test(training,common,inference): add Hypothesis property-based tests

[WilliamBerryiii]

Pull Request

Description

Added Hypothesis property-based testing across all three Python source packages (common, inference, training), covering configuration models, CLI argument handling, plotting utilities, robot types, Azure ML context, metrics extraction, and ANSI stream stripping. A shared test helper reduced duplicated module-loading boilerplate, and two targeted fixes addressed a production exception gap and a Windows test compatibility issue.

Closes #240

Type of Change

• 🐛 Bug fix (non-breaking change fixing an issue)
• ✨ New feature (non-breaking change adding functionality)
• 💥 Breaking change (fix or feature causing existing functionality to change)
• 📚 Documentation update
• 🏗️ Infrastructure change (Terraform/IaC)
• ♻️ Refactoring (no functional changes)

Component(s) Affected

• deploy/000-prerequisites - Azure subscription setup
• deploy/001-iac - Terraform infrastructure
• deploy/002-setup - OSMO control plane / Helm
• deploy/004-workflow - Training workflows
• src/training - Python training scripts
• docs/ - Documentation

Testing Performed

• Terraform plan reviewed (no unexpected changes)
• Terraform apply tested in dev environment
• Training scripts tested locally with Isaac Sim
• OSMO workflow submitted successfully
• Smoke tests passed (smoke_test_azure.py)

Documentation Impact

• No documentation changes needed
• Documentation updated in this PR
• Documentation issue filed

Bug Fix Checklist

• Linked to issue being fixed
• Regression test included, OR
• Justification for no regression test:

Checklist

• My code follows the project conventions
• Commit messages follow conventional commit format
• I have performed a self-review
• Documentation impact assessed above
• No new linting warnings introduced

---

Changes

Property-Based Tests (7 new files)

Seven new Hypothesis test files were added following the test_<module>_hypothesis.py naming convention, keeping property-based tests separate from existing example-based suites.

• Added config model property tests in tests/common/test_config_models_hypothesis.py covering roundtrip serialization, invalid name rejection, threshold ordering, duplicate topic detection, and boundary values for TopicConfig, GpioTriggerConfig, PositionTriggerConfig, DiskThresholds, VrTriggerConfig, GapDetectionConfig, and RecordingConfig
• Added CLI argument example tests in tests/common/test_cli_args.py covering add_rsl_rl_args and update_rsl_rl_cfg — argument registration, defaults, string parsing, resume flag, logger choices, config overrides, seed randomization, and project name propagation
• Added plotting property tests in tests/inference/test_plotting_hypothesis.py for plot_action_deltas, plot_cumulative_positions, plot_error_heatmap, plot_summary_panel, and plot_aggregate_summary using custom composite strategies and headless matplotlib rendering
• Added robot types property tests in tests/inference/test_robot_types_hypothesis.py for RobotObservation and JointPositionCommand — valid shape acceptance, invalid shape rejection via flatmap, as_absolute additivity, and timestamp preservation
• Added Azure ML context property tests in tests/training/test_context_hypothesis.py using mock-injection for azure.ai.ml, azure.identity, and mlflow — tested _optional_env, upload_file, upload_checkpoint, and upload_files_batch
• Added metrics extraction property tests in tests/training/test_metrics_hypothesis.py for _extract_from_value using FakeTensor and NumpyArrayLike test doubles to avoid torch/numpy dependencies, with statistical invariant assertions (min ≤ mean ≤ max)
• Added ANSI stream property tests in tests/training/test_stream_hypothesis.py for AnsiStrippingStream — plain text passthrough, ANSI code stripping, carriage return normalization, and encoding delegation

Production Fix

• Added RuntimeError to the exception tuple in _extract_from_value in src/training/utils/metrics.py, handling torch tensors that raise RuntimeError during .item() calls on multi-element tensors

Test Infrastructure

Extracted a shared module-loading helper and fixed a cross-platform compatibility issue.

• Added tests/training/conftest.py with load_training_module helper using importlib.util to load training source modules without importing the full dependency tree
  • Adopted by test_env.py and test_metrics.py, replacing duplicated boilerplate
• Replaced chmod(0o444) with monkeypatch.setattr("os.access", ...) in tests/common/test_config_models.py for Windows compatibility where POSIX permission bits do not reliably restrict write access

Dependencies

• Added dev dependencies in pyproject.toml: hypothesis>=6.100.0, numpy>=1.26.0,<3.0.0, matplotlib>=3.10.8
• Configured Hypothesis globally: max_examples = 50, deadline = 500 ms
• Added "flatmap" to .cspell/general-technical.txt and .hypothesis/ to .gitignore
• Updated uv.lock with transitive dependencies: contourpy, cycler, fonttools, pillow, pyparsing, sortedcontainers

Related Issues

Closes #240

Notes

All 147 tests pass (0 failures, 3 PydanticJsonSchemaWarnings). Ruff reports no lint warnings on new or modified files.

[github-actions]

Dependency Review

The following issues were found:

• ✅ 0 vulnerable package(s)
• ✅ 0 package(s) with incompatible licenses
• ✅ 0 package(s) with invalid SPDX license definitions
• ⚠️ 3 package(s) with unknown licenses.

See the Details below.

License Issues

uv.lock

Package	Version	License	Issue Type
hypothesis	6.151.9	Null	Unknown License
kiwisolver	1.5.0	Null	Unknown License
numpy	2.4.3	Null	Unknown License

OpenSSF Scorecard

Package	Version	Score	Details
pip/contourpy	1.3.3	Unknown	Unknown
pip/cycler	0.12.1	Unknown	Unknown
pip/fonttools	4.62.1	🟢 5.8	Details Check Score Reason Dangerous-Workflow 🟢 10 no dangerous workflow patterns detected Maintained 🟢 10 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10 Code-Review 🟢 4 Found 7/16 approved changesets -- score normalized to 4 Security-Policy 🟢 10 security policy file detected Token-Permissions ⚠️ 0 detected GitHub workflow tokens with excessive permissions CII-Best-Practices ⚠️ 0 no effort to earn an OpenSSF best practices badge detected License 🟢 10 license file detected Binary-Artifacts 🟢 10 no binaries found in the repo Pinned-Dependencies ⚠️ 0 dependency not pinned by hash detected -- score normalized to 0 Fuzzing ⚠️ 0 project is not fuzzed Signed-Releases ⚠️ -1 no releases found Branch-Protection ⚠️ -1 internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md Packaging 🟢 10 packaging workflow detected SAST ⚠️ 0 SAST tool is not run on all commits -- score normalized to 0
pip/hypothesis	6.151.9	Unknown	Unknown
pip/kiwisolver	1.5.0	Unknown	Unknown
pip/matplotlib	3.10.8	Unknown	Unknown
pip/numpy	2.4.3	Unknown	Unknown
pip/pillow	12.1.1	Unknown	Unknown
pip/pyparsing	3.3.2	Unknown	Unknown
pip/sortedcontainers	2.4.0	Unknown	Unknown

Scanned Files

• uv.lock

[nguyena2]

Credit-style rating:

PR Credit Score: 832/850
Equivalent grade: Excellent (approve)
Why this score: very strong coverage improvement, minimal production risk, green CI, and clean scope; slight deduction only for increased test/dependency surface area that may add future maintenance/runtime overhead.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 9.79%. Comparing base (083a8af) to head (512d55d).
⚠️ Report is 4 commits behind head on main.

Additional details and impacted files

@@          Coverage Diff          @@
##            main    #268   +/-   ##
=====================================
  Coverage   9.79%   9.79%           
=====================================
  Files         29      29           
  Lines       3881    3881           
  Branches     497     497           
=====================================
  Hits         380     380           
  Misses      3491    3491           
  Partials      10      10           

Flag	Coverage Δ		*Carryforward flag
pester	79.87% <ø> (ø)
pytest	6.89% <ø> (ø)		Carriedforward from b309580

*This pull request uses carry forward flags. Click here to find out more.

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