7bb2905cca
- Change SQLite database path from `/home/oib/windsurf/aitbc/data/` to `/opt/data/` - Fix foreign key references to use correct table names (users, wallets, gpu_registry) - Replace governance router with new governance and community routers - Add multi-modal RL router to main application - Simplify DEPLOYMENT_READINESS_REPORT.md to focus on production deployment status - Update governance router with decentralized DAO voting
746 lines
26 KiB
Python
746 lines
26 KiB
Python
"""
|
|
Marketplace Analytics System Integration Tests
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|
Comprehensive testing for analytics, insights, reporting, and dashboards
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|
"""
|
|
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|
import pytest
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|
import asyncio
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|
from datetime import datetime, timedelta
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|
from uuid import uuid4
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|
from typing import Dict, Any
|
|
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|
from sqlmodel import Session, select
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|
from sqlalchemy.exc import SQLAlchemyError
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|
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|
from apps.coordinator_api.src.app.services.analytics_service import (
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|
MarketplaceAnalytics, DataCollector, AnalyticsEngine, DashboardManager
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|
)
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from apps.coordinator_api.src.app.domain.analytics import (
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|
MarketMetric, MarketInsight, AnalyticsReport, DashboardConfig,
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|
AnalyticsPeriod, MetricType, InsightType, ReportType
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|
)
|
|
|
|
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|
class TestDataCollector:
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|
"""Test data collection functionality"""
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|
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|
@pytest.fixture
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|
def data_collector(self):
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|
return DataCollector()
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|
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|
def test_collect_transaction_volume(self, data_collector):
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"""Test transaction volume collection"""
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|
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|
session = MockSession()
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|
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|
# Test daily collection
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start_time = datetime.utcnow() - timedelta(days=1)
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end_time = datetime.utcnow()
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|
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|
volume_metric = asyncio.run(
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data_collector.collect_transaction_volume(
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session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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|
)
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|
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|
# Verify metric structure
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|
assert volume_metric is not None
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|
assert volume_metric.metric_name == "transaction_volume"
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assert volume_metric.metric_type == MetricType.VOLUME
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assert volume_metric.period_type == AnalyticsPeriod.DAILY
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assert volume_metric.unit == "AITBC"
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assert volume_metric.category == "financial"
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assert volume_metric.value > 0
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assert "by_trade_type" in volume_metric.breakdown
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|
assert "by_region" in volume_metric.breakdown
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|
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|
# Verify change percentage calculation
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|
assert volume_metric.change_percentage is not None
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|
assert volume_metric.previous_value is not None
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|
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|
def test_collect_active_agents(self, data_collector):
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"""Test active agents collection"""
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|
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|
session = MockSession()
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|
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start_time = datetime.utcnow() - timedelta(days=1)
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end_time = datetime.utcnow()
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|
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|
agents_metric = asyncio.run(
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data_collector.collect_active_agents(
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session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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|
)
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|
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|
# Verify metric structure
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|
assert agents_metric is not None
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|
assert agents_metric.metric_name == "active_agents"
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|
assert agents_metric.metric_type == MetricType.COUNT
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|
assert agents_metric.unit == "agents"
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assert agents_metric.category == "agents"
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assert agents_metric.value > 0
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assert "by_role" in agents_metric.breakdown
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assert "by_tier" in agents_metric.breakdown
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assert "by_region" in agents_metric.breakdown
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|
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def test_collect_average_prices(self, data_collector):
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"""Test average price collection"""
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|
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session = MockSession()
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|
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start_time = datetime.utcnow() - timedelta(days=1)
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end_time = datetime.utcnow()
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|
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|
price_metric = asyncio.run(
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data_collector.collect_average_prices(
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session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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)
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|
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|
# Verify metric structure
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assert price_metric is not None
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|
assert price_metric.metric_name == "average_price"
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assert price_metric.metric_type == MetricType.AVERAGE
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assert price_metric.unit == "AITBC"
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assert price_metric.category == "pricing"
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assert price_metric.value > 0
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assert "by_trade_type" in price_metric.breakdown
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|
assert "by_tier" in price_metric.breakdown
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|
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|
def test_collect_success_rates(self, data_collector):
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|
"""Test success rate collection"""
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|
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|
session = MockSession()
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|
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|
start_time = datetime.utcnow() - timedelta(days=1)
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|
end_time = datetime.utcnow()
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|
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|
success_metric = asyncio.run(
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data_collector.collect_success_rates(
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session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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|
)
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|
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|
# Verify metric structure
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|
assert success_metric is not None
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|
assert success_metric.metric_name == "success_rate"
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assert success_metric.metric_type == MetricType.PERCENTAGE
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assert success_metric.unit == "%"
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assert success_metric.category == "performance"
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assert 70.0 <= success_metric.value <= 95.0 # Clamped range
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assert "by_trade_type" in success_metric.breakdown
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assert "by_tier" in success_metric.breakdown
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|
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|
def test_collect_supply_demand_ratio(self, data_collector):
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"""Test supply/demand ratio collection"""
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|
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|
session = MockSession()
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|
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|
start_time = datetime.utcnow() - timedelta(days=1)
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|
end_time = datetime.utcnow()
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|
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|
ratio_metric = asyncio.run(
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data_collector.collect_supply_demand_ratio(
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|
session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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|
)
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|
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|
# Verify metric structure
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|
assert ratio_metric is not None
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|
assert ratio_metric.metric_name == "supply_demand_ratio"
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assert ratio_metric.metric_type == MetricType.RATIO
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assert ratio_metric.unit == "ratio"
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assert ratio_metric.category == "market"
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assert 0.5 <= ratio_metric.value <= 2.0 # Clamped range
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assert "by_trade_type" in ratio_metric.breakdown
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assert "by_region" in ratio_metric.breakdown
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|
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|
def test_collect_market_metrics_batch(self, data_collector):
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"""Test batch collection of all market metrics"""
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|
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|
session = MockSession()
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|
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|
start_time = datetime.utcnow() - timedelta(days=1)
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end_time = datetime.utcnow()
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metrics = asyncio.run(
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data_collector.collect_market_metrics(
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session, AnalyticsPeriod.DAILY, start_time, end_time
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|
)
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)
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|
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# Verify all metrics were collected
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assert len(metrics) == 5 # Should collect 5 metrics
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metric_names = [m.metric_name for m in metrics]
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expected_names = [
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"transaction_volume", "active_agents", "average_price",
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"success_rate", "supply_demand_ratio"
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]
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for name in expected_names:
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assert name in metric_names
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def test_different_periods(self, data_collector):
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"""Test collection for different time periods"""
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session = MockSession()
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periods = [AnalyticsPeriod.HOURLY, AnalyticsPeriod.DAILY, AnalyticsPeriod.WEEKLY, AnalyticsPeriod.MONTHLY]
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for period in periods:
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if period == AnalyticsPeriod.HOURLY:
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start_time = datetime.utcnow() - timedelta(hours=1)
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end_time = datetime.utcnow()
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elif period == AnalyticsPeriod.WEEKLY:
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start_time = datetime.utcnow() - timedelta(weeks=1)
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end_time = datetime.utcnow()
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elif period == AnalyticsPeriod.MONTHLY:
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start_time = datetime.utcnow() - timedelta(days=30)
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end_time = datetime.utcnow()
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else:
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start_time = datetime.utcnow() - timedelta(days=1)
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end_time = datetime.utcnow()
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metrics = asyncio.run(
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data_collector.collect_market_metrics(
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session, period, start_time, end_time
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)
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)
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|
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|
# Verify metrics were collected for each period
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assert len(metrics) > 0
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for metric in metrics:
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assert metric.period_type == period
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|
|
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class TestAnalyticsEngine:
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|
"""Test analytics engine functionality"""
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|
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|
@pytest.fixture
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|
def analytics_engine(self):
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|
return AnalyticsEngine()
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|
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|
@pytest.fixture
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|
def sample_metrics(self):
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|
"""Create sample metrics for testing"""
|
|
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|
return [
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MarketMetric(
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|
metric_name="transaction_volume",
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metric_type=MetricType.VOLUME,
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|
period_type=AnalyticsPeriod.DAILY,
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|
value=1200.0,
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previous_value=1000.0,
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|
change_percentage=20.0,
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unit="AITBC",
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category="financial",
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|
recorded_at=datetime.utcnow(),
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|
period_start=datetime.utcnow() - timedelta(days=1),
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|
period_end=datetime.utcnow()
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),
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MarketMetric(
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|
metric_name="success_rate",
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metric_type=MetricType.PERCENTAGE,
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|
period_type=AnalyticsPeriod.DAILY,
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|
value=85.0,
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|
previous_value=90.0,
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change_percentage=-5.56,
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|
unit="%",
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category="performance",
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|
recorded_at=datetime.utcnow(),
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period_start=datetime.utcnow() - timedelta(days=1),
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|
period_end=datetime.utcnow()
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),
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|
MarketMetric(
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|
metric_name="active_agents",
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|
metric_type=MetricType.COUNT,
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|
period_type=AnalyticsPeriod.DAILY,
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|
value=180.0,
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|
previous_value=150.0,
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|
change_percentage=20.0,
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|
unit="agents",
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|
category="agents",
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|
recorded_at=datetime.utcnow(),
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|
period_start=datetime.utcnow() - timedelta(days=1),
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|
period_end=datetime.utcnow()
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)
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|
]
|
|
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|
def test_analyze_trends(self, analytics_engine, sample_metrics):
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|
"""Test trend analysis"""
|
|
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|
session = MockSession()
|
|
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|
insights = asyncio.run(
|
|
analytics_engine.analyze_trends(sample_metrics, session)
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|
)
|
|
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|
# Verify insights were generated
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|
assert len(insights) > 0
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|
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|
# Check for significant changes
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|
significant_insights = [i for i in insights if abs(i.insight_data.get("change_percentage", 0)) >= 5.0]
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|
assert len(significant_insights) > 0
|
|
|
|
# Verify insight structure
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|
for insight in insights:
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|
assert insight.insight_type == InsightType.TREND
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|
assert insight.title is not None
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|
assert insight.description is not None
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|
assert insight.confidence_score >= 0.7
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assert insight.impact_level in ["low", "medium", "high", "critical"]
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assert insight.related_metrics is not None
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assert insight.recommendations is not None
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|
assert insight.insight_data is not None
|
|
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|
def test_detect_anomalies(self, analytics_engine, sample_metrics):
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|
"""Test anomaly detection"""
|
|
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|
session = MockSession()
|
|
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|
insights = asyncio.run(
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|
analytics_engine.detect_anomalies(sample_metrics, session)
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|
)
|
|
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|
# Verify insights were generated (may be empty for normal data)
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|
for insight in insights:
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|
assert insight.insight_type == InsightType.ANOMALY
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|
assert insight.title is not None
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|
assert insight.description is not None
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|
assert insight.confidence_score >= 0.0
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|
assert insight.insight_data.get("anomaly_type") is not None
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|
assert insight.insight_data.get("deviation_percentage") is not None
|
|
|
|
def test_identify_opportunities(self, analytics_engine, sample_metrics):
|
|
"""Test opportunity identification"""
|
|
|
|
session = MockSession()
|
|
|
|
# Add supply/demand ratio metric for opportunity testing
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|
ratio_metric = MarketMetric(
|
|
metric_name="supply_demand_ratio",
|
|
metric_type=MetricType.RATIO,
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|
period_type=AnalyticsPeriod.DAILY,
|
|
value=0.7, # High demand, low supply
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|
previous_value=1.2,
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|
change_percentage=-41.67,
|
|
unit="ratio",
|
|
category="market",
|
|
recorded_at=datetime.utcnow(),
|
|
period_start=datetime.utcnow() - timedelta(days=1),
|
|
period_end=datetime.utcnow()
|
|
)
|
|
|
|
metrics_with_ratio = sample_metrics + [ratio_metric]
|
|
|
|
insights = asyncio.run(
|
|
analytics_engine.identify_opportunities(metrics_with_ratio, session)
|
|
)
|
|
|
|
# Verify opportunity insights were generated
|
|
opportunity_insights = [i for i in insights if i.insight_type == InsightType.OPPORTUNITY]
|
|
assert len(opportunity_insights) > 0
|
|
|
|
# Verify opportunity structure
|
|
for insight in opportunity_insights:
|
|
assert insight.insight_type == InsightType.OPPORTUNITY
|
|
assert "opportunity_type" in insight.insight_data
|
|
assert "recommended_action" in insight.insight_data
|
|
assert insight.suggested_actions is not None
|
|
|
|
def test_assess_risks(self, analytics_engine, sample_metrics):
|
|
"""Test risk assessment"""
|
|
|
|
session = MockSession()
|
|
|
|
insights = asyncio.run(
|
|
analytics_engine.assess_risks(sample_metrics, session)
|
|
)
|
|
|
|
# Verify risk insights were generated
|
|
risk_insights = [i for i in insights if i.insight_type == InsightType.WARNING]
|
|
|
|
# Check for declining success rate risk
|
|
success_rate_insights = [
|
|
i for i in risk_insights
|
|
if "success_rate" in i.related_metrics and i.insight_data.get("decline_percentage", 0) < -10.0
|
|
]
|
|
|
|
if success_rate_insights:
|
|
assert len(success_rate_insights) > 0
|
|
for insight in success_rate_insights:
|
|
assert insight.impact_level in ["medium", "high", "critical"]
|
|
assert insight.suggested_actions is not None
|
|
|
|
def test_generate_insights_comprehensive(self, analytics_engine, sample_metrics):
|
|
"""Test comprehensive insight generation"""
|
|
|
|
session = MockSession()
|
|
|
|
start_time = datetime.utcnow() - timedelta(days=1)
|
|
end_time = datetime.utcnow()
|
|
|
|
insights = asyncio.run(
|
|
analytics_engine.generate_insights(session, AnalyticsPeriod.DAILY, start_time, end_time)
|
|
)
|
|
|
|
# Verify all insight types were considered
|
|
insight_types = set(i.insight_type for i in insights)
|
|
expected_types = {InsightType.TREND, InsightType.ANOMALY, InsightType.OPPORTUNITY, InsightType.WARNING}
|
|
|
|
# At least trends should be generated
|
|
assert InsightType.TREND in insight_types
|
|
|
|
# Verify insight quality
|
|
for insight in insights:
|
|
assert 0.0 <= insight.confidence_score <= 1.0
|
|
assert insight.impact_level in ["low", "medium", "high", "critical"]
|
|
assert insight.recommendations is not None
|
|
assert len(insight.recommendations) > 0
|
|
|
|
|
|
class TestDashboardManager:
|
|
"""Test dashboard management functionality"""
|
|
|
|
@pytest.fixture
|
|
def dashboard_manager(self):
|
|
return DashboardManager()
|
|
|
|
def test_create_default_dashboard(self, dashboard_manager):
|
|
"""Test default dashboard creation"""
|
|
|
|
session = MockSession()
|
|
|
|
dashboard = asyncio.run(
|
|
dashboard_manager.create_default_dashboard(session, "user_001", "Test Dashboard")
|
|
)
|
|
|
|
# Verify dashboard structure
|
|
assert dashboard.dashboard_id is not None
|
|
assert dashboard.name == "Test Dashboard"
|
|
assert dashboard.dashboard_type == "default"
|
|
assert dashboard.owner_id == "user_001"
|
|
assert dashboard.status == "active"
|
|
assert len(dashboard.widgets) == 4 # Default widgets
|
|
assert len(dashboard.filters) == 2 # Default filters
|
|
assert dashboard.refresh_interval == 300
|
|
assert dashboard.auto_refresh is True
|
|
|
|
# Verify default widgets
|
|
widget_names = [w["type"] for w in dashboard.widgets]
|
|
expected_widgets = ["metric_cards", "line_chart", "map", "insight_list"]
|
|
|
|
for widget in expected_widgets:
|
|
assert widget in widget_names
|
|
|
|
def test_create_executive_dashboard(self, dashboard_manager):
|
|
"""Test executive dashboard creation"""
|
|
|
|
session = MockSession()
|
|
|
|
dashboard = asyncio.run(
|
|
dashboard_manager.create_executive_dashboard(session, "exec_user_001")
|
|
)
|
|
|
|
# Verify executive dashboard structure
|
|
assert dashboard.dashboard_type == "executive"
|
|
assert dashboard.owner_id == "exec_user_001"
|
|
assert dashboard.refresh_interval == 600 # 10 minutes for executive
|
|
assert dashboard.dashboard_settings["theme"] == "executive"
|
|
assert dashboard.dashboard_settings["compact_mode"] is True
|
|
|
|
# Verify executive widgets
|
|
widget_names = [w["type"] for w in dashboard.widgets]
|
|
expected_widgets = ["kpi_cards", "area_chart", "gauge_chart", "leaderboard", "alert_list"]
|
|
|
|
for widget in expected_widgets:
|
|
assert widget in widget_names
|
|
|
|
def test_default_widgets_structure(self, dashboard_manager):
|
|
"""Test default widgets structure"""
|
|
|
|
widgets = dashboard_manager.default_widgets
|
|
|
|
# Verify all required widgets are present
|
|
required_widgets = ["market_overview", "trend_analysis", "geographic_distribution", "recent_insights"]
|
|
assert set(widgets.keys()) == set(required_widgets)
|
|
|
|
# Verify widget structure
|
|
for widget_name, widget_config in widgets.items():
|
|
assert "type" in widget_config
|
|
assert "layout" in widget_config
|
|
assert "x" in widget_config["layout"]
|
|
assert "y" in widget_config["layout"]
|
|
assert "w" in widget_config["layout"]
|
|
assert "h" in widget_config["layout"]
|
|
|
|
|
|
class TestMarketplaceAnalytics:
|
|
"""Test main marketplace analytics service"""
|
|
|
|
@pytest.fixture
|
|
def mock_session(self):
|
|
"""Mock database session"""
|
|
class MockSession:
|
|
def __init__(self):
|
|
self.data = {}
|
|
self.committed = False
|
|
|
|
def exec(self, query):
|
|
# Mock query execution
|
|
if hasattr(query, 'where'):
|
|
return []
|
|
return []
|
|
|
|
def add(self, obj):
|
|
self.data[obj.id if hasattr(obj, 'id') else 'temp'] = obj
|
|
|
|
def commit(self):
|
|
self.committed = True
|
|
|
|
def refresh(self, obj):
|
|
pass
|
|
|
|
return MockSession()
|
|
|
|
@pytest.fixture
|
|
def analytics_service(self, mock_session):
|
|
return MarketplaceAnalytics(mock_session)
|
|
|
|
def test_collect_market_data(self, analytics_service, mock_session):
|
|
"""Test market data collection"""
|
|
|
|
result = asyncio.run(
|
|
analytics_service.collect_market_data(AnalyticsPeriod.DAILY)
|
|
)
|
|
|
|
# Verify result structure
|
|
assert "period_type" in result
|
|
assert "start_time" in result
|
|
assert "end_time" in result
|
|
assert "metrics_collected" in result
|
|
assert "insights_generated" in result
|
|
assert "market_data" in result
|
|
|
|
# Verify market data
|
|
market_data = result["market_data"]
|
|
expected_metrics = ["transaction_volume", "active_agents", "average_price", "success_rate", "supply_demand_ratio"]
|
|
|
|
for metric in expected_metrics:
|
|
assert metric in market_data
|
|
assert isinstance(market_data[metric], (int, float))
|
|
assert market_data[metric] >= 0
|
|
|
|
assert result["metrics_collected"] > 0
|
|
assert result["insights_generated"] > 0
|
|
|
|
def test_generate_insights(self, analytics_service, mock_session):
|
|
"""Test insight generation"""
|
|
|
|
result = asyncio.run(
|
|
analytics_service.generate_insights("daily")
|
|
)
|
|
|
|
# Verify result structure
|
|
assert "period_type" in result
|
|
assert "start_time" in result
|
|
assert "end_time" in result
|
|
assert "total_insights" in result
|
|
assert "insight_groups" in result
|
|
assert "high_impact_insights" in result
|
|
assert "high_confidence_insights" in result
|
|
|
|
# Verify insight groups
|
|
insight_groups = result["insight_groups"]
|
|
assert isinstance(insight_groups, dict)
|
|
|
|
# Should have at least trends
|
|
assert "trend" in insight_groups
|
|
|
|
# Verify insight data structure
|
|
for insight_type, insights in insight_groups.items():
|
|
assert isinstance(insights, list)
|
|
for insight in insights:
|
|
assert "id" in insight
|
|
assert "type" in insight
|
|
assert "title" in insight
|
|
assert "description" in insight
|
|
assert "confidence" in insight
|
|
assert "impact" in insight
|
|
assert "recommendations" in insight
|
|
|
|
def test_create_dashboard(self, analytics_service, mock_session):
|
|
"""Test dashboard creation"""
|
|
|
|
result = asyncio.run(
|
|
analytics_service.create_dashboard("user_001", "default")
|
|
)
|
|
|
|
# Verify result structure
|
|
assert "dashboard_id" in result
|
|
assert "name" in result
|
|
assert "type" in result
|
|
assert "widgets" in result
|
|
assert "refresh_interval" in result
|
|
assert "created_at" in result
|
|
|
|
# Verify dashboard was created
|
|
assert result["type"] == "default"
|
|
assert result["widgets"] > 0
|
|
assert result["refresh_interval"] == 300
|
|
|
|
def test_get_market_overview(self, analytics_service, mock_session):
|
|
"""Test market overview"""
|
|
|
|
overview = asyncio.run(
|
|
analytics_service.get_market_overview()
|
|
)
|
|
|
|
# Verify overview structure
|
|
assert "timestamp" in overview
|
|
assert "period" in overview
|
|
assert "metrics" in overview
|
|
assert "insights" in overview
|
|
assert "alerts" in overview
|
|
assert "summary" in overview
|
|
|
|
# Verify summary data
|
|
summary = overview["summary"]
|
|
assert "total_metrics" in summary
|
|
assert "active_insights" in summary
|
|
assert "active_alerts" in summary
|
|
assert "market_health" in summary
|
|
assert summary["market_health"] in ["healthy", "warning", "critical"]
|
|
|
|
def test_different_periods(self, analytics_service, mock_session):
|
|
"""Test analytics for different time periods"""
|
|
|
|
periods = ["daily", "weekly", "monthly"]
|
|
|
|
for period in periods:
|
|
# Test data collection
|
|
result = asyncio.run(
|
|
analytics_service.collect_market_data(AnalyticsPeriod(period.upper()))
|
|
)
|
|
|
|
assert result["period_type"] == period.upper()
|
|
assert result["metrics_collected"] > 0
|
|
|
|
# Test insight generation
|
|
insights = asyncio.run(
|
|
analytics_service.generate_insights(period)
|
|
)
|
|
|
|
assert insights["period_type"] == period
|
|
assert insights["total_insights"] >= 0
|
|
|
|
|
|
# Mock Session Class
|
|
class MockSession:
|
|
"""Mock database session for testing"""
|
|
|
|
def __init__(self):
|
|
self.data = {}
|
|
self.committed = False
|
|
|
|
def exec(self, query):
|
|
# Mock query execution
|
|
if hasattr(query, 'where'):
|
|
return []
|
|
return []
|
|
|
|
def add(self, obj):
|
|
self.data[obj.id if hasattr(obj, 'id') else 'temp'] = obj
|
|
|
|
def commit(self):
|
|
self.committed = True
|
|
|
|
def refresh(self, obj):
|
|
pass
|
|
|
|
|
|
# Performance Tests
|
|
class TestAnalyticsPerformance:
|
|
"""Performance tests for analytics system"""
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_bulk_metric_collection_performance(self):
|
|
"""Test performance of bulk metric collection"""
|
|
|
|
# Test collecting metrics for multiple periods
|
|
# Should complete within acceptable time limits
|
|
|
|
pass
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_insight_generation_performance(self):
|
|
"""Test insight generation performance"""
|
|
|
|
# Test generating insights with large datasets
|
|
# Should complete within acceptable time limits
|
|
|
|
pass
|
|
|
|
|
|
# Utility Functions
|
|
def create_test_metric(**kwargs) -> Dict[str, Any]:
|
|
"""Create test metric data"""
|
|
|
|
defaults = {
|
|
"metric_name": "test_metric",
|
|
"metric_type": MetricType.VALUE,
|
|
"period_type": AnalyticsPeriod.DAILY,
|
|
"value": 100.0,
|
|
"previous_value": 90.0,
|
|
"change_percentage": 11.11,
|
|
"unit": "units",
|
|
"category": "test",
|
|
"recorded_at": datetime.utcnow(),
|
|
"period_start": datetime.utcnow() - timedelta(days=1),
|
|
"period_end": datetime.utcnow()
|
|
}
|
|
|
|
defaults.update(kwargs)
|
|
return defaults
|
|
|
|
|
|
def create_test_insight(**kwargs) -> Dict[str, Any]:
|
|
"""Create test insight data"""
|
|
|
|
defaults = {
|
|
"insight_type": InsightType.TREND,
|
|
"title": "Test Insight",
|
|
"description": "Test description",
|
|
"confidence_score": 0.8,
|
|
"impact_level": "medium",
|
|
"related_metrics": ["test_metric"],
|
|
"time_horizon": "short_term",
|
|
"recommendations": ["Test recommendation"],
|
|
"insight_data": {"test": "data"}
|
|
}
|
|
|
|
defaults.update(kwargs)
|
|
return defaults
|
|
|
|
|
|
# Test Configuration
|
|
@pytest.fixture(scope="session")
|
|
def test_config():
|
|
"""Test configuration for analytics system tests"""
|
|
|
|
return {
|
|
"test_metric_count": 100,
|
|
"test_insight_count": 50,
|
|
"test_report_count": 20,
|
|
"performance_threshold_ms": 5000,
|
|
"memory_threshold_mb": 200
|
|
}
|
|
|
|
|
|
# Test Markers
|
|
pytest.mark.unit = pytest.mark.unit
|
|
pytest.mark.integration = pytest.mark.integration
|
|
pytest.mark.performance = pytest.mark.performance
|
|
pytest.mark.slow = pytest.mark.slow
|