Drop caret upper bounds on runtime dependencies

[balloob]

Description

Drop the caret (^) upper bounds on the runtime dependencies (aiohttp, yarl, pycognito, tenacity), replacing them with lower-bound-only >= constraints.

A caret constraint expands to an implicit < next-major upper bound. For a library that is too limiting for consumers that must resolve a single version set across many packages. Home Assistant, for example, can't pair nice-go with another integration that needs a newer major of a shared dependency — concretely, it currently can't adopt tenacity 9.x (required by another dependency) because nice-go caps it at <9. The preference is to rely on consumers' test suites to catch real incompatibilities with new versions rather than pre-emptively capping.

I verified that the latest tenacity (9.1.4) still provides every symbol nice-go imports — retry, retry_base, retry_if_exception_type, wait_random_exponential, before_sleep_log, RetryCallState — so lifting that cap is safe.

poetry.lock was refreshed (content-hash only; no dependency versions changed).

Checklist

• Tests covering the new functionality have been added
• Documentation has been updated OR the change is too minor to be documented
• Changes are listed in the CHANGELOG.md OR changes are insignificant

🤖 Generated with Claude Code
https://claude.ai/code/session_016huRs96kGdQbNQopXseC4H

Summary by Sourcery

Relax runtime dependency version constraints to remove implicit upper bounds while keeping existing minimum supported versions.

Enhancements:

• Allow newer versions of aiohttp, yarl, pycognito, and tenacity by switching to lower-bound-only dependency constraints in pyproject.toml.

Build:

• Refresh Poetry lockfile metadata to reflect the updated dependency constraints without changing resolved versions.

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

This PR relaxes runtime dependency version constraints in pyproject.toml by removing caret-based upper bounds and refreshing poetry.lock’s content hash without changing resolved versions.

File-Level Changes

Change	Details	Files
Relax runtime dependency constraints to use lower-bound-only versions instead of caret-based upper bounds.	Updated aiohttp dependency constraint from a caret range to a >= lower-bound-only constraint. Updated yarl dependency constraint from a caret range to a >= lower-bound-only constraint. Updated pycognito dependency constraint from a caret range to a >= lower-bound-only constraint. Updated tenacity dependency constraint from a caret range to a >= lower-bound-only constraint, relying on consumer tests for compatibility with newer majors. Refreshed poetry.lock so its content-hash matches the updated pyproject.toml without altering locked dependency versions.	pyproject.toml poetry.lock

Possibly linked issues

• #(none provided): PR removes tenacity’s <9 cap (and other caps), directly satisfying the request to relax tenacity versioning.

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[sourcery-ai]

Hey - I've left some high level feedback:

• Since you're intentionally relying on downstream tests to catch future major-version breaks, consider adding a CI job that periodically runs the test suite against the latest releases of these now-unbounded runtime dependencies to surface incompatibilities early.
• You might want to align the versioning strategy for aiobotocore with the other runtime dependencies (either keep its <4.0.0 upper bound on purpose and comment why, or relax it similarly) so consumers have a consistent expectation across all dependencies.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- Since you're intentionally relying on downstream tests to catch future major-version breaks, consider adding a CI job that periodically runs the test suite against the latest releases of these now-unbounded runtime dependencies to surface incompatibilities early.
- You might want to align the versioning strategy for `aiobotocore` with the other runtime dependencies (either keep its `<4.0.0` upper bound on purpose and comment why, or relax it similarly) so consumers have a consistent expectation across all dependencies.

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