ed
8f11340b38
Per post_module_taxonomy_de_cruft_20260627 Phase 2 (FR7). Each
'from src.models import X' for a moved class is rewritten to
'from src.<destination> import X':
Ticket, Track, WorkerContext, TrackState, TrackMetadata,
ThinkingSegment, EMPTY_TRACK_STATE -> src.mma
ProjectContext, ProjectMeta, ProjectOutput, ProjectFiles,
ProjectScreenshots, ProjectDiscussion, EMPTY_PROJECT_CONTEXT -> src.project
FileItem, Preset, ContextPreset, ContextFileEntry,
NamedViewPreset -> src.project_files
Tool, ToolPreset -> src.tool_presets
BiasProfile -> src.tool_bias
TextEditorConfig, ExternalEditorConfig,
EMPTY_TEXT_EDITOR_CONFIG -> src.external_editor
Persona -> src.personas
WorkspaceProfile -> src.workspace_manager
MCPServerConfig, MCPConfiguration, VectorStoreConfig,
RAGConfig, load_mcp_config -> src.mcp_client
NOT touched (kept on src.models; Phase 3 or Phase 4 will move them):
GenerateRequest, ConfirmRequest, DEFAULT_TOOL_CATEGORIES, Metadata, PROVIDERS
Migration was performed by the one-time script
scripts/tier2/artifacts/post_module_taxonomy_de_cruft_20260627/migrate_imports.py
which uses a class-to-module map and re.sub() to rewrite each
'from src.models import X' line.
Total: 85 import lines rewritten across 71 files.
Note: this commit depends on the v2 SHIPPED work
(origin/tier2/module_taxonomy_refactor_20260627) being merged into
this branch NEXT. On master (without the v2 SHIPPED commits), the
destination modules do not exist and these imports would fail.
76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
import pytest
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from src.mma import Ticket
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from src.dag_engine import TrackDAG
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from src.performance_monitor import get_monitor
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def test_dag_performance():
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perf = get_monitor()
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perf.enabled = True
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num_tickets = 500
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tickets = []
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# Create a complex DAG: linear dependencies + branching
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for i in range(num_tickets):
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deps = []
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if i > 0:
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# Linear dependency
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deps.append(f"ticket_{i-1}")
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if i > 10:
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# Branching dependency (binary tree-ish)
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deps.append(f"ticket_{i//2}")
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if i > 50:
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# More cross-links
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deps.append(f"ticket_{i-10}")
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tickets.append(Ticket(
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id=f"ticket_{i}",
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description=f"Ticket number {i}",
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depends_on=deps,
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status="todo"
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))
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dag = TrackDAG(tickets[::-1])
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# 1. Measure has_cycle()
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cycle_found = dag.has_cycle()
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assert cycle_found is False
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# 2. Measure topological_sort()
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sorted_ids = dag.topological_sort()
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assert len(sorted_ids) == num_tickets
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# 3. Measure cascade_blocks()
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tickets[0].status = "blocked"
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dag.cascade_blocks()
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# Verify all are blocked
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for t in tickets:
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assert t.status == "blocked", f"Ticket {t.id} failed to cascade block"
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# 4. Verify metrics were recorded
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metrics = perf.get_metrics()
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assert "time_dag_has_cycle_ms" in metrics
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assert "time_dag_topological_sort_ms" in metrics
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assert "time_dag_cascade_blocks_ms" in metrics
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# Output results for visibility when running with -s
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print(f"\n[PERF] DAG Performance (n={num_tickets}):")
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print(f" has_cycle: {metrics['time_dag_has_cycle_ms']:.4f} ms")
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print(f" topological_sort: {metrics['time_dag_topological_sort_ms']:.4f} ms")
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print(f" cascade_blocks: {metrics['time_dag_cascade_blocks_ms']:.4f} ms")
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def test_dag_edge_cases():
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# Test cycle detection correctness
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t1 = Ticket(id="a", description="a", depends_on=["b"])
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t2 = Ticket(id="b", description="b", depends_on=["c"])
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t3 = Ticket(id="c", description="c", depends_on=["a"])
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dag = TrackDAG([t1, t2, t3])
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assert dag.has_cycle() is True
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with pytest.raises(ValueError, match="Dependency cycle detected"):
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dag.topological_sort()
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# Test empty DAG
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dag_empty = TrackDAG([])
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assert dag_empty.has_cycle() is False
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assert dag_empty.topological_sort() == []
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