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-24.6-cp312-cp312-macosx_11_0_universal2.whl (651.0 kB view details)

Uploaded CPython 3.12 macOS 11.0+ universal2 (ARM64, x86-64)

pyats.datastructures-24.6-cp311-cp311-macosx_11_0_universal2.whl (644.5 kB view details)

Uploaded CPython 3.11 macOS 11.0+ universal2 (ARM64, x86-64)

pyats.datastructures-24.6-cp310-cp310-macosx_11_0_universal2.whl (634.1 kB view details)

Uploaded CPython 3.10 macOS 11.0+ universal2 (ARM64, x86-64)

pyats.datastructures-24.6-cp39-cp39-musllinux_1_2_x86_64.whl (358.9 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ x86-64

pyats.datastructures-24.6-cp39-cp39-macosx_11_0_universal2.whl (636.5 kB view details)

Uploaded CPython 3.9 macOS 11.0+ universal2 (ARM64, x86-64)

pyats.datastructures-24.6-cp38-cp38-macosx_11_0_universal2.whl (639.5 kB view details)

Uploaded CPython 3.8 macOS 11.0+ universal2 (ARM64, x86-64)

File details

Details for the file pyats.datastructures-24.6-cp312-cp312-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp312-cp312-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fa65d88159704c6fbf79d0932f81e125db1024d306237bfa98df159306019c9c
MD5 79a66f052742e5ff0c316143c49ce3f6
BLAKE2b-256 06c05f6c9d7bb4b858c73619f5685b0b13b044709f0b90a8773f7db82a8640c5

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp312-cp312-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp312-cp312-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b68fc5ecdcc12690eb6c4775723c777ddac889f4b34a53bc22f5fa372718e09c
MD5 76d9eff53e92f25d773f6af661ff6af2
BLAKE2b-256 ac34a1bef371c31270a7eda954fadb27f321dd5b45445c2bc4b6125b506d0777

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp312-cp312-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp312-cp312-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 44b4b56a32f94218ba947310f4fa44b4711625cd4855c03e5dad90adc4b60262
MD5 71c0f915fa495f4a3483389bd9d45b52
BLAKE2b-256 a311a1b0746eb57cb5abba4334dc10601c6d14127c6f68ce5a457545eb8d5765

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp311-cp311-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp311-cp311-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c0084e5a857c9f589df7d0d33b650a1added0cd4895007040cf7dcef02441027
MD5 e42d949e0c0a8b2fe4e491504b6cd126
BLAKE2b-256 5a81fe26990c5e939f0dbda3d2f79d679f14a861e60b37adda2fe3640131529e

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp311-cp311-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp311-cp311-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 73329bb9af9b8c3d9ed3d233346f75ca9c758353ebfe7fb37d283f087600b79c
MD5 bc1580d7b7b797edd4e6afe061ea1885
BLAKE2b-256 495e1ebd2e91c0847121ec1d6c13d9150835be4408c81a7b942c59af58e3de95

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp311-cp311-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp311-cp311-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 1145a65bc2791bdd30aacc7d26df68b2e4920a40fb046478b61f09aaa7c8ebdd
MD5 c5c6e972c8b1a43782f686a4c2479c18
BLAKE2b-256 0e12a93f58be0e3f59a64c64ee1713793f01e5a6c13670f9f9a8b7c57093933d

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp310-cp310-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp310-cp310-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ef822daa6e3782cceb1ac3488a040149cf7a23bc199539d70918ff0b2b7e1ed9
MD5 a26be9b9012dabaecb33534a172e9d42
BLAKE2b-256 517b4fea31b2b246863984bace5938f8577a183904936cbe1b55526754c8d19b

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp310-cp310-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp310-cp310-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2fec76ae448d52d13fc43a1f0aaee596ca5317954e192b15ad17bd2224c5a4de
MD5 a8edcaa96995bd01136c3ca961957f2f
BLAKE2b-256 a6ada368c576c7d1b3f8dd45f1215fc171d237024377a6bad42a5609b7cc1b18

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp310-cp310-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp310-cp310-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 e6393f638ee57321a5d9e90a02ecc8d3037e83f12752b371616687a1dde17cb2
MD5 c0a5fe7bc195c7fde06c78f69e1095f4
BLAKE2b-256 c7ec4a9242f01c919e7ba4a07fe808857483c556777b4007b8d982a16af6cdf9

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 7e66b2b2aa9a14bebefe1ef55c5b1583ed65a96d5a967d109e5aa7b2b4e22dde
MD5 4412e55663702942c487ce11276a3449
BLAKE2b-256 a3ecfad4b82b66a5f32123757cf81a485d3fd225c4b745140ae1abc97ee4b4ac

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 31072c54c359ead52f53801904b937adf0925ff06ffd11a54dec40d669b0ff77
MD5 6f117cb34945aa2b01b1ce1cf5291d6c
BLAKE2b-256 017dd0573b1d1dcc1caec480008cd702a6e54105b9d366d990565be55046efd5

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp39-cp39-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp39-cp39-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 411c224834639ca60023c0f84b4a515e4fbb8571fd0177064e3d51b621b8020e
MD5 3be7f2b4b14cf98c0ab84ad5108ef120
BLAKE2b-256 07237c19d0229e541b5f77829942750122223e7182ae433a8801a4c50b293051

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp39-cp39-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp39-cp39-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 3350d8149cadfc891f618d4289872971288a8266a28f7b4cd49634492902ec5c
MD5 ef9f31106e710ea282e16e967cff4e22
BLAKE2b-256 e7c51d5a172da09f92a9bebb2c50cf49f9e8fdfc0f18f3f3d59262670d43dc38

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b2f0d91bb92b0a2973f0ffa48e6cf327e071afcd4c7b7f200ec7545b4a2041eb
MD5 e0207d36b051902066144fb592688188
BLAKE2b-256 3141379c9cadf9fac48f31f3b73d0e0652eb84a76b601448f4e643700c670f33

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp38-cp38-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp38-cp38-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 9b7590e2cc02efd83cf55f5b873f86b2b9ddc69ecb1ba8aa461bbb785877116d
MD5 1c3e00ad088144562ea1b7dfeb2df86b
BLAKE2b-256 c609b1f6835583004b8eb3462668e2b7518ab8982a722f74253d7c26d7b5679a

See more details on using hashes here.

Provenance

File details

Details for the file pyats.datastructures-24.6-cp38-cp38-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for pyats.datastructures-24.6-cp38-cp38-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 9a7c037e0ae341d3dd25be531ed6172f0d7b7a8f993c2f4755a8e2d8b0a8ce97
MD5 985e67ef4197055d59b18a4b5ab32f22
BLAKE2b-256 a4c84a6422ce3b234abb9e47dd186191759112fffc9c40a863691da8ae95860a

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