Skip to main content

pyATS Datastructures: Extended Datastructures for Grownups

Project description

pyATS is an end-to-end testing ecosystem, specializing in data-driven and reusable testing, and engineered to be suitable for Agile, rapid development iterations. Extensible by design, pyATS enables developers start with small, simple and linear test cases, and scale towards large, complex and asynchronous test suites.

pyATS is initially developed internally in Cisco, and is now available to the general public starting late 2017 through Cisco DevNet. Visit the pyATS home page at

https://developer.cisco.com/site/pyats/

Datastructures Package

This is a sub-component of pyATS that defines various local, advanced datastructures used throughout pyATS.

Requirements

pyATS currently supports Python 3.4+ on Linux & Mac systems. Windows platforms are not yet supported.

Quick Start

# install pyats as a whole
$ pip install pyats

# to upgrade this package manually
$ pip install --upgrade pyats.datastructures

# to install alpha/beta versions, add --pre
$ pip install --pre pyats.datastructures

For more information on setting up your Python development environment, such as creating virtual environment and installing pip on your system, please refer to Virtual Environment and Packages in Python tutorials.

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

pyats.datastructures-22.8-cp310-cp310-macosx_11_0_arm64.whl (265.3 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyats.datastructures-22.8-cp310-cp310-macosx_10_10_x86_64.whl (304.0 kB view details)

Uploaded CPython 3.10 macOS 10.10+ x86-64

pyats.datastructures-22.8-cp39-cp39-macosx_11_0_arm64.whl (264.9 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyats.datastructures-22.8-cp39-cp39-macosx_10_10_x86_64.whl (303.5 kB view details)

Uploaded CPython 3.9 macOS 10.10+ x86-64

pyats.datastructures-22.8-cp38-cp38-macosx_11_0_arm64.whl (261.1 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyats.datastructures-22.8-cp38-cp38-macosx_10_10_x86_64.whl (296.0 kB view details)

Uploaded CPython 3.8 macOS 10.10+ x86-64

pyats.datastructures-22.8-cp37-cp37m-macosx_10_16_x86_64.whl (286.8 kB view details)

Uploaded CPython 3.7m macOS 10.16+ x86-64

pyats.datastructures-22.8-cp37-cp37m-macosx_10_10_x86_64.whl (291.1 kB view details)

Uploaded CPython 3.7m macOS 10.10+ x86-64

File details

Details for the file pyats.datastructures-22.8-cp310-cp310-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp310-cp310-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 2760d7e204c5784ee3932effa27b598130f587e2ffe34e10950390196538ec15
MD5 ac6542857b71805ba99866412d266378
BLAKE2b-256 2755d9e227a50f39dbb747931889dd848ae956272e9aa1bc2dea968db8e15b03

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 099eded81b454f95ed524a2f8ca8cfc669ba5b565d9d2b4e183d800d18e6759b
MD5 6d087618526db905b43dfb71ff414d9f
BLAKE2b-256 ba24e3c7e928f1bf08552b9547282b70cca0c6bf747fa9450a63fe976fdbb3be

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp310-cp310-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp310-cp310-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 b9f5c25d99ec8af652544408fa2bd17498ee9c63799d39f62dca8f53b6a4a812
MD5 b09d501cec80ab9a06c30a244e3d9e52
BLAKE2b-256 4f357f5341e4816f6dd5adcf565a24facd68ced01af1b247a109ca26f51d98bb

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp39-cp39-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 bf42a51dbf62d49c0e58ba707f4c7a34a9d89f1e857dec9aa42b3c0abe94932e
MD5 3772827fc37641ad1eee239c7f510c86
BLAKE2b-256 dfa0e40a39b79a1de80af2ce12f4507ed6fb905b26b3e758ad8cb64769326f34

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 27a0ae36cce1899af1a9c6a2cfa81e84a097e57f01b90e3b92008fefa3362102
MD5 0797133fd91df45106750a9af85a89f1
BLAKE2b-256 235a6e440e1d3f35078a61f111e34325c93901ff71ab5871a9ad71ec8b60abe4

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp39-cp39-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp39-cp39-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 c0355caaffb140700558d25be1e69acc2feb4597e306488207dd8445a7581f23
MD5 39962b6d9537de31a8503ac037aefafa
BLAKE2b-256 af7e5a37747ef158458dd963dffee956ce8b1c8da30bcb9aa5cbb069505aac86

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 a3a43e4ccd08c9fecaaca457a0f475a60d28c6535bf74169a40da9f4c7d72803
MD5 cdb7149026e71a848abf2a5437062811
BLAKE2b-256 c181e9feaba8d3d1629314b771295e5e976ddc9946a7924ed098687e990292a5

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4b6a729f5aa565bf7d0573963522535e20210abc34c51fa83b4ca12de6f15247
MD5 11f24e6e1eaebdf51b5efdac98fb9d36
BLAKE2b-256 8d511d97ff1e8c1433c6b1aa30a0811274e293fe35ba881543052bf55773621f

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp38-cp38-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp38-cp38-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 520d3c0291cb89bdc5c4324a1b1d69b5ae2ad369f27cc4ca58468c983eef9bf3
MD5 c1d2bb587aa83c33ef1ca786e37f2004
BLAKE2b-256 b4ebc8860a7d385a53fccdb53df8e3eed05dc7d19cb167e6c4426935391175dc

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 7bc85a247b30ac45387792de936ddb476c46e63400b03c31d53fccc44786ce35
MD5 a90a350f9502c34a1749b800cda03e2b
BLAKE2b-256 ac0c7cb7a5964c8a62332dcef9e2708c9889c1c519849adca1ff2b6da7f8f857

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp37-cp37m-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp37-cp37m-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 e10dba35943fea4bf7b42ad0ee6e6bea2779fc951da8b35f93fc8851063d5f27
MD5 d23f530d977dd4b8cc13c16a75659080
BLAKE2b-256 1f55d808c1319284a63e102cd454eb21f43f4153c9b8fd456314cf9da417d5bd

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-22.8-cp37-cp37m-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-22.8-cp37-cp37m-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 6bbf59e6542f43e8c5a6bef44aa9d538fc19acd34c780cf2bef66f995105a08b
MD5 8290e3d0be4acf8bafea182c3a6693f7
BLAKE2b-256 521e99703b9cb244944c8da5db49b35f9900911302bc6acacb5180d998586622

See more details on using hashes here.

Provenance

Supported by

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