Lots of improvements and adding a script to post to reddit.
This commit is contained in:
@@ -4,7 +4,7 @@ import sqlite3
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import time
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from .ticker_extractor import COMMON_WORDS_BLACKLIST
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from .logger_setup import get_logger
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from datetime import datetime, timedelta
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from datetime import datetime, timedelta, timezone
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DB_FILE = "reddit_stocks.db"
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log = get_logger()
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@@ -276,13 +276,6 @@ def generate_summary_report(limit=20):
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)
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conn.close()
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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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conn = get_db_connection()
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results = conn.execute("SELECT DISTINCT name FROM subreddits ORDER BY name ASC;").fetchall()
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conn.close()
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return [row['name'] for row in results]
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def add_or_update_post_analysis(conn, post_data):
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"""
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Inserts a new post analysis record or updates an existing one.
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@@ -302,35 +295,15 @@ def add_or_update_post_analysis(conn, post_data):
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)
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conn.commit()
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def get_deep_dive_details(ticker_symbol):
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"""
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Gets all analyzed posts that mention a specific ticker.
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"""
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conn = get_db_connection()
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query = """
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SELECT DISTINCT p.*, s.name as subreddit_name FROM posts p
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JOIN mentions m ON p.post_id = m.post_id
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JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON p.subreddit_id = s.id
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WHERE LOWER(t.symbol) = LOWER(?)
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ORDER BY p.post_timestamp DESC;
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"""
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results = conn.execute(query, (ticker_symbol,)).fetchall()
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conn.close()
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return results
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def get_overall_summary(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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SELECT t.symbol, t.market_cap, t.closing_price, 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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GROUP BY t.symbol, t.market_cap, t.closing_price 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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@@ -339,86 +312,87 @@ def get_overall_summary(limit=50):
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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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SELECT t.symbol, t.market_cap, t.closing_price, 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 LOWER(s.name) = LOWER(?)
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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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FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
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WHERE LOWER(s.name) = LOWER(?) GROUP BY t.symbol, t.market_cap, t.closing_price 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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def get_daily_summary_for_subreddit(subreddit_name):
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""" Gets a summary for the DAILY image view (last 24 hours). """
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conn = get_db_connection()
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one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
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one_day_ago_timestamp = int(one_day_ago.timestamp())
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query = """
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SELECT
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t.symbol,
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SELECT 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 = 'comment' THEN 1 END) as comment_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.mention_sentiment < -0.1 THEN 1 END) as bearish_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 LOWER(s.name) = LOWER(?)
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GROUP BY t.symbol
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ORDER BY (post_mentions + comment_mentions) DESC
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LIMIT 10;
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
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WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
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GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
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"""
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results = conn.execute(query, (subreddit_name,)).fetchall()
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results = conn.execute(query, (subreddit_name, one_day_ago_timestamp)).fetchall()
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conn.close()
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return results
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def get_weekly_summary_for_subreddit(subreddit_name):
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""" Gets a summary for the WEEKLY image view (last 7 days). """
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conn = get_db_connection()
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seven_days_ago = datetime.utcnow() - timedelta(days=7)
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seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
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seven_days_ago_timestamp = int(seven_days_ago.timestamp())
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query = """
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SELECT
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t.symbol,
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SELECT 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 = 'comment' THEN 1 END) as comment_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.mention_sentiment < -0.1 THEN 1 END) as bearish_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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FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
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WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
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GROUP BY t.symbol
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ORDER BY (post_mentions + comment_mentions) DESC
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LIMIT 10;
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GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
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"""
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results = conn.execute(query, (subreddit_name, seven_days_ago_timestamp)).fetchall()
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conn.close()
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return results
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def get_overall_image_view_summary():
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"""
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Gets a summary of top tickers across ALL subreddits for the image view.
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"""
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""" Gets a summary of top tickers across ALL subreddits for the image view. """
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conn = get_db_connection()
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query = """
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SELECT
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t.symbol,
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SELECT 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 = 'comment' THEN 1 END) as comment_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.mention_sentiment < -0.1 THEN 1 END) as bearish_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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-- No JOIN or WHERE for subreddit, as we want all of them
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GROUP BY t.symbol
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ORDER BY (post_mentions + comment_mentions) DESC
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LIMIT 10;
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FROM mentions m JOIN tickers t ON m.ticker_id = t.id
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GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
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"""
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results = conn.execute(query).fetchall()
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conn.close()
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return results
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return results
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def get_deep_dive_details(ticker_symbol):
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""" Gets all analyzed posts that mention a specific ticker. """
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conn = get_db_connection()
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query = """
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SELECT DISTINCT p.*, s.name as subreddit_name FROM posts p
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JOIN mentions m ON p.post_id = m.post_id JOIN tickers t ON m.ticker_id = t.id
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JOIN subreddits s ON p.subreddit_id = s.id
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WHERE LOWER(t.symbol) = LOWER(?) ORDER BY p.post_timestamp DESC;
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"""
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results = conn.execute(query, (ticker_symbol,)).fetchall()
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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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""" Gets a unique list of all subreddits we have data for. """
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conn = get_db_connection()
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results = conn.execute("SELECT DISTINCT name FROM subreddits ORDER BY name ASC;").fetchall()
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conn.close()
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return [row['name'] for row in results]
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