mirror of
https://github.com/Xe138/AI-Trader.git
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Bill
14cf88f642
Major improvements: - Fixed all 42 broken tests (database connection leaks) - Added db_connection() context manager for proper cleanup - Created comprehensive test suites for undertested modules New test coverage: - tools/general_tools.py: 26 tests (97% coverage) - tools/price_tools.py: 11 tests (validates NASDAQ symbols, date handling) - api/price_data_manager.py: 12 tests (85% coverage) - api/routes/results_v2.py: 3 tests (98% coverage) - agent/reasoning_summarizer.py: 2 tests (87% coverage) - api/routes/period_metrics.py: 2 edge case tests (100% coverage) - agent/mock_provider: 1 test (100% coverage) Database fixes: - Added db_connection() context manager to prevent leaks - Updated 16+ test files to use context managers - Fixed drop_all_tables() to match new schema - Added CHECK constraint for action_type - Added ON DELETE CASCADE to trading_days foreign key Test improvements: - Updated SQL INSERT statements with all required fields - Fixed date parameter handling in API integration tests - Added edge case tests for validation functions - Fixed import errors across test suite Results: - Total coverage: 84.81% (was 61%) - Tests passing: 406 (was 364 with 42 failures) - Total lines covered: 6364 of 7504 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
"""Tests for period metrics calculations."""
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from datetime import datetime
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from api.routes.period_metrics import calculate_period_metrics
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def test_calculate_period_metrics_basic():
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"""Test basic period metrics calculation."""
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metrics = calculate_period_metrics(
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starting_value=10000.0,
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ending_value=10500.0,
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start_date="2025-01-16",
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end_date="2025-01-20",
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trading_days=3
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)
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assert metrics["starting_portfolio_value"] == 10000.0
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assert metrics["ending_portfolio_value"] == 10500.0
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assert metrics["period_return_pct"] == 5.0
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assert metrics["calendar_days"] == 5
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assert metrics["trading_days"] == 3
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# annualized_return = ((10500/10000) ** (365/5) - 1) * 100 = ~3422%
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assert 3400 < metrics["annualized_return_pct"] < 3450
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def test_calculate_period_metrics_zero_return():
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"""Test period metrics when no change."""
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metrics = calculate_period_metrics(
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starting_value=10000.0,
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ending_value=10000.0,
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start_date="2025-01-16",
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end_date="2025-01-16",
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trading_days=1
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)
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assert metrics["period_return_pct"] == 0.0
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assert metrics["annualized_return_pct"] == 0.0
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assert metrics["calendar_days"] == 1
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def test_calculate_period_metrics_negative_return():
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"""Test period metrics with loss."""
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metrics = calculate_period_metrics(
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starting_value=10000.0,
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ending_value=9500.0,
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start_date="2025-01-16",
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end_date="2025-01-23",
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trading_days=5
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)
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assert metrics["period_return_pct"] == -5.0
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assert metrics["calendar_days"] == 8
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# Negative annualized return
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assert metrics["annualized_return_pct"] < 0
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def test_calculate_period_metrics_zero_starting_value():
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"""Test period metrics when starting value is zero (edge case)."""
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metrics = calculate_period_metrics(
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starting_value=0.0,
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ending_value=1000.0,
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start_date="2025-01-16",
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end_date="2025-01-20",
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trading_days=3
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)
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# Should handle division by zero gracefully
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assert metrics["period_return_pct"] == 0.0
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assert metrics["annualized_return_pct"] == 0.0
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def test_calculate_period_metrics_negative_ending_value():
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"""Test period metrics when ending value is negative (edge case)."""
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metrics = calculate_period_metrics(
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starting_value=10000.0,
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ending_value=-100.0,
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start_date="2025-01-16",
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end_date="2025-01-20",
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trading_days=3
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)
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# Should handle negative ending value gracefully
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assert metrics["annualized_return_pct"] == 0.0
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