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728fe43571
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ef91b735b7
| Author | SHA1 | Date | |
|---|---|---|---|
| ef91b735b7 | |||
| d330f31950 |
@@ -46,12 +46,12 @@ def initialize_db():
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ticker_id INTEGER,
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ticker_id INTEGER,
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subreddit_id INTEGER,
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subreddit_id INTEGER,
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post_id TEXT NOT NULL,
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post_id TEXT NOT NULL,
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mention_type TEXT NOT NULL, -- Can be 'post' or 'comment'
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mention_type TEXT NOT NULL,
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mention_sentiment REAL, -- Renamed from sentiment_score for clarity
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post_avg_sentiment REAL, -- NEW: Stores the avg sentiment of the whole post
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mention_timestamp INTEGER NOT NULL,
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mention_timestamp INTEGER NOT NULL,
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sentiment_score REAL,
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FOREIGN KEY (ticker_id) REFERENCES tickers (id),
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FOREIGN KEY (ticker_id) REFERENCES tickers (id),
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FOREIGN KEY (subreddit_id) REFERENCES subreddits (id),
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FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
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UNIQUE(ticker_id, post_id, mention_type, sentiment_score)
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)
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)
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""")
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""")
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@@ -105,13 +105,69 @@ def clean_stale_tickers():
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conn.close()
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conn.close()
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print(f"Cleanup complete. Removed {deleted_count} records.")
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print(f"Cleanup complete. Removed {deleted_count} records.")
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def get_db_connection():
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conn = sqlite3.connect(DB_FILE)
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conn.row_factory = sqlite3.Row
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return conn
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def add_mention(conn, ticker_id, subreddit_id, post_id, mention_type, timestamp, sentiment):
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def initialize_db():
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conn = get_db_connection()
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cursor = conn.cursor()
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS tickers (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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symbol TEXT NOT NULL UNIQUE,
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market_cap INTEGER,
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closing_price REAL,
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last_updated INTEGER
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)
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""")
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS subreddits (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT NOT NULL UNIQUE
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)
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""")
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS mentions (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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ticker_id INTEGER,
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subreddit_id INTEGER,
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post_id TEXT NOT NULL,
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mention_type TEXT NOT NULL,
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mention_sentiment REAL,
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post_avg_sentiment REAL,
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mention_timestamp INTEGER NOT NULL,
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FOREIGN KEY (ticker_id) REFERENCES tickers (id),
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FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
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)
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""")
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cursor.execute("""
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CREATE TABLE IF NOT EXISTS posts (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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post_id TEXT NOT NULL UNIQUE,
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title TEXT NOT NULL,
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post_url TEXT,
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subreddit_id INTEGER,
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post_timestamp INTEGER,
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comment_count INTEGER,
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avg_comment_sentiment REAL,
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FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
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)
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""")
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conn.commit()
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conn.close()
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print("Database initialized successfully.")
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def add_mention(conn, ticker_id, subreddit_id, post_id, mention_type, timestamp, mention_sentiment, post_avg_sentiment=None):
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cursor = conn.cursor()
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cursor = conn.cursor()
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try:
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try:
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cursor.execute(
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cursor.execute(
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"INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_type, mention_timestamp, sentiment_score) VALUES (?, ?, ?, ?, ?, ?)",
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"""
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(ticker_id, subreddit_id, post_id, mention_type, timestamp, sentiment)
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INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_type, mention_timestamp, mention_sentiment, post_avg_sentiment)
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VALUES (?, ?, ?, ?, ?, ?, ?)
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""",
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(ticker_id, subreddit_id, post_id, mention_type, timestamp, mention_sentiment, post_avg_sentiment)
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)
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)
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conn.commit()
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conn.commit()
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except sqlite3.IntegrityError:
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except sqlite3.IntegrityError:
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@@ -150,19 +206,26 @@ def generate_summary_report(limit=20):
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print(f"\n--- Top {limit} Tickers by Mention Count ---")
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print(f"\n--- Top {limit} Tickers by Mention Count ---")
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conn = get_db_connection()
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conn = get_db_connection()
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cursor = conn.cursor()
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cursor = conn.cursor()
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# --- UPDATED QUERY: Changed m.sentiment_score to m.mention_sentiment ---
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query = """
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query = """
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SELECT
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SELECT
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t.symbol, t.market_cap, COUNT(m.id) as mention_count,
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t.symbol, t.market_cap, t.closing_price,
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SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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COUNT(m.id) as mention_count,
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SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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SUM(CASE WHEN m.mention_sentiment BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id
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GROUP BY t.symbol, t.market_cap ORDER BY mention_count DESC LIMIT ?;
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GROUP BY t.symbol, t.market_cap, t.closing_price
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ORDER BY mention_count DESC
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LIMIT ?;
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"""
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"""
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results = cursor.execute(query, (limit,)).fetchall()
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results = cursor.execute(query, (limit,)).fetchall()
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header = f"{'Ticker':<8} | {'Mentions':<8} | {'Bullish':<8} | {'Bearish':<8} | {'Neutral':<8} | {'Market Cap':<15}"
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header = f"{'Ticker':<8} | {'Mentions':<8} | {'Bullish':<8} | {'Bearish':<8} | {'Neutral':<8} | {'Market Cap':<15} | {'Close Price':<12}"
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print(header)
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print(header)
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print("-" * len(header))
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print("-" * (len(header) + 2)) # Adjusted separator length
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for row in results:
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for row in results:
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market_cap_str = "N/A"
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market_cap_str = "N/A"
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if row['market_cap'] and row['market_cap'] > 0:
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if row['market_cap'] and row['market_cap'] > 0:
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@@ -170,45 +233,19 @@ def generate_summary_report(limit=20):
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if mc >= 1e12: market_cap_str = f"${mc/1e12:.2f}T"
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if mc >= 1e12: market_cap_str = f"${mc/1e12:.2f}T"
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elif mc >= 1e9: market_cap_str = f"${mc/1e9:.2f}B"
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elif mc >= 1e9: market_cap_str = f"${mc/1e9:.2f}B"
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else: market_cap_str = f"${mc/1e6:.2f}M"
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else: market_cap_str = f"${mc/1e6:.2f}M"
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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}")
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conn.close()
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def get_overall_summary(limit=50):
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closing_price_str = f"${row['closing_price']:.2f}" if row['closing_price'] else "N/A"
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conn = get_db_connection()
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query = """
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SELECT
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t.symbol, t.market_cap, t.closing_price, -- Added closing_price
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COUNT(m.id) as mention_count,
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SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id
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GROUP BY t.symbol, t.market_cap, t.closing_price -- Added closing_price
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ORDER BY mention_count DESC LIMIT ?;
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"""
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results = conn.execute(query, (limit,)).fetchall()
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conn.close()
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return results
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def get_subreddit_summary(subreddit_name, limit=50):
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print(
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conn = get_db_connection()
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f"{row['symbol']:<8} | "
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query = """
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f"{row['mention_count']:<8} | "
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SELECT
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f"{row['bullish_mentions']:<8} | "
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t.symbol, t.market_cap, t.closing_price, -- Added closing_price
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f"{row['bearish_mentions']:<8} | "
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COUNT(m.id) as mention_count,
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f"{row['neutral_mentions']:<8} | "
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SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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f"{market_cap_str:<15} | "
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SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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f"{closing_price_str:<12}"
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SUM(CASE WHEN m.sentiment_score BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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)
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FROM mentions m
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JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON m.subreddit_id = s.id
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WHERE s.name = ?
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GROUP BY t.symbol, t.market_cap, t.closing_price -- Added closing_price
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ORDER BY mention_count DESC LIMIT ?;
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"""
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results = conn.execute(query, (subreddit_name, limit)).fetchall()
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conn.close()
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conn.close()
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return results
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def get_all_scanned_subreddits():
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def get_all_scanned_subreddits():
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"""Gets a unique list of all subreddits we have data for."""
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"""Gets a unique list of all subreddits we have data for."""
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@@ -253,20 +290,52 @@ def get_deep_dive_details(ticker_symbol):
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conn.close()
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conn.close()
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return results
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return results
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def get_image_view_summary(subreddit_name):
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def get_overall_summary(limit=50):
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"""
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conn = get_db_connection()
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Gets a summary of tickers for the image view, including post, comment,
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query = """
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and sentiment counts.
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SELECT
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"""
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t.symbol, t.market_cap, t.closing_price,
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COUNT(m.id) as mention_count,
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SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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SUM(CASE WHEN m.mention_sentiment BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id
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GROUP BY t.symbol, t.market_cap, t.closing_price
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ORDER BY mention_count DESC LIMIT ?;
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"""
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results = conn.execute(query, (limit,)).fetchall()
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conn.close()
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return results
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def get_subreddit_summary(subreddit_name, limit=50):
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conn = get_db_connection()
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query = """
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SELECT
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t.symbol, t.market_cap, t.closing_price,
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COUNT(m.id) as mention_count,
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SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
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SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
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SUM(CASE WHEN m.mention_sentiment BETWEEN -0.1 AND 0.1 THEN 1 ELSE 0 END) as neutral_mentions
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FROM mentions m
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JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON m.subreddit_id = s.id
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WHERE s.name = ?
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GROUP BY t.symbol, t.market_cap, t.closing_price
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ORDER BY mention_count DESC LIMIT ?;
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"""
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results = conn.execute(query, (subreddit_name, limit)).fetchall()
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conn.close()
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return results
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def get_image_view_summary(subreddit_name):
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conn = get_db_connection()
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conn = get_db_connection()
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# This query now also counts sentiment types
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query = """
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query = """
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SELECT
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SELECT
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t.symbol,
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t.symbol,
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COUNT(CASE WHEN m.mention_type = 'post' THEN 1 END) as post_mentions,
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COUNT(CASE WHEN m.mention_type = 'post' THEN 1 END) as post_mentions,
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COUNT(CASE WHEN m.mention_type = 'comment' THEN 1 END) as comment_mentions,
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COUNT(CASE WHEN m.mention_type = 'comment' THEN 1 END) as comment_mentions,
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COUNT(CASE WHEN m.sentiment_score > 0.1 THEN 1 END) as bullish_mentions,
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COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
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COUNT(CASE WHEN m.sentiment_score < -0.1 THEN 1 END) as bearish_mentions
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COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
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FROM mentions m
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FROM mentions m
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JOIN tickers t ON m.ticker_id = t.id
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JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON m.subreddit_id = s.id
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JOIN subreddits s ON m.subreddit_id = s.id
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@@ -280,23 +349,16 @@ def get_image_view_summary(subreddit_name):
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return results
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return results
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def get_weekly_summary_for_subreddit(subreddit_name):
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def get_weekly_summary_for_subreddit(subreddit_name):
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"""
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Gets a weekly summary for a specific subreddit for the image view.
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"""
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conn = get_db_connection()
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conn = get_db_connection()
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# Calculate the timestamp for 7 days ago
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seven_days_ago = datetime.utcnow() - timedelta(days=7)
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seven_days_ago = datetime.utcnow() - timedelta(days=7)
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seven_days_ago_timestamp = int(seven_days_ago.timestamp())
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seven_days_ago_timestamp = int(seven_days_ago.timestamp())
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# The query is the same as before, but with an added WHERE clause for the timestamp
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query = """
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query = """
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SELECT
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SELECT
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t.symbol,
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t.symbol,
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COUNT(CASE WHEN m.mention_type = 'post' THEN 1 END) as post_mentions,
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COUNT(CASE WHEN m.mention_type = 'post' THEN 1 END) as post_mentions,
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COUNT(CASE WHEN m.mention_type = 'comment' THEN 1 END) as comment_mentions,
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COUNT(CASE WHEN m.mention_type = 'comment' THEN 1 END) as comment_mentions,
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COUNT(CASE WHEN m.sentiment_score > 0.1 THEN 1 END) as bullish_mentions,
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COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
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COUNT(CASE WHEN m.sentiment_score < -0.1 THEN 1 END) as bearish_mentions
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COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
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FROM mentions m
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FROM mentions m
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JOIN tickers t ON m.ticker_id = t.id
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JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON m.subreddit_id = s.id
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JOIN subreddits s ON m.subreddit_id = s.id
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@@ -3,50 +3,52 @@
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COMMON_WORDS_BLACKLIST = {
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COMMON_WORDS_BLACKLIST = {
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"401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
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"401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
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"AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
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"AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
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"ARE", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL", "ATM",
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"ARE", "AREA", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL",
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"AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA", "BIG",
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"ATM", "AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA",
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"BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS", "BRB",
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"BIG", "BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS",
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"BRL", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST", "BUT", "BUY",
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"BRB", "BRL", "BROKE", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST",
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"BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO", "CEST", "CET",
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"BUT", "BUY", "BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO",
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"CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC", "CNY", "COKE",
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"CEST", "CET", "CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC",
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"COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB", "CTO", "CYCLE",
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"CNY", "COKE", "COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB",
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"CZK", "DAO", "DATE", "DAX", "DAY", "DCA", "DD", "DEBT", "DEX", "DIA",
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"CTO", "CYCLE", "CZK", "DAO", "DATE", "DAX", "DAY", "DAYS", "DCA", "DD",
|
||||||
"DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE", "DOJ", "DONT", "DR",
|
"DEBT", "DEX", "DIA", "DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE",
|
||||||
"EACH", "EARLY", "EARN", "ECB", "EDGAR", "EDIT", "EDT", "EMA", "END", "EOD",
|
"DOJ", "DONT", "DR", "EACH", "EARLY", "EARN", "EAST", "ECB", "EDGAR", "EDIT",
|
||||||
"EOW", "EOY", "EPA", "EPS", "ER", "ESG", "EST", "ETF", "ETFS", "ETH",
|
"EDT", "EMA", "END", "ENV", "EOD", "EOW", "EOY", "EPA", "EPS", "ER",
|
||||||
"EU", "EUR", "EV", "EVEN", "EVERY", "FAQ", "FAR", "FAST", "FBI", "FD",
|
"ESG", "EST", "ETF", "ETFS", "ETH", "EU", "EUR", "EV", "EVEN", "EVERY",
|
||||||
"FDA", "FIHTX", "FINRA", "FINT", "FINTX", "FINTY", "FIRST", "FOMC", "FOMO", "FOR",
|
"FAQ", "FAR", "FAST", "FBI", "FD", "FDA", "FIHTX", "FINRA", "FINT", "FINTX",
|
||||||
"FOREX", "FRAUD", "FRG", "FROM", "FSPSX", "FTSE", "FUCK", "FUD", "FULL", "FUND",
|
"FINTY", "FIRST", "FOMC", "FOMO", "FOR", "FOREX", "FRAUD", "FRG", "FROM", "FSPSX",
|
||||||
"FXAIX", "FXIAX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET",
|
"FTD", "FTSE", "FUCK", "FUD", "FULL", "FUND", "FXAIX", "FXIAX", "FY", "FYI",
|
||||||
"GL", "GLHF", "GMT", "GO", "GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB",
|
"FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET", "GL", "GLHF", "GMT", "GO",
|
||||||
"GTG", "HALF", "HAS", "HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT",
|
"GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB", "GTG", "GUH", "HALF", "HAS",
|
||||||
"HKD", "HODL", "HOLD", "HOUR", "HSA", "HUF", "IF", "II", "IKZ", "IMHO",
|
"HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT", "HKD", "HODL", "HOLD",
|
||||||
"IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISM",
|
"HOUR", "HSA", "HUF", "HUGE", "IBS", "IF", "II", "IKKE", "IKZ", "IMHO",
|
||||||
"IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY", "JST",
|
"IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISIN",
|
||||||
"JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST", "LATE",
|
"ISM", "IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY",
|
||||||
"LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC", "LLM",
|
"JST", "JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST",
|
||||||
"LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A", "MA",
|
"LATE", "LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC",
|
||||||
"MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID", "MIGHT",
|
"LLM", "LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A",
|
||||||
"MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST", "MXN",
|
"MA", "MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID",
|
||||||
"MY", "NATO", "NEAR", "NEED", "NEVER", "NEW", "NEXT", "NFA", "NFC", "NFT",
|
"MIGHT", "MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST",
|
||||||
"NGMI", "NIGHT", "NO", "NOK", "NONE", "NOT", "NOW", "NSA", "NULL", "NUT",
|
"MXN", "MY", "NASA", "NATO", "NEAR", "NEAT", "NEED", "NEVER", "NEW", "NEXT",
|
||||||
"NYSE", "NZD", "OBV", "OEM", "OF", "OG", "OK", "OLD", "ON", "ONE",
|
"NFA", "NFC", "NFT", "NGMI", "NIGHT", "NO", "NOK", "NONE", "NORTH", "NOT",
|
||||||
"ONLY", "OP", "OPEX", "OR", "OS", "OSCE", "OTC", "OTM", "OUGHT", "OUT",
|
"NOW", "NSA", "NULL", "NUT", "NYSE", "NZ", "NZD", "OBV", "OEM", "OF",
|
||||||
"OVER", "OWN", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG", "PEW", "PLAN",
|
"OG", "OK", "OLD", "ON", "ONE", "ONLY", "OP", "OPEX", "OR", "OS",
|
||||||
"PLN", "PM", "PMI", "POC", "POS", "PPI", "PR", "PRICE", "PROFIT", "PSA",
|
"OSCE", "OTC", "OTM", "OUGHT", "OUT", "OVER", "OWN", "PANIC", "PC", "PDT",
|
||||||
"PST", "PT", "PUT", "Q1", "Q2", "Q3", "Q4", "QQQ", "QR", "RBA",
|
"PE", "PEAK", "PEG", "PEW", "PLAN", "PLN", "PM", "PMI", "POC", "POS",
|
||||||
"RBNZ", "RE", "REAL", "REIT", "REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK",
|
"POSCO", "PPI", "PR", "PRICE", "PROFIT", "PSA", "PST", "PT", "PUT", "Q1",
|
||||||
"ROE", "ROFL", "ROI", "ROTH", "RSD", "RSI", "RUB", "RULE", "SAME", "SAVE",
|
"Q2", "Q3", "Q4", "QQQ", "QR", "RBA", "RBNZ", "RE", "REAL", "REIT",
|
||||||
"SCALP", "SCAM", "SCHB", "SEC", "SEE", "SEK", "SELL", "SEP", "SGD", "SHALL",
|
"REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK", "ROE", "ROFL", "ROI", "ROTH",
|
||||||
"SHARE", "SHORT", "SL", "SMA", "SMALL", "SO", "SOLIS", "SOME", "SOON", "SP",
|
"RSD", "RSI", "RUB", "RULE", "SAME", "SAVE", "SCALP", "SCAM", "SCHB", "SEC",
|
||||||
"SPAC", "SPEND", "SPLG", "SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR",
|
"SEE", "SEK", "SELL", "SEP", "SGD", "SHALL", "SHARE", "SHORT", "SL", "SMA",
|
||||||
"SWING", "TA", "TAG", "TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS",
|
"SMALL", "SO", "SOLIS", "SOME", "SOON", "SOUTH", "SP", "SPAC", "SPEND", "SPLG",
|
||||||
"TIME", "TITS", "TL", "TL;DR", "TLDR", "TO", "TODAY", "TOTAL", "TRADE", "TREND",
|
"SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR", "SWING", "TA", "TAG",
|
||||||
"TRUE", "TRY", "TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA",
|
"TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS", "TIME", "TITS", "TL",
|
||||||
"USD", "UTC", "VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH",
|
"TL;DR", "TLDR", "TO", "TODAY", "TOLD", "TOTAL", "TRADE", "TREND", "TRUE", "TRY",
|
||||||
"WAY", "WE", "WEB3", "WEEK", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WORDS",
|
"TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA", "USD", "UTC",
|
||||||
"WORTH", "WOULD", "WSB", "WTF", "XRP", "YES", "YET", "YIELD", "YOLO", "YOU",
|
"VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH", "WAY", "WE",
|
||||||
"YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
|
"WEB3", "WEEK", "WEST", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WIRE", "WORDS",
|
||||||
|
"WORTH", "WOULD", "WSB", "WTF", "XO", "XRP", "YES", "YET", "YIELD", "YOLO",
|
||||||
|
"YOU", "YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
|
||||||
}
|
}
|
||||||
|
|
||||||
def format_and_print_list(word_set, words_per_line=10):
|
def format_and_print_list(word_set, words_per_line=10):
|
||||||
|
|||||||
@@ -43,6 +43,11 @@ def get_reddit_instance():
|
|||||||
return praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent)
|
return praw.Reddit(client_id=client_id, client_secret=client_secret, user_agent=user_agent)
|
||||||
|
|
||||||
def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100, days_to_scan=1):
|
def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100, days_to_scan=1):
|
||||||
|
"""
|
||||||
|
Scans subreddits with a hybrid mention counting logic.
|
||||||
|
- If a ticker is in the title, it gets credit for all comments.
|
||||||
|
- If not, tickers only get credit for direct mentions in comments.
|
||||||
|
"""
|
||||||
conn = database.get_db_connection()
|
conn = database.get_db_connection()
|
||||||
post_age_limit = days_to_scan * 86400
|
post_age_limit = days_to_scan * 86400
|
||||||
current_time = time.time()
|
current_time = time.time()
|
||||||
@@ -56,53 +61,77 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
|
|||||||
|
|
||||||
for submission in subreddit.new(limit=post_limit):
|
for submission in subreddit.new(limit=post_limit):
|
||||||
if (current_time - submission.created_utc) > post_age_limit:
|
if (current_time - submission.created_utc) > post_age_limit:
|
||||||
print(f" -> Reached posts older than the {days_to_scan}-day limit. Moving to next subreddit.")
|
print(f" -> Reached posts older than the {days_to_scan}-day limit.")
|
||||||
break
|
break
|
||||||
|
|
||||||
post_text = submission.title + " " + submission.selftext
|
# --- NEW HYBRID LOGIC ---
|
||||||
tickers_in_post = extract_tickers(post_text)
|
|
||||||
if tickers_in_post:
|
tickers_in_title = set(extract_tickers(submission.title))
|
||||||
post_sentiment = get_sentiment_score(submission.title)
|
all_tickers_found_in_post = set(tickers_in_title) # Start a set to track all tickers for financials
|
||||||
for ticker_symbol in set(tickers_in_post):
|
|
||||||
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
|
||||||
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'post', int(submission.created_utc), post_sentiment)
|
|
||||||
|
|
||||||
ticker_info = database.get_ticker_info(conn, ticker_id)
|
|
||||||
if not ticker_info['last_updated'] or (current_time - ticker_info['last_updated'] > MARKET_CAP_REFRESH_INTERVAL):
|
|
||||||
print(f" -> Fetching financial data for {ticker_symbol}...")
|
|
||||||
financials = get_financial_data(ticker_symbol)
|
|
||||||
database.update_ticker_financials(
|
|
||||||
conn, ticker_id,
|
|
||||||
financials['market_cap'] or ticker_info['market_cap'],
|
|
||||||
financials['closing_price'] or ticker_info['closing_price']
|
|
||||||
)
|
|
||||||
|
|
||||||
submission.comments.replace_more(limit=0)
|
submission.comments.replace_more(limit=0)
|
||||||
all_comment_sentiments = []
|
all_comments = submission.comments.list()[:comment_limit]
|
||||||
for comment in submission.comments.list()[:comment_limit]:
|
|
||||||
all_comment_sentiments.append(get_sentiment_score(comment.body))
|
# --- CASE A: Tickers were found in the title ---
|
||||||
tickers_in_comment = extract_tickers(comment.body)
|
if tickers_in_title:
|
||||||
if tickers_in_comment:
|
print(f" -> Title Mention(s): {', '.join(tickers_in_title)}. Attributing all comments.")
|
||||||
|
post_sentiment = get_sentiment_score(submission.title)
|
||||||
|
|
||||||
|
# Add one 'post' mention for each title ticker
|
||||||
|
for ticker_symbol in tickers_in_title:
|
||||||
|
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
||||||
|
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'post', int(submission.created_utc), post_sentiment)
|
||||||
|
|
||||||
|
# Add one 'comment' mention for EACH comment FOR EACH title ticker
|
||||||
|
for comment in all_comments:
|
||||||
comment_sentiment = get_sentiment_score(comment.body)
|
comment_sentiment = get_sentiment_score(comment.body)
|
||||||
for ticker_symbol in set(tickers_in_comment):
|
for ticker_symbol in tickers_in_title:
|
||||||
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
||||||
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
|
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
|
||||||
|
|
||||||
|
# --- CASE B: No tickers in the title, scan comments individually ---
|
||||||
|
else:
|
||||||
|
for comment in all_comments:
|
||||||
|
tickers_in_comment = set(extract_tickers(comment.body))
|
||||||
|
if tickers_in_comment:
|
||||||
|
all_tickers_found_in_post.update(tickers_in_comment) # Add to our set for financials
|
||||||
|
comment_sentiment = get_sentiment_score(comment.body)
|
||||||
|
for ticker_symbol in tickers_in_comment:
|
||||||
|
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
||||||
|
database.add_mention(conn, ticker_id, subreddit_id, submission.id, 'comment', int(comment.created_utc), comment_sentiment)
|
||||||
|
|
||||||
|
# --- EFFICIENT FINANCIALS UPDATE ---
|
||||||
|
# Now, update market cap once for every unique ticker found in the whole post
|
||||||
|
for ticker_symbol in all_tickers_found_in_post:
|
||||||
|
ticker_id = database.get_or_create_entity(conn, 'tickers', 'symbol', ticker_symbol)
|
||||||
|
ticker_info = database.get_ticker_info(conn, ticker_id)
|
||||||
|
if not ticker_info['last_updated'] or (current_time - ticker_info['last_updated'] > MARKET_CAP_REFRESH_INTERVAL):
|
||||||
|
print(f" -> Fetching financial data for {ticker_symbol}...")
|
||||||
|
financials = get_financial_data(ticker_symbol)
|
||||||
|
database.update_ticker_financials(
|
||||||
|
conn, ticker_id,
|
||||||
|
financials['market_cap'] or ticker_info['market_cap'],
|
||||||
|
financials['closing_price'] or ticker_info['closing_price']
|
||||||
|
)
|
||||||
|
|
||||||
|
# --- DEEP DIVE SAVE (Still valuable) ---
|
||||||
|
all_comment_sentiments = [get_sentiment_score(c.body) for c in all_comments]
|
||||||
avg_sentiment = sum(all_comment_sentiments) / len(all_comment_sentiments) if all_comment_sentiments else 0
|
avg_sentiment = sum(all_comment_sentiments) / len(all_comment_sentiments) if all_comment_sentiments else 0
|
||||||
post_analysis_data = {
|
post_analysis_data = {
|
||||||
"post_id": submission.id, "title": submission.title,
|
"post_id": submission.id, "title": submission.title,
|
||||||
"post_url": f"https://reddit.com{submission.permalink}",
|
"post_url": f"https://reddit.com{submission.permalink}", "subreddit_id": subreddit_id,
|
||||||
"subreddit_id": subreddit_id, "post_timestamp": int(submission.created_utc),
|
"post_timestamp": int(submission.created_utc), "comment_count": len(all_comments),
|
||||||
"comment_count": len(all_comment_sentiments), "avg_comment_sentiment": avg_sentiment
|
"avg_comment_sentiment": avg_sentiment
|
||||||
}
|
}
|
||||||
database.add_or_update_post_analysis(conn, post_analysis_data)
|
database.add_or_update_post_analysis(conn, post_analysis_data)
|
||||||
|
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
print(f"Could not scan r/{subreddit_name}. Error: {e}")
|
print(f"Could not scan r/{subreddit_name}. Error: {e}")
|
||||||
|
|
||||||
conn.close()
|
conn.close()
|
||||||
print("\n--- Scan Complete ---")
|
print("\n--- Scan Complete ---")
|
||||||
|
|
||||||
|
|
||||||
def main():
|
def main():
|
||||||
"""Main function to run the Reddit stock analysis tool."""
|
"""Main function to run the Reddit stock analysis tool."""
|
||||||
parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.", formatter_class=argparse.RawTextHelpFormatter)
|
parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.", formatter_class=argparse.RawTextHelpFormatter)
|
||||||
|
|||||||
@@ -7,50 +7,52 @@ import re
|
|||||||
COMMON_WORDS_BLACKLIST = {
|
COMMON_WORDS_BLACKLIST = {
|
||||||
"401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
|
"401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
|
||||||
"AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
|
"AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
|
||||||
"ARE", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL", "ATM",
|
"ARE", "AREA", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL",
|
||||||
"AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA", "BIG",
|
"ATM", "AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA",
|
||||||
"BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS", "BRB",
|
"BIG", "BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS",
|
||||||
"BRL", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST", "BUT", "BUY",
|
"BRB", "BRL", "BROKE", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST",
|
||||||
"BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO", "CEST", "CET",
|
"BUT", "BUY", "BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO",
|
||||||
"CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC", "CNY", "COKE",
|
"CEST", "CET", "CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC",
|
||||||
"COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB", "CTO", "CYCLE",
|
"CNY", "COKE", "COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB",
|
||||||
"CZK", "DAO", "DATE", "DAX", "DAY", "DCA", "DD", "DEBT", "DEX", "DIA",
|
"CTO", "CYCLE", "CZK", "DAO", "DATE", "DAX", "DAY", "DAYS", "DCA", "DD",
|
||||||
"DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE", "DOJ", "DONT", "DR",
|
"DEBT", "DEX", "DIA", "DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE",
|
||||||
"EACH", "EARLY", "EARN", "ECB", "EDGAR", "EDIT", "EDT", "EMA", "END", "EOD",
|
"DOJ", "DONT", "DR", "EACH", "EARLY", "EARN", "EAST", "ECB", "EDGAR", "EDIT",
|
||||||
"EOW", "EOY", "EPA", "EPS", "ER", "ESG", "EST", "ETF", "ETFS", "ETH",
|
"EDT", "EMA", "END", "ENV", "EOD", "EOW", "EOY", "EPA", "EPS", "ER",
|
||||||
"EU", "EUR", "EV", "EVEN", "EVERY", "FAQ", "FAR", "FAST", "FBI", "FD",
|
"ESG", "EST", "ETF", "ETFS", "ETH", "EU", "EUR", "EV", "EVEN", "EVERY",
|
||||||
"FDA", "FIHTX", "FINRA", "FINT", "FINTX", "FINTY", "FIRST", "FOMC", "FOMO", "FOR",
|
"FAQ", "FAR", "FAST", "FBI", "FD", "FDA", "FIHTX", "FINRA", "FINT", "FINTX",
|
||||||
"FOREX", "FRAUD", "FRG", "FROM", "FSPSX", "FTSE", "FUCK", "FUD", "FULL", "FUND",
|
"FINTY", "FIRST", "FOMC", "FOMO", "FOR", "FOREX", "FRAUD", "FRG", "FROM", "FSPSX",
|
||||||
"FXAIX", "FXIAX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET",
|
"FTD", "FTSE", "FUCK", "FUD", "FULL", "FUND", "FXAIX", "FXIAX", "FY", "FYI",
|
||||||
"GL", "GLHF", "GMT", "GO", "GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB",
|
"FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET", "GL", "GLHF", "GMT", "GO",
|
||||||
"GTG", "HALF", "HAS", "HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT",
|
"GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB", "GTG", "GUH", "HALF", "HAS",
|
||||||
"HKD", "HODL", "HOLD", "HOUR", "HSA", "HUF", "IF", "II", "IKZ", "IMHO",
|
"HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT", "HKD", "HODL", "HOLD",
|
||||||
"IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISM",
|
"HOUR", "HSA", "HUF", "HUGE", "IBS", "IF", "II", "IKKE", "IKZ", "IMHO",
|
||||||
"IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY", "JST",
|
"IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISIN",
|
||||||
"JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST", "LATE",
|
"ISM", "IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY",
|
||||||
"LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC", "LLM",
|
"JST", "JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST",
|
||||||
"LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A", "MA",
|
"LATE", "LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC",
|
||||||
"MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID", "MIGHT",
|
"LLM", "LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A",
|
||||||
"MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST", "MXN",
|
"MA", "MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID",
|
||||||
"MY", "NATO", "NEAR", "NEED", "NEVER", "NEW", "NEXT", "NFA", "NFC", "NFT",
|
"MIGHT", "MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST",
|
||||||
"NGMI", "NIGHT", "NO", "NOK", "NONE", "NOT", "NOW", "NSA", "NULL", "NUT",
|
"MXN", "MY", "NASA", "NATO", "NEAR", "NEAT", "NEED", "NEVER", "NEW", "NEXT",
|
||||||
"NYSE", "NZD", "OBV", "OEM", "OF", "OG", "OK", "OLD", "ON", "ONE",
|
"NFA", "NFC", "NFT", "NGMI", "NIGHT", "NO", "NOK", "NONE", "NORTH", "NOT",
|
||||||
"ONLY", "OP", "OPEX", "OR", "OS", "OSCE", "OTC", "OTM", "OUGHT", "OUT",
|
"NOW", "NSA", "NULL", "NUT", "NYSE", "NZ", "NZD", "OBV", "OEM", "OF",
|
||||||
"OVER", "OWN", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG", "PEW", "PLAN",
|
"OG", "OK", "OLD", "ON", "ONE", "ONLY", "OP", "OPEX", "OR", "OS",
|
||||||
"PLN", "PM", "PMI", "POC", "POS", "PPI", "PR", "PRICE", "PROFIT", "PSA",
|
"OSCE", "OTC", "OTM", "OUGHT", "OUT", "OVER", "OWN", "PANIC", "PC", "PDT",
|
||||||
"PST", "PT", "PUT", "Q1", "Q2", "Q3", "Q4", "QQQ", "QR", "RBA",
|
"PE", "PEAK", "PEG", "PEW", "PLAN", "PLN", "PM", "PMI", "POC", "POS",
|
||||||
"RBNZ", "RE", "REAL", "REIT", "REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK",
|
"POSCO", "PPI", "PR", "PRICE", "PROFIT", "PSA", "PST", "PT", "PUT", "Q1",
|
||||||
"ROE", "ROFL", "ROI", "ROTH", "RSD", "RSI", "RUB", "RULE", "SAME", "SAVE",
|
"Q2", "Q3", "Q4", "QQQ", "QR", "RBA", "RBNZ", "RE", "REAL", "REIT",
|
||||||
"SCALP", "SCAM", "SCHB", "SEC", "SEE", "SEK", "SELL", "SEP", "SGD", "SHALL",
|
"REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK", "ROE", "ROFL", "ROI", "ROTH",
|
||||||
"SHARE", "SHORT", "SL", "SMA", "SMALL", "SO", "SOLIS", "SOME", "SOON", "SP",
|
"RSD", "RSI", "RUB", "RULE", "SAME", "SAVE", "SCALP", "SCAM", "SCHB", "SEC",
|
||||||
"SPAC", "SPEND", "SPLG", "SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR",
|
"SEE", "SEK", "SELL", "SEP", "SGD", "SHALL", "SHARE", "SHORT", "SL", "SMA",
|
||||||
"SWING", "TA", "TAG", "TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS",
|
"SMALL", "SO", "SOLIS", "SOME", "SOON", "SOUTH", "SP", "SPAC", "SPEND", "SPLG",
|
||||||
"TIME", "TITS", "TL", "TL;DR", "TLDR", "TO", "TODAY", "TOTAL", "TRADE", "TREND",
|
"SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR", "SWING", "TA", "TAG",
|
||||||
"TRUE", "TRY", "TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA",
|
"TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS", "TIME", "TITS", "TL",
|
||||||
"USD", "UTC", "VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH",
|
"TL;DR", "TLDR", "TO", "TODAY", "TOLD", "TOTAL", "TRADE", "TREND", "TRUE", "TRY",
|
||||||
"WAY", "WE", "WEB3", "WEEK", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WORDS",
|
"TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA", "USD", "UTC",
|
||||||
"WORTH", "WOULD", "WSB", "WTF", "XRP", "YES", "YET", "YIELD", "YOLO", "YOU",
|
"VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH", "WAY", "WE",
|
||||||
"YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
|
"WEB3", "WEEK", "WEST", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WIRE", "WORDS",
|
||||||
|
"WORTH", "WOULD", "WSB", "WTF", "XO", "XRP", "YES", "YET", "YIELD", "YOLO",
|
||||||
|
"YOU", "YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
|
||||||
}
|
}
|
||||||
|
|
||||||
def extract_tickers(text):
|
def extract_tickers(text):
|
||||||
|
|||||||
Reference in New Issue
Block a user