pkhamre/reddit_stock_analyzer
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Lots of improvements and adding a script to post to reddit.

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This commit is contained in:
Pål-Kristian Hamre
2025-07-22 16:26:40 +02:00
parent d4ed76e153
commit f6ea86fa91
8 changed files with 384 additions and 119 deletions
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18
rstat_tool/dashboard.py
View File

@@ -1,14 +1,14 @@
# rstat_tool/dashboard.py
from flask import Flask, render_template
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from .logger_setup import get_logger
from .database import (
get_overall_summary,
get_subreddit_summary,
get_all_scanned_subreddits,
get_deep_dive_details,
get_image_view_summary,
get_daily_summary_for_subreddit,
get_weekly_summary_for_subreddit,
get_overall_image_view_summary
)
@@ -55,13 +55,13 @@ def deep_dive(symbol):
posts = get_deep_dive_details(symbol)
return render_template("deep_dive.html", posts=posts, symbol=symbol)
@app.route("/image/<name>")
def image_view(name):
@app.route("/image/daily/<name>")
def daily_image_view(name):
"""The handler for the image-style dashboard."""
tickers = get_image_view_summary(name)
current_date = datetime.utcnow().strftime("%Y-%m-%d")
tickers = get_daily_summary_for_subreddit(name)
current_date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
return render_template(
"image_view.html",
"daily_image_view.html",
tickers=tickers,
subreddit_name=name,
current_date=current_date
@@ -73,7 +73,7 @@ def weekly_image_view(name):
tickers = get_weekly_summary_for_subreddit(name)
# Create the date range string for the title
end_date = datetime.utcnow()
end_date = datetime.now(timezone.utc)
start_date = end_date - timedelta(days=7)
date_range_str = f"{start_date.strftime('%b %d')} - {end_date.strftime('%b %d, %Y')}"
@@ -88,7 +88,7 @@ def weekly_image_view(name):
def overall_image_view():
"""The handler for the overall image-style dashboard."""
tickers = get_overall_image_view_summary()
current_date = datetime.utcnow().strftime("%Y-%m-%d")
current_date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
return render_template(
"overall_image_view.html",
tickers=tickers,

116
rstat_tool/database.py
View File

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