Add data source tests to CI for MSN and Yahoo (closes #59)

.github/workflows/python-app.yml

@@ -32,5 +32,4 @@ jobs:
         pip install pytest==8.2.1
         pip install -e .
     - name: Test with pytest
-      run: |
-        python run_all_tests.py && pytest
+      run: pytest

isthisstockgood/Active/MSNMoney.py

@@ -1,6 +1,8 @@
 import json
 import isthisstockgood.RuleOneInvestingCalculations as RuleOne
 
+
+
 class MSNMoney:
   # This key appears to be fixed? So we can use it for now /shrug
   _API_KEY = '0QfOX3Vn51YCzitbLaRkTTBadtWpgTN8NZLW0C1SEM'
@@ -78,7 +80,7 @@ def parse_annual_report_data(self, content):
     most_recent_statement = annual_statements[max(annual_statements.keys())]
     if not most_recent_statement:
       return
-    self.total_debt = str(float(most_recent_statement.get('longTermDebt', 0)))
+    self.total_debt = float(most_recent_statement.get('longTermDebt', 0))
     self.shares_outstanding = float(most_recent_statement.get('sharesOutstanding', 0))
 
     key_metrics = data.get('analysis', {}).get('keyMetrics', {})
@@ -92,7 +94,7 @@ def parse_ratios_data(self, content):
       return False
 
     self.name = json_content.get('displayName', '')
-    self.industy = json_content.get('industry', '')
+    self.industry = json_content.get('industry', '')
 
     # PE Ratios
     self._parse_pe_ratios(yearly_data)

isthisstockgood/CompanyInfo.py

@@ -0,0 +1,28 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class CompanyInfo:
+    ticker_symbol: str
+    name: str
+    description: str
+    industry: str
+    current_price: float
+    average_volume: float
+    market_cap: float
+    shares_outstanding: int
+    pe_high: float
+    pe_low: float
+    roic: float
+    roic_averages: [float]
+    equity: float
+    equity_growth_rates: [float]
+    free_cash_flow: float
+    free_cash_flow_growth_rates: [float]
+    revenue: float
+    revenue_growth_rates: [float]
+    eps: float
+    eps_growth_rates: [float]
+    debt_equity_ratio: float
+    last_year_net_income: float
+    total_debt: float

tests/test_DataSources.py

@@ -0,0 +1,70 @@
+from isthisstockgood.CompanyInfo import CompanyInfo
+from isthisstockgood.DataFetcher import DataFetcher
+
+
+def test_msn_money():
+    test_ticker = 'MSFT'
+    test_name = 'Microsoft Corp'
+
+    data = get_msn_money_data(test_ticker)
+
+    assert data.ticker_symbol == test_ticker
+    assert data.name == test_name
+    assert data.description != ''
+    assert data.industry != ''
+    assert data.current_price > 0.0
+    assert data.average_volume > 0
+    assert data.market_cap > 0.0
+    assert data.shares_outstanding > 0
+    assert data.pe_high > 0.0
+    assert data.pe_low > 0.0
+    assert data.roic != []
+    assert data.roic_averages != []
+    assert data.equity != []
+    assert data.equity_growth_rates != []
+    assert data.free_cash_flow != []
+    assert data.free_cash_flow_growth_rates != []
+    assert data.revenue != []
+    assert data.revenue_growth_rates != []
+    assert data.eps != []
+    assert data.eps_growth_rates != []
+    assert data.debt_equity_ratio > 0.0
+    assert data.last_year_net_income > 0.0
+    assert data.total_debt >= 0.0
+
+def test_yahoo():
+    test_ticker = 'MSFT'
+    test_name = 'Microsoft Corp'
+
+    data = get_yahoo_data(test_ticker)
+
+    assert data.ticker_symbol == test_ticker
+    assert float(data.five_year_growth_rate) > 0.0
+
+def get_msn_money_data(ticker):
+    data_fetcher = DataFetcher()
+    data_fetcher.ticker_symbol = ticker
+
+    # Make all network request asynchronously to build their portion of
+    # the json results.
+    data_fetcher.fetch_msn_money_data()
+
+    # Wait for each RPC result before proceeding.
+    for rpc in data_fetcher.rpcs:
+      rpc.result()
+
+    return CompanyInfo(**vars(data_fetcher.msn_money))
+
+def get_yahoo_data(ticker):
+    data_fetcher = DataFetcher()
+    data_fetcher.ticker_symbol = ticker
+
+    # Make all network request asynchronously to build their portion of
+    # the json results.
+    data_fetcher.fetch_yahoo_finance_analysis()
+
+    # Wait for each RPC result before proceeding.
+    for rpc in data_fetcher.rpcs:
+      rpc.result()
+
+    return data_fetcher.yahoo_finance_analysis