documentation changes

dinero/app.py

@@ -1,3 +1,4 @@
+# pylint: disable=invalid-escape
 """
 Module level docstring for Stock Dashboard Application
 
@@ -21,6 +22,7 @@
     $ streamlit run app.py
 
 """
+# Importing required libraries
 import streamlit as st
 import pandas as pd
 
@@ -38,6 +40,7 @@
 #st.set_theme('dark')
 st.set_page_config(layout="wide")
 
+# Defining colors for better readability
 HEADING_COLOR = "#86B6F6"
 NEWS_ARTICLE_COLOR = "#E3DFFD"
 NEWS_ARTICLE_DATE_COLOR = "#89CFF3"
@@ -47,6 +50,7 @@
 NEGATIVE_COLOR = "#D24545"   # Red
 HIGHLIGHT_COLOR_BLUE = "#AEDEFC"
 
+# Dictionaries created to MAP elements with HTML strings
 kpi_description_mapping = {
     "MA" : f'''The <span style='color:{NEGATIVE_COLOR}'><b>Moving Average (MA)
             </b></span> helps <span style='color:{HIGHLIGHT_COLOR_BLUE}'><i>smooth out
@@ -139,30 +143,39 @@
 
 st.image("frontend/logo.png", use_column_width=True)
 
+# Sidebar content
 st.sidebar.markdown(f'''<h1 style='color:{NEWS_ARTICLE_DATE_COLOR}; text-align: center;'>
                 📊 Welcome the the Stock Analysis Platform!</h1>''',
                 unsafe_allow_html=True)
-st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR}; text-align: center;'>
+st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR};'>
                 Click on the various tabs to dive deep into stock data and
                 news headlines! 💼📰</h2>''',
                 unsafe_allow_html=True)
-st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR}; text-align: center;'>
+st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR};'>
                 Use the filters to select company, date range,
                 and technical indicators, to ensure you get
                 tailored insights! 📅🔍</h2>''',
                 unsafe_allow_html=True)
-st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR}; text-align: center;'>
+st.sidebar.markdown(f'''<h2 style='color:{NEWS_ARTICLE_COLOR};'>
                 Understand the sentiment and keywords of
                 news events, and analyze their correlation
                 with stock price movements! 📈🔍</h2>''',
                 unsafe_allow_html=True)
-
-
+st.sidebar.markdown('''<hr class="horizontal-line">''', unsafe_allow_html=True)
+st.sidebar.markdown('''Refer to our [tool guide](examples/tool_guide_for_user.md)
+            for detailed instructions on how to use the stock analysis tool''')
+st.sidebar.markdown('''
+    Refer to our documentation for more information on these complex financial terms:
+    [Documentation](https://drive.google.com/file/d/1H8gJ8gjN8jLVqtD8mAAAB5-VOmehDnhr/view?usp=sharing)
+''')
+
+# Creating streamlit tabs
 tab1, tab2, tab3, tab4 = st.tabs(["📈 Stock Performance Overview",
                                   "🔍 Explore Stock Technical Indicators",
                                   "📰 Latest News Headlines and Articles",
                                   "💡 Explore More Tickers or Update Data!"])
 
+# Tab 1: Stock Performance Overview
 with tab1:
 
     company_option = st.selectbox('Choose the Company Stock you Wish to View!',
@@ -210,7 +223,7 @@
             movements.
         ''', unsafe_allow_html=True)
 
-
+# Tab 2: Explore Stock Technical Indicators
 with tab2:
     st.markdown(f'''<h2 style='color:{HEADING_COLOR}; text-align: center;'>
                 LEVERAGING TECHNICAL INDICATORS</h2>''', unsafe_allow_html=True)
@@ -240,6 +253,7 @@
     with st.expander("🛈 What do These Numbers Mean?"):
         st.markdown(kpi_chart_info_mapping[kpi_name], unsafe_allow_html=True)
 
+# Tab 3: Latest News Headlines and Articles
 with tab3:
     st.markdown(f'''<h2 style='color:{HEADING_COLOR}; text-align:
                 center;'>BEYOND HEADLINES : DECODING NEWS SENTIMENT</h2>'''
@@ -327,6 +341,7 @@
 
                 st.markdown('<hr class="horizontal-line">', unsafe_allow_html=True)
 
+# Tab 4: Explore More Tickers or Update Data!
 with tab4:
     selected_ticker = st.text_input('➕ Add New Ticker')
     selected_time = st.text_input('''(Optional) 🕒 Input a time period

dinero/backend/visualization.py

@@ -13,6 +13,15 @@
 from backend.stock_data_manager import get_stock_data
 from backend.kpi_manager import get_technical_indicator
 
+TIME_BUTTONS = [
+    {'step': 'all', 'label': 'All'},
+    {'count': 3, 'step': 'year', 'stepmode': 'backward', 'label': '3 Year'},
+    {'count': 1, 'step': 'year', 'stepmode': 'backward', 'label': '1 Year'},
+    {'count': 6, 'step': 'month', 'stepmode': 'backward', 'label': '6 Month'},
+    {'count': 1, 'step': 'month', 'stepmode': 'backward', 'label': '1 Month'},
+    {'count': 1, 'step': 'year', 'stepmode': 'todate', 'label': '1 Year To Date'}
+]
+
 def plot_stock_price(ticker_symbol):
     """
     Plot a candlestick chart for the given stock ticker symbol.
@@ -42,15 +51,7 @@ def plot_stock_price(ticker_symbol):
     fig_candlestick.update_layout(title=f'Candlestick Chart',
                                 xaxis_title="Date", yaxis_title="Price")
     fig_candlestick.update_layout(hovermode="x unified")
-    time_buttons = [
-        {'step': 'all', 'label': 'All'},
-        {'count': 3, 'step': 'year', 'stepmode': 'backward', 'label': '3 Year'},
-        {'count': 1, 'step': 'year', 'stepmode': 'backward', 'label': '1 Year'},
-        {'count': 6, 'step': 'month', 'stepmode': 'backward', 'label': '6 Month'},
-        {'count': 1, 'step': 'month', 'stepmode': 'backward', 'label': '1 Month'},
-        {'count': 1, 'step': 'year', 'stepmode': 'todate', 'label': '1 Year To Date'}
-    ]
-    fig_candlestick.update_xaxes(rangeselector={'buttons': time_buttons})
+    fig_candlestick.update_xaxes(rangeselector={'buttons': TIME_BUTTONS})
     fig_candlestick.update_yaxes(autorange=True, fixedrange = False)
 
     return fig_candlestick
@@ -113,15 +114,6 @@ def plot_kpis(stock_fig, ticker_symbol, length, kpi_name):
     kpi_fig.update_traces(xaxis='x1')
     kpi_fig.update_layout(title=f'{kpi_name} for {ticker_symbol}',
                           xaxis_title="Date", yaxis_title="Price")
-
-    time_buttons = [
-        {'step': 'all', 'label': 'All'},
-        {'count': 3, 'step': 'year', 'stepmode': 'backward', 'label': '3 Year'},
-        {'count': 1, 'step': 'year', 'stepmode': 'backward', 'label': '1 Year'},
-        {'count': 6, 'step': 'month', 'stepmode': 'backward', 'label': '6 Month'},
-        {'count': 1, 'step': 'month', 'stepmode': 'backward', 'label': '1 Month'},
-        {'count': 1, 'step': 'year', 'stepmode': 'todate', 'label': '1 Year To Date'}
-    ]
-    kpi_fig.update_xaxes(rangeselector={'buttons': time_buttons})
+    kpi_fig.update_xaxes(rangeselector={'buttons': TIME_BUTTONS})
     kpi_fig.update_yaxes(autorange=True, fixedrange = False)
     return kpi_fig

dinero/tests/test_app.py

@@ -10,7 +10,13 @@
 """
 
 import unittest
+from unittest import mock
 from streamlit.testing.v1 import AppTest
+import pandas as pd
+
+
+@mock.patch('backend.processing.get_sentiments')
+
 
 class TestStreamlitApp(unittest.TestCase):
     """
@@ -42,20 +48,29 @@ class TestStreamlitApp(unittest.TestCase):
     - update_data_for_new_ticker: Test the update of data for a newly added
                                 ticker in the Streamlit application.
     """
-
-    def test_smoke_app(self):
+    mocked_sentiment_dataframe = pd.DataFrame({"Date": ["2022-02-02"],
+                                                   "Title": ["Mock Data News"],
+                                                   "Link" : ["www.google.com"],
+                                                   "Compound Sentiment Score": [0.2],
+                                                   "Positive Sentiment Score": [0.2],
+                                                   "Negative Sentiment Score": [0.2],
+                                                   "Neutral Sentiment Score": [0.2]})
+    def test_smoke_app(self,mock_get_sentiment):
         """
         Test the basic functionality of the Streamlit application.
         This test checks if the application loads without raising any exceptions.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
         assert not at.exception
 
-    def test_number_and_titles_of_tabs(self):
+    def test_number_and_titles_of_tabs(self,mock_get_sentiment):
         """
         This test verifies if the titles of the tabs match the expected labels.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
 
         expected_labels = ["📈 Stock Performance Overview",
                         "🔍 Explore Stock Technical Indicators",
@@ -65,27 +80,31 @@ def test_number_and_titles_of_tabs(self):
         for i, expected_label in enumerate(expected_labels):
             assert at.tabs[i].label == expected_label
 
-    def test_stock_options(self):
+    def test_stock_options(self,mock_get_sentiment):
         """
         This test verifies if there are atleast five company tickers and the
         functionality of selecting stock options.This test also verifies
         if the action on a select button successfully runs in the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         assert len(at.tabs[0].selectbox[0].label) >= 5
 
         at.tabs[0].selectbox[0].select_index(0).run()
         assert not at.exception
 
-    def test_technical_indicator_options(self):
+    def test_technical_indicator_options(self,mock_get_sentiment):
         """
         Test the technical indicator options in the Streamlit application
         and checks the selection and value of technical indicators. This test
         also verifies if the action on a select button successfully
         runs in the application.
         """
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
 
-        at = AppTest.from_file("../app.py", default_timeout=20).run()
+        at = AppTest.from_file("../app.py").run()
         assert at.tabs[1].selectbox[0].label == 'Select Technical Indicator'
         assert at.tabs[1].selectbox[0].options == ["MA", "RSI", "ROC", "BBP"]
 
@@ -97,67 +116,79 @@ def test_technical_indicator_options(self):
         assert not at.exception
         assert at.tabs[1].selectbox[0].value == "RSI"
 
-    def test_technical_indicator_length(self):
+    def test_technical_indicator_length(self,mock_get_sentiment):
         """
         Test the input of technical indicator length in the Streamlit application
         to checks the input of a numerical value for the technical
         indicator length. This test also verifies if any valid user input
         would run successfully in the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         assert at.tabs[1].number_input[0].label == 'Input a length'
         at.tabs[1].number_input[0].set_value(5).run()
         assert not at.exception
 
-    def test_number_of_days_input(self):
+    def test_number_of_days_input(self,mock_get_sentiment):
         """
         Test the input of the number of days in the Streamlit application and
         this test verifies the input of a numerical value for the number of days.
         This test also verifies if any valid user input would run s
         successfully in the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         at.tabs[2].number_input[0].set_value(50).run()
         assert not at.exception
 
-    def test_percentage_change_option(self):
+    def test_percentage_change_option(self,mock_get_sentiment):
         """
         Test the input of the percentage change in the Streamlit application
         and this test verifies the input of a numerical value for the the
         percentage change in stock price. This test also verifies if any valid
         user input would run successfully in the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=10).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         at.tabs[2].number_input[1].set_value(-5).run()
         assert not at.exception
 
-    def test_add_new_company_ticker_input(self):
+    def test_add_new_company_ticker_input(self,mock_get_sentiment):
         """
         Test the input of a new company ticker in the Streamlit application.
         This test verifies if any valid user input would run successfully in
         the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=20).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         assert at.tabs[3].text_input[0].label == '➕ Add New Ticker'
         assert at.tabs[3].text_input[0].set_value('AMZN').run()
         assert not at.exception
 
-    def test_add_new_ticker_time_period_input(self):
+    def test_add_new_ticker_time_period_input(self,mock_get_sentiment):
         """
         Test the input of time period for a new ticker in the Streamlit application.
         This test checks the input of a time period for a newly added ticker symbol
         and verifies if any valid user input would run successfully in the application.
         """
-        at = AppTest.from_file("../app.py", default_timeout=20).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         at.tabs[3].text_input[1].set_value('5d').run()
         assert not at.exception
 
-    def update_data_for_new_ticker(self):
+    def update_data_for_new_ticker(self,mock_get_sentiment):
         """
         Test the update of data for a newly added ticker in the Streamlit application.
         This test verifies the functionality of updating data for a newly added ticker.
         """
-        at = AppTest.from_file("../app.py", default_timeout=20).run()
+        mock_get_sentiment.return_value = self.mocked_sentiment_dataframe
+        at = AppTest.from_file("../app.py").run()
+        at = AppTest.from_file("../app.py").run()
         assert at.tabs[3].button[0].label == "🔁 Click to Update Ticker Data to the Most Recent"
         at.tabs[3].button[0].click().run()
         assert not at.exception

dinero/tests/test_visualization.py

@@ -13,7 +13,8 @@
 
 from backend.visualization import (
     plot_stock_price,
-    plot_kpis
+    plot_kpis,
+    TIME_BUTTONS
 )
 
 class TestVisualization(unittest.TestCase):
@@ -48,16 +49,8 @@ def test_plot_stock_price_selector_view_adjustment(self):
         and if y-axis range is set to auto.
         """
         stock_price_fig = plot_stock_price('MSFT')
-        time_buttons = [
-        {'step': 'all', 'label': 'All'},
-        {'count': 3, 'step': 'year', 'stepmode': 'backward', 'label': '3 Year'},
-        {'count': 1, 'step': 'year', 'stepmode': 'backward', 'label': '1 Year'},
-        {'count': 6, 'step': 'month', 'stepmode': 'backward', 'label': '6 Month'},
-        {'count': 1, 'step': 'month', 'stepmode': 'backward', 'label': '1 Month'},
-        {'count': 1, 'step': 'year', 'stepmode': 'todate', 'label': '1 Year To Date'}
-        ]
         self.assertEqual(len(stock_price_fig.layout.xaxis.rangeselector.buttons),
-                        len(time_buttons))
+                        len(TIME_BUTTONS))
         self.assertTrue(stock_price_fig.layout.yaxis.autorange)
         self.assertFalse(stock_price_fig.layout.yaxis.fixedrange)