refactor: miscellaneous copilot suggestions on bulk type checking

[mayankansys]

Context

Copilot suggestions identified several code quality issues across the PyFluent codebase during the initial type-checking PR review (Issue #4761). These issues collectively impact code reliability, maintainability, and Python compatibility:

• Resource Management Issues: File descriptor leaks due to missing context managers
• Dead Code: Duplicate variable assignments indicating maintenance debt
• Type System Problems: Invalid type annotations that violate Python runtime semantics
• Missing Type Hints: Return types missing for certain code paths
• Type Inconsistencies: Conflicting type signatures and annotations
• Compatibility Issues: Python version-specific API usage without proper version guards
• Public API Issues: Wildcard imports breaking module introspection (dir())
• Test Fragility: Tests with brittle assumptions about dependency versions

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Change Summary

This PR addresses critical code quality improvements across the PyFluent codebase:

1. GPU Validation Type Fix (launcher/launch_options.py)

   • Fixed type mismatch in _validate_gpu() function
   • Added proper None check before dimension type conversion
   • Prevents ValueError when dimension=None is passed

2. Array Type Annotation Fix (filereader/case_file.py)

   • Corrected _get_nodes() return type annotation
   • Updated to accurately reflect ndarray slice return type

3. TypeVar Constraint Fix (fluent_connection.py)

   • Fixed TypeVar binding constraint
   • Updated callable signature to properly reflect parameter and return types

4. Module Configuration (module_config.py)

   • Added version guard for Python 3.11+ compatibility
   • Implemented fallback for inspect.getmembers_static() on earlier Python versions

5. Public API Module Discovery (__init__.py)

   • Added explicit __all__ list with all exported symbols for clarity
   • Implemented custom __getattr__() for dynamic module loading
   • Implemented custom __dir__() to properly expose submodules in dir() output
   • Supports lazy loading of submodules to reduce import time
   • Maintains backward compatibility with existing code

6. Return Type Simplification (streaming_services/field_data_streaming.py)

   • Simplified overly complex return type annotation
   • Added explicit list conversion for dict_values
   • Improved code clarity without changing functionality

7. Import Cleanup (launcher/launcher.py)

   • Removed unused imports to reduce dependencies

8. Documentation Enhancement (launcher/launcher.py)

   • Updated docstring to accurately reflect return types for different scenarios

9. Test Resilience (tests/test_launcher.py)

   • Made pandas reference test more robust
   • Changed from hardcoded count assumptions to flexible checks
   • Accounts for pandas-stubs presence in dependency variations

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Rationale

1. Type Safety: Better type annotations help catch errors early and improve IDE support
2. Code Reliability: Prevents resource leaks and runtime errors
3. Python Version Support: Works across all supported Python versions
4. Consistent Public API: Module discovery works correctly with dir() and __all__
5. Code Clarity: Easier to understand and maintain
6. Stable Tests: Tests work reliably across different dependency versions

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Impact

• Launcher System: Stronger type checking for GPU and container launch scenarios
• File Reader: More accurate data type annotations
• Core Package: Faster imports with lazy module loading, better module discovery
• Module Configuration: Works with Python 3.11+ versions
• Streaming Services: Clearer, simpler type annotations
• Tests: More reliable across different dependency versions

[codacy-production]

Up to standards ✅

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