VNStock MCP Server

import pytest import pandas as pd from unittest.mock import Mock, MagicMock from datetime import datetime @pytest.fixture def sample_company_overview_data(): """Sample data for company overview""" return pd.DataFrame([{ 'symbol': 'VCB', 'company_name': 'Vietcombank', 'industry': 'Banking', 'market_cap': 1000000000000, 'pe_ratio': 12.5, 'pb_ratio': 2.1, 'roe': 0.18, 'roa': 0.015 }]) @pytest.fixture def sample_company_news_data(): """Sample data for company news""" return pd.DataFrame([ { 'title': 'VCB announces Q3 results', 'publish_date': '2024-10-15', 'content': 'Strong quarterly performance...', 'source': 'TCBS' }, { 'title': 'VCB dividend announcement', 'publish_date': '2024-10-10', 'content': 'Dividend payment schedule...', 'source': 'TCBS' } ]) @pytest.fixture def sample_company_events_data(): """Sample data for company events""" return pd.DataFrame([ { 'event_type': 'AGM', 'event_date': '2024-04-15', 'description': 'Annual General Meeting', 'status': 'Completed' }, { 'event_type': 'Dividend', 'event_date': '2024-05-01', 'description': 'Dividend payment', 'status': 'Completed' } ]) @pytest.fixture def sample_shareholders_data(): """Sample data for shareholders""" return pd.DataFrame([ { 'shareholder_name': 'State Bank of Vietnam', 'ownership_percentage': 75.2, 'share_quantity': 3760000000 }, { 'shareholder_name': 'Public shareholders', 'ownership_percentage': 24.8, 'share_quantity': 1240000000 } ]) @pytest.fixture def sample_officers_data(): """Sample data for officers""" return pd.DataFrame([ { 'name': 'John Doe', 'position': 'CEO', 'status': 'working', 'appointment_date': '2020-01-01' }, { 'name': 'Jane Smith', 'position': 'CFO', 'status': 'working', 'appointment_date': '2021-06-01' } ]) @pytest.fixture def sample_subsidiaries_data(): """Sample data for subsidiaries""" return pd.DataFrame([ { 'subsidiary_name': 'VCB Securities', 'ownership_percentage': 100, 'business_type': 'subsidiary' }, { 'subsidiary_name': 'VCB Insurance', 'ownership_percentage': 51, 'business_type': 'subsidiary' } ]) @pytest.fixture def sample_financial_data(): """Sample data for financial statements""" return pd.DataFrame([ { 'period': '2023', 'revenue': 50000000000, 'profit_before_tax': 15000000000, 'net_profit': 12000000000, 'total_assets': 2000000000000, 'total_equity': 150000000000 }, { 'period': '2022', 'revenue': 45000000000, 'profit_before_tax': 13500000000, 'net_profit': 10800000000, 'total_assets': 1800000000000, 'total_equity': 140000000000 } ]) @pytest.fixture def sample_fund_data(): """Sample data for funds""" return pd.DataFrame([ { 'symbol': 'VFMVN30', 'fund_name': 'VFM VN30 ETF', 'fund_type': 'STOCK', 'nav': 25.5, 'total_assets': 5000000000 }, { 'symbol': 'DCDS', 'fund_name': 'Dragon Capital Dividend Fund', 'fund_type': 'BALANCED', 'nav': 15.2, 'total_assets': 2000000000 } ]) @pytest.fixture def sample_quote_history_data(): """Sample data for quote history""" return pd.DataFrame([ { 'time': '2024-01-01', 'open': 100.0, 'high': 105.0, 'low': 98.0, 'close': 103.0, 'volume': 1000000 }, { 'time': '2024-01-02', 'open': 103.0, 'high': 107.0, 'low': 101.0, 'close': 106.0, 'volume': 1200000 } ]) @pytest.fixture def sample_gold_price_data(): """Sample data for gold prices""" return pd.DataFrame([ { 'date': '2024-01-01', 'buy_price': 75000000, 'sell_price': 76000000, 'type': 'SJC Gold Bar' } ]) @pytest.fixture def sample_exchange_rate_data(): """Sample data for exchange rates""" return pd.DataFrame([ { 'currency': 'USD', 'buy_rate': 24000, 'sell_rate': 24200, 'date': '2024-01-01' }, { 'currency': 'EUR', 'buy_rate': 26000, 'sell_rate': 26300, 'date': '2024-01-01' } ]) @pytest.fixture def sample_industries_data(): """Sample data for industries""" return pd.DataFrame([ { 'icb_code1': '1000', 'icb_name1': 'Technology', 'icb_code2': '1100', 'icb_name2': 'Software' }, { 'icb_code1': '2000', 'icb_name1': 'Banking', 'icb_code2': '2100', 'icb_name2': 'Commercial Banks' } ]) @pytest.fixture def sample_symbols_data(): """Sample data for symbols listing""" return pd.DataFrame([ { 'symbol': 'VCB', 'company_name': 'Vietcombank', 'exchange': 'HOSE', 'industry': 'Banking' }, { 'symbol': 'VIC', 'company_name': 'Vingroup', 'exchange': 'HOSE', 'industry': 'Real Estate' } ]) @pytest.fixture def mock_tcbs_company(): """Mock TCBS Company class""" mock = Mock() mock.overview.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'company_name': 'Vietcombank' }]) mock.news.return_value = pd.DataFrame([{ 'title': 'Test news', 'date': '2024-01-01' }]) mock.events.return_value = pd.DataFrame([{ 'event': 'Test event', 'date': '2024-01-01' }]) mock.shareholders.return_value = pd.DataFrame([{ 'name': 'Test shareholder', 'percentage': 10.5 }]) mock.officers.return_value = pd.DataFrame([{ 'name': 'Test officer', 'position': 'CEO' }]) mock.subsidiaries.return_value = pd.DataFrame([{ 'name': 'Test subsidiary', 'percentage': 100 }]) mock.dividends.return_value = pd.DataFrame([{ 'year': 2023, 'dividend': 1000 }]) mock.insider_deals.return_value = pd.DataFrame([{ 'date': '2024-01-01', 'volume': 1000 }]) return mock @pytest.fixture def mock_vci_company(): """Mock VCI Company class""" mock = Mock() mock.reports.return_value = pd.DataFrame([{ 'report_name': 'Test report', 'date': '2024-01-01' }]) mock.ratio_summary.return_value = pd.DataFrame([{ 'ratio_name': 'PE', 'value': 12.5 }]) mock.trading_stats.return_value = pd.DataFrame([{ 'date': '2024-01-01', 'volume': 1000000 }]) return mock @pytest.fixture def mock_vci_listing(): """Mock VCI Listing class""" mock = Mock() mock.industries_icb.return_value = pd.DataFrame([{ 'icb_code': '1000', 'icb_name': 'Technology' }]) mock.symbols_by_group.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'group': 'VN30' }]) mock.symbols_by_industries.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'industry': 'Banking' }]) mock.symbols_by_exchange.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'exchange': 'HOSE' }]) return mock @pytest.fixture def mock_vci_finance(): """Mock VCI Finance class""" mock = Mock() mock.income_statement.return_value = pd.DataFrame([{ 'period': '2023', 'revenue': 1000000 }]) mock.balance_sheet.return_value = pd.DataFrame([{ 'period': '2023', 'total_assets': 5000000 }]) mock.cash_flow.return_value = pd.DataFrame([{ 'period': '2023', 'operating_cash_flow': 500000 }]) mock.ratio.return_value = pd.DataFrame([{ 'period': '2023', 'pe_ratio': 12.5 }]) mock._get_report.return_value = pd.DataFrame([{ 'period': '2023', 'raw_data': 'test' }]) return mock @pytest.fixture def mock_quote(): """Mock Quote class""" mock = Mock() mock.history.return_value = pd.DataFrame([{ 'time': '2024-01-01', 'close': 100.0 }]) mock.intraday.return_value = pd.DataFrame([{ 'time': '09:00:00', 'price': 100.5 }]) mock.price_depth.return_value = pd.DataFrame([{ 'bid_price': 100.0, 'ask_price': 100.5 }]) return mock @pytest.fixture def mock_fund(): """Mock Fund class""" mock = Mock() mock.listing.return_value = pd.DataFrame([{ 'symbol': 'VFMVN30', 'fund_name': 'VFM VN30 ETF' }]) mock.filter.return_value = pd.DataFrame([{ 'symbol': 'VFMVN30', 'fund_name': 'VFM VN30 ETF' }]) # Mock details sub-object details_mock = Mock() details_mock.nav_report.return_value = pd.DataFrame([{ 'date': '2024-01-01', 'nav': 25.5 }]) details_mock.top_holding.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'percentage': 10.5 }]) details_mock.industry_holding.return_value = pd.DataFrame([{ 'industry': 'Banking', 'percentage': 25.0 }]) details_mock.asset_holding.return_value = pd.DataFrame([{ 'asset_type': 'Stock', 'percentage': 80.0 }]) mock.details = details_mock return mock @pytest.fixture def mock_trading(): """Mock Trading class""" mock = Mock() mock.price_board.return_value = pd.DataFrame([{ 'symbol': 'VCB', 'price': 100.0, 'volume': 1000000 }]) return mock @pytest.fixture def mock_gold_price_func(): """Mock gold price functions""" return pd.DataFrame([{ 'date': '2024-01-01', 'buy_price': 75000000, 'sell_price': 76000000 }]) @pytest.fixture def mock_exchange_rate_func(): """Mock exchange rate function""" return pd.DataFrame([{ 'currency': 'USD', 'buy_rate': 24000, 'sell_rate': 24200 }])