performance.py•4.07 kB
# src/models/performance.py
from __future__ import annotations
from pydantic import BaseModel, Field, field_validator
from pydantic_core.core_schema import ValidationInfo
from typing import Literal
from datetime import datetime
from decimal import Decimal
class PerformanceBenchmarkResult(BaseModel):
"""
Performance benchmark result for regression detection.
Constitutional Compliance:
- Principle VIII: Pydantic-based type safety with validators
- Principle IV: Validates performance against constitutional targets
"""
# Identification
benchmark_id: str = Field(
description="Unique identifier for this benchmark run (UUID)"
)
server_id: Literal["codebase-mcp", "workflow-mcp"] = Field(
description="Server identifier"
)
operation_type: Literal["index", "search", "project_switch", "entity_query"] = Field(
description="Operation being benchmarked"
)
# Timing
timestamp: datetime = Field(
description="Benchmark execution timestamp (ISO 8601)"
)
# Latency Metrics (in milliseconds)
latency_p50_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="50th percentile latency in milliseconds"
)
latency_p95_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="95th percentile latency in milliseconds"
)
latency_p99_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="99th percentile latency in milliseconds"
)
latency_mean_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="Mean latency in milliseconds"
)
latency_min_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="Minimum latency in milliseconds"
)
latency_max_ms: Decimal = Field(
ge=0,
decimal_places=2,
description="Maximum latency in milliseconds"
)
# Test Parameters
sample_size: int = Field(
ge=1,
description="Number of iterations in the benchmark"
)
test_parameters: dict[str, str | int | float] = Field(
default_factory=dict,
description="Test-specific parameters (e.g., file_count, query_text)"
)
# Validation
pass_status: Literal["pass", "fail", "warning"] = Field(
description="Pass/fail status against target thresholds"
)
target_threshold_ms: Decimal | None = Field(
default=None,
description="Target threshold for this operation (from constitution)"
)
@field_validator("latency_p95_ms")
@classmethod
def validate_p95_ordering(cls, v: Decimal, info: ValidationInfo) -> Decimal:
"""Validate p95 >= p50."""
if "latency_p50_ms" in info.data and v < info.data["latency_p50_ms"]:
raise ValueError("latency_p95_ms must be >= latency_p50_ms")
return v
@field_validator("latency_p99_ms")
@classmethod
def validate_p99_ordering(cls, v: Decimal, info: ValidationInfo) -> Decimal:
"""Validate p99 >= p95."""
if "latency_p95_ms" in info.data and v < info.data["latency_p95_ms"]:
raise ValueError("latency_p99_ms must be >= latency_p95_ms")
return v
class Config:
json_schema_extra = {
"example": {
"benchmark_id": "550e8400-e29b-41d4-a716-446655440000",
"server_id": "codebase-mcp",
"operation_type": "search",
"timestamp": "2025-10-13T10:30:00Z",
"latency_p50_ms": 245.32,
"latency_p95_ms": 478.91,
"latency_p99_ms": 512.45,
"latency_mean_ms": 268.77,
"latency_min_ms": 198.12,
"latency_max_ms": 543.88,
"sample_size": 100,
"test_parameters": {
"query_text": "authentication logic",
"concurrent_clients": 10
},
"pass_status": "pass",
"target_threshold_ms": 500.0
}
}