Merge pull request #45 from shivam096/cindy-backend

Cindy backend

.github/workflows/build_test.yml

@@ -87,7 +87,8 @@ jobs:
       # Next step: run pylint. Anything less than 10/10 will fail.
       - name: Lint with pylint
         run: |
-          pylint dinero/**/*.py || exit 0
+          pylint dinero/**/*.py
+
 
       # Next step: run the unit tests with code coverage.
       - name: Unit tests

dinero/backend/stock_data_manager.py

@@ -7,6 +7,7 @@
     3. update_stock_data()
     4. get_stock_data(ticker_symbol)
     5. get_filtered_stock_data(ticker_symbol, start_date='', end_date='')
+    6. get_last_n_days(stock_data, n_days)
 """
 import os
 
@@ -35,6 +36,10 @@ def download_stock_data(ticker_symbol, period_str='5y'):
     Save non-empty data to 'data/{ticker_symbol}.csv', do nothing otherwise.
     Print progress messages (complate or fail) to terminal.
 
+    Exceptions:
+    TypeError if ticker_symbol or period_str is not string
+    ValueError if period_str has invalid format or ticker data not found.
+
     Example:
     >> download_stock_data("AAPL", "max")
     =================================================================================
@@ -49,16 +54,21 @@ def download_stock_data(ticker_symbol, period_str='5y'):
     1 Failed download:
         ['MFT']: Exception('%ticker%: No data found, symbol may be delisted')
     """
+    if not (isinstance(ticker_symbol, str) and isinstance(period_str, str)):
+        raise TypeError("Arguments must be strings.")
     period_str = period_str.lower()
     ticker_symbol = ticker_symbol.upper()
+    if not (period_str == 'max' or period_str[-1] in ['d','y']
+            or period_str[-2:] in ['wk','mo']):
+        raise ValueError("period format: 'max', 'd', 'wk', 'mo', 'y' (case insensitive).")
+
     data = yf.download(ticker_symbol, period=period_str)
 
     if len(data) == 0:
-        return len(data)
+        raise ValueError("Fail to download: no data, ticker symbol may be delisted ")
 
     file_path = os.path.join(DEFAULT_DATABASE_PATH, f'{ticker_symbol}.csv')
     data.to_csv(file_path)
-
     return len(data)
 
 def get_existing_tickers():
@@ -69,7 +79,8 @@ def get_existing_tickers():
     list: A list of existing ticker symbol strings.
         Return empty list if data folder is empty.
     """
-    return [file[:-4] for file in os.listdir('data') if file.endswith('.csv')]
+    return [file[:-4] for file in os.listdir(DEFAULT_DATABASE_PATH)
+            if file.endswith('.csv')]
 
 def update_stock_data():
     """
@@ -103,14 +114,19 @@ def get_stock_data(ticker_symbol):
 
     Returns:
     pd.DataFrame: A DataFrame containing the stock data.
+
+    Exceptions:
+    TypeError if ticker_symbol is not a string
+    ValueError if ticker not in database
     """
+    if not isinstance(ticker_symbol, str):
+        raise TypeError("ticker symbol must be strings.")
     ticker_symbol = ticker_symbol.upper()
     file_path = os.path.join(DEFAULT_DATABASE_PATH, f'{ticker_symbol}.csv')
     if not os.path.exists(file_path):
         raise ValueError("No such database. Please download initial data first.")
     return pd.read_csv(file_path)
 
-
 def get_filtered_stock_data(ticker_symbol, start_date='1900-01-01', end_date=''):
     """
     Function to fetch stock data of the ticker within given timeframe from statistic database.
@@ -125,54 +141,63 @@ def get_filtered_stock_data(ticker_symbol, start_date='1900-01-01', end_date='')
     Returns:
     pd.DataFrame: A DataFrame containing the filtered stock data.
 
-    Raises:
+    Exceptions:
+    TypeError:
+        If start_date or end_data is not string
     ValueError:
-        If start_date is later than end_date.
+        If start_date or end_date has invalid date format
+        or start_date is later than end_date.
     """
     stock_data = get_stock_data(ticker_symbol)
 
-    start_date = pd.to_datetime(start_date, format='%Y-%m-%d')
+    if not (isinstance(start_date, str) and isinstance(end_date, str)):
+        raise TypeError("Dates must be strings in form of 'yyyy-mm-dd'.")
 
-    if len(end_date) == 0:
+    if len(start_date.strip()) == 0:
+        start_date = '1900-01-01'
+    start_date = pd.to_datetime(start_date, format='%Y-%m-%d', errors='coerce')
+    if pd.isnull(start_date):
+        raise ValueError("Valid Format of start date should be 'yyyy-mm-dd'.")
+    if len(end_date.strip()) == 0:
         end_date = pd.Timestamp.today() + pd.DateOffset(1)
-    end_date = pd.to_datetime(end_date, format='%Y-%m-%d')
+    end_date = pd.to_datetime(end_date, format='%Y-%m-%d', errors='coerce')
+    if pd.isnull(end_date):
+        raise ValueError("Valid Format of end date should be 'yyyy-mm-dd'.")
 
     if start_date > end_date:
         raise ValueError("Start date after end date.")
 
     return stock_data.query(f"'{start_date}' <= Date <= '{end_date}'")
 
-def get_last_n_days(df, n_days):
+def get_last_n_days(stock_data, n_days):
     """
     Extracts the last n_days rows from the DataFrame.
 
     Parameters:
-        df (DataFrame): Input DataFrame.
+        stock_data (DataFrame): Input DataFrame.
         n_days (int): Number of days from the end of the DataFrame.
 
     Returns:
         DataFrame: DataFrame containing the last n_days rows, or the entire
         DataFrame if n_days exceeds the number of rows.
 
-
-    Raises:
-    ValueError:
-        If the number of days entered is a negative integer or 0.
-    TypeError:
-        If the number of days enetered is not an integer
+    Exceptions:
+    ValueError if the number of days entered is a negative integer or 0.
+    TypeError if stock_data is not pd.DataFrame or n_days is not an integer
     """
-
-    # Ensure n_days is a positive integer
+    # Ensure stock_data is a dataframe and n_days is a positive integer
+    if not isinstance(stock_data, pd.DataFrame):
+        raise TypeError("data must be pandas dataframe")
     if not isinstance(n_days, int):
         raise TypeError("Number of Days must be an Integer")
     if n_days <= 0:
         raise ValueError("Number of days must be a positive integer")
 
     # Check if n_days exceeds the number of rows in the DataFrame
-    if n_days >= len(df):
-        return df  # Return the entire DataFrame
+    if n_days >= len(stock_data):
+        return stock_data  # Return the entire DataFrame
 
     # Get the last n_days rows from the DataFrame
-    last_n_days_df = df.iloc[-n_days:]
+    last_n_days_df = stock_data.iloc[-n_days:]
 
     return last_n_days_df

dinero/backend/visualization.py

@@ -39,7 +39,7 @@ def plot_stock_price(ticker_symbol):
                                             name='Candlestick'))
 
     # Update layout for candlestick chart
-    fig_candlestick.update_layout(title=f'Candlestick Chart',
+    fig_candlestick.update_layout(title=f'{ticker_symbol} Candlestick Chart',
                                 xaxis_title="Date", yaxis_title="Price")
     fig_candlestick.update_layout(hovermode="x unified")
     time_buttons = [

dinero/tests/test_stock_data_manager.py

@@ -19,6 +19,7 @@
     update_stock_data,
     get_stock_data,
     get_filtered_stock_data,
+    get_last_n_days,
     DEFAULT_DATABASE_PATH
 )
 
@@ -30,45 +31,74 @@ class TestStockDataManager(unittest.TestCase):
         3. update_stock_data()
         4. get_stock_data(ticker_symbol)
         5. get_filtered_stock_data(ticker_symbol, start_date='', end_date='')
+        6. get_last_n_days(stock_data, n_days)
 
     Notes:
-    `get_existing_tickers` is TRIVIAL and is called by update_stock_data(),
+    2.`get_existing_tickers` is TRIVIAL and is called by update_stock_data(),
     so it has no explicit testing.
     """
 
     @mock.patch('backend.stock_data_manager.yf.download')
     def test_default_download_stock_data(self, mock_download):
         """
         Test download with (valid) default period
-        (using mock to avoid changing database)
+        (using mock to simulate yfinance download)
         """
-        sample_data = f'{DEFAULT_DATABASE_PATH}/MSFT.csv'
-        mock_download.return_value = pd.read_csv(sample_data)
-        num = download_stock_data('valid_ticker')
+        mock_download.return_value = pd.DataFrame({"Close": [100, 200, 300]})
+        num = download_stock_data('test_ticker')
         self.assertIsInstance(num, int)
-        file_path = f'{DEFAULT_DATABASE_PATH}/VALID_TICKER.csv'
+        file_path = f'{DEFAULT_DATABASE_PATH}/TEST_TICKER.csv'
         self.assertTrue(os.path.exists(file_path))
         os.remove(file_path)
 
-    def test_download_stock_data_invalid_input(self):
+    @mock.patch('backend.stock_data_manager.yf.download')
+    def test_download_stock_data_invalid_input_type(self, mock_download):
+        """
+        Test download with invalid input type
+        (using mock to simulate yfinance download)
+        """
+        mock_download.return_value = pd.DataFrame({"Close": [100, 200, 300]})
+        with self.assertRaises(TypeError):
+            download_stock_data('test_ticker', 1)
+        file_path = f'{DEFAULT_DATABASE_PATH}/TEST_TICKER.csv'
+        self.assertFalse(os.path.exists(file_path))
+
+    @mock.patch('backend.stock_data_manager.yf.download')
+    def test_download_stock_data_invalid_period(self, mock_download):
         """
-        Test download with invalid input
+        Test download with invalid period input
+        (using mock to simulate yfinance download)
+        """
+        mock_download.return_value = pd.DataFrame({"Close": [100, 200, 300]})
+        with self.assertRaises(ValueError):
+            download_stock_data('test_ticker', '1')
+        file_path = f'{DEFAULT_DATABASE_PATH}/TEST_TICKER.csv'
+        self.assertFalse(os.path.exists(file_path))
+
+    @mock.patch('backend.stock_data_manager.yf.download')
+    def test_download_stock_data_invalid_ticker(self, mock_download):
         """
-        num = download_stock_data('invalid', '1d')
-        self.assertEqual(num, 0)
+        Test download with invalid ticker input
+        (using mock to simulate yfinance download)
+        """
+        mock_download.return_value = pd.DataFrame()
+        with self.assertRaises(ValueError):
+            download_stock_data('invalid', '1d')
         file_path = f'{DEFAULT_DATABASE_PATH}/INVALID.csv'
         self.assertFalse(os.path.exists(file_path))
 
     @mock.patch('backend.stock_data_manager.yf.download')
     def test_update_stock_data(self, mock_download):
         """
         Test update stock database
-        (using mock to avoid changing database)
+        (using mock to simulate yfinance download)
         """
         mock_download.return_value = pd.DataFrame()
-        tikers = update_stock_data()
-        self.assertIsInstance(tikers, list)
-
+        tickers = update_stock_data()
+        self.assertIsInstance(tickers, list)
+        for ticker in tickers:
+            file_path = f'{DEFAULT_DATABASE_PATH}/{ticker}.csv'
+            self.assertTrue(os.path.exists(file_path))
 
     @mock.patch("backend.stock_data_manager.pd.read_csv")
     def test_get_stock_data(self, mock_read_csv):
@@ -86,6 +116,8 @@ def test_get_stock_data_invalid_ticker(self):
         """
         Test fetch non-existing stock data from database
         """
+        with self.assertRaises(TypeError):
+            get_stock_data(1)
         with self.assertRaises(ValueError):
             get_stock_data('NON_EXISTENT_SYMBOL')
 
@@ -109,9 +141,34 @@ def test_get_filtered_stock_data_with_invalid_input(self):
         """
         Test fetch filtered stock data from database with invalid input
         """
+        with self.assertRaises(TypeError):
+            get_filtered_stock_data('MSFT', 20240101, '2023/01/0')
         with self.assertRaises(ValueError):
             get_filtered_stock_data('MSFT', '2024/01/01', '2023/01/0')
 
+    def test_get_last_n_days_valid(self):
+        """
+        Test get data of n last days from dataframe with valid input
+        (num of days > len(dataframe))
+        """
+        test_df = pd.DataFrame({"Date": ['2023/01/0', '2023/10/01',
+                                         '2024/11/01','2024/01/01']})
+        test_result = get_last_n_days(test_df,6)
+        self.assertIsInstance(test_result, pd.DataFrame)
+        self.assertEqual(len(test_result), 4)
+
+    def test_get_last_n_days_invalid(self):
+        """
+        Test get data of n last days from dataframe with invalid input
+        """
+        test_df = pd.DataFrame({"Date": ['2023/01/0', '2023/10/01',
+                                         '2024/11/01','2024/01/01']})
+        with self.assertRaises(TypeError):
+            get_last_n_days(['2023/01/0'],2)
+        with self.assertRaises(TypeError):
+            get_last_n_days(test_df,"1")
+        with self.assertRaises(ValueError):
+            get_last_n_days(test_df,-1)
 
 if __name__ == '__main__':
     unittest.main()

dinero/tests/test_visualization.py

@@ -27,17 +27,19 @@ def test_plot_stock_price_layout(self):
         """
         Test the layout of the stock price candlestick chart.
 
-        Checks if the layout of the candlestick chart is as expected.
+        Checks if the layout of the candlestick chart is as expected:
+            chart type and tittles
+            tooltips
         """
         stock_price_fig = plot_stock_price('MSFT')
         self.assertIsInstance(stock_price_fig, go.Figure)
         self.assertEqual(len(stock_price_fig.data), 1)
         self.assertEqual(stock_price_fig.data[0].type, 'candlestick')
-        self.assertEqual(stock_price_fig.layout.hovermode, 'x unified')
         self.assertEqual(stock_price_fig.layout.title['text'],
-                         'Candlestick Chart')
+                         'MSFT Candlestick Chart')
         self.assertEqual(stock_price_fig.layout.xaxis.title['text'], 'Date')
         self.assertEqual(stock_price_fig.layout.yaxis.title['text'], 'Price')
+        self.assertEqual(stock_price_fig.layout.hovermode, 'x unified')
 
     def test_plot_stock_price_selector_view_adjustment(self):
         """
@@ -63,9 +65,9 @@ def test_plot_stock_price_selector_view_adjustment(self):
 
     def test_plot_kpi_ma(self):
         """
-        Test plotting Moving Average (MA) on the stock price chart.
+        Test technical indicaters plotting using Moving Average (MA).
 
-        Checks if Moving Average is correctly added to the stock price candlestick chart.
+        Checks if MA trace is correctly added to the stock price candlestick chart.
         """
         stock_price_fig = plot_stock_price('MSFT')
         kpi_fig = plot_kpis(stock_price_fig, 'MSFT', 50, 'MA')
@@ -80,7 +82,7 @@ def test_plot_kpi_other(self):
         Test plotting other technical indicators on the stock price chart.
 
         Checks if other technical indicators are correctly added to
-        the stock price candlestick chart.
+        the plot groups with the stock price chart.
         """
         stock_price_fig = plot_stock_price('MSFT')
         kpi_fig = plot_kpis(stock_price_fig, 'MSFT', 50, 'ROC')