data-platform-helpers
Decision gist · record as of 2026-08-14
Yes, if you are building or maintaining Juju charms for distributed data platforms and need reliable version validation across related applications. The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Not relevant for non-charm contexts.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; designed for use within Juju charm applications.
- Low install friction with a pure Python wheel.
- Actively maintained with a recent release.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
last release 2026-06-17 (58 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 103,478 downloads/mo, #12,802 on PyPI
Alternatives
Verify before relying
pip install data-platform-helpers==1.1.0
from data_platform_helpers.version_check import CrossAppVersionChecker
version_checker = CrossAppVersionChecker(
charm_instance,
version="1.0",
relations_to_check=["relation1", "relation2"]
)
if not version_checker.are_related_apps_valid():
print(version_checker.get_invalid_versions())- Whether the Advanced Statuses Handler and Interfaces modules are fully implemented or still in development (description marks Interfaces as V1 and Statuses as TBD).
- Specific version range syntax supported by the version_validity_range parameter.
- Whether the package works outside Juju charm contexts or is charm-specific.
What it is and what it does
data-platform-helpers is a utility library for validating version consistency across distributed data platform components, particularly in Juju charm deployments. Its primary feature is a CrossAppVersionChecker that enforces version alignment between related applications—for example, ensuring that Kafka brokers and Kafka Connect instances, or shards and cluster managers, run compatible versions. You instantiate the checker with your charm instance, the current version, and a list of relations to monitor; it then validates that related applications meet your version constraints and can report which relations have mismatched versions.
The package also includes Data Interfaces V1, a set of abstractions intended for charm libraries and other code that needs parts of the data interfaces specification but cannot use the charm-lib directly. It depends on ops (Juju charm framework), pydantic (for data validation), and rich (for terminal output). The library targets Python 3.10 and later and is classified as production-stable.
Use it for
- Enforce version compatibility in a sharded cluster where all shards and the cluster manager must run the same component versions.
- Validate that Kafka Connect and Kafka broker applications maintain compatible underlying versions during deployments.
- Check version alignment across multiple related charm applications during upgrade or join events.
- Provide standardized data interfaces for charm libraries that need cross-application communication patterns.
- Log or fail charm events when related applications have mismatched versions that would cause operational issues.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or maintaining Juju charms for distributed data platforms and need reliable version validation across related applications.
The low install friction, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Not relevant for non-charm contexts.
Install
data-platform-helpers on PyPI
Before you install
Low install friction with a pure Python wheel. Actively maintained with a recent release. Depends on ops, pydantic, and rich—all stable, widely-used libraries.
Requires Python 3.10 or later; designed for use within Juju charm applications.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install data-platform-helpers==1.1.0
from data_platform_helpers.version_check import CrossAppVersionChecker
version_checker = CrossAppVersionChecker(
charm_instance,
version="1.0",
relations_to_check=["relation1", "relation2"]
)
if not version_checker.are_related_apps_valid():
print(version_checker.get_invalid_versions())
Verify before relying
- Whether the Advanced Statuses Handler and Interfaces modules are fully implemented or still in development (description marks Interfaces as V1 and Statuses as TBD).
- Specific version range syntax supported by the version_validity_range parameter.
- Whether the package works outside Juju charm contexts or is charm-specific.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesopspydanticrich |
| Maintenance | Actively maintained 58 days since the last release |
| First released | |
| Downloads | 103,478 / month, #12,802 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/StableIntended Audience :: DevelopersIntended Audience :: System AdministratorsOperating System :: POSIX :: Linux |
Evidence: data_platform_helpers-1.1.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “cross-app version validation”
- data-platform-helpersProvides version checking and validation utilities for distributed…
- semantic-versionParses, validates, and compares semantic version strings according to…
- mozilla-versionParse and validate Mozilla product version numbers, classify them as…
Give your agent the search over MCP, or paste the wish link into any chat.
More Distributed Computing packages
gRPC Python is an HTTP/2-based RPC framework that enables you to define and call remote procedures across network boundaries using protocol buffers for serialization.
Install it if you need RPC communication in a distributed system or are integrating with existing gRPC services.
execnet lets you spawn and communicate with Python interpreters across local processes, remote hosts, and different platforms, using a simple API for task distribution and inter-process messaging.
However, the aging maintenance status (275 days since last release) means you should verify it meets your concurrency and performance needs before committing to a…
Cloudpickle extends Python's standard pickle module to serialize lambda functions, interactively-defined functions and classes, and other constructs that the default pickle cannot handle, making it suitable for cluster computing and remote code execution.
Install it if you need to serialize lambda functions, interactively-defined code, or non-standard Python constructs for cluster computing or distributed execution.
Provides a unified, open()-compatible Python API for streaming large files from remote storage (S3, GCS, Azure, HDFS, SFTP, HTTP) and local filesystems, with transparent compression support.
Install it if you work with large files on cloud storage or remote systems and want to avoid writing boilerplate around multiple SDKs.
Portalocker provides cross-platform file locking with support for exclusive and shared locks, plus Redis-based distributed locks and process-aware PID file locking.
Install it if you need file or process coordination; the optional extras (pywin32, redis) are only required for specific lock types.
Ray is a distributed computing framework that scales Python applications from a single machine to multi-node clusters, providing abstractions for parallel tasks, stateful actors, and shared objects.
See also charmcraftlocal · charm-refresh-build-version · cosl · charmlibs-pathops · pytest-operator · bpyutils · nr-util · ops-scenario · ops · pyats.utils