pkhamre/reddit_stock_analyzer
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Added web dashboard.

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This commit is contained in:
Pål-Kristian Hamre
2025-07-21 20:13:18 +02:00
parent e6a853ed38
commit b82ba39aab
9 changed files with 321 additions and 60 deletions
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88
rstat_tool/database.py
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@@ -2,7 +2,6 @@
import sqlite3
import time
# --- IMPORT ADDED BACK IN ---
from .ticker_extractor import COMMON_WORDS_BLACKLIST
DB_FILE = "reddit_stocks.db"
@@ -14,9 +13,13 @@ def get_db_connection():
return conn
def initialize_db():
# ... (This function is unchanged)
"""
Initializes the database and creates the necessary tables if they don't exist.
"""
conn = get_db_connection()
cursor = conn.cursor()
# --- Create tickers table ---
cursor.execute("""
CREATE TABLE IF NOT EXISTS tickers (
id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -25,12 +28,16 @@ def initialize_db():
last_updated INTEGER
)
""")
# --- Create subreddits table ---
cursor.execute("""
CREATE TABLE IF NOT EXISTS subreddits (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL UNIQUE
)
""")
# --- Create mentions table ---
cursor.execute("""
CREATE TABLE IF NOT EXISTS mentions (
id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -44,11 +51,11 @@ def initialize_db():
UNIQUE(ticker_id, post_id, sentiment_score)
)
""")
conn.commit()
conn.close()
print("Database initialized successfully.")
# --- CLEANUP FUNCTION ADDED BACK IN ---
def clean_stale_tickers():
"""
Removes tickers and their associated mentions from the database
@@ -58,7 +65,6 @@ def clean_stale_tickers():
conn = get_db_connection()
cursor = conn.cursor()
# Find ticker IDs that match the blacklist
placeholders = ','.join('?' for _ in COMMON_WORDS_BLACKLIST)
query = f"SELECT id, symbol FROM tickers WHERE symbol IN ({placeholders})"
@@ -74,11 +80,7 @@ def clean_stale_tickers():
ticker_id = ticker['id']
ticker_symbol = ticker['symbol']
print(f"Removing stale ticker '{ticker_symbol}' (ID: {ticker_id})...")
# 1. Delete all mentions associated with this ticker ID
cursor.execute("DELETE FROM mentions WHERE ticker_id = ?", (ticker_id,))
# 2. Delete the ticker itself
cursor.execute("DELETE FROM tickers WHERE id = ?", (ticker_id,))
deleted_count = conn.total_changes
@@ -88,7 +90,7 @@ def clean_stale_tickers():
def add_mention(conn, ticker_id, subreddit_id, post_id, timestamp, sentiment):
# ... (This function is unchanged)
"""Adds a new mention with its sentiment score to the database."""
cursor = conn.cursor()
try:
cursor.execute(
@@ -99,49 +101,44 @@ def add_mention(conn, ticker_id, subreddit_id, post_id, timestamp, sentiment):
except sqlite3.IntegrityError:
pass
# ... (get_or_create_entity, update_ticker_market_cap, get_ticker_info are unchanged)
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']
if result:
return result['id']
else:
cursor.execute(f"INSERT INTO {table_name} ({column_name}) VALUES (?)", (value,))
conn.commit()
return cursor.lastrowid
def update_ticker_market_cap(conn, ticker_id, market_cap):
# ...
"""Updates the market cap and timestamp for a specific ticker."""
cursor = conn.cursor()
current_timestamp = int(time.time())
cursor.execute("UPDATE tickers SET market_cap = ?, last_updated = ? WHERE id = ?", (market_cap, current_timestamp, ticker_id))
conn.commit()
def get_ticker_info(conn, ticker_id):
# ...
"""Retrieves all info for a specific ticker by its ID."""
cursor = conn.cursor()
cursor.execute("SELECT * FROM tickers WHERE id = ?", (ticker_id,))
return cursor.fetchone()
def generate_summary_report(limit=20):
# ... (This function is unchanged)
"""Queries the DB to generate a summary for the command-line tool."""
print(f"\n--- Top {limit} Tickers by Mention Count ---")
conn = get_db_connection()
cursor = conn.cursor()
query = """
SELECT
t.symbol,
t.market_cap,
COUNT(m.id) as mention_count,
t.symbol, t.market_cap, COUNT(m.id) as mention_count,
SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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 ?;
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 ?;
"""
results = cursor.execute(query, (limit,)).fetchall()
header = f"{'Ticker':<8} | {'Mentions':<8} | {'Bullish':<8} | {'Bearish':<8} | {'Neutral':<8} | {'Market Cap':<15}"
@@ -155,4 +152,47 @@ def generate_summary_report(limit=20):
elif mc >= 1e9: market_cap_str = f"${mc/1e9:.2f}B"
else: market_cap_str = f"${mc/1e6:.2f}M"
print(f"{row['symbol']:<8} | {row['mention_count']:<8} | {row['bullish_mentions']:<8} | {row['bearish_mentions']:<8} | {row['neutral_mentions']:<8} | {market_cap_str:<15}")
conn.close()
conn.close()
def get_overall_summary(limit=50):
"""Gets the top tickers across all subreddits for the dashboard."""
conn = get_db_connection()
query = """
SELECT
t.symbol, t.market_cap, COUNT(m.id) as mention_count,
SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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 ?;
"""
results = conn.execute(query, (limit,)).fetchall()
conn.close()
return results
def get_subreddit_summary(subreddit_name, limit=50):
"""Gets the top tickers for a specific subreddit for the dashboard."""
conn = get_db_connection()
query = """
SELECT
t.symbol, t.market_cap, COUNT(m.id) as mention_count,
SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
FROM mentions m
JOIN tickers t ON m.ticker_id = t.id
JOIN subreddits s ON m.subreddit_id = s.id
WHERE s.name = ?
GROUP BY t.symbol, t.market_cap ORDER BY mention_count DESC LIMIT ?;
"""
results = conn.execute(query, (subreddit_name, limit)).fetchall()
conn.close()
return results
def get_all_scanned_subreddits():
"""Gets a unique list of all subreddits we have data for."""
# --- THIS IS THE CORRECTED LINE ---
conn = get_db_connection()
results = conn.execute("SELECT DISTINCT name FROM subreddits ORDER BY name ASC;").fetchall()
conn.close()
return [row['name'] for row in results]