Sentiment analyzis.

database.py

@@ -12,11 +12,13 @@ def get_db_connection():
     return conn
 
 def initialize_db():
-    """Initializes the database and creates tables if they don't exist."""
+    """
+    Initializes the database and creates the necessary tables if they don't exist.
+    """
     conn = get_db_connection()
     cursor = conn.cursor()
 
-    # --- Create tickers table ---
+    # --- Create tickers table (This is the corrected section) ---
     cursor.execute("""
         CREATE TABLE IF NOT EXISTS tickers (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -26,7 +28,7 @@ def initialize_db():
         )
     """)
 
-    # --- Create subreddits table ---
+    # --- Create subreddits table (This is the corrected section) ---
     cursor.execute("""
         CREATE TABLE IF NOT EXISTS subreddits (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -34,7 +36,7 @@ def initialize_db():
         )
     """)
 
-    # --- Create mentions table ---
+    # --- Create mentions table with sentiment_score column ---
     cursor.execute("""
         CREATE TABLE IF NOT EXISTS mentions (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -53,12 +55,23 @@ def initialize_db():
     conn.close()
     print("Database initialized successfully.")
 
+def add_mention(conn, ticker_id, subreddit_id, post_id, timestamp, sentiment):
+    """Adds a new mention with its sentiment score to the database."""
+    cursor = conn.cursor()
+    try:
+        cursor.execute(
+            "INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_timestamp, sentiment_score) VALUES (?, ?, ?, ?, ?)",
+            (ticker_id, subreddit_id, post_id, timestamp, sentiment)
+        )
+        conn.commit()
+    except sqlite3.IntegrityError:
+        pass  # Ignore duplicate mentions
+
 def get_or_create_entity(conn, table_name, column_name, value):
     """Generic function to get or create an entity and return its ID."""
     cursor = conn.cursor()
     cursor.execute(f"SELECT id FROM {table_name} WHERE {column_name} = ?", (value,))
     result = cursor.fetchone()
-
     if result:
         return result['id']
     else:
@@ -66,18 +79,6 @@ def get_or_create_entity(conn, table_name, column_name, value):
         conn.commit()
         return cursor.lastrowid
 
-def add_mention(conn, ticker_id, subreddit_id, post_id, timestamp):
-    """Adds a new mention to the database, ignoring duplicates."""
-    cursor = conn.cursor()
-    try:
-        cursor.execute(
-            "INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_timestamp) VALUES (?, ?, ?, ?)",
-            (ticker_id, subreddit_id, post_id, timestamp)
-        )
-        conn.commit()
-    except sqlite3.IntegrityError:
-        pass
-
 def update_ticker_market_cap(conn, ticker_id, market_cap):
     """Updates the market cap and timestamp for a specific ticker."""
     cursor = conn.cursor()
@@ -95,7 +96,7 @@ def get_ticker_info(conn, ticker_id):
     return cursor.fetchone()
 
 def generate_summary_report():
-    """Queries the DB to generate and print a summary with market caps."""
+    """Queries the DB to generate a summary with market caps and avg. sentiment."""
     print("\n--- Summary Report ---")
     conn = get_db_connection()
     cursor = conn.cursor()
@@ -104,33 +105,38 @@ def generate_summary_report():
         SELECT
             t.symbol,
             t.market_cap,
-            COUNT(m.id) as mention_count
+            COUNT(m.id) as mention_count,
+            AVG(m.sentiment_score) as avg_sentiment
         FROM mentions m
         JOIN tickers t ON m.ticker_id = t.id
         GROUP BY t.symbol, t.market_cap
         ORDER BY mention_count DESC
         LIMIT 20;
     """
-
     results = cursor.execute(query).fetchall()
 
-    print(f"{'Ticker':<10} | {'Mentions':<10} | {'Market Cap':<20}")
-    print("-" * 45)
+    print(f"{'Ticker':<10} | {'Mentions':<10} | {'Sentiment':<18} | {'Market Cap':<20}")
+    print("-" * 65)
 
     for row in results:
+        # Format Market Cap
         market_cap_str = "N/A"
-        if row['market_cap']:
-            # Format market cap into a readable string (e.g., $1.23T, $45.6B, $123.4M)
+        if row['market_cap'] and row['market_cap'] > 0:
             mc = row['market_cap']
-            if mc >= 1e12:
-                market_cap_str = f"${mc/1e12:.2f}T"
-            elif mc >= 1e9:
-                market_cap_str = f"${mc/1e9:.2f}B"
-            elif mc >= 1e6:
-                market_cap_str = f"${mc/1e6:.2f}M"
-            else:
-                market_cap_str = f"${mc:,}"
+            if mc >= 1e12: market_cap_str = f"${mc/1e12:.2f}T"
+            elif mc >= 1e9: market_cap_str = f"${mc/1e9:.2f}B"
+            elif mc >= 1e6: market_cap_str = f"${mc/1e6:.2f}M"
+            else: market_cap_str = f"${mc:,}"
+        
+        # Determine Sentiment Label
+        sentiment_score = row['avg_sentiment']
+        if sentiment_score is not None:
+            if sentiment_score > 0.1: sentiment_label = f"Bullish ({sentiment_score:+.2f})"
+            elif sentiment_score < -0.1: sentiment_label = f"Bearish ({sentiment_score:+.2f})"
+            else: sentiment_label = f"Neutral ({sentiment_score:+.2f})"
+        else:
+            sentiment_label = "N/A"
 
-        print(f"{row['symbol']:<10} | {row['mention_count']:<10} | {market_cap_str:<20}")
+        print(f"{row['symbol']:<10} | {row['mention_count']:<10} | {sentiment_label:<18} | {market_cap_str:<20}")
 
     conn.close()