Skip to main content

Water Network Tool for Resilience

Project description

<h1> <img src=”https://raw.githubusercontent.com/usepa/wntr/main/documentation/_static/logo.jpg” width=”375”> </h1><br>

[![build](https://github.com/USEPA/WNTR/workflows/build/badge.svg)](https://github.com/USEPA/WNTR/actions/workflows/build_tests.yml) [![Coverage Status](https://coveralls.io/repos/github/USEPA/WNTR/badge.svg?branch=main)](https://coveralls.io/github/USEPA/WNTR?branch=main) [![Documentation Status](https://github.com/USEPA/WNTR/actions/workflows/build_deploy_pages.yml/badge.svg)](https://github.com/usepa/wntr/actions/workflows/build_deploy_pages.yml)

The Water Network Tool for Resilience (WNTR) is a Python package designed to simulate and analyze resilience of water distribution networks. The software includes capability to:

  • Generate water network models

  • Modify network structure and operations

  • Add disruptive events including pipe leaks

  • Add response/repair strategies

  • Simulate pressure dependent demand and demand-driven hydraulics

  • Simulate water quality

  • Evaluate resilience

  • Visualize results

For more information, go to https://usepa.github.io/WNTR/

Installation

The latest release of WNTR can be installed from PyPI or Anaconda using one of the following commands in a command line or PowerShell prompt.

See [installation instructions](https://usepa.github.io/WNTR/installation.html) for more details.

Citing WNTR

To cite WNTR, use one of the following references:

  • Klise, K.A., Hart, D.B., Bynum, M., Hogge, J., Haxton, T., Murray, R., Burkhardt, J. (2020). Water Network Tool for Resilience (WNTR) User Manual: Version 0.2.3. U.S. EPA Office of Research and Development, Washington, DC, EPA/600/R-20/185, 82p.

  • Klise, K.A., Murray, R., Haxton, T. (2018). An overview of the Water Network Tool for Resilience (WNTR), In Proceedings of the 1st International WDSA/CCWI Joint Conference, Kingston, Ontario, Canada, July 23-25, 075, 8p.

  • Klise, K.A., Bynum, M., Moriarty, D., Murray, R. (2017). A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study, Environmental Modelling and Software, 95, 420-431, doi: 10.1016/j.envsoft.2017.06.022

License

WNTR is released under the Revised BSD license. See [LICENSE.md](https://github.com/USEPA/WNTR/blob/main/LICENSE.md) for more details.

Organization

Directories
  • wntr - Python package

  • documentation - User manual

  • examples - Examples and network files

Contact

EPA Disclaimer

The United States Environmental Protection Agency (EPA) GitHub project code is provided on an “as is” basis and the user assumes responsibility for its use. EPA has relinquished control of the information and no longer has responsibility to protect the integrity , confidentiality, or availability of the information. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by EPA. The EPA seal and logo shall not be used in any manner to imply endorsement of any commercial product or activity by EPA or the United States Government.

Sandia Funding Statement

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.

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

wntr-1.3.0rc3.tar.gz (541.8 kB view details)

Uploaded Source

Built Distributions

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

wntr-1.3.0rc3-cp312-cp312-win_amd64.whl (729.2 kB view details)

Uploaded CPython 3.12Windows x86-64

wntr-1.3.0rc3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

wntr-1.3.0rc3-cp312-cp312-macosx_11_0_arm64.whl (730.1 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

wntr-1.3.0rc3-cp312-cp312-macosx_10_13_x86_64.whl (735.0 kB view details)

Uploaded CPython 3.12macOS 10.13+ x86-64

wntr-1.3.0rc3-cp311-cp311-win_amd64.whl (728.5 kB view details)

Uploaded CPython 3.11Windows x86-64

wntr-1.3.0rc3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

wntr-1.3.0rc3-cp311-cp311-macosx_11_0_arm64.whl (729.6 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

wntr-1.3.0rc3-cp311-cp311-macosx_10_9_x86_64.whl (734.1 kB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

wntr-1.3.0rc3-cp310-cp310-win_amd64.whl (728.7 kB view details)

Uploaded CPython 3.10Windows x86-64

wntr-1.3.0rc3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

wntr-1.3.0rc3-cp310-cp310-macosx_11_0_arm64.whl (729.6 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

wntr-1.3.0rc3-cp310-cp310-macosx_10_9_x86_64.whl (733.9 kB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

wntr-1.3.0rc3-cp39-cp39-win_amd64.whl (728.7 kB view details)

Uploaded CPython 3.9Windows x86-64

wntr-1.3.0rc3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

wntr-1.3.0rc3-cp39-cp39-macosx_11_0_arm64.whl (729.4 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

wntr-1.3.0rc3-cp39-cp39-macosx_10_9_x86_64.whl (733.6 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

wntr-1.3.0rc3-cp38-cp38-win_amd64.whl (729.2 kB view details)

Uploaded CPython 3.8Windows x86-64

wntr-1.3.0rc3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.5 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

wntr-1.3.0rc3-cp38-cp38-macosx_11_0_arm64.whl (729.7 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

wntr-1.3.0rc3-cp38-cp38-macosx_10_9_x86_64.whl (734.0 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

File details

Details for the file wntr-1.3.0rc3.tar.gz.

File metadata

  • Download URL: wntr-1.3.0rc3.tar.gz
  • Upload date:
  • Size: 541.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3.tar.gz
Algorithm Hash digest
SHA256 21a4e06d595975dd7f8af03fc9e46aa24a2036803763f88e489f459a91cf2bce
MD5 7574e289dc304305b8865bf37296f112
BLAKE2b-256 3ac621999cc6f1df45a7d3260097fd4f9e445a6cc771a5a2d612dd9283270e98

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: wntr-1.3.0rc3-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 729.2 kB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 bb2c20eaf13f94f6fc20f43cd24e859902131d725c06db4708db5eee22bb6aec
MD5 adf12d6ee9e034459e32a1ef1f68187b
BLAKE2b-256 f2a95f0f1972d53bc856ff5651f4081b98038d1ffabefa62fee4dffc1236f32e

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 593c68f73322d23e00afd2910d5a95ad5733b0907ea9cd9d12ce897c1c5bdaec
MD5 9357ec8e6cd301eefb97a211b0ee8dff
BLAKE2b-256 92534d2dbb3f9a602c9a92b4fa767a6a873a515d07fe0b8ffdb6e011976ac5b3

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 145ce66eef7fbdcc38d00ea3f635ac2474786e565160a1e8f7d78ecdc47a000d
MD5 79d27d03136e06c7c2d636ae7c70e743
BLAKE2b-256 e43aae421abb3bc2040ca39b1bdbf04423254e50951053099f7f81fa45d6a46b

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e724d2ac77377909169259820e8fae304d3135260ffbad6763e598521bd5b21c
MD5 cff0f390c90187a0d07550c9220fcb6d
BLAKE2b-256 258a66cd73689237dda42d4be2617d673a807ad73269d583bf829c132fc4a1d8

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: wntr-1.3.0rc3-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 728.5 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 499ea0ca528f7811bddf32a94db1b72411d95234f46e241d8eeddd3b4092ef82
MD5 edbbd219ea2e7ceccaacacb8389c3bf7
BLAKE2b-256 21db80113cc950a60f74684120b1d6d16da7bbba614603280490641f59de915b

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a6ba76a7c889b9c7a1492dc0000ff83c721a288eb4574184c47270ca8af9ec52
MD5 e1d59cced67bdf4ace6d81e9a48f596c
BLAKE2b-256 ed064af150ffcb2c3fa84ae1748e9210bc83392fefd3e47dbcaef891adbce8d9

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 35e60af6ca0e1699aba467853751f40bec3fa3416275eb9b2316027eb48df763
MD5 49652e473a8ae85c3ad374de33eefb03
BLAKE2b-256 067e5c1b60b42ea95b6a3a42b0a452b84214f0085f1df43f1d83988c7afce190

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bd709abe9ae95de3ac8d138c1faff5c462bd87f1d7bfaa7e101a3aab6f13bbc2
MD5 abbfcbc4d6efff17bf57927d5b85e411
BLAKE2b-256 5ee61ba42b2fc86fcad69ea82b7a7020ae2e6fdcb21a42e556ccf8ec9babb1ff

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: wntr-1.3.0rc3-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 728.7 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 35309b08d549de2373205e439f90b7a29d5917b05250c5fe86e92c5b5762ad6e
MD5 9c5eb42641dc3da7603b674c8673e921
BLAKE2b-256 ce3c08f40eae3a477a93e1ef648fb580d2377f9ebfa98a326c25142538dcaf9c

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1393c0b603f3f159ad8bdbfb4b62d06808583e8904d9e69e48c511a25ecb102c
MD5 a9fefc6b71f12a47f20b11f0576de325
BLAKE2b-256 d5ef245d8f0992df0114906d2fb97e6cc70730abcad9d6804929aa48c32c05c4

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 02007a14c8884909779900919ada45f73700f35d5874a59b459862a84836299b
MD5 7060709213ce9f24e423d38132ba85d9
BLAKE2b-256 70fa7ec4986055f6ee8637223b568c588437ec64b07e2d9de07ddb9d01f38c44

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 795977e7efa46f4c8cbc693d3863771bcb806b16a38c3e39a5c72425e6ce71cc
MD5 4a1b33c8d1f0a9fd1888a840dd63a444
BLAKE2b-256 5f42f4be2a370ee6e8d28c204dd8788980c45e1d129f97e4f26e7d0c9bbba7b5

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: wntr-1.3.0rc3-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 728.7 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 daa298104db246345912d89b452855e10c8271bc17530f34f2a7a9b8e5af393d
MD5 c542fea0f43e4c8f086b4fce79a40ef6
BLAKE2b-256 00ea5b24cac81c172f039a386a30ffc182636b04ee87f666befb99db5768360d

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fe6ba05bd7099bdd685d121ba3a568d29d07b3109f9528112d189356116aea82
MD5 5e4075dece4e1324867434a22aa7cda4
BLAKE2b-256 0051a1a18af7b7f444089c85165cce649fdaedbb045f8d9d6f7ae730066454d8

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9744d99d558fc0cdcf60e3d59f0a5dc5b17af85789da88587df041f748245682
MD5 5bd5f16ab9bc3ca649b9e4d9d0cf557d
BLAKE2b-256 bfe46b1b3e02cd0837d60de97b1632011fdceb5ff7b91f12f04eb1f7d207b392

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 7434462bebd6bdef16010b692023d9014b1d3c66816dce080c7a56030dd28c3f
MD5 b834bd18a3b44b24a7256fceff014d73
BLAKE2b-256 30dde209414a009fb59c0b7d4e37128beded10c29026c0bdef8249e09d44f875

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: wntr-1.3.0rc3-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 729.2 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.8

File hashes

Hashes for wntr-1.3.0rc3-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 7f9e123332d9975b029baa9f4c9441e5a70d135c7807e93434b8767beafeb660
MD5 60c866d5202a046d6be795574b51461e
BLAKE2b-256 57f47b05404e0c268cf190b7db6cf4a34eac3d1472ca6e7c5d3dd5329c684ea5

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b3e077264d183b3b73c1c80ea5e230c7ecd252a176ed2ea8fb9fa04fc3fcf6a8
MD5 89ad4f883745efe107e1f41386b7bac3
BLAKE2b-256 10ff73698bcce9d4c6659666ff43c1529cbc90ad8886b41a3e13e9066243fc27

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 89b85c3af98462016838be35a1768cb5c0384544b5c8aa65049795abd096b101
MD5 cac54df4edca9df8b5aff32c31a9433b
BLAKE2b-256 9b00d905f79a5bf1949d9b8e59cc76e8791822a2405ab3e47d34f10964e3efca

See more details on using hashes here.

File details

Details for the file wntr-1.3.0rc3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for wntr-1.3.0rc3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5fae09a3ef744519e66277a12a8113e4755a185a0d9ccfbc738b52b6fed26b47
MD5 39da7e9c8961c36acd0aa5d02e087bc4
BLAKE2b-256 2dd1d615ed8d82e9a0b1550f4702a0a214704e9d4465bc916b20d468f68f81cf

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