Some tests modules added

Author: rahuldhurkunde

.github/workflows/ci.yml

@@ -0,0 +1,30 @@
+name: Python Application CI
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+permissions:
+  contents: read
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Python 3.12
+      uses: actions/setup-python@v5
+      with:
+        python-version: "3.12"
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+    - name: Test with pytest
+      run: |
+        export PYTHONPATH=.
+        pytest tests

requirements.txt

@@ -4,3 +4,4 @@ watchdog
 # Added for fetching stock prices
 yfinance
 plotly
+pytest

tests/run_tests.sh

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+PYTHONPATH=. pytest tests

tests/test_indicators.py

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+import pandas as pd
+import numpy as np
+import pytest
+from indicators import add_moving_average, add_52w_high_low, calculate_rsi
+
+@pytest.fixture
+def sample_price_df():
+    # Create a simple DataFrame for testing
+    dates = pd.date_range(start='2023-01-01', periods=100)
+    data = {
+        'AAPL': np.arange(100, 200),  # Linear increase
+        'GOOG': np.random.rand(100) * 100
+    }
+    return pd.DataFrame(data, index=dates)
+
+def test_add_moving_average(sample_price_df):
+    df = sample_price_df.copy()
+    df = add_moving_average(df, ma_periods=[10, 20])
+    
+    assert 'AAPL_MA10' in df.columns
+    assert 'AAPL_MA20' in df.columns
+    assert 'GOOG_MA10' in df.columns
+    
+    # Check simple calculation for linear increase (avg of last 10 of 100..109 is roughly 104.5)
+    # The first 9 values should be NaN if min_periods wasn't 1, but logic uses min_periods=1
+    assert not df['AAPL_MA10'].isnull().all()
+    
+    # Verify values for a known sequence
+    # AAPL is 100, 101, 102... 
+    # At index 0 (value 100), MA10 (min_periods=1) should be 100
+    assert df['AAPL_MA10'].iloc[0] == 100.0
+    
+    # At index 9 (value 109), MA10 is avg(100...109) = 104.5
+    assert df['AAPL_MA10'].iloc[9] == 104.5
+
+def test_add_52w_high_low(sample_price_df):
+    df = sample_price_df.copy()
+    # Ensure enough data or check min_periods behavior
+    # Code uses min_periods=1
+    df = add_52w_high_low(df)
+    
+    assert 'AAPL_52w_high' in df.columns
+    assert 'AAPL_52w_low' in df.columns
+    
+    # For monotonically increasing AAPL (100 to 199)
+    # The 52w high at the last point should be the current price
+    assert df['AAPL_52w_high'].iloc[-1] == 199
+    # The 52w low at the last point should be the price 52 weeks ago (or start of data)
+    # Since we only have 100 days, it's the min of the whole window so far, which is 100
+    assert df['AAPL_52w_low'].iloc[-1] == 100
+
+def test_calculate_rsi(sample_price_df):
+    df = sample_price_df.copy()
+    rsi_df = calculate_rsi(df)
+    
+    assert 'AAPL' in rsi_df.columns
+    assert 'GOOG' in rsi_df.columns
+    
+    # RSI should be between 0 and 100
+    assert rsi_df.max().max() <= 100
+    assert rsi_df.min().min() >= 0
+    
+    # For a constantly increasing stock (AAPL), RSI should be high (near 100)
+    # Use a slice to avoid initial warmup period
+    assert rsi_df['AAPL'].iloc[-1] > 70

tests/test_news.py

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+import pytest
+from unittest.mock import MagicMock, patch
+from news import get_news
+
+@patch('news.yf.Ticker')
+def test_get_news(mock_ticker):
+    # Mock data structure matching yfinance news format
+    mock_news_data = [
+        {
+            'content': {
+                'title': 'Stock goes up',
+                'canonicalUrl': {'url': 'http://example.com/news1'}
+            },
+            'publisher': 'The News Publisher'
+        },
+        {
+            'content': {
+                'title': 'Market crash?',
+                # Missing url test
+            },
+            # Missing publisher test
+        }
+    ]
+    
+    mock_instance = MagicMock()
+    mock_instance.news = mock_news_data
+    mock_ticker.return_value = mock_instance
+    
+    news_list = get_news('TEST')
+    
+    assert len(news_list) == 2
+    assert news_list[0]['headline'] == 'Stock goes up'
+    assert news_list[0]['link'] == 'http://example.com/news1'
+    assert news_list[0]['publisher'] == 'The News Publisher'
+    
+    # Check defaults
+    assert news_list[1]['headline'] == 'Market crash?'
+    assert news_list[1]['link'] == 'N/A - No Link Found'
+    assert news_list[1]['publisher'] == 'N/A - No Publisher'
+
+@patch('news.yf.Ticker')
+def test_get_news_empty(mock_ticker):
+    mock_instance = MagicMock()
+    mock_instance.news = []
+    mock_ticker.return_value = mock_instance
+    
+    news_list = get_news('EMPTY')
+    assert news_list == []

tests/test_utils.py

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+import pytest
+import pandas as pd
+from unittest.mock import MagicMock, patch
+from utils import get_price_data
+
+@patch('utils.yf.Ticker')
+def test_get_price_data(mock_ticker):
+    # Setup mock return data
+    mock_hist = pd.DataFrame({
+        'Open': [100, 102],
+        'High': [105, 106],
+        'Low': [99, 101],
+        'Close': [101, 105],
+    }, index=pd.to_datetime(['2023-01-01', '2023-01-02']))
+    mock_hist.index.name = 'Date'
+    
+    mock_instance = MagicMock()
+    mock_instance.history.return_value = mock_hist
+    mock_ticker.return_value = mock_instance
+    
+    start = '2023-01-01'
+    end = '2023-01-03'
+    tickers = ['TEST']
+    
+    df = get_price_data(tickers, start, end)
+    
+    assert not df.empty
+    assert 'Ticker' in df.columns
+    assert 'Price' in df.columns
+    assert df['Ticker'].iloc[0] == 'TEST'
+    assert df['Price'].iloc[0] == 101 # Close price renamed to Price
+    
+@patch('utils.yf.Ticker')
+def test_get_price_data_empty(mock_ticker):
+    # Setup mock to return empty
+    mock_instance = MagicMock()
+    mock_instance.history.return_value = pd.DataFrame()
+    mock_ticker.return_value = mock_instance
+    
+    df = get_price_data(['EMPTY'], '2023-01-01', '2023-01-02')
+    
+    assert df.empty
+    assert 'Ticker' in df.columns
+    assert 'Price' in df.columns