TSLA stock sentiment

TSLA_streamlit_app.py

@@ -1,203 +0,0 @@
-from datetime import date
-from datetime import datetime
-import re
-
-import numpy as np  
-import pandas as pd 
-from PIL import Image
-import plotly.express as px  
-import plotly.graph_objects as go
-import streamlit as st  
-import time
-
-from plotly.subplots import make_subplots
-
-# Read CSV file into pandas and extract timestamp data
-# dfSentiment = ### YOUR LINE OF CODE HERE
-dfSentiment = pd.read_csv('../Phase_I-Proof_of_concept/TSLASentimentAnalyzer/sentiment_data.csv')
-dfSentiment['timestamp'] = [datetime.strptime(dt, '%Y-%m-%d') for dt in dfSentiment['timestamp'].tolist()]
-
-# Multi-select columns to build chart
-col_list = dfSentiment.columns.tolist()
-
-
-r_sentiment = re.compile(".*sentiment")
-sentiment_cols = list(filter(r_sentiment.match, col_list))
-
-r_post = re.compile(".*post")
-post_list = ist(filter(r_post.match, col_list))
-
-
-r_perc= re.compile(".*perc")
-perc_list = list(filter(r_perc.match, col_list))
-
-r_close = re.compile(".*close")
-close_list = list(filter(r_close.match, col_list))
-
-r_volume = re.compile(".*volume")
-volume_list = list(filter(r_volume.match, col_list))
-
-sentiment_cols = sentiment_cols + post_list
-stocks_cols = close_list + volume_list
-
-# Config for page
-st.set_page_config(
-    page_title= 'TSLA Bot',
-    page_icon='✅',
-    layout='wide',
-)
-
-with st.sidebar:
-    # FourthBrain logo to sidebar
-    fourthbrain_logo = Image.open('./images/fourthbrain_logo.png')
-    st.image([fourthbrain_logo], width=300)
-
-    # Date selection filters
-    start_date_filter = st.date_input(
-        'Start Date',
-        min(dfSentiment['timestamp']),
-        min_value=min(dfSentiment['timestamp']),
-        max_value=max(dfSentiment['timestamp'])
-        )
-        
-
-    end_date_filter = st.date_input(
-        'End Date',
-        max(dfSentiment['timestamp']),
-        min_value=min(dfSentiment['timestamp']),
-        max_value=max(dfSentiment['timestamp'])
-        )
-
-    sentiment_select = st.selectbox('Select Sentiment/Reddit Data', sentiment_cols)
-    stock_select = st.selectbox('Select Stock Data', stocks_cols)
-
-# Banner with TSLA and Reddit images
-tsla_logo = Image.open('./images/tsla_logo.png')
-reddit_logo = Image.open('./images/reddit_logo.png')
-st.image([tsla_logo, reddit_logo], width=200)
-
-# dashboard title
-st.title('TSLA Subreddit and Stock Price')
-
-## dataframe filter
-# start date
-dfSentiment = dfSentiment[dfSentiment['timestamp'] >= datetime(start_date_filter.year, start_date_filter.month, start_date_filter.day)]
-    
-# end date
-dfSentiment = dfSentiment[dfSentiment['timestamp'] <= datetime(end_date_filter.year, end_date_filter.month, end_date_filter.day)]
-dfSentiment = dfSentiment.reset_index(drop=True)
-
-
-# creating a single-element container
-placeholder = st.empty()
-
-# near real-time / live feed simulation
-for i in range(1, len(dfSentiment)-1):
-
-    # creating KPIs
-    last_close =  dfSentiment['close'][i]
-    last_close_lag1 = dfSentiment['close'][i-1]
-    last_sentiment = dfSentiment['sentiment_score'][i]
-    last_sentiment_lag1 = dfSentiment['sentiment_score'][i-1]
-
-
-    with placeholder.container():
-
-        # create columns
-        kpi1, kpi2 = st.columns(3)
-
-        # fill in those three columns with respective metrics or KPIs
-        kpi1.metric(
-            label='Sentiment Score',
-            value=round(last_sentiment, 3),
-            delta=round(last_sentiment_lag1, 3),
-        )
-        
-        kpi2.metric(
-            label='Last Closing Price',
-            value=round(last_close),
-            delta=round(last_close - last_close_lag1)
-        )
-        
-
-        # create two columns for charts
-        fig_col1, fig_col2 = st.columns(2)
-        
-        with fig_col1:
-            # Add traces
-            fig=make_subplots(specs=[[{"secondary_y":True}]])
-
-
-            fig.add_trace(                               
-                go.Scatter(                          
-                x=dfSentiment['timestamp'][0:i],
-                y=dfSentiment[sentiment_select][0:i],
-                name=sentiment_select,
-                mode='lines',                            
-                hoverinfo='none',                        
-                )              
-            )
-
-            if sentiment_select.startswith('perc') == True:
-                yaxis_label = '% Change Sentiment'
-
-            elif sentiment_select in sentiment_cols:
-                yaxis_label = 'Sentiment Score'
-
-            elif sentiment_select in post_list:
-                yaxis_label = 'Volume'
-
-            fig.layout.yaxis.title=yaxis_label
-                                          
-            if stock_select.startswith('perc') == True:
-                fig.add_trace(                               
-                    go.Scatter(                          
-                    x=dfSentiment['timestamp'][0:i],
-                    y=dfSentiment[stock_select][0:i],
-                    name=stock_select,
-                    mode='lines',                            
-                    hoverinfo='none', 
-                    yaxis='y2',                    
-                    ) 
-                )
-                fig.layout.yaxis2.title='% Change Stock Price ($US)'
-            
-            elif stock_select == 'volume':
-                fig.add_trace(                               
-                    go.Scatter(                          
-                    x=dfSentiment['timestamp'][0:i],
-                    y=dfSentiment[stock_select][0:i],
-                    name=stock_select,
-                    mode='lines',                            
-                    hoverinfo='none', 
-                    yaxis='y2',                    
-                    ) 
-                )
-                
-                fig.layout.yaxis2.title="Shares Traded"
-
-
-            else:
-                fig.add_trace(                               
-                    go.Scatter(                          
-                    x=dfSentiment['timestamp'][0:i],
-                    y=dfSentiment[stock_select][0:i],
-                    name=stock_select,
-                    mode='lines',                            
-                    hoverinfo='none', 
-                    yaxis='y2',                    
-                    ) 
-                )
-
-                fig.layout.yaxis2.title='Stock Price ($USD)'
-
-
-            fig.layout.xaxis.title='Timestamp'
-
-            # write the figure throught streamlit
-            st.write(fig)
-
-
-        st.markdown('### Detailed Data View')
-        st.dataframe(dfSentiment.iloc[:, 1:][0:i])
-        time.sleep(1)

requirements.txt

@@ -0,0 +1,9 @@
+pandas==1.4.2
+matplotlib==3.5.2
+streamlit==1.10.0
+transformers==4.19.4
+pydantic==1.9.1
+praw==7.6.0
+pytorch-pretrained-bert==0.6.2
+loguru==0.6.0
+plotly==5.9.0