pyats.datastructures
pyATS Datastructures: Extended Datastructures for Grownups
Decision gist · record as of 2026-08-14
Yes, if you are adopting pyATS or need the specific data structures it provides (AttrDict, ListDict, WeakList). The package is actively maintained, has no external dependencies, and carries a permissive Apache 2.0 license. Install friction is moderate due to compiled wheels, but this is standard for the platform. Not necessary if you do not use pyATS and can meet your data structure needs with standard Python collections.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later; Linux and macOS only (Windows not supported per documentation).
- Medium install friction due to compiled wheels for multiple Python versions and platforms (cp310–cp314 across macOS, Linux, and musllinux).
- Active maintenance with a release 7 days ago.
License · maintenance · safety
Apache 2.0 (permissive) — Licensed under Apache 2.0 (permissive), allowing use in commercial and proprietary projects with minimal restrictions beyond attribution and liability disclaimers.
last release 2026-08-07 (7 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 297,105 downloads/mo, #7,888 on PyPI
Alternatives
Verify before relying
pip install pyats.datastructures
from pyats.datastructures import AttrDict, ListDict, WeakList
my_dict = AttrDict(name='test')
print(my_dict.name)- Specific API surface and behavioral differences of WeakList, ListDict, and logic utilities.
- Whether this package is intended for standalone use or primarily as a dependency of the larger pyATS ecosystem.
- Performance characteristics or memory benefits of WeakList compared to standard Python collections.
What it is and what it does
pyats.datastructures is a sub-component of the pyATS testing framework that provides specialized data structures for Python developers. It includes WeakList, ListDict, AttrDict, and logic utilities—types designed to handle advanced use cases within the pyATS ecosystem and beyond. The package has no runtime dependencies and is available as pre-compiled wheels for Python 3.9 through 3.14 on macOS and Linux platforms.
The package is maintained as part of Cisco's pyATS project, which focuses on data-driven and reusable testing for agile development. While it can be installed standalone, it is typically used as a dependency when adopting pyATS or when a project requires the specific data structure behaviors it provides. Installation is straightforward via pip, though the compiled nature of the wheels means platform compatibility is limited to the supported architectures.
Use it for
- Use it as part of pyATS test suite setup to leverage specialized collection types in test data management.
- Use it to build attribute-accessible dictionaries (AttrDict) where dot notation is preferred over bracket access.
- Use it in projects requiring weak reference collections (WeakList) to avoid circular reference issues.
- Use it to combine list and dictionary semantics (ListDict) when both indexed and keyed access patterns are needed.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are adopting pyATS or need the specific data structures it provides (AttrDict, ListDict, WeakList).
The package is actively maintained, has no external dependencies, and carries a permissive Apache 2.0 license. Install friction is moderate due to compiled wheels, but this is standard for the platform. Not necessary if you do not use pyATS and can meet your data structure needs with standard Python collections.
Install
pyats-datastructures on PyPI
Before you install
Medium install friction due to compiled wheels for multiple Python versions and platforms (cp310–cp314 across macOS, Linux, and musllinux). Active maintenance with a release 7 days ago. No runtime dependencies, simplifying integration.
Requires Python 3.8 or later; Linux and macOS only (Windows not supported per documentation).
License in practice
Licensed under Apache 2.0 (permissive), allowing use in commercial and proprietary projects with minimal restrictions beyond attribution and liability disclaimers.
Quickstart
pip install pyats.datastructures
from pyats.datastructures import AttrDict, ListDict, WeakList
my_dict = AttrDict(name='test')
print(my_dict.name)Verify before relying
- Specific API surface and behavioral differences of WeakList, ListDict, and logic utilities.
- Whether this package is intended for standalone use or primarily as a dependency of the larger pyATS ecosystem.
- Performance characteristics or memory benefits of WeakList compared to standard Python collections.
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 7 days since the last release |
| First released | |
| Downloads | 297,105 / month, #7,888 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableDevelopment Status :: 6 - MatureEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: System AdministratorsIntended Audience :: Telecommunications IndustryLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOSOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Software Development :: Build ToolsTopic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python ModulesTopic :: Software Development :: Testing |
Evidence: pyats_datastructures-26.7-cp310-cp310-macosx_11_0_universal2.whl; pyats_datastructures-26.7-cp310-cp310-manylinux2014_aarch64.whl; pyats_datastructures-26.7-cp310-cp310-manylinux2014_x86_64.whl; pyats_datastructures-26.7-cp311-cp311-macosx_11_0_universal2.whl; pyats_datastructures-26.7-cp311-cp311-manylinux2014_aarch64.whl; pyats_datastructures-26.7-cp311-cp311-manylinux2014_x86_64.whl; pyats_datastructures-26.7-cp312-cp312-macosx_11_0_universal2.whl; pyats_datastructures-26.7-cp312-cp312-manylinux2014_aarch64.whl; pyats_datastructures-26.7-cp312-cp312-manylinux2014_x86_64.whl; pyats_datastructures-26.7-cp312-cp312-musllinux_1_2_x86_64.whl; pyats_datastructures-26.7-cp313-cp313-macosx_11_0_universal2.whl; pyats_datastructures-26.7-cp313-cp313-manylinux2014_aarch64.whl; pyats_datastructures-26.7-cp313-cp313-manylinux2014_x86_64.whl; pyats_datastructures-26.7-cp314-cp314-macosx_11_0_universal2.whl; pyats_datastructures-26.7-cp314-cp314-manylinux2014_aarch64.whl; pyats_datastructures-26.7-cp314-cp314-manylinux2014_x86_64.whl
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See also pyats.utils · pyats.aetest · pyats · pyats.reporter · pyats.log · pyats.robot · pyats.async · pyats.results · pyats.tcl · pyats.aereport