Skip to main content

pyATS Tcl: Tcl Integration and Objects

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/

Tcl Package

This is a sub-component of pyATS that wraps Python tkinter module in Python for better interface & datastructure casting.

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.tcl

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

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.

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.tcl-22.4-cp310-cp310-manylinux1_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.10

pyats.tcl-22.4-cp310-cp310-macosx_11_0_arm64.whl (453.5 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyats.tcl-22.4-cp310-cp310-macosx_10_16_x86_64.whl (545.0 kB view details)

Uploaded CPython 3.10 macOS 10.16+ x86-64

pyats.tcl-22.4-cp310-cp310-macosx_10_10_x86_64.whl (559.5 kB view details)

Uploaded CPython 3.10 macOS 10.10+ x86-64

pyats.tcl-22.4-cp39-cp39-musllinux_1_2_x86_64.whl (543.6 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.2+ x86-64

pyats.tcl-22.4-cp39-cp39-manylinux1_x86_64.whl (2.5 MB view details)

Uploaded CPython 3.9

pyats.tcl-22.4-cp39-cp39-macosx_11_0_arm64.whl (453.3 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyats.tcl-22.4-cp39-cp39-macosx_10_16_x86_64.whl (544.8 kB view details)

Uploaded CPython 3.9 macOS 10.16+ x86-64

pyats.tcl-22.4-cp39-cp39-macosx_10_10_x86_64.whl (559.2 kB view details)

Uploaded CPython 3.9 macOS 10.10+ x86-64

pyats.tcl-22.4-cp38-cp38-manylinux1_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.8

pyats.tcl-22.4-cp38-cp38-macosx_11_0_arm64.whl (452.0 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyats.tcl-22.4-cp38-cp38-macosx_10_16_x86_64.whl (531.0 kB view details)

Uploaded CPython 3.8 macOS 10.16+ x86-64

pyats.tcl-22.4-cp38-cp38-macosx_10_10_x86_64.whl (547.6 kB view details)

Uploaded CPython 3.8 macOS 10.10+ x86-64

pyats.tcl-22.4-cp37-cp37m-manylinux1_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.7m

pyats.tcl-22.4-cp37-cp37m-macosx_10_16_x86_64.whl (516.3 kB view details)

Uploaded CPython 3.7m macOS 10.16+ x86-64

pyats.tcl-22.4-cp37-cp37m-macosx_10_10_x86_64.whl (533.3 kB view details)

Uploaded CPython 3.7m macOS 10.10+ x86-64

pyats.tcl-22.4-cp36-cp36m-manylinux1_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.6m

pyats.tcl-22.4-cp36-cp36m-macosx_10_16_x86_64.whl (519.4 kB view details)

Uploaded CPython 3.6m macOS 10.16+ x86-64

pyats.tcl-22.4-cp36-cp36m-macosx_10_10_x86_64.whl (535.9 kB view details)

Uploaded CPython 3.6m macOS 10.10+ x86-64

File details

Details for the file pyats.tcl-22.4-cp310-cp310-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp310-cp310-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 a04061c4e2ce73370961b05d41c8c1dc787fb642c89d833ab496a6f67f850e31
MD5 753737913530159228bb5ddb2b77800e
BLAKE2b-256 b310880bfe6e3ac2e5964d548e805283914e7bbf655457984b6389f681c094f7

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 631472f08c294b1479b81d59e382e9011076305e87aadd9aed837dc8358bc434
MD5 0c042764c3fa6b91c1868ba3af6be8c9
BLAKE2b-256 96039c59df7a7948705674e3dd208517d9071c908cc83025dd46a4bcf85340f5

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp310-cp310-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp310-cp310-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 3999f8a461480e29dbe35c886394d94c6d5e9556eabb2562bbb9afb6fbe99943
MD5 b84f626d2fb9dcb9fa7ab4cb752a4828
BLAKE2b-256 c90627b778fd2c90fb836b61c659004ccbcf1857cb52a596b142a9f9828ea9c6

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp310-cp310-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp310-cp310-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 298467f44e23f31753c5e30dcaea418766fde0f88629a0031d4ca5eb81b76e8c
MD5 c1148c5301e403c4cffac1fe1c385b81
BLAKE2b-256 354cb7e2925e261854b91802a2e0cf4edb5eceb7b184c5257fb0dce1ffb07ded

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

  • Download URL: pyats.tcl-22.4-cp39-cp39-musllinux_1_2_x86_64.whl
  • Upload date:
  • Size: 543.6 kB
  • Tags: CPython 3.9, musllinux: musl 1.2+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.1 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.10

File hashes

Hashes for pyats.tcl-22.4-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 7d03f7e5eeb69e9a370cf43edda8b3a3a286f017a18fb6a16f0fc5a77225f199
MD5 d29cbadb50b668141d472e4b73b5074a
BLAKE2b-256 3e95daa5b60a86f0122380e9fe2a639d7a8515d3e8e7d47356cf50ff5e8b1c28

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp39-cp39-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 b052b7a5557275271baeb51c6ef4b0cc4449e6f550e6d456c1d5d4e85c0ebe5b
MD5 12d0eac680cd1952ac7a0dab06b96e63
BLAKE2b-256 34d8c440684ea2618dc08a33d9d1f56d7474cb98ac6d88c1d492340070c747a2

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 68b8a8c736dcf9870673df9e3ab140324ad1ff088f9cb72f5a9825c69914926e
MD5 e8ef806520cf3b68b5ee5618ca21659a
BLAKE2b-256 f2e93b79a9e6c8d1b3ae1db8a69504301eb9a6f5a13b675a2b0f377a98017d65

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp39-cp39-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp39-cp39-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 e4808633cc4856e97f296922b9646c2abe3eec9c8d22b95bd993f254a69dae16
MD5 3127535e8ad5dea07b0deade95a07316
BLAKE2b-256 dcb6292822dd325d8e96426e1c326caeb1bc98670eb4bede876db24af480de7c

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp39-cp39-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp39-cp39-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 9c988a322ec1b49f0679474ccafb1284aa705b3da4ae88c4d5d9f500ba7ddfb2
MD5 00b5ced5584861904bf7d55fb4410dda
BLAKE2b-256 717a44785cfeee2d23cc843f71de3fe0c884bc8414f0e580b17f14c0dd470439

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c40b75fea303cf9b8d71dd068ddad5d2abcfa4488d942d76dc378845c09f14af
MD5 681eb3c5e77cb54c8eb27b26e4b84bf2
BLAKE2b-256 bb3a7d3f4ef067f3211e97ff92721fcd3c926caffc3cb6b3bae66a2fcf67409d

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5b98307016e936568b8ad76976ffbf552db38bea4fe2a747f55aff8fa4c405d8
MD5 3c053a8201ee86e53b4940130b169d99
BLAKE2b-256 f96a7607b2eef0c56eda91a8d0818f552a128658a96f8f0d40d899bc361bcf29

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp38-cp38-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp38-cp38-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 5515cc10ba765790dbac12701a6ab47aa6b8871ec6d4b7b31ed025a167f5a1e3
MD5 2668a9a02e439f80c77699a63687f01e
BLAKE2b-256 8688aa1b81b703fea0b2a0c209b9569b563f44a132957747ede2bfee5dc15e8e

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp38-cp38-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp38-cp38-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 8fb6991014380c2f1ff2affac40731b30e64fec3be79060b869b26ababdd81e7
MD5 e251e104d76a4952374165cdf86db12a
BLAKE2b-256 009bdfedb61d97e4c8b19c8806ec9ac889feca4a26f06b9d07e873a390fa8212

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 fb623f3ce2f4e312ff20177d84d6e3a02f377c01dc3bb912b387b4b8468a0b1c
MD5 6c209e46b77c71e3cdf7b7c1ea82e8dc
BLAKE2b-256 2f00f4cc8e05e5eaf8a984b8134ae34cd87842b9bfc48b4d704556ae23b663df

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp37-cp37m-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp37-cp37m-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 808db40baa80ff4e1eed1b8e1e4841fd6c64c2e310e13c0c1a5f20402f350eb0
MD5 3ed50e0af8d769d74f6f7ef128747f98
BLAKE2b-256 4862b5328b17e6233955519c1ba30672178fbaada94c5fb3a9d5496ff8ad1d55

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp37-cp37m-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp37-cp37m-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 10bad233f5baa082db08752cc94081e7fe4423796671afcaaf6823b34478dc82
MD5 695534f21ba2d14b0a82fc7a6062dba7
BLAKE2b-256 159e9f9c52e7e4f880d6661760162616c78c08da0b21253089951c0726f0591c

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 3561c5f213310cc514f3ccf252bd0d43d8c4c18a5ca393330598a32e14637a2a
MD5 c2aea1ab45c0e904782fe84b901c817a
BLAKE2b-256 e04dac6ed07c937af95d9d2166947dd1dda6065e33fa20ca9c2d2d22d3676a23

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp36-cp36m-macosx_10_16_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp36-cp36m-macosx_10_16_x86_64.whl
Algorithm Hash digest
SHA256 96fbfc225516721ade76bf673c19b1189b137ecd7ce274c69b23c225575e77d0
MD5 778f3fbfc751105b1dc5b5e691904cc9
BLAKE2b-256 b735dffa9f3f99c31dd0782e088c2937a37bdb10491e868f106d0cb14bab1e39

See more details on using hashes here.

Provenance

File details

Details for the file pyats.tcl-22.4-cp36-cp36m-macosx_10_10_x86_64.whl.

File metadata

File hashes

Hashes for pyats.tcl-22.4-cp36-cp36m-macosx_10_10_x86_64.whl
Algorithm Hash digest
SHA256 e1f197a856d446dcb9109f366169e465456855627efe978b89656282fd3d89da
MD5 51f98fcb6ee64f60dcdb9c2ec50e7c44
BLAKE2b-256 786a5ba081697c0b5c4ca112c4a4a767d27f6532d32f38f3d33293afd136402c

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