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test: improve test coverage from 61% to 84.81%

Browse Source 
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>
This commit is contained in:
Bill Ballou
2025-11-07 21:02:38 -05:00
parent 61baf3f90f
commit 14cf88f642
30 changed files with 1840 additions and 1013 deletions
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309
tests/e2e/test_full_simulation_workflow.py
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@@ -22,7 +22,7 @@ import json
from fastapi.testclient import TestClient
from pathlib import Path
from datetime import datetime
from api.database import Database
from api.database import Database, db_connection
@pytest.fixture
@@ -140,45 +140,44 @@ def _populate_test_price_data(db_path: str):
"2025-01-18": 1.02 # Back to 2% increase
}
conn = get_db_connection(db_path)
cursor = conn.cursor()
with db_connection(db_path) as conn:
cursor = conn.cursor()
for symbol in symbols:
for date in test_dates:
multiplier = price_multipliers[date]
base_price = 100.0
for symbol in symbols:
for date in test_dates:
multiplier = price_multipliers[date]
base_price = 100.0
# Insert mock price data with variations
# Insert mock price data with variations
cursor.execute("""
INSERT OR IGNORE INTO price_data
(symbol, date, open, high, low, close, volume, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
""", (
symbol,
date,
base_price * multiplier, # open
base_price * multiplier * 1.05, # high
base_price * multiplier * 0.98, # low
base_price * multiplier * 1.02, # close
1000000, # volume
datetime.utcnow().isoformat() + "Z"
))
# Add coverage record
cursor.execute("""
INSERT OR IGNORE INTO price_data
(symbol, date, open, high, low, close, volume, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
INSERT OR IGNORE INTO price_data_coverage
(symbol, start_date, end_date, downloaded_at, source)
VALUES (?, ?, ?, ?, ?)
""", (
symbol,
date,
base_price * multiplier, # open
base_price * multiplier * 1.05, # high
base_price * multiplier * 0.98, # low
base_price * multiplier * 1.02, # close
1000000, # volume
datetime.utcnow().isoformat() + "Z"
"2025-01-16",
"2025-01-18",
datetime.utcnow().isoformat() + "Z",
"test_fixture_e2e"
))
# Add coverage record
cursor.execute("""
INSERT OR IGNORE INTO price_data_coverage
(symbol, start_date, end_date, downloaded_at, source)
VALUES (?, ?, ?, ?, ?)
""", (
symbol,
"2025-01-16",
"2025-01-18",
datetime.utcnow().isoformat() + "Z",
"test_fixture_e2e"
))
conn.commit()
conn.close()
conn.commit()
@pytest.mark.e2e
@@ -220,119 +219,118 @@ class TestFullSimulationWorkflow:
populates the trading_days table using Database helper methods and verifies
the Results API works correctly.
"""
from api.database import Database, get_db_connection
from api.database import Database, db_connection, get_db_connection
# Get database instance
db = Database(e2e_client.db_path)
# Create a test job
job_id = "test-job-e2e-123"
conn = get_db_connection(e2e_client.db_path)
cursor = conn.cursor()
with db_connection(e2e_client.db_path) as conn:
cursor = conn.cursor()
cursor.execute("""
INSERT INTO jobs (job_id, config_path, status, date_range, models, created_at)
VALUES (?, ?, ?, ?, ?, ?)
""", (
job_id,
"test_config.json",
"completed",
'["2025-01-16", "2025-01-18"]',
'["test-mock-e2e"]',
datetime.utcnow().isoformat() + "Z"
))
conn.commit()
cursor.execute("""
INSERT INTO jobs (job_id, config_path, status, date_range, models, created_at)
VALUES (?, ?, ?, ?, ?, ?)
""", (
job_id,
"test_config.json",
"completed",
'["2025-01-16", "2025-01-18"]',
'["test-mock-e2e"]',
datetime.utcnow().isoformat() + "Z"
))
conn.commit()
# 1. Create Day 1 trading_day record (first day, zero P&L)
day1_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-16",
starting_cash=10000.0,
starting_portfolio_value=10000.0,
daily_profit=0.0,
daily_return_pct=0.0,
ending_cash=8500.0, # Bought $1500 worth of stock
ending_portfolio_value=10000.0, # 10 shares * $100 + $8500 cash
reasoning_summary="Analyzed market conditions. Bought 10 shares of AAPL at $150.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt for trading..."},
{"role": "assistant", "content": "I will analyze AAPL..."},
{"role": "tool", "name": "get_price", "content": "AAPL price: $150"},
{"role": "assistant", "content": "Buying 10 shares of AAPL..."}
]),
total_actions=1,
session_duration_seconds=45.5,
days_since_last_trading=0
)
# 1. Create Day 1 trading_day record (first day, zero P&L)
day1_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-16",
starting_cash=10000.0,
starting_portfolio_value=10000.0,
daily_profit=0.0,
daily_return_pct=0.0,
ending_cash=8500.0, # Bought $1500 worth of stock
ending_portfolio_value=10000.0, # 10 shares * $100 + $8500 cash
reasoning_summary="Analyzed market conditions. Bought 10 shares of AAPL at $150.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt for trading..."},
{"role": "assistant", "content": "I will analyze AAPL..."},
{"role": "tool", "name": "get_price", "content": "AAPL price: $150"},
{"role": "assistant", "content": "Buying 10 shares of AAPL..."}
]),
total_actions=1,
session_duration_seconds=45.5,
days_since_last_trading=0
)
# Add Day 1 holdings and actions
db.create_holding(day1_id, "AAPL", 10)
db.create_action(day1_id, "buy", "AAPL", 10, 150.0)
# Add Day 1 holdings and actions
db.create_holding(day1_id, "AAPL", 10)
db.create_action(day1_id, "buy", "AAPL", 10, 150.0)
# 2. Create Day 2 trading_day record (with P&L from price change)
# AAPL went from $100 to $105 (5% gain), so portfolio value increased
day2_starting_value = 8500.0 + (10 * 105.0) # Cash + holdings valued at new price = $9550
day2_profit = day2_starting_value - 10000.0 # $9550 - $10000 = -$450 (loss)
day2_return_pct = (day2_profit / 10000.0) * 100 # -4.5%
# 2. Create Day 2 trading_day record (with P&L from price change)
# AAPL went from $100 to $105 (5% gain), so portfolio value increased
day2_starting_value = 8500.0 + (10 * 105.0) # Cash + holdings valued at new price = $9550
day2_profit = day2_starting_value - 10000.0 # $9550 - $10000 = -$450 (loss)
day2_return_pct = (day2_profit / 10000.0) * 100 # -4.5%
day2_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-17",
starting_cash=8500.0,
starting_portfolio_value=day2_starting_value,
daily_profit=day2_profit,
daily_return_pct=day2_return_pct,
ending_cash=7000.0, # Bought more stock
ending_portfolio_value=9500.0,
reasoning_summary="Continued trading. Added 5 shares of MSFT.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt..."},
{"role": "assistant", "content": "I will buy MSFT..."}
]),
total_actions=1,
session_duration_seconds=38.2,
days_since_last_trading=1
)
day2_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-17",
starting_cash=8500.0,
starting_portfolio_value=day2_starting_value,
daily_profit=day2_profit,
daily_return_pct=day2_return_pct,
ending_cash=7000.0, # Bought more stock
ending_portfolio_value=9500.0,
reasoning_summary="Continued trading. Added 5 shares of MSFT.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt..."},
{"role": "assistant", "content": "I will buy MSFT..."}
]),
total_actions=1,
session_duration_seconds=38.2,
days_since_last_trading=1
)
# Add Day 2 holdings and actions
db.create_holding(day2_id, "AAPL", 10)
db.create_holding(day2_id, "MSFT", 5)
db.create_action(day2_id, "buy", "MSFT", 5, 100.0)
# Add Day 2 holdings and actions
db.create_holding(day2_id, "AAPL", 10)
db.create_holding(day2_id, "MSFT", 5)
db.create_action(day2_id, "buy", "MSFT", 5, 100.0)
# 3. Create Day 3 trading_day record
day3_starting_value = 7000.0 + (10 * 102.0) + (5 * 102.0) # Different prices
day3_profit = day3_starting_value - day2_starting_value
day3_return_pct = (day3_profit / day2_starting_value) * 100
# 3. Create Day 3 trading_day record
day3_starting_value = 7000.0 + (10 * 102.0) + (5 * 102.0) # Different prices
day3_profit = day3_starting_value - day2_starting_value
day3_return_pct = (day3_profit / day2_starting_value) * 100
day3_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-18",
starting_cash=7000.0,
starting_portfolio_value=day3_starting_value,
daily_profit=day3_profit,
daily_return_pct=day3_return_pct,
ending_cash=7000.0, # No trades
ending_portfolio_value=day3_starting_value,
reasoning_summary="Held positions. No trades executed.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt..."},
{"role": "assistant", "content": "Holding positions..."}
]),
total_actions=0,
session_duration_seconds=12.1,
days_since_last_trading=1
)
day3_id = db.create_trading_day(
job_id=job_id,
model="test-mock-e2e",
date="2025-01-18",
starting_cash=7000.0,
starting_portfolio_value=day3_starting_value,
daily_profit=day3_profit,
daily_return_pct=day3_return_pct,
ending_cash=7000.0, # No trades
ending_portfolio_value=day3_starting_value,
reasoning_summary="Held positions. No trades executed.",
reasoning_full=json.dumps([
{"role": "user", "content": "System prompt..."},
{"role": "assistant", "content": "Holding positions..."}
]),
total_actions=0,
session_duration_seconds=12.1,
days_since_last_trading=1
)
# Add Day 3 holdings (no actions, just holding)
db.create_holding(day3_id, "AAPL", 10)
db.create_holding(day3_id, "MSFT", 5)
# Add Day 3 holdings (no actions, just holding)
db.create_holding(day3_id, "AAPL", 10)
db.create_holding(day3_id, "MSFT", 5)
# Ensure all data is committed
db.connection.commit()
conn.close()
# Ensure all data is committed
db.connection.commit()
# 4. Query each day individually to get detailed format
# Query Day 1
@@ -450,39 +448,38 @@ class TestFullSimulationWorkflow:
# 10. Verify database structure directly
from api.database import get_db_connection
conn = get_db_connection(e2e_client.db_path)
cursor = conn.cursor()
with db_connection(e2e_client.db_path) as conn:
cursor = conn.cursor()
# Check trading_days table
cursor.execute("""
SELECT COUNT(*) FROM trading_days
WHERE job_id = ? AND model = ?
""", (job_id, "test-mock-e2e"))
# Check trading_days table
cursor.execute("""
SELECT COUNT(*) FROM trading_days
WHERE job_id = ? AND model = ?
""", (job_id, "test-mock-e2e"))
count = cursor.fetchone()[0]
assert count == 3, f"Expected 3 trading_days records, got {count}"
count = cursor.fetchone()[0]
assert count == 3, f"Expected 3 trading_days records, got {count}"
# Check holdings table
cursor.execute("""
SELECT COUNT(*) FROM holdings h
JOIN trading_days td ON h.trading_day_id = td.id
WHERE td.job_id = ? AND td.model = ?
""", (job_id, "test-mock-e2e"))
# Check holdings table
cursor.execute("""
SELECT COUNT(*) FROM holdings h
JOIN trading_days td ON h.trading_day_id = td.id
WHERE td.job_id = ? AND td.model = ?
""", (job_id, "test-mock-e2e"))
holdings_count = cursor.fetchone()[0]
assert holdings_count > 0, "Expected some holdings records"
holdings_count = cursor.fetchone()[0]
assert holdings_count > 0, "Expected some holdings records"
# Check actions table
cursor.execute("""
SELECT COUNT(*) FROM actions a
JOIN trading_days td ON a.trading_day_id = td.id
WHERE td.job_id = ? AND td.model = ?
""", (job_id, "test-mock-e2e"))
# Check actions table
cursor.execute("""
SELECT COUNT(*) FROM actions a
JOIN trading_days td ON a.trading_day_id = td.id
WHERE td.job_id = ? AND td.model = ?
""", (job_id, "test-mock-e2e"))
actions_count = cursor.fetchone()[0]
assert actions_count > 0, "Expected some action records"
actions_count = cursor.fetchone()[0]
assert actions_count > 0, "Expected some action records"
conn.close()
# The main test above verifies:
# - Results API filtering (by job_id)