Lots of improvements and adding a script to post to reddit.

.gitignore

@@ -6,3 +6,4 @@ __pycache__/
 *.db
 *.log
 reddit_stock_analyzer.egg-info/
+images/

README.md

@@ -156,3 +156,167 @@ This command starts a local web server to let you explore the data you've collec
 *   **Subreddit Pages:** Click any subreddit in the navigation bar to see a dashboard specific to that community.
 *   **Deep Dive:** In any table, click on a ticker's symbol to see a detailed breakdown of every post it was mentioned in.
 *   **Shareable Images:** On a subreddit's page, click "(View Daily Image)" or "(View Weekly Image)" to generate a polished, shareable summary card.
+
+
+### 3. Exporting Shareable Images (`.png`)
+
+In addition to viewing the dashboards in a browser, the project includes a powerful script to programmatically save the 'image views' as static `.png` files. This is ideal for automation, scheduled tasks (cron jobs), or sharing the results on social media platforms like your `r/rstat` subreddit.
+
+#### One-Time Setup
+
+The image exporter uses the Playwright library to control a headless browser. Before using it for the first time, you must install the necessary browser runtimes with this command:
+
+```bash
+playwright install
+```
+
+#### Usage Workflow
+
+The exporter works by taking a high-quality screenshot of the live web page. Therefore, the process requires two steps running in two separate terminals.
+
+**Step 1: Start the Web Dashboard**
+
+The web server must be running for the exporter to have a page to screenshot. Open a terminal and run:
+
+```bash
+rstat-dashboard
+```
+Leave this terminal running.
+
+**Step 2: Run the Export Script**
+
+Open a **second terminal** in the same project directory. You can now run the `export_image.py` script with the desired arguments.
+
+**Examples:**
+
+*   To export the **daily** summary image for `r/wallstreetbets`:
+    ```bash
+    python export_image.py wallstreetbets
+    ```
+
+*   To export the **weekly** summary image for `r/wallstreetbets`:
+    ```bash
+    python export_image.py wallstreetbets --weekly
+    ```
+
+*   To export the **overall** summary image (across all subreddits):
+    ```bash
+    python export_image.py --overall
+    ```
+
+#### Output
+
+After running a command, a new `.png` file (e.g., `wallstreetbets_daily_1690000000.png`) will be saved in the images-directory in the root directory of the project.
+
+
+
+## 4. Full Automation: Posting to Reddit via Cron Job
+
+The final piece of the project is a script that automates the entire process: scraping data, generating an image, and posting it to a target subreddit like `r/rstat`. This is designed to be run via a scheduled task or cron job.
+
+### Prerequisites for Posting
+
+The posting script needs to log in to your Reddit account. You must add your Reddit username and password to your `.env` file.
+
+**Add these two lines to your `.env` file:**
+```
+REDDIT_USERNAME=YourRedditUsername
+REDDIT_PASSWORD=YourRedditPassword
+```
+*(For security, it's recommended to use a dedicated bot account for this, not your personal account.)*
+
+### The `post_to_reddit.py` Script
+
+This is a standalone script located in the project's root directory that finds the most recently generated image and posts it to Reddit.
+
+**Manual Usage:**
+
+You can run this script manually from your terminal. This is great for testing or one-off posts.
+
+*   **Post the latest OVERALL summary image to `r/rstat`:**
+    ```bash
+    python post_to_reddit.py
+    ```
+
+*   **Post the latest DAILY image for a specific subreddit:**
+    ```bash
+    python post_to_reddit.py --subreddit wallstreetbets
+    ```
+
+*   **Post the latest WEEKLY image for a specific subreddit:**
+    ```bash
+    python post_to_reddit.py --subreddit wallstreetbets --weekly
+    ```
+
+*   **Post to a different target subreddit (e.g., a test subreddit):**
+    ```bash
+    python post_to_reddit.py --target-subreddit MyTestSub
+    ```
+
+### Setting Up the Cron Job for Full Automation
+
+To run the entire pipeline automatically every day, you can use a simple shell script controlled by `cron`.
+
+**Step 1: Create a Job Script**
+
+Create a file named `run_daily_job.sh` in the root of your project directory. This script will run all the necessary commands in the correct order.
+
+**`run_daily_job.sh`:**
+```bash
+#!/bin/bash
+
+# CRITICAL: Navigate to the project directory using an absolute path.
+# Replace '/path/to/your/project/reddit_stock_analyzer' with your actual path.
+cd /path/to/your/project/reddit_stock_analyzer
+
+# CRITICAL: Activate the virtual environment using an absolute path.
+source /path/to/your/project/reddit_stock_analyzer/.venv/bin/activate
+
+echo "--- Starting RSTAT Daily Job on $(date) ---"
+
+# 1. Scrape data from the last 24 hours for all subreddits in the config.
+echo "Step 1: Scraping new data..."
+rstat --config subreddits.json --days 1
+
+# 2. Start the dashboard in the background so the exporter can access it.
+echo "Step 2: Starting dashboard in background..."
+rstat-dashboard &
+DASHBOARD_PID=$!
+
+# Give the server a moment to start up.
+sleep 10
+
+# 3. Export the overall summary image.
+echo "Step 3: Exporting overall summary image..."
+python export_image.py --overall
+
+# 4. Post the newly created overall summary image to r/rstat.
+echo "Step 4: Posting image to Reddit..."
+python post_to_reddit.py --target-subreddit rstat
+
+# 5. Clean up by stopping the background dashboard server.
+echo "Step 5: Stopping dashboard server..."
+kill $DASHBOARD_PID
+
+echo "--- RSTAT Daily Job Complete ---"
+```**Before proceeding, you must edit the two absolute paths at the top of this script to match your system.**
+
+**Step 2: Make the Script Executable**
+
+In your terminal, run the following command:
+```bash
+chmod +x run_daily_job.sh
+```
+
+**Step 3: Schedule the Cron Job**
+
+1.  Open your crontab editor by running `crontab -e`.
+2.  Add a new line to the file to schedule the job. For example, to run the script **every day at 10:00 PM**, add the following line:
+
+    ```
+    0 22 * * * /path/to/your/project/reddit_stock_analyzer/run_daily_job.sh >> /path/to/your/project/reddit_stock_analyzer/cron.log 2>&1
+    ```
+    *   `0 22 * * *` means at minute 0 of hour 22, every day, every month, every day of the week.
+    *   `>> /path/to/your/.../cron.log 2>&1` is highly recommended. It redirects all output (both standard and error) from the script into a log file, so you can check if the job ran successfully.
+
+Your project is now fully automated to scrape, analyze, visualize, and post data every day.

export_image.py

@@ -1,51 +1,73 @@
 # export_image.py
 
 import argparse
-from playwright.sync_api import sync_playwright
+import os
 import time
+from playwright.sync_api import sync_playwright
 
-def export_subreddit_image(subreddit_name, weekly=False):
+# Define the output directory as a constant
-    """
+OUTPUT_DIR = "images"
-    Launches a headless browser to take a screenshot of a subreddit's image view.
+
-    """
+def export_image(url_path, filename_prefix):
-    view_type = "weekly" if weekly else "daily"
+    """
-    print(f"Exporting {view_type} image for r/{subreddit_name}...")
+    Launches a headless browser, navigates to a URL path, and screenshots
+    the .image-container element, saving it to the OUTPUT_DIR.
+    """
+    print(f"-> Preparing to export image for: {filename_prefix}")
+
+    # 1. Ensure the output directory exists
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
 
-    # The URL our Flask app serves
     base_url = "http://127.0.0.1:5000"
-    path = f"image/weekly/{subreddit_name}" if weekly else f"image/{subreddit_name}"
+    url = f"{base_url}/{url_path}"
-    url = f"{base_url}/{path}"
     
-    # Define the output filename
+    # 2. Construct the full output path including the new directory
-    output_file = f"{subreddit_name}_{'weekly' if weekly else 'daily'}_{int(time.time())}.png"
+    output_file = os.path.join(OUTPUT_DIR, f"{filename_prefix}_{int(time.time())}.png")
 
     with sync_playwright() as p:
-        browser = p.chromium.launch()
+        try:
-        page = browser.new_page()
+            browser = p.chromium.launch()
+            page = browser.new_page()
             
-        # Set a large viewport for high-quality screenshots
+            page.set_viewport_size({"width": 1920, "height": 1080})
-        page.set_viewport_size({"width": 1920, "height": 1080})
             
-        print(f"Navigating to {url}...")
+            print(f"  Navigating to {url}...")
-        page.goto(url)
+            page.goto(url, wait_until="networkidle") # Wait for network to be idle
             
-        # Important: Give the page a second to ensure all styles and fonts have loaded
+            # Target the specific element we want to screenshot
-        page.wait_for_timeout(1000) 
+            element = page.locator(".image-container")
             
-        # Target the specific element we want to screenshot
+            print(f"  Saving screenshot to {output_file}...")
-        element = page.locator(".image-container")
+            element.screenshot(path=output_file)
             
-        print(f"Saving screenshot to {output_file}...")
+            browser.close()
-        element.screenshot(path=output_file)
+            print(f"-> Export complete! Image saved to {output_file}")
+
+        except Exception as e:
+            print(f"\nAn error occurred during export: {e}")
+            print("Please ensure the 'rstat-dashboard' server is running in another terminal.")
 
-        browser.close()
-        print("Export complete!")
 
 if __name__ == "__main__":
+    # Use a mutually exclusive group to ensure only one mode is chosen
     parser = argparse.ArgumentParser(description="Export subreddit sentiment images.")
-    parser.add_argument("subreddit", help="The name of the subreddit to export.")
+    group = parser.add_mutually_exclusive_group(required=True)
-    parser.add_argument("--weekly", action="store_true", help="Export the weekly view instead of the daily view.")
+    group.add_argument("-s", "--subreddit", help="The name of the subreddit to export.")
+    group.add_argument("-o", "--overall", action="store_true", help="Export the overall summary image.")
+    
+    parser.add_argument("-w", "--weekly", action="store_true", help="Export the weekly view instead of the daily view (only for --subreddit).")
     args = parser.parse_args()
 
-    # NOTE: This script assumes your 'rstat-dashboard' server is already running in another terminal.
+    # Determine the correct URL path and filename based on arguments
-    export_subreddit_image(args.subreddit, args.weekly)
+    if args.subreddit:
+        view_type = "weekly" if args.weekly else "daily"
+        url_path_to_render = f"image/{view_type}/{args.subreddit}"
+        filename_prefix_to_save = f"{args.subreddit}_{view_type}"
+        export_image(url_path_to_render, filename_prefix_to_save)
+    
+    elif args.overall:
+        if args.weekly:
+            print("Warning: --weekly flag has no effect with --overall. Exporting overall summary.")
+        url_path_to_render = "image/overall"
+        filename_prefix_to_save = "overall_summary"
+        export_image(url_path_to_render, filename_prefix_to_save)

post_to_reddit.py

@@ -0,0 +1,104 @@
+# post_to_reddit.py
+
+import argparse
+import os
+import glob
+from datetime import datetime, timezone
+import praw
+from dotenv import load_dotenv
+
+# --- CONFIGURATION ---
+IMAGE_DIR = "images"
+
+def get_reddit_instance():
+    """Initializes and returns a PRAW Reddit instance from .env credentials."""
+    load_dotenv()
+    client_id = os.getenv("REDDIT_CLIENT_ID")
+    client_secret = os.getenv("REDDIT_CLIENT_SECRET")
+    user_agent = os.getenv("REDDIT_USER_AGENT")
+    username = os.getenv("REDDIT_USERNAME") # <-- Add your Reddit username to .env
+    password = os.getenv("REDDIT_PASSWORD") # <-- Add your Reddit password to .env
+
+    if not all([client_id, client_secret, user_agent, username, password]):
+        print("Error: Reddit API credentials (including username/password) not found in .env file.")
+        return None
+    
+    return praw.Reddit(
+        client_id=client_id,
+        client_secret=client_secret,
+        user_agent=user_agent,
+        username=username,
+        password=password
+    )
+
+def find_latest_image(pattern):
+    """Finds the most recent file in the IMAGE_DIR that matches a given pattern."""
+    try:
+        search_path = os.path.join(IMAGE_DIR, pattern)
+        list_of_files = glob.glob(search_path)
+        if not list_of_files:
+            return None
+        # The latest file will be the one with the highest modification time
+        latest_file = max(list_of_files, key=os.path.getmtime)
+        return latest_file
+    except Exception as e:
+        print(f"Error finding image file: {e}")
+        return None
+
+def main():
+    """Main function to find an image and post it to Reddit."""
+    parser = argparse.ArgumentParser(description="Find the latest sentiment image and post it to a subreddit.")
+    parser.add_argument("-s", "--subreddit", help="The source subreddit of the image to post. (Defaults to overall summary)")
+    parser.add_argument("-w", "--weekly", action="store_true", help="Post the weekly summary instead of the daily one.")
+    parser.add_argument("-t", "--target-subreddit", default="rstat", help="The subreddit to post the image to. (Default: rstat)")
+    args = parser.parse_args()
+
+    # --- 1. Determine filename pattern and post title ---
+    current_date_str = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+    
+    if args.subreddit:
+        view_type = "weekly" if args.weekly else "daily"
+        filename_pattern = f"{args.subreddit.lower()}_{view_type}_*.png"
+        post_title = f"{view_type.capitalize()} Ticker Sentiment for r/{args.subreddit} ({current_date_str})"
+    else:
+        # Default to the overall summary
+        if args.weekly:
+            print("Warning: --weekly flag has no effect for overall summary. Posting overall daily image.")
+        filename_pattern = "overall_summary_*.png"
+        post_title = f"Overall Top 10 Ticker Mentions Across Reddit ({current_date_str})"
+    
+    print(f"Searching for image pattern: {filename_pattern}")
+    
+    # --- 2. Find the latest image file ---
+    image_to_post = find_latest_image(filename_pattern)
+    
+    if not image_to_post:
+        print(f"Error: No image found matching the pattern '{filename_pattern}'. Please run the scraper and exporter first.")
+        return
+
+    print(f"Found image: {image_to_post}")
+    
+    # --- 3. Connect to Reddit and submit ---
+    reddit = get_reddit_instance()
+    if not reddit:
+        return
+        
+    try:
+        target_sub = reddit.subreddit(args.target_subreddit)
+        print(f"Submitting '{post_title}' to r/{target_sub.display_name}...")
+        
+        submission = target_sub.submit_image(
+            title=post_title,
+            image_path=image_to_post,
+            flair_id=None # Optional: You can add a flair ID here if you want
+        )
+        
+        print("\n--- Post Successful! ---")
+        print(f"Post URL: {submission.shortlink}")
+
+    except Exception as e:
+        print(f"\nAn error occurred while posting to Reddit: {e}")
+
+
+if __name__ == "__main__":
+    main()

rstat_tool/cleanup.py

@@ -2,10 +2,13 @@
 
 import argparse
 from . import database
+from .logger_setup import get_logger
 # We can't reuse load_subreddits from main anymore if it's not in the same file
 # So we will duplicate it here. It's small and keeps this script self-contained.
 import json
 
+log = get_logger()
+
 def load_subreddits(filepath):
     """Loads a list of subreddits from a JSON file."""
     try:
@@ -13,7 +16,7 @@ def load_subreddits(filepath):
             data = json.load(f)
             return data.get("subreddits", [])
     except (FileNotFoundError, json.JSONDecodeError) as e:
-        print(f"Error loading config file '{filepath}': {e}")
+        log.error(f"Error loading config file '{filepath}': {e}")
         return None
 
 def run_cleanup():
@@ -52,17 +55,17 @@ def run_cleanup():
         run_any_task = True
         # If --all is used, default to 'subreddits.json' if --subreddits wasn't also specified
         config_file = args.subreddits or 'subreddits.json'
-        print(f"\nCleaning subreddits based on active list in: {config_file}")
+        log.info(f"\nCleaning subreddits based on active list in: {config_file}")
         active_subreddits = load_subreddits(config_file)
         if active_subreddits is not None:
             database.clean_stale_subreddits(active_subreddits)
 
     if not run_any_task:
         parser.print_help()
-        print("\nError: Please provide at least one cleanup option (e.g., --tickers, --subreddits, --all).")
+        log.error("\nError: Please provide at least one cleanup option (e.g., --tickers, --subreddits, --all).")
         return
 
-    print("\nCleanup finished.")
+    log.info("\nCleanup finished.")
 
 if __name__ == "__main__":
     run_cleanup()

rstat_tool/dashboard.py

@@ -1,17 +1,19 @@
 # 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
 )
 
+log = get_logger()
 app = Flask(__name__, template_folder='../templates')
 
 @app.template_filter('format_mc')
@@ -53,13 +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>")
+@app.route("/image/daily/<name>")
-def image_view(name):
+def daily_image_view(name):
     """The handler for the image-style dashboard."""
-    tickers = get_image_view_summary(name)
+    tickers = get_daily_summary_for_subreddit(name)
-    current_date = datetime.utcnow().strftime("%Y-%m-%d")
+    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
@@ -71,7 +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')}"
 
@@ -86,7 +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,
@@ -95,9 +97,9 @@ def overall_image_view():
 
 def start_dashboard():
     """The main function called by the 'rstat-dashboard' command."""
-    print("Starting Flask server...")
+    log.info("Starting Flask server...")
-    print("Open http://127.0.0.1:5000 in your browser.")
+    log.info("Open http://127.0.0.1:5000 in your browser.")
-    print("Press CTRL+C to stop the server.")
+    log.info("Press CTRL+C to stop the server.")
     app.run(debug=True)
 
 if __name__ == "__main__":

rstat_tool/database.py

@@ -3,9 +3,11 @@
 import sqlite3
 import time
 from .ticker_extractor import COMMON_WORDS_BLACKLIST
-from datetime import datetime, timedelta
+from .logger_setup import get_logger
+from datetime import datetime, timedelta, timezone
 
 DB_FILE = "reddit_stocks.db"
+log = get_logger()
 
 def get_db_connection():
     """Establishes a connection to the SQLite database."""
@@ -71,14 +73,14 @@ def initialize_db():
 
     conn.commit()
     conn.close()
-    print("Database initialized successfully.")
+    log.info("Database initialized successfully.")
 
 def clean_stale_tickers():
     """
     Removes tickers and their associated mentions from the database
     if the ticker symbol exists in the COMMON_WORDS_BLACKLIST.
     """
-    print("\n--- Cleaning Stale Tickers from Database ---")
+    log.info("\n--- Cleaning Stale Tickers from Database ---")
     conn = get_db_connection()
     cursor = conn.cursor()
 
@@ -89,27 +91,27 @@ def clean_stale_tickers():
     stale_tickers = cursor.fetchall()
 
     if not stale_tickers:
-        print("No stale tickers to clean.")
+        log.info("No stale tickers to clean.")
         conn.close()
         return
 
     for ticker in stale_tickers:
         ticker_id = ticker['id']
         ticker_symbol = ticker['symbol']
-        print(f"Removing stale ticker '{ticker_symbol}' (ID: {ticker_id})...")
+        log.info(f"Removing stale ticker '{ticker_symbol}' (ID: {ticker_id})...")
         cursor.execute("DELETE FROM mentions WHERE ticker_id = ?", (ticker_id,))
         cursor.execute("DELETE FROM tickers WHERE id = ?", (ticker_id,))
     
     deleted_count = conn.total_changes
     conn.commit()
     conn.close()
-    print(f"Cleanup complete. Removed {deleted_count} records.")
+    log.info(f"Cleanup complete. Removed {deleted_count} records.")
 
 def clean_stale_subreddits(active_subreddits):
     """
     Removes all data associated with subreddits that are NOT in the active list.
     """
-    print("\n--- Cleaning Stale Subreddits from Database ---")
+    log.info("\n--- Cleaning Stale Subreddits from Database ---")
     conn = get_db_connection()
     cursor = conn.cursor()
     cursor.execute("SELECT id, name FROM subreddits")
@@ -117,20 +119,20 @@ def clean_stale_subreddits(active_subreddits):
     stale_sub_ids = []
     for sub in db_subreddits:
         if sub['name'] not in active_subreddits:
-            print(f"Found stale subreddit to remove: r/{sub['name']}")
+            log.info(f"Found stale subreddit to remove: r/{sub['name']}")
             stale_sub_ids.append(sub['id'])
     if not stale_sub_ids:
-        print("No stale subreddits to clean.")
+        log.info("No stale subreddits to clean.")
         conn.close()
         return
     for sub_id in stale_sub_ids:
-        print(f"  -> Deleting associated data for subreddit ID: {sub_id}")
+        log.info(f"  -> Deleting associated data for subreddit ID: {sub_id}")
         cursor.execute("DELETE FROM mentions WHERE subreddit_id = ?", (sub_id,))
         cursor.execute("DELETE FROM posts WHERE subreddit_id = ?", (sub_id,))
         cursor.execute("DELETE FROM subreddits WHERE id = ?", (sub_id,))
     conn.commit()
     conn.close()
-    print("Stale subreddit cleanup complete.")
+    log.info("Stale subreddit cleanup complete.")
 
 def get_db_connection():
     conn = sqlite3.connect(DB_FILE)
@@ -184,7 +186,7 @@ def initialize_db():
     """)
     conn.commit()
     conn.close()
-    print("Database initialized successfully.")
+    log.info("Database initialized successfully.")
 
 def add_mention(conn, ticker_id, subreddit_id, post_id, mention_type, timestamp, mention_sentiment, post_avg_sentiment=None):
     cursor = conn.cursor()
@@ -230,7 +232,7 @@ def get_ticker_info(conn, ticker_id):
 
 def generate_summary_report(limit=20):
     """Queries the DB to generate a summary for the command-line tool."""
-    print(f"\n--- Top {limit} Tickers by Mention Count ---")
+    log.info(f"\n--- Top {limit} Tickers by Mention Count ---")
     conn = get_db_connection()
     cursor = conn.cursor()
     
@@ -274,13 +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.
@@ -300,35 +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
+        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
-            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
+        GROUP BY t.symbol, t.market_cap, t.closing_price ORDER BY mention_count DESC LIMIT ?;
-        ORDER BY mention_count DESC LIMIT ?;
     """
     results = conn.execute(query, (limit,)).fetchall()
     conn.close()
@@ -337,86 +312,87 @@ def get_overall_summary(limit=50):
 def get_subreddit_summary(subreddit_name, limit=50):
     conn = get_db_connection()
     query = """
-        SELECT
+        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as mention_count,
-            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
-        JOIN tickers t ON m.ticker_id = t.id
+        WHERE LOWER(s.name) = LOWER(?) GROUP BY t.symbol, t.market_cap, t.closing_price ORDER BY mention_count DESC LIMIT ?;
-        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
+        SELECT t.symbol,
-            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
-        JOIN tickers t ON m.ticker_id = t.id
+        WHERE LOWER(s.name) = LOWER(?) AND m.mention_timestamp >= ?
-        JOIN subreddits s ON m.subreddit_id = s.id
+        GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
-        WHERE LOWER(s.name) = LOWER(?)
-        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
+        SELECT t.symbol,
-            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id JOIN subreddits s ON m.subreddit_id = s.id
-        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
+        GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
-        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
+        SELECT t.symbol,
-            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
-        JOIN tickers t ON m.ticker_id = t.id
+        GROUP BY t.symbol ORDER BY (post_mentions + comment_mentions) DESC LIMIT 10;
-        -- 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;
     """
     results = conn.execute(query).fetchall()
     conn.close()
     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]

rstat_tool/logger_setup.py

@@ -0,0 +1,47 @@
+# rstat_tool/logger_setup.py
+
+import logging
+import sys
+
+# Get the root logger
+logger = logging.getLogger("rstat_app")
+logger.setLevel(logging.INFO) # Set the minimum level of messages to handle
+
+# Prevent the logger from propagating messages to the parent (root) logger
+logger.propagate = False
+
+# Only add handlers if they haven't been added before
+# This prevents duplicate log messages if this function is called multiple times.
+if not logger.handlers:
+    # --- Console Handler ---
+    # This handler prints logs to the standard output (your terminal)
+    console_handler = logging.StreamHandler(sys.stdout)
+    console_handler.setLevel(logging.INFO)
+    # A simple formatter for the console
+    console_formatter = logging.Formatter('%(message)s')
+    console_handler.setFormatter(console_formatter)
+    logger.addHandler(console_handler)
+
+    # --- File Handler ---
+    # This handler writes logs to a file
+    # 'a' stands for append mode
+    file_handler = logging.FileHandler("rstat.log", mode='a')
+    file_handler.setLevel(logging.INFO)
+    # A more detailed formatter for the file, including timestamp and log level
+    file_formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
+    file_handler.setFormatter(file_formatter)
+    logger.addHandler(file_handler)
+
+# Get the logger used by the yfinance library
+yfinance_logger = logging.getLogger("yfinance")
+# Set its level to capture warnings and errors
+yfinance_logger.setLevel(logging.WARNING)
+# Add our existing handlers to it. This tells yfinance's logger
+# to send its messages to our console and our log file.
+if not yfinance_logger.handlers:
+    yfinance_logger.addHandler(console_handler)
+    yfinance_logger.addHandler(file_handler)
+
+def get_logger():
+    """A simple function to get our configured logger."""
+    return logger

rstat_tool/main.py

@@ -12,17 +12,20 @@ from dotenv import load_dotenv
 from . import database
 from .ticker_extractor import extract_tickers
 from .sentiment_analyzer import get_sentiment_score
+from .logger_setup import get_logger
 
 load_dotenv()
 MARKET_CAP_REFRESH_INTERVAL = 86400
 POST_AGE_LIMIT = 86400 
 
+log = get_logger()
+
 def load_subreddits(filepath):
     try:
         with open(filepath, 'r') as f:
             return json.load(f).get("subreddits", [])
     except (FileNotFoundError, json.JSONDecodeError) as e:
-        print(f"Error loading config file '{filepath}': {e}")
+        log.error(f"Error loading config file '{filepath}': {e}")
         return None
 
 def get_financial_data(ticker_symbol):
@@ -52,7 +55,7 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
     post_age_limit = days_to_scan * 86400
     current_time = time.time()
     
-    print(f"\nScanning {len(subreddits_list)} subreddit(s) for NEW posts in the last {days_to_scan} day(s)...")
+    log.info(f"\nScanning {len(subreddits_list)} subreddit(s) for NEW posts in the last {days_to_scan} day(s)...")
     for subreddit_name in subreddits_list:
         try:
             # Always use the lowercase version of the name for consistency.
@@ -60,15 +63,13 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
             
             subreddit_id = database.get_or_create_entity(conn, 'subreddits', 'name', normalized_sub_name)
             subreddit = reddit.subreddit(normalized_sub_name)
-            print(f"Scanning r/{normalized_sub_name}...")
+            log.info(f"Scanning r/{normalized_sub_name}...")
             
             for submission in subreddit.new(limit=post_limit):
                 if (current_time - submission.created_utc) > post_age_limit:
-                    print(f"  -> Reached posts older than the {days_to_scan}-day limit.")
+                    log.info(f"  -> Reached posts older than the {days_to_scan}-day limit.")
                     break
                 
-                # --- NEW HYBRID LOGIC ---
-                
                 tickers_in_title = set(extract_tickers(submission.title))
                 all_tickers_found_in_post = set(tickers_in_title) # Start a set to track all tickers for financials
 
@@ -77,7 +78,7 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
                 
                 # --- CASE A: Tickers were found in the title ---
                 if tickers_in_title:
-                    print(f"  -> Title Mention(s): {', '.join(tickers_in_title)}. Attributing all comments.")
+                    log.info(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
@@ -109,7 +110,7 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
                     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}...")
+                        log.info(f"    -> Fetching financial data for {ticker_symbol}...")
                         financials = get_financial_data(ticker_symbol)
                         database.update_ticker_financials(
                             conn, ticker_id,
@@ -129,10 +130,10 @@ def scan_subreddits(reddit, subreddits_list, post_limit=100, comment_limit=100,
                 database.add_or_update_post_analysis(conn, post_analysis_data)
                 
         except Exception as e:
-            print(f"Could not scan r/{subreddit_name}. Error: {e}")
+            log.error(f"Could not scan r/{subreddit_name}. Error: {e}")
             
     conn.close()
-    print("\n--- Scan Complete ---")
+    log.info("\n--- Scan Complete ---")
 
 
 def main():
@@ -147,19 +148,18 @@ def main():
     parser.add_argument("-l", "--limit", type=int, default=20, help="Number of tickers to show in the CLI report.\n(Default: 20)")
     args = parser.parse_args()
 
-    # --- THIS IS THE CORRECTED LOGIC BLOCK ---
     if args.subreddit:
         # If --subreddit is used, create a list with just that one.
         subreddits_to_scan = [args.subreddit]
-        print(f"Targeted Scan Mode: Focusing on r/{args.subreddit}")
+        log.info(f"Targeted Scan Mode: Focusing on r/{args.subreddit}")
     else:
         # Otherwise, load from the config file.
-        print(f"Config Scan Mode: Loading subreddits from {args.config}")
+        log.info(f"Config Scan Mode: Loading subreddits from {args.config}")
         # Use the correct argument name: args.config
         subreddits_to_scan = load_subreddits(args.config) 
 
     if not subreddits_to_scan:
-        print("Error: No subreddits to scan. Please check your config file or --subreddit argument.")
+        log.error("Error: No subreddits to scan. Please check your config file or --subreddit argument.")
         return
 
     # --- Initialize and Run ---

templates/subreddit.html

@@ -5,7 +5,7 @@
 {% block content %}
     <h1>
         Top 10 Tickers in r/{{ subreddit_name }}
-        <a href="/image/{{ subreddit_name }}" target="_blank" style="font-size: 0.8rem; margin-left: 1rem; font-weight: normal;">(View Daily Image)</a>
+        <a href="/image/daily/{{ subreddit_name }}" target="_blank" style="font-size: 0.8rem; margin-left: 1rem; font-weight: normal;">(View Daily Image)</a>
         <!-- ADD THIS NEW LINK -->
         <a href="/image/weekly/{{ subreddit_name }}" target="_blank" style="font-size: 0.8rem; margin-left: 1rem; font-weight: normal;">(View Weekly Image)</a>
     </h1>