Initial project structure

tests/conftest.py

@@ -0,0 +1,183 @@
+"""Shared test fixtures."""
+
+from __future__ import annotations
+
+from datetime import datetime, timezone
+from uuid import UUID, uuid4
+
+import pytest
+
+from mosaicstack_telemetry.config import TelemetryConfig
+from mosaicstack_telemetry.types.events import (
+    Complexity,
+    Harness,
+    Outcome,
+    Provider,
+    TaskCompletionEvent,
+    TaskType,
+)
+from mosaicstack_telemetry.types.predictions import (
+    CorrectionFactors,
+    PredictionData,
+    PredictionMetadata,
+    PredictionQuery,
+    PredictionResponse,
+    QualityPrediction,
+    TokenDistribution,
+)
+
+TEST_API_KEY = "a" * 64
+TEST_INSTANCE_ID = "12345678-1234-1234-1234-123456789abc"
+TEST_SERVER_URL = "https://telemetry.example.com"
+
+
+@pytest.fixture()
+def config() -> TelemetryConfig:
+    """Create a valid test configuration."""
+    return TelemetryConfig(
+        server_url=TEST_SERVER_URL,
+        api_key=TEST_API_KEY,
+        instance_id=TEST_INSTANCE_ID,
+        submit_interval_seconds=1.0,
+        max_queue_size=100,
+        batch_size=10,
+        request_timeout_seconds=5.0,
+        max_retries=1,
+    )
+
+
+@pytest.fixture()
+def dry_run_config() -> TelemetryConfig:
+    """Create a test configuration with dry_run enabled."""
+    return TelemetryConfig(
+        server_url=TEST_SERVER_URL,
+        api_key=TEST_API_KEY,
+        instance_id=TEST_INSTANCE_ID,
+        submit_interval_seconds=1.0,
+        max_queue_size=100,
+        batch_size=10,
+        request_timeout_seconds=5.0,
+        dry_run=True,
+        max_retries=1,
+    )
+
+
+@pytest.fixture()
+def disabled_config() -> TelemetryConfig:
+    """Create a disabled test configuration."""
+    return TelemetryConfig(
+        server_url=TEST_SERVER_URL,
+        api_key=TEST_API_KEY,
+        instance_id=TEST_INSTANCE_ID,
+        enabled=False,
+    )
+
+
+@pytest.fixture()
+def sample_instance_id() -> UUID:
+    """Return a fixed instance UUID for testing."""
+    return UUID(TEST_INSTANCE_ID)
+
+
+@pytest.fixture()
+def sample_event(sample_instance_id: UUID) -> TaskCompletionEvent:
+    """Create a sample task completion event."""
+    return TaskCompletionEvent(
+        instance_id=sample_instance_id,
+        event_id=uuid4(),
+        timestamp=datetime.now(timezone.utc),
+        task_duration_ms=30000,
+        task_type=TaskType.IMPLEMENTATION,
+        complexity=Complexity.MEDIUM,
+        harness=Harness.CLAUDE_CODE,
+        model="claude-sonnet-4-20250514",
+        provider=Provider.ANTHROPIC,
+        estimated_input_tokens=5000,
+        estimated_output_tokens=2000,
+        actual_input_tokens=5200,
+        actual_output_tokens=1800,
+        estimated_cost_usd_micros=10000,
+        actual_cost_usd_micros=9500,
+        quality_gate_passed=True,
+        quality_gates_run=[],
+        quality_gates_failed=[],
+        context_compactions=0,
+        context_rotations=0,
+        context_utilization_final=0.4,
+        outcome=Outcome.SUCCESS,
+        retry_count=0,
+        language="python",
+        repo_size_category=None,
+    )
+
+
+def make_event(instance_id: UUID | None = None) -> TaskCompletionEvent:
+    """Factory helper to create a sample event with optional overrides."""
+    return TaskCompletionEvent(
+        instance_id=instance_id or UUID(TEST_INSTANCE_ID),
+        event_id=uuid4(),
+        timestamp=datetime.now(timezone.utc),
+        task_duration_ms=15000,
+        task_type=TaskType.DEBUGGING,
+        complexity=Complexity.LOW,
+        harness=Harness.AIDER,
+        model="gpt-4o",
+        provider=Provider.OPENAI,
+        estimated_input_tokens=1000,
+        estimated_output_tokens=500,
+        actual_input_tokens=1100,
+        actual_output_tokens=480,
+        estimated_cost_usd_micros=3000,
+        actual_cost_usd_micros=2800,
+        quality_gate_passed=True,
+        quality_gates_run=[],
+        quality_gates_failed=[],
+        context_compactions=0,
+        context_rotations=0,
+        context_utilization_final=0.2,
+        outcome=Outcome.SUCCESS,
+        retry_count=0,
+    )
+
+
+@pytest.fixture()
+def sample_prediction_query() -> PredictionQuery:
+    """Create a sample prediction query."""
+    return PredictionQuery(
+        task_type=TaskType.IMPLEMENTATION,
+        model="claude-sonnet-4-20250514",
+        provider=Provider.ANTHROPIC,
+        complexity=Complexity.MEDIUM,
+    )
+
+
+@pytest.fixture()
+def sample_prediction_response() -> PredictionResponse:
+    """Create a sample prediction response."""
+    return PredictionResponse(
+        prediction=PredictionData(
+            input_tokens=TokenDistribution(p10=1000, p25=2000, median=3000, p75=4000, p90=5000),
+            output_tokens=TokenDistribution(p10=500, p25=1000, median=1500, p75=2000, p90=2500),
+            cost_usd_micros={"p10": 1000, "median": 3000, "p90": 5000},
+            duration_ms={"p10": 10000, "median": 30000, "p90": 60000},
+            correction_factors=CorrectionFactors(input=1.05, output=0.95),
+            quality=QualityPrediction(gate_pass_rate=0.85, success_rate=0.9),
+        ),
+        metadata=PredictionMetadata(
+            sample_size=150,
+            fallback_level=0,
+            confidence="high",
+        ),
+    )
+
+
+def make_batch_response_json(events: list[TaskCompletionEvent]) -> dict:
+    """Create a batch response JSON dict for a list of events (all accepted)."""
+    return {
+        "accepted": len(events),
+        "rejected": 0,
+        "results": [
+            {"event_id": str(e.event_id), "status": "accepted", "error": None}
+            for e in events
+        ],
+    }