Cycle 8: CI Stabilization and Dependency Improvements

[NITISH-R-G]

This cycle focused on ensuring the stability of the CI pipeline and improving the developer experience.

It accomplishes this by pinning the version of jscpd to 4.0.0 and ignoring build artifacts, which were causing CI failures. To improve local checks and avoid issues for new developers, required tools like mypy, bandit, openenv-core, and vulture were added as explicit dev dependencies in pyproject.toml.

Additionally, .mypy_cache/ and .ruff_cache/ were added to .gitignore to prevent cache bloat in the repository.

Strict ruff linting rules were implemented in .ruff.toml and tech debt across the codebase was automatically resolved. Lastly, the CI pipeline was updated to include automated security auditing with bandit and environment validation with openenv-core, as documented and justified in CYCLE_8_REPORT.md.

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PR created automatically by Jules for task 643167812270706846 started by @NITISH-R-G

Summary by Sourcery

Stabilize repository quality checks and improve local development validation through pinned CI tooling, stronger linting, and explicit development dependencies.

Enhancements:

• Enforce broader Ruff linting rules and clean up codebase technical debt, including modernized type annotations and import/style improvements.
• Add explicit development dependencies for local static analysis and environment validation tools.

CI:

• Stabilize code-quality checks by pinning jscpd to version 4.0.0 and excluding generated build artifacts from duplicate-code analysis.
• Add Bandit security scanning and OpenEnv environment validation to the CI pipeline.

Documentation:

• Add a Cycle 8 report documenting repository health findings and the CI and developer-experience improvements.

Chores:

• Ignore mypy and Ruff cache directories to keep generated files out of the repository.

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Reviewer's Guide

This PR stabilizes the CI/code-quality pipeline and improves local developer ergonomics by pinning/ignoring noisy tooling inputs, tightening Ruff configuration, adding dev-only dependencies, and applying automated lint fixes across the EV grid codebase, server, tools, viz, and training scripts.

Flow diagram for local developer validation setup

flowchart TD
    Checkout[Developer checkout]
    Install["Install dev dependencies"]
    Checks["Run local quality checks"]
    CI["CI uses the same validation tools"]
    Clean["Caches and build artifacts remain untracked"]

    Checkout --> Install
    Install --> Checks
    Checks --> CI
    Checkout --> Clean

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File-Level Changes

Change	Details	Files
CI workflow now includes security and environment validation and has a pinned jscpd version that ignores build artifacts.	Add Bandit SAST step running python -m bandit -r . -c pyproject.toml in code-quality workflow. Add OpenEnv validation step using openenv validate "$GITHUB_WORKSPACE" in code-quality workflow. Pin jscpd installation to version 4.0.0 via npm. Extend jscpd ignore patterns to exclude dist/ and build/ artifacts in duplicate-code checks.	.github/workflows/code-quality.yml
Repository configuration is hardened for dev experience and cleanliness, with explicit dev dependencies and expanded gitignore/cache handling.	Add mypy, bandit, openenv-core, and vulture to [project.optional-dependencies].dev in pyproject. Ignore .mypy_cache/ and .ruff_cache/ in .gitignore to avoid committing caches. Document motivations, risks, and roadmap for these changes in CYCLE_8_REPORT.md.	pyproject.toml .gitignore CYCLE_8_REPORT.md
Ruff configuration is made stricter and tuned, and the codebase is auto-fixed to comply (imports, typing style, minor logic/style cleanups).	Configure Ruff select to enable a wide set of rule families (UP, B, C4, SIM, PLC, I, BLE, TRY, RUF, FURB, PIE, EXE, PLR). Expand Ruff ignore list to carve out specific rules that are noisy or not yet enforced. Apply Ruff-driven cleanups: reorder imports, remove unused imports, and simplify small logic blocks across EV oracle, server, tools, viz, training. Switch from typing.Optional[...] to `	Noneunion types in multiple functions and models.</li><li>Tighten dict initialization patterns and for-loops (e.g., usedict.fromkeys, iterate directly over dicts instead of .keys()`).

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