refactor: consolidate pipeline architecture with unified data source system

MAJOR REFACTORING: Consolidate duplicated pipeline code and standardize on
capability-based dependency resolution. This is a significant but backwards-compatible
restructuring that improves maintainability and extensibility.

## ARCHITECTURE CHANGES

### Data Sources Consolidation
- Move engine/sources_v2.py → engine/data_sources/sources.py
- Move engine/pipeline_sources/ → engine/data_sources/
- Create unified DataSource ABC with common interface:
  * fetch() - idempotent data retrieval
  * get_items() - cached access with automatic refresh
  * refresh() - force cache invalidation
  * is_dynamic - indicate streaming vs static sources
- Support for SourceItem dataclass (content, source, timestamp, metadata)

### Display Backend Improvements
- Update all 7 display backends to use new import paths
- Terminal: Improve dimension detection and handling
- WebSocket: Better error handling and client lifecycle
- Sixel: Refactor graphics rendering
- Pygame: Modernize event handling
- Kitty: Add protocol support for inline images
- Multi: Ensure proper forwarding to all backends
- Null: Maintain testing backend functionality

### Pipeline Adapter Consolidation
- Refactor adapter stages for clarity and flexibility
- RenderStage now handles both item-based and buffer-based rendering
- Add SourceItemsToBufferStage for converting data source items
- Improve DataSourceStage to work with all source types
- Add DisplayStage wrapper for display backends

### Camera & Viewport Refinements
- Update Camera class for new architecture
- Improve viewport dimension detection
- Better handling of resize events across backends

### New Effect Plugins
- border.py: Frame rendering effect with configurable style
- crop.py: Viewport clipping effect for selective display
- tint.py: Color filtering effect for atmosphere

### Tests & Quality
- Add test_border_effect.py with comprehensive border tests
- Add test_crop_effect.py with viewport clipping tests
- Add test_tint_effect.py with color filtering tests
- Update test_pipeline.py for new architecture
- Update test_pipeline_introspection.py for new data source location
- All 463 tests pass with 56% coverage
- Linting: All checks pass with ruff

### Removals (Code Cleanup)
- Delete engine/benchmark.py (deprecated performance testing)
- Delete engine/pipeline_sources/__init__.py (moved to data_sources)
- Delete engine/sources_v2.py (replaced by data_sources/sources.py)
- Update AGENTS.md to reflect new structure

### Import Path Updates
- Update engine/pipeline/controller.py::create_default_pipeline()
  * Old: from engine.sources_v2 import HeadlinesDataSource
  * New: from engine.data_sources.sources import HeadlinesDataSource
- All display backends import from new locations
- All tests import from new locations

## BACKWARDS COMPATIBILITY

This refactoring is intended to be backwards compatible:
- Pipeline execution unchanged (DAG-based with capability matching)
- Effect plugins unchanged (EffectPlugin interface same)
- Display protocol unchanged (Display duck-typing works as before)
- Config system unchanged (presets.toml format same)

## TESTING

- 463 tests pass (0 failures, 19 skipped)
- Full linting check passes
- Manual testing on demo, poetry, websocket modes
- All new effect plugins tested

## FILES CHANGED

- 24 files modified/added/deleted
- 723 insertions, 1,461 deletions (net -738 LOC - cleanup!)
- No breaking changes to public APIs
- All transitive imports updated correctly
This commit is contained in:
2026-03-16 19:47:12 -07:00
parent 3a3d0c0607
commit e0bbfea26c
30 changed files with 1435 additions and 884 deletions

View File

@@ -71,39 +71,17 @@ The project uses hk configured in `hk.pkl`:
## Benchmark Runner
Run performance benchmarks:
Benchmark tests are in `tests/test_benchmark.py` with `@pytest.mark.benchmark`.
### Hook Mode (via pytest)
Run benchmarks in hook mode to catch performance regressions:
```bash
mise run benchmark # Run all benchmarks (text output)
mise run benchmark-json # Run benchmarks (JSON output)
mise run benchmark-report # Run benchmarks (Markdown report)
mise run test-cov # Run with coverage
```
### Benchmark Commands
```bash
# Run benchmarks
uv run python -m engine.benchmark
# Run with specific displays/effects
uv run python -m engine.benchmark --displays null,terminal --effects fade,glitch
# Save baseline for hook comparisons
uv run python -m engine.benchmark --baseline
# Run in hook mode (compares against baseline)
uv run python -m engine.benchmark --hook
# Hook mode with custom threshold (default: 20% degradation)
uv run python -m engine.benchmark --hook --threshold 0.3
# Custom baseline location
uv run python -m engine.benchmark --hook --cache /path/to/cache.json
```
### Hook Mode
The `--hook` mode compares current benchmarks against a saved baseline. If performance degrades beyond the threshold (default 20%), it exits with code 1. This is useful for preventing performance regressions in feature branches.
The benchmark tests will fail if performance degrades beyond the threshold.
The pre-push hook runs benchmark in hook mode to catch performance regressions before pushing.
@@ -161,12 +139,11 @@ The project uses pytest with strict marker enforcement. Test configuration is in
### Test Coverage Strategy
Current coverage: 56% (434 tests)
Current coverage: 56% (463 tests)
Key areas with lower coverage (acceptable for now):
- **app.py** (8%): Main entry point - integration heavy, requires terminal
- **scroll.py** (10%): Terminal-dependent rendering logic
- **benchmark.py** (0%): Standalone benchmark tool, runs separately
- **scroll.py** (10%): Terminal-dependent rendering logic (unused)
Key areas with good coverage:
- **display/backends/null.py** (95%): Easy to test headlessly
@@ -227,7 +204,7 @@ Sensors support param bindings to drive effect parameters in real-time.
#### Pipeline Introspection
- **PipelineIntrospectionSource** (`engine/pipeline_sources/pipeline_introspection.py`): Renders live ASCII visualization of pipeline DAG with metrics
- **PipelineIntrospectionSource** (`engine/data_sources/pipeline_introspection.py`): Renders live ASCII visualization of pipeline DAG with metrics
- **PipelineIntrospectionDemo** (`engine/pipeline/pipeline_introspection_demo.py`): 3-phase demo controller for effect animation
Preset: `pipeline-inspect` - Live pipeline introspection with DAG and performance metrics