rollback

.gitignore

@@ -1,2 +1,5 @@
 secrets.json
-fin_data.db
+fin_data.db
+streamlit_config.json
+edgar-crawler/
+.venv/

app.py

@@ -2,15 +2,23 @@ import streamlit as st
 import sqlite3
 import pandas as pd
 import streamlit as st
+import pygwalker as pyg
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+
+st.set_page_config(
+    page_title="Financial Data",
+    page_icon="📈",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+st.set_title('Financial Data')
 
 
 conn = sqlite3.connect('fin_data.db')
 c = conn.cursor()
 c.execute("""
-       select * from test
+       select * from company_news
 """)
 
 rows = c.fetchall()
@@ -18,11 +26,22 @@ rows = c.fetchall()
 # Extract column names from the cursor
 column_names = [description[0] for description in c.description]
 
+conn.commit()
+conn.close()
+
 # Create a DataFrame
 df = pd.DataFrame(rows, columns=column_names)
 
-print(df)
+# setup pygwalker configuration: https://github.com/Kanaries/pygwalker
+def load_config(file_path):
+    with open(file_path, 'r') as config_file:
+        config_str = config_file.read()
+    return config_str
+config = load_config('config.json')
+pyg.walk(df, env='Streamlit', dark='dark', spec=config)
+
+# show the dataframe just to test
 st.dataframe(df)
 
-conn.commit()
-conn.close()
+
+

fin_data_api.py

@@ -30,38 +30,72 @@ def sentiment_analysis(headline:str) -> str:
     
     :param1 headline: Text string: 'Apple is the best company in the world'
     """
-    nlp = pipeline("sentiment-analysis")
+    nlp = pipeline("sentiment-analysis", model="ProsusAI/finbert")
     return nlp(headline)
 
 
-## get news articles for a company 
-#res_news = get_finnhub_data('/company-news?symbol=AAPL&from=2023-08-15&to=2023-08-20')
-#print(res_news[0].keys())
-#for item in res_news:
-    #dt_object = datetime.datetime.fromtimestamp(item['datetime']).strftime("%Y-%m-%d")
-    #print(item['headline'], item['source'], dt_object)
+# --------------------------------- get news articles for a company --------------------------------- #
+conn = sqlite3.connect('fin_data.db')
+c = conn.cursor()
+
+c.execute("""create table if not exists company_news ( 
+        id text primary key, 
+        ticker text, 
+        category text, 
+        headline text, 
+        date_stamp text, 
+        sentiment_label text,
+        sentiment_score real
+        )""")
+
+
+res_news = get_finnhub_data('/company-news?symbol=AAPL&from=2023-08-15&to=2023-08-17')
+print(res_news[0].keys())
+for item in res_news:
+    dt_object = datetime.datetime.fromtimestamp(item['datetime']).strftime("%Y-%m-%d")
+    sentiment = sentiment_analysis(item['headline'])
+    sentiment_label = sentiment[0]['label']
+    sentiment_score = sentiment[0]['score']
+    print(item['headline'], dt_object, sentiment[0]['label'])
+
+    # Prepare your query and data
+    query = """
+    INSERT INTO company_news 
+    VALUES (?, ?, ?, ?, ?, ?, ?)
+    """
+    data = (item['id'], 'AAPL', item['category'], item['headline'], dt_object, sentiment_label, sentiment_score)
+
+    # Execute the query with the data
+    #c.execute(query, data)
+
+    
+rows = c.execute("""
+       select * from company_news
+""")
+
+column_names = [description[0] for description in c.description]
 
+# Create a DataFrame
+df = pd.DataFrame(rows, columns=column_names)
+
+print(df)
+
+
+# --------------------------------- get basic financials ---------------------------------#
 
-## get basic financials
 #res_basic_fins = get_finnhub_data('/stock/metric?symbol=AAPL&metric=all')
 #print(res_basic_fins['metric'].keys())
 #print(res_basic_fins['series']['annual'].keys())
 #print(res_basic_fins['series']['quarterly'].keys())
 
 
-## get insider sentiment
+# --------------------------------- get insider sentiment --------------------------------- #
+
 #res_sentiment = get_finnhub_data('/stock/insider-sentiment?symbol=AAPL')
 #print(res_sentiment['data'][0].keys())
 
 
-# # put data in database after figuring out what data we want to store
-# conn = sqlite3.connect('fin_data.db')
-# c = conn.cursor()
-# c.execute("""
-#        insert into test values (2, 'test value two')
-# """)
-
 
 
-# conn.commit()
-# conn.close()
+conn.commit()
+conn.close()

requirements.txt

@@ -17,4 +17,5 @@ transformers
 requests
 datetime
 pysqlite3 == 0.5.2
-streamlit
+streamlit
+pygwalker