pkhamre/reddit_stock_analyzer
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Change dashboards to show daily only.

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Pål-Kristian Hamre
2025-07-25 16:55:37 +02:00
parent 841f6a5305
commit 0d6d9516d7
3 changed files with 31 additions and 10 deletions
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37
rstat_tool/database.py
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@@ -204,31 +204,47 @@ def add_or_update_post_analysis(conn, post_data):
)
conn.commit()
def get_overall_summary(limit=50):
def get_overall_summary(limit=10):
"""
Gets the top tickers across all subreddits from the LAST 24 HOURS.
"""
conn = get_db_connection()
one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
one_day_ago_timestamp = int(one_day_ago.timestamp())
query = """
SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
SUM(CASE WHEN m.mention_sentiment 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, t.closing_price ORDER BY mention_count DESC LIMIT ?;
WHERE m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
GROUP BY t.symbol, t.market_cap, t.closing_price
ORDER BY mention_count DESC LIMIT ?;
"""
results = conn.execute(query, (limit,)).fetchall()
results = conn.execute(query, (one_day_ago_timestamp, limit)).fetchall()
conn.close()
return results
def get_subreddit_summary(subreddit_name, limit=50):
def get_subreddit_summary(subreddit_name, limit=10):
"""
Gets the top tickers for a specific subreddit from the LAST 24 HOURS.
"""
conn = get_db_connection()
one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
one_day_ago_timestamp = int(one_day_ago.timestamp())
query = """
SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
SUM(CASE WHEN m.mention_sentiment > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
SUM(CASE WHEN m.mention_sentiment < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
SUM(CASE WHEN m.mention_sentiment 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 LOWER(s.name) = LOWER(?) GROUP BY t.symbol, t.market_cap, t.closing_price ORDER BY mention_count DESC LIMIT ?;
WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
GROUP BY t.symbol, t.market_cap, t.closing_price
ORDER BY mention_count DESC LIMIT ?;
"""
results = conn.execute(query, (subreddit_name, limit)).fetchall()
results = conn.execute(query, (subreddit_name, one_day_ago_timestamp, limit)).fetchall()
conn.close()
return results
@@ -274,8 +290,12 @@ def get_weekly_summary_for_subreddit(subreddit_name, for_date):
return results, start_of_week, end_of_week
def get_overall_image_view_summary():
""" Gets a summary of top tickers across ALL subreddits for the image view. """
"""
Gets a summary of top tickers across ALL subreddits for the DAILY image view (last 24 hours).
"""
conn = get_db_connection()
one_day_ago = datetime.now(timezone.utc) - timedelta(days=1)
one_day_ago_timestamp = int(one_day_ago.timestamp())
query = """
SELECT
t.symbol, t.market_cap, t.closing_price,
@@ -283,10 +303,11 @@ def get_overall_image_view_summary():
COUNT(CASE WHEN m.mention_sentiment > 0.1 THEN 1 END) as bullish_mentions,
COUNT(CASE WHEN m.mention_sentiment < -0.1 THEN 1 END) as bearish_mentions
FROM mentions m JOIN tickers t ON m.ticker_id = t.id
WHERE m.mention_timestamp >= ? -- <-- ADDED TIME FILTER
GROUP BY t.symbol, t.market_cap, t.closing_price
ORDER BY total_mentions DESC LIMIT 10;
"""
results = conn.execute(query).fetchall()
results = conn.execute(query, (one_day_ago_timestamp,)).fetchall()
conn.close()
return results