"""
Tests for finviz service and tools.
"""
import pytest
from unittest.mock import patch, MagicMock
import pandas as pd
class TestFinvizService:
"""Tests for finviz_service.py functions."""
@patch('finvizfinance.quote.finvizfinance')
def test_get_stock_fundamentals_success(self, mock_finviz):
"""Test successful fundamentals fetch."""
from mtdata.services.finviz_service import get_stock_fundamentals
mock_stock = MagicMock()
mock_stock.ticker_fundament.return_value = {
"P/E": "28.5",
"Market Cap": "3.0T",
"EPS (ttm)": "6.05",
}
mock_finviz.return_value = mock_stock
result = get_stock_fundamentals("AAPL")
assert result["success"] is True
assert result["symbol"] == "AAPL"
assert "fundamentals" in result
assert result["fundamentals"]["P/E"] == "28.5"
@patch('finvizfinance.quote.finvizfinance')
def test_get_stock_fundamentals_error(self, mock_finviz):
"""Test fundamentals fetch with error."""
from mtdata.services.finviz_service import get_stock_fundamentals
mock_finviz.side_effect = Exception("Network error")
result = get_stock_fundamentals("INVALID")
assert "error" in result
@patch('finvizfinance.quote.finvizfinance')
def test_get_stock_news_success(self, mock_finviz):
"""Test successful news fetch."""
from mtdata.services.finviz_service import get_stock_news
mock_stock = MagicMock()
mock_df = pd.DataFrame([
{"Title": "News 1", "Link": "http://example.com/1", "Date": "2024-01-01"},
{"Title": "News 2", "Link": "http://example.com/2", "Date": "2024-01-02"},
])
mock_stock.ticker_news.return_value = mock_df
mock_finviz.return_value = mock_stock
result = get_stock_news("AAPL", limit=10)
assert result["success"] is True
assert result["symbol"] == "AAPL"
assert result["count"] == 2
assert len(result["news"]) == 2
@patch('finvizfinance.quote.finvizfinance')
def test_get_stock_insider_trades_success(self, mock_finviz):
"""Test successful insider trades fetch."""
from mtdata.services.finviz_service import get_stock_insider_trades
mock_stock = MagicMock()
mock_df = pd.DataFrame([
{"Owner": "John Doe", "Relationship": "CEO", "Transaction": "Buy"},
])
mock_stock.ticker_inside_trader.return_value = mock_df
mock_finviz.return_value = mock_stock
result = get_stock_insider_trades("AAPL")
assert result["success"] is True
assert result["count"] == 1
@patch('finvizfinance.quote.finvizfinance')
def test_get_stock_ratings_success(self, mock_finviz):
"""Test successful ratings fetch."""
from mtdata.services.finviz_service import get_stock_ratings
mock_stock = MagicMock()
mock_df = pd.DataFrame([
{"Date": "2024-01-01", "Analyst": "Goldman Sachs", "Rating": "Buy"},
])
mock_stock.ticker_outer_ratings.return_value = mock_df
mock_finviz.return_value = mock_stock
result = get_stock_ratings("AAPL")
assert result["success"] is True
assert result["count"] == 1
@patch('finvizfinance.screener.overview.Overview')
def test_screen_stocks_success(self, mock_overview_class):
"""Test successful stock screening."""
from mtdata.services.finviz_service import screen_stocks
mock_screener = MagicMock()
mock_df = pd.DataFrame([
{"Ticker": "AAPL", "Company": "Apple Inc.", "Market Cap": "3.0T"},
{"Ticker": "MSFT", "Company": "Microsoft", "Market Cap": "2.8T"},
])
mock_screener.screener_view.return_value = mock_df
mock_overview_class.return_value = mock_screener
result = screen_stocks(
filters={"Exchange": "NASDAQ", "Sector": "Technology"},
limit=10
)
assert result["success"] is True
assert result["count"] == 2
@patch('finvizfinance.screener.overview.Overview')
def test_screen_stocks_no_results(self, mock_overview_class):
"""Test screening with no results."""
from mtdata.services.finviz_service import screen_stocks
mock_screener = MagicMock()
mock_screener.screener_view.return_value = pd.DataFrame()
mock_overview_class.return_value = mock_screener
result = screen_stocks(filters={"Market Cap": "Mega (>$200bln)"})
assert result["success"] is True
assert result["count"] == 0
@patch('finvizfinance.forex.Forex')
def test_get_forex_performance(self, mock_forex_class):
"""Test forex performance fetch."""
from mtdata.services.finviz_service import get_forex_performance
mock_forex = MagicMock()
mock_df = pd.DataFrame([
{"Ticker": "EUR/USD", "Price": "1.08", "Change": "0.5%"},
])
mock_forex.performance.return_value = mock_df
mock_forex_class.return_value = mock_forex
result = get_forex_performance()
assert result["success"] is True
assert result["market"] == "forex"
@patch('finvizfinance.crypto.Crypto')
def test_get_crypto_performance(self, mock_crypto_class):
"""Test crypto performance fetch."""
from mtdata.services.finviz_service import get_crypto_performance
mock_crypto = MagicMock()
mock_df = pd.DataFrame([
{"Ticker": "BTC", "Price": "45000", "Change": "2.5%"},
])
mock_crypto.performance.return_value = mock_df
mock_crypto_class.return_value = mock_crypto
result = get_crypto_performance()
assert result["success"] is True
assert result["market"] == "crypto"
@patch("finvizfinance.earnings.Earnings")
def test_get_earnings_calendar_success(self, mock_earnings_class):
"""Test earnings calendar fetch."""
from mtdata.services.finviz_service import get_earnings_calendar
mock_earnings = MagicMock()
mock_df = pd.DataFrame(
[
{"Ticker": "AAPL", "Earnings": "2026-01-10", "EPS Est": "2.10"},
{"Ticker": "MSFT", "Earnings": "2026-01-11", "EPS Est": "3.20"},
]
)
mock_earnings.df = mock_df
mock_earnings_class.return_value = mock_earnings
result = get_earnings_calendar(period="This Week", limit=10, page=1)
mock_earnings_class.assert_called_once_with(period="This Week")
assert result["success"] is True
assert result["period"] == "This Week"
assert result["count"] == 2
assert len(result["earnings"]) == 2
@patch("finvizfinance.earnings.Earnings")
def test_get_earnings_calendar_invalid_period(self, mock_earnings_class):
"""Test earnings calendar with invalid period."""
from mtdata.services.finviz_service import get_earnings_calendar
mock_earnings_class.side_effect = ValueError(
"Invalid period 'Bad'. Available period: ['This Week', 'Next Week']"
)
result = get_earnings_calendar(period="Bad")
assert "error" in result
@patch("mtdata.services.finviz_service._fetch_finviz_economic_calendar_items")
def test_get_economic_calendar_success(self, mock_fetch_items):
"""Test economic calendar fetch."""
from mtdata.services.finviz_service import get_economic_calendar
mock_fetch_items.return_value = [
{
"calendarId": 0,
"ticker": "USD",
"event": "Out of range",
"category": "Test",
"date": "2026-01-03T08:30:00",
"actual": "",
"forecast": "",
"previous": "",
"importance": 1,
},
{
"calendarId": 1,
"ticker": "USD",
"event": "Nonfarm Payrolls",
"category": "Employment",
"date": "2026-01-04T08:30:00",
"actual": "",
"forecast": "",
"previous": "",
"importance": 3,
},
{
"calendarId": 2,
"ticker": "USD",
"event": "ISM Services",
"category": "Business",
"date": "2026-01-04T10:00:00",
"actual": "",
"forecast": "",
"previous": "",
"importance": 2,
},
]
result = get_economic_calendar(limit=10, page=1, date_from="2026-01-04", date_to="2026-01-04")
assert result["success"] is True
assert result["source"] == "finviz_api"
assert result["count"] == 2
assert result["total"] == 2
assert len(result["events"]) == 2
assert len(result["items"]) == 2
result_high = get_economic_calendar(
impact="high",
limit=10,
page=1,
date_from="2026-01-04",
date_to="2026-01-05",
)
assert result_high["success"] is True
assert result_high["impact"] == "high"
assert result_high["total"] == 1
assert len(result_high["events"]) == 1
@patch("mtdata.services.finviz_service._fetch_finviz_economic_calendar_items")
def test_get_economic_calendar_invalid_impact(self, mock_fetch_items):
"""Test economic calendar with invalid impact filter."""
from mtdata.services.finviz_service import get_economic_calendar
mock_fetch_items.return_value = []
result = get_economic_calendar(impact="extreme")
assert "error" in result
@patch("mtdata.services.finviz_service._fetch_finviz_economic_calendar_items")
def test_get_economic_calendar_date_from_defaults_to_week(self, mock_fetch_items):
"""If date_from is provided without date_to, default to a 7-day window."""
from mtdata.services.finviz_service import get_economic_calendar
mock_fetch_items.return_value = []
get_economic_calendar(date_from="2026-01-05", limit=10, page=1)
_, kwargs = mock_fetch_items.call_args
assert kwargs["date_from"] == "2026-01-05"
assert kwargs["date_to"] == "2026-01-12"
@patch("mtdata.services.finviz_service._fetch_finviz_economic_calendar_items")
def test_get_economic_calendar_weekend_anchor_shifts_to_monday(self, mock_fetch_items):
"""If date_from is a weekend, shift the API anchor to the next Monday but keep the requested range."""
from mtdata.services.finviz_service import get_economic_calendar
mock_fetch_items.return_value = [
{
"calendarId": 1,
"ticker": "USD",
"event": "Test",
"category": "Test",
"date": "2025-01-06T10:00:00",
"actual": "",
"forecast": "",
"previous": "",
"importance": 2,
},
]
result = get_economic_calendar(date_from="2025-01-05", limit=10, page=1)
assert result["success"] is True
assert result["dateFrom"] == "2025-01-05"
assert result["dateTo"] == "2025-01-12"
_, kwargs = mock_fetch_items.call_args
assert kwargs["date_from"] == "2025-01-06"
@patch("mtdata.services.finviz_service._fetch_finviz_calendar_paged")
def test_get_earnings_calendar_api_success(self, mock_fetch_paged):
"""Test earnings calendar API fetch."""
from mtdata.services.finviz_service import get_earnings_calendar_api
mock_fetch_paged.return_value = {
"items": [{"ticker": "AAPL", "date": "2026-01-05", "eps": "2.10"}],
"page": 1,
"pageSize": 50,
"totalItemsCount": 1,
"totalPages": 1,
}
result = get_earnings_calendar_api(date_from="2026-01-05", date_to="2026-01-12", limit=50, page=1)
assert result["success"] is True
assert result["calendar"] == "earnings"
assert result["dateFrom"] == "2026-01-05"
assert result["dateTo"] == "2026-01-12"
assert result["count"] == 1
assert result["total"] == 1
assert len(result["items"]) == 1
assert len(result["earnings"]) == 1
@patch("mtdata.services.finviz_service._fetch_finviz_calendar_paged")
def test_get_dividends_calendar_api_success(self, mock_fetch_paged):
"""Test dividends calendar API fetch."""
from mtdata.services.finviz_service import get_dividends_calendar_api
mock_fetch_paged.return_value = {
"items": [{"ticker": "MSFT", "exDate": "2026-01-06", "amount": "0.75"}],
"page": 1,
"pageSize": 50,
"totalItemsCount": 1,
"totalPages": 1,
}
result = get_dividends_calendar_api(date_from="2026-01-05", date_to="2026-01-12", limit=50, page=1)
assert result["success"] is True
assert result["calendar"] == "dividends"
assert result["dateFrom"] == "2026-01-05"
assert result["dateTo"] == "2026-01-12"
assert result["count"] == 1
assert result["total"] == 1
assert len(result["items"]) == 1
assert len(result["dividends"]) == 1
class TestFinvizTools:
"""Tests for finviz MCP tools."""
@patch('mtdata.services.finviz_service.get_stock_fundamentals')
def test_finviz_fundamentals_tool(self, mock_get_fundamentals):
"""Test finviz_fundamentals tool."""
# Import the service function directly to test logic without MCP server init
from mtdata.services.finviz_service import get_stock_fundamentals as fn
mock_get_fundamentals.return_value = {
"success": True,
"symbol": "AAPL",
"fundamentals": {"P/E": "28.5"},
}
# Call the mocked function
result = mock_get_fundamentals("AAPL")
mock_get_fundamentals.assert_called_once_with("AAPL")
assert result["success"] is True
@patch('mtdata.services.finviz_service.screen_stocks')
def test_finviz_screen_tool_with_filters(self, mock_screen):
"""Test finviz_screen tool with JSON filters."""
import json
mock_screen.return_value = {"success": True, "count": 5, "stocks": []}
# Simulate what finviz_screen does: parse JSON and call service
filters_str = '{"Exchange": "NASDAQ"}'
filters_dict = json.loads(filters_str)
result = mock_screen(filters=filters_dict, order=None, limit=10, view="overview")
mock_screen.assert_called_once_with(
filters={"Exchange": "NASDAQ"},
order=None,
limit=10,
view="overview"
)
assert result["success"] is True
def test_finviz_screen_tool_invalid_json(self):
"""Test finviz_screen tool with invalid JSON."""
import json
filters_str = "not valid json"
try:
json.loads(filters_str)
result = {"success": True}
except (json.JSONDecodeError, TypeError):
result = {"error": f"Invalid filters JSON: {filters_str}"}
assert "error" in result
