whl
Algorithm Hash digest
SHA256 56b40d65950d0a3b2a27e83a02a83bd84cc53417d4e7164276599a08ea0a8063
MD5 eb590031eb9d8ded03493bd67dfdcdc0
BLAKE2b-256 1ae14b0769801b8a19e8cb05a0826a14b16fe8c70384e4bb79b9b0ab067cfc91

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp314-cp314-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp314-cp314-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 fea8022804249f59cfb49f50b7d3ea625905563ccc04dc7b1c71388b478acbc5
MD5 8afa76dfb739132738827de5de5d4c30
BLAKE2b-256 51e93e03477a5417009ef05a27d59237fa78b664dc74a2892546ff42ca478c4f

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: pyvroom-1.15.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 cd496dcb4ae373d98baff760eeefb493b7b1d55ecbc59f6b30220f8e96d7404b
MD5 8cbebf4a8b2989eab11f614b34952055
BLAKE2b-256 066470f2c1a106224acf3b56723017683da37ed6b731fefe17461e7b5cbbdc36

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp313-cp313-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp313-cp313-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 ba959af4209b49008a291fd20521da423b002378fbb6d087b2f563f97e143df2
MD5 ef1dafe4e2481956279ae0f4757c940c
BLAKE2b-256 8f522cd1eb66efb8ffb7dcc77e0d07df378d411ae00bd421b08e9cead14b022c

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp313-cp313-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp313-cp313-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 9afa30edd258389595f9a8da4559832cfb8442deba71dbd3f73bab3c7fbdda90
MD5 cdf74160262ec626938b883003dcc6f3
BLAKE2b-256 ba74633dfe3fdf45773030124cb11c80ec1dd84fdcfb0a802331ef14bb23bc31

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp313-cp313-macosx_15_0_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp313-cp313-macosx_15_0_x86_64.whl
Algorithm Hash digest
SHA256 94f28efc5dc923ce0c02234340c975e1f23d7c2c34da9a28e69a45a67a557ac7
MD5 e8ea0f3ec4199046c3f1b71780aa9be8
BLAKE2b-256 9e23a2134dc02d95c0d81a24d80518858bfb983c097a09ee1ce2f5f502924f97

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 f6d7045ab71ab2cc862b2b94cb6d3dbff32973a1b11929506873359718b2f0b3
MD5 c9724f931c0d1eb22eb20c9e5c464e71
BLAKE2b-256 cdf6438ce9b5b7c0f3d47cf9cb38fa757cbe22b9c5b0f9efdc5e97617c97b662

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pyvroom-1.15.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 ea23d0e204cdd7c79639b787133ec1ec2e7e61fe500b45f5548514dc3cb39f89
MD5 0592677b0b38a58cda4183f93c2a155a
BLAKE2b-256 df0ea40d78534a086d54c620455f76b5fe116d12f61c98622cd482a4cc0f0f9f

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp312-cp312-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp312-cp312-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 80150b72cafbd508a1efaec0fc99d11ba21532ca449e71996a4cff165a776ce4
MD5 822408dea29c93ffe1a944ca6b678161
BLAKE2b-256 ca5cb9035699c7c4169f0dc7fb26661887400cce008f10bd3515744c81eb4df8

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp312-cp312-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp312-cp312-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 6861e26ff503bde787cb35f2caf5c416dea5de99a406c8faca944476d9197f20
MD5 968a7dfca489ef506e03f3dbeef3dbcf
BLAKE2b-256 892dbc44fa156d1a31ebc5209d71365a6e66ad73ea09e2eb6aba43263a00ba4b

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp312-cp312-macosx_15_0_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp312-cp312-macosx_15_0_x86_64.whl
Algorithm Hash digest
SHA256 95f647115831342dd032d1d6ef33526b3947bc39d626f7466468c9b7cb0cae57
MD5 750db8028f364bc6e529e8c9393b6362
BLAKE2b-256 be3e57928b724c845a6e0068de75377e155a993ce4b3f076d44ca627270f8afd

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp312-cp312-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp312-cp312-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 669f4c1b9efd619064785aac245a1ad2b3b922d9aea8a10c911e7ac29579ed90
MD5 3766ff226f47d58a26b61fdf4cf3551b
BLAKE2b-256 ec5c5621e786ad02f959f81d1f06a5a65e8b4669c727e3305c87426809176d2a

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyvroom-1.15.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 1c4c60d9c63d8143c050ec09d5c72f5440b7c8f890f6b996afef7e9ff4b9b333
MD5 31bfccba8502f265dd6f8404512ff926
BLAKE2b-256 592704a6c8b6c19cf9434b7ac45b84d1e05489f1896328a022530bc4ee5e0201

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp311-cp311-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp311-cp311-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 09077ab5be1b1660dfddaaaccb9c2a846aa05b11598fd064b1f98e14c0a2ff1d
MD5 541a20a9884258634ad9f6ace62b48c1
BLAKE2b-256 8609769f97c062275afa55b902502af4dec909d58935e167c32cb6496035a613

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp311-cp311-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp311-cp311-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 12604ab38d42fff84dd2f1e24c215a0d28e588f93b41adf296663ad4a63db5cf
MD5 e6bd03378b52787392a32083dc0aae26
BLAKE2b-256 0cb0485c0e920058a71f889caadfcbb0a40d4f0706ad9cd0b1f828a0c156b18f

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp311-cp311-macosx_15_0_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp311-cp311-macosx_15_0_x86_64.whl
Algorithm Hash digest
SHA256 40f89ea148ae51d915c8cee3503ebbe6f80bf10f1016948e9f9b5a1c1917148a
MD5 164d61ddbf22a99bb4ce28dc598de435
BLAKE2b-256 b33b79faed2c91e88fce6b3b2d692d9d5e7c479839932bd8de1afe6e0445c2ea

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp311-cp311-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp311-cp311-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 40a9a750d7d29fde9f325db2b3e318ae81b47f0276819d1cbafd6518c89aed6c
MD5 15b0133cd1da72f016f6807be656946f
BLAKE2b-256 bef97c7e8f688b93cf09e60d84810505c54912e4bc304a60837211aae158cd21

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyvroom-1.15.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 2.1 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyvroom-1.15.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 ba285b3733eb2b2a5a6a26be1b8aac9fd1658e3e442411ec94233bb74ab010cd
MD5 2b5624e7d1cc4e88665810f27e31f787
BLAKE2b-256 4f315ac81762089e7ea01bcdf180cf0cd3d011a49ee29363cd004cdb92eccf10

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp310-cp310-manylinux_2_34_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp310-cp310-manylinux_2_34_x86_64.whl
Algorithm Hash digest
SHA256 11cb21508ec7b2a3c6ea9aac5f0f9bc4e11db5742a2823072454e03c3308aaac
MD5 7086ef153e933dced86050c55c2e59a8
BLAKE2b-256 b8492625d2330741675705ab742225a8a00918b2cfdc90ed8e1354be646bd62f

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp310-cp310-manylinux_2_34_aarch64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp310-cp310-manylinux_2_34_aarch64.whl
Algorithm Hash digest
SHA256 5fd523b7ce608323eb65a6ab7742306075300361c86c4257385ece84f476f834
MD5 1a3d88988905088aede81c60c5c0fbbb
BLAKE2b-256 c03300a9b0714b1941f9671c74e879ec41528f127e43d56706c3a04ef871e5f9

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp310-cp310-macosx_15_0_x86_64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp310-cp310-macosx_15_0_x86_64.whl
Algorithm Hash digest
SHA256 439ab43ea8e978cd0bcc7225ca05a6ead5924914b2f378082157eaa9148b70bd
MD5 e6295e7fac0b4308ec6aa1393a705a5e
BLAKE2b-256 7f9793e6ba98e26bff6c25bcb5f9005a8e3ccb6adc9387914f6c9802cb448392

See more details on using hashes here.

File details

Details for the file pyvroom-1.15.0-cp310-cp310-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for pyvroom-1.15.0-cp310-cp310-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 a9a17455513d98f210b977f3a26b0f49d25e78fbe134c95a64062700acd1c8a3
MD5 56b7f8012cfc120fc4187ea1a2e1e309
BLAKE2b-256 d8b367273aca3946dd0f8b334efc5255c5aa4db2820d5f0697c4fe01a63c7887

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page