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#!/usr/bin/env python3
"""
Comprehensive analytics testing module for FRED ML
Consolidates functionality from multiple test files into enterprise-grade test suite
"""
import sys
import os
import pytest
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
# Add project root to path
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../..')))
class TestAnalyticsImports:
"""Test analytics module imports and basic functionality"""
def test_imports(self):
"""Test if all required modules can be imported"""
try:
from src.core.enhanced_fred_client import EnhancedFREDClient
from src.analysis.comprehensive_analytics import ComprehensiveAnalytics
from src.analysis.economic_forecasting import EconomicForecaster
from src.analysis.economic_segmentation import EconomicSegmentation
from src.analysis.statistical_modeling import StatisticalModeling
assert True
except ImportError as e:
pytest.fail(f"Import test failed: {e}")
def test_fred_client_structure(self):
"""Test FRED client functionality"""
try:
from src.core.enhanced_fred_client import EnhancedFREDClient
client = EnhancedFREDClient("test_key")
# Test basic functionality - check for the correct method names
assert hasattr(client, 'fetch_economic_data')
assert hasattr(client, 'fetch_quarterly_data')
except Exception as e:
pytest.fail(f"FRED Client test failed: {e}")
def test_analytics_structure(self):
"""Test analytics module structure"""
try:
from src.analysis.comprehensive_analytics import ComprehensiveAnalytics
analytics = ComprehensiveAnalytics("test_key")
required_methods = [
'run_complete_analysis',
'_run_statistical_analysis',
'_run_forecasting_analysis',
'_run_segmentation_analysis',
'_extract_insights'
]
for method in required_methods:
assert hasattr(analytics, method), f"Missing method: {method}"
except Exception as e:
pytest.fail(f"Analytics structure test failed: {e}")
class TestMathematicalFixes:
"""Test mathematical fixes and data processing"""
def setup_method(self):
"""Set up test data"""
self.dates = pd.date_range('2020-01-01', periods=100, freq='ME')
self.test_data = pd.DataFrame({
'GDPC1': np.random.normal(22000, 1000, 100), # Billions
'INDPRO': np.random.normal(100, 5, 100), # Index
'CPIAUCSL': np.random.normal(250, 10, 100), # Index
'FEDFUNDS': np.random.normal(2, 0.5, 100), # Percent
'PAYEMS': np.random.normal(150000, 5000, 100) # Thousands
}, index=self.dates)
def test_mathematical_fixes_import(self):
"""Test mathematical fixes module import"""
try:
from src.analysis.mathematical_fixes import MathematicalFixes
fixes = MathematicalFixes()
assert fixes is not None
except ImportError as e:
pytest.fail(f"Mathematical fixes import failed: {e}")
def test_unit_normalization(self):
"""Test unit normalization functionality"""
try:
from src.analysis.mathematical_fixes import MathematicalFixes
fixes = MathematicalFixes()
normalized_data = fixes.normalize_units(self.test_data)
assert normalized_data.shape == self.test_data.shape
assert not normalized_data.isnull().all().all()
except Exception as e:
pytest.fail(f"Unit normalization test failed: {e}")
def test_frequency_alignment(self):
"""Test frequency alignment functionality"""
try:
from src.analysis.mathematical_fixes import MathematicalFixes
fixes = MathematicalFixes()
aligned_data = fixes.align_frequencies(self.test_data, target_freq='QE')
# The aligned data might be longer due to interpolation
assert len(aligned_data) > 0
assert not aligned_data.isnull().all().all()
except Exception as e:
pytest.fail(f"Frequency alignment test failed: {e}")
def test_growth_rate_calculation(self):
"""Test growth rate calculation"""
try:
from src.analysis.mathematical_fixes import MathematicalFixes
fixes = MathematicalFixes()
growth_data = fixes.calculate_growth_rates(self.test_data, method='pct_change')
assert growth_data.shape == self.test_data.shape
# Growth rates should have some NaN values (first row)
assert growth_data.isnull().sum().sum() > 0
except Exception as e:
pytest.fail(f"Growth rate calculation test failed: {e}")
def test_comprehensive_fixes(self):
"""Test comprehensive fixes application"""
try:
from src.analysis.mathematical_fixes import MathematicalFixes
fixes = MathematicalFixes()
fixed_data, fix_info = fixes.apply_comprehensive_fixes(
self.test_data,
target_freq='QE',
growth_method='pct_change',
normalize_units=True
)
assert fixed_data is not None
assert isinstance(fix_info, dict)
# Check for any of the expected keys in fix_info
expected_keys = ['fixes_applied', 'frequency_alignment', 'growth_calculation', 'unit_normalization']
assert any(key in fix_info for key in expected_keys)
except Exception as e:
pytest.fail(f"Comprehensive fixes test failed: {e}")
class TestConfiguration:
"""Test configuration and environment setup"""
def test_config_loading(self):
"""Test configuration loading"""
try:
# Test if config can be loaded
import os
fred_key = os.getenv('FRED_API_KEY', 'test_key')
assert fred_key is not None
assert len(fred_key) > 0
except Exception as e:
pytest.fail(f"Configuration test failed: {e}")
def test_config_import(self):
"""Test config.settings import"""
try:
from config.settings import Config
assert Config is not None
except ImportError:
# Config import might fail in test environment, which is OK
pass
class TestAppFunctionality:
"""Test application functionality and health checks"""
def test_app_health_check(self):
"""Test app health check functionality"""
# This would test the actual app if running
# For now, just test the function exists
def mock_health_check():
return True
assert mock_health_check() is True
def test_fred_api_integration(self):
"""Test FRED API integration"""
try:
import requests
# Test with a mock API call
api_key = "test_key"
test_url = f"https://api.stlouisfed.org/fred/series?series_id=GDP&api_key={api_key}&file_type=json"
# This would fail with test key, but we're testing the structure
assert "api.stlouisfed.org" in test_url
assert "GDP" in test_url
except Exception as e:
pytest.fail(f"FRED API integration test failed: {e}")
class TestDataValidation:
"""Test data validation and quality checks"""
def test_data_structure_validation(self):
"""Test data structure validation"""
test_data = pd.DataFrame({
'GDPC1': [22000, 22100, 22200],
'INDPRO': [100, 101, 102],
'CPIAUCSL': [250, 251, 252]
})
# Basic validation
assert not test_data.empty
assert len(test_data.columns) > 0
assert len(test_data) > 0
assert not test_data.isnull().all().all()
def test_data_type_validation(self):
"""Test data type validation"""
test_data = pd.DataFrame({
'GDPC1': [22000, 22100, 22200],
'INDPRO': [100, 101, 102],
'CPIAUCSL': [250, 251, 252]
})
# Check numeric types
for col in test_data.columns:
assert pd.api.types.is_numeric_dtype(test_data[col])
if __name__ == "__main__":
pytest.main([__file__]) |