Update README.

.dockerignore

@@ -0,0 +1,94 @@
+# Git
+.git
+.gitignore
+.gitattributes
+
+
+# CI
+.codeclimate.yml
+.travis.yml
+.taskcluster.yml
+
+# Docker
+docker-compose.yml
+Dockerfile
+.docker
+.dockerignore
+
+# Byte-compiled / optimized / DLL files
+**/__pycache__/
+**/*.py[cod]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.cache
+nosetests.xml
+coverage.xml
+
+# Translations
+*.mo
+*.pot
+
+# Ignore Node.js dependencies (they will be installed inside the container)
+node_modules/
+
+# Ignore database and log files
+*.db
+*.log
+*.db-journal
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Virtual environment
+.env
+.venv/
+venv/
+
+# PyCharm
+.idea
+
+# Python mode for VIM
+.ropeproject
+**/.ropeproject
+
+# Vim swap files
+**/*.swp
+
+# VS Code
+.vscode/

.gitignore

@@ -5,4 +5,8 @@ __pycache__/
 *.sqlite3
 *.db
 *.log
-reddit_stock_analyzer.egg-info/
+reddit_stock_analyzer.egg-info/
+images/
+public/
+config/certbot/
+node_modules/

Dockerfile

@@ -0,0 +1,31 @@
+FROM node:24.5.0-bookworm-slim AS builder
+
+WORKDIR /usr/src/build
+
+COPY package.json package-lock.json ./
+
+RUN npm install
+
+COPY tailwind.config.js ./
+COPY templates/ ./templates/
+COPY static/css/input.css ./static/css/input.css
+
+RUN npx tailwindcss -i ./static/css/input.css -o ./static/css/style.css --minify
+
+FROM python:3.13.6-slim
+
+EXPOSE 5000
+
+WORKDIR /usr/src/app
+
+COPY requirements.txt .
+
+RUN python3 -m pip install --upgrade pip
+RUN python3 -m pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+COPY --from=builder /usr/src/build/static/css/style.css ./static/css/style.css
+
+RUN python3 -m pip install -e .
+
+CMD [ "gunicorn", "--config", "rstat_tool/gunicorn-cfg.py", "-k", "sync", "rstat_tool.dashboard:app" ]

README.md

@@ -1,158 +1,308 @@
-# rstat - Reddit Stock Analyzer
+<div align="center">
 
-A powerful, installable command-line tool and web dashboard to scan Reddit for stock ticker mentions, perform sentiment analysis, generate insightful reports, and create shareable summary images.
+# RSTAT — Reddit Stock Analyzer
 
-## Key Features
+Scan Reddit for stock ticker mentions, score sentiment, enrich with price/market cap, and explore the results in a clean web dashboard. Automate shareable images and post them to Reddit.
 
-*   **Dual-Interface:** Use a flexible command-line tool (`rstat`) for data collection and a simple web dashboard (`rstat-dashboard`) for data visualization.
-*   **Flexible Data Scraping:**
-    *   Scan subreddits from a config file or target a single subreddit on the fly.
-    *   Configure the time window to scan posts from the last 24 hours (for daily cron jobs) or back-fill data from several past days (e.g., last 7 days).
-    *   Fetches from `/new` to capture the most recent discussions.
-*   **Deep Analysis & Storage:**
-    *   Scans both post titles and comments, differentiating between the two.
-    *   Performs a "deep dive" analysis on posts to calculate the average sentiment of the entire comment section.
-    *   Persists all data in a local SQLite database (`reddit_stocks.db`) to track trends over time.
-*   **Rich Data Enrichment:**
-    *   Calculates sentiment (Bullish, Bearish, Neutral) for every mention using NLTK.
-    *   Fetches and stores daily closing prices and market capitalization from Yahoo Finance.
-*   **Interactive Web Dashboard:**
-    *   View Top 10 tickers across all subreddits or on a per-subreddit basis.
-    *   Click any ticker to get a "Deep Dive" page, showing every post it was mentioned in.
-*   **Shareable Summary Images:**
-    *   Generate clean, dark-mode summary images for both daily and weekly sentiment for any subreddit, perfect for sharing.
-*   **High-Quality Data:**
-    *   Uses a configurable blacklist and smart filtering to reduce false positives.
-    *   Automatically cleans the database of invalid tickers if the blacklist is updated.
+</div>
 
-## Project Structure
+## Highlights
+
+- CLI + Web UI: Collect data with `rstat`, browse it with `rstat-dashboard`.
+- Smart ticker parsing: Prefer $TSLA/$AAPL “golden” matches; fall back to filtered ALL-CAPS words.
+- Sentiment: VADER (NLTK) scores for titles and comments; “deep dive” averages per post.
+- Storage: Local SQLite database `reddit_stocks.db` with de-duped mentions and post analytics.
+- Enrichment: Yahoo Finance market cap + latest close fetched in batch and on-demand.
+- Images: Export polished daily/weekly summary PNGs for subreddits or “overall”.
+- Automation: Optional cron job plus one-command posting to Reddit with OAuth refresh tokens.
+
+## Repository layout
 
 ```
-reddit_stock_analyzer/
-├── .env                  # Your secret API keys
-├── requirements.txt      # Project dependencies
-├── setup.py              # Installation script for the tool
-├── subreddits.json       # Default list of subreddits to scan
-├── templates/            # HTML templates for the web dashboard
-│   ├── base.html
-│   ├── index.html
-│   ├── subreddit.html
-│   ├── deep_dive.html
-│   ├── image_view.html
-│   └── weekly_image_view.html
-└── rstat_tool/           # The main source code package
-    ├── __init__.py
-    ├── main.py           # Scraper entry point and CLI logic
-    ├── dashboard.py      # Web dashboard entry point (Flask app)
-    ├── database.py       # All SQLite database functions
-    └── ...
+.
+├── Dockerfile                     # Multi-stage build (Tailwind -> Python + gunicorn)
+├── docker-compose.yml             # Prod (nginx + varnish optional) + dashboard
+├── docker-compose-dev.yml         # Dev compose (local nginx)
+├── requirements.txt               # Python deps
+├── setup.py                       # Installs console scripts
+├── subreddits.json                # Default subreddits list
+├── reddit_stocks.db               # SQLite database (generated/updated by CLI)
+├── export_image.py                # Generate shareable PNGs (Playwright)
+├── post_to_reddit.py              # Post latest PNG to Reddit
+├── get_refresh_token.py           # One-time OAuth2 refresh token helper
+├── fetch_close_price.py           # Utility for closing price (yfinance)
+├── fetch_market_cap.py            # Utility for market cap (yfinance)
+├── rstat_tool/
+│   ├── main.py                    # CLI entry (rstat)
+│   ├── dashboard.py               # Flask app entry (rstat-dashboard)
+│   ├── database.py                # SQLite schema + queries
+│   ├── ticker_extractor.py        # Ticker parsing + blacklist
+│   ├── sentiment_analyzer.py      # VADER sentiment
+│   ├── cleanup.py                 # Cleanup utilities (rstat-cleanup)
+│   ├── flair_finder.py            # Fetch subreddit flair IDs (rstat-flairs)
+│   ├── logger_setup.py            # Logging
+│   └── setup_nltk.py              # One-time VADER download
+├── templates/                     # Jinja2 templates (Tailwind 4 styling)
+└── static/                        # Favicon + generated CSS (style.css)
 ```
 
-## Setup and Installation
+## Requirements
 
-Follow these steps to set up the project on your local machine.
+- Python 3.10+ (Docker image uses Python 3.13-slim)
+- Reddit API app (script type) for read + submit
+- For optional image export: Playwright browsers
+- For UI development (optional): Node 18+ to rebuild Tailwind CSS
 
-### 1. Prerequisites
-*   Python 3.7+
-*   Git
+## Setup
+
+1) Clone and enter the repo
 
-### 2. Clone the Repository
 ```bash
-git clone <your-repository-url>
+git clone <your-repo>
 cd reddit_stock_analyzer
 ```
 
-### 3. Set Up a Python Virtual Environment
-It is highly recommended to use a virtual environment to manage dependencies.
+2) Create and activate a virtualenv
 
-**On macOS / Linux:**
-```bash
-python3 -m venv .venv
-source .venv/bin/activate
-```
+- bash/zsh:
+    ```bash
+    python3 -m venv .venv
+    source .venv/bin/activate
+    ```
+- fish:
+    ```fish
+    python3 -m venv .venv
+    source .venv/bin/activate.fish
+    ```
 
-**On Windows:**
-```bash
-python -m venv .venv
-.\.venv\Scripts\activate
-```
+3) Install Python dependencies and commands
 
-### 4. Install Dependencies
 ```bash
 pip install -r requirements.txt
+pip install -e .
 ```
 
-### 5. Configure Reddit API Credentials
-1.  Go to the [Reddit Apps preferences page](https://www.reddit.com/prefs/apps) and create a new "script" app.
-2.  Create a file named `.env` in the root of the project directory.
-3.  Add your credentials to the `.env` file like this:
+4) Configure environment
 
-    ```
-    REDDIT_CLIENT_ID=your_client_id_from_reddit
-    REDDIT_CLIENT_SECRET=your_client_secret_from_reddit
-    REDDIT_USER_AGENT=A custom user agent string (e.g., python:rstat:v1.2)
-    ```
+Create a `.env` file in the repo root with your Reddit app credentials:
+
+```
+REDDIT_CLIENT_ID=your_client_id
+REDDIT_CLIENT_SECRET=your_client_secret
+REDDIT_USER_AGENT=python:rstat:v1.0 (by u/yourname)
+```
+
+Optional (after OAuth step below):
+
+```
+REDDIT_REFRESH_TOKEN=your_refresh_token
+```
+
+5) One-time NLTK setup
 
-### 6. Set Up NLTK
-Run the included setup script **once** to download the required `vader_lexicon` for sentiment analysis.
 ```bash
 python rstat_tool/setup_nltk.py
 ```
 
-### 7. Build and Install the Commands
-Install the tool in "editable" mode. This creates the `rstat` and `rstat-dashboard` commands in your virtual environment and links them to your source code.
+6) Configure subreddits (optional)
+
+Edit `subreddits.json` to your liking. It ships with a sane default list.
+
+## CLI usage (rstat)
+
+The `rstat` command collects Reddit data and updates the database. Credentials are read from `.env`.
+
+Common flags (see `rstat --help`):
+
+- `--config FILE`       Use a JSON file with `{"subreddits": [ ... ]}` (default: `subreddits.json`)
+- `--subreddit NAME`    Scan a single subreddit instead of the config
+- `--days N`            Only scan posts from the last N days (default 1)
+- `--posts N`           Max posts per subreddit to check (default 200)
+- `--comments N`        Max comments per post to scan (default 100)
+- `--no-financials`     Skip Yahoo Finance during the scan (faster)
+- `--update-top-tickers` Update financials for tickers that are currently top daily/weekly
+- `--update-financials-only [TICKER]` Update all or a single ticker’s market cap/close
+- `--stdout`            Log to console as well as file; `--debug` for verbose
+
+Examples:
 
 ```bash
-pip install -e .
+# Scan configured subs for last 24h, including financials
+rstat --days 1
+
+# Target a single subreddit for the past week, scan more comments
+rstat --subreddit wallstreetbets --days 7 --comments 250
+
+# Skip financials during scan, then update only top tickers
+rstat --no-financials
+rstat --update-top-tickers
+
+# Update financials for all tickers in DB
+rstat --update-financials-only
+
+# Update a single ticker (case-insensitive)
+rstat --update-financials-only TSLA
 ```
-The installation is now complete.
+
+How mentions are detected:
+
+- If a post contains any $TICKER (e.g., `$TSLA`) anywhere, we use “golden-only” mode: only $-prefixed tickers are considered.
+- Otherwise, we fall back to filtered ALL-CAPS 2–5 letter words, excluding a large blacklist to avoid false positives.
+- Title tickers attribute all comments in the thread; otherwise, we scan comments directly for mentions.
+
+## Web dashboard (rstat-dashboard)
+
+Start the dashboard and open http://127.0.0.1:5000
+
+```bash
+rstat-dashboard
+```
+
+Features:
+
+- Overall top 10 (daily/weekly) across all subs
+- Per-subreddit dashboards (daily/weekly)
+- Deep Dive pages listing posts analyzed for a ticker
+- Shareable image-friendly views (UI hides nav when `?image=true`)
+
+The dashboard reads from `reddit_stocks.db`. Run `rstat` first so you have data.
+
+## Image export (export_image.py)
+
+Exports a high-res PNG of the dashboard views via Playwright. Note: the script currently uses `https://rstat.net` as its base URL.
+
+```bash
+# Overall daily image
+python export_image.py --overall
+
+# Subreddit daily image
+python export_image.py --subreddit wallstreetbets
+
+# Weekly view
+python export_image.py --subreddit wallstreetbets --weekly
+```
+
+Output files are saved into the `images/` folder, e.g. `overall_summary_daily_1700000000.png`.
+
+Tip: If you want to export from a local dashboard instead of rstat.net, edit `base_url` in `export_image.py`.
+
+## Post images to Reddit (post_to_reddit.py)
+
+One-time OAuth2 step to obtain a refresh token:
+
+1) In your Reddit app settings, set the redirect URI to exactly `http://localhost:5000` (matches the script).
+2) Run:
+
+```bash
+python get_refresh_token.py
+```
+
+Follow the on-screen steps: open the generated URL, allow, copy the redirected URL, paste back. Add the printed token to `.env` as `REDDIT_REFRESH_TOKEN`.
+
+Now you can post:
+
+```bash
+# Post the most recent overall image to r/rstat
+python post_to_reddit.py
+
+# Post the most recent daily image for a subreddit
+python post_to_reddit.py --subreddit wallstreetbets
+
+# Post weekly image for a subreddit
+python post_to_reddit.py --subreddit wallstreetbets --weekly
+
+# Choose a target subreddit and (optionally) a flair ID
+python post_to_reddit.py --subreddit wallstreetbets --target-subreddit rstat --flair-id <ID>
+```
+
+Need a flair ID? Use the helper:
+
+```bash
+rstat-flairs wallstreetbets
+```
+
+## Cleanup utilities (rstat-cleanup)
+
+Remove blacklisted “ticker” rows and/or purge data for subreddits no longer in your config.
+
+```bash
+# Show help
+rstat-cleanup --help
+
+# Remove tickers that are in the internal COMMON_WORDS_BLACKLIST
+rstat-cleanup --tickers
+
+# Remove any subreddit data not in subreddits.json
+rstat-cleanup --subreddits
+
+# Use a custom config file
+rstat-cleanup --subreddits my_subs.json
+
+# Run both tasks
+rstat-cleanup --all
+```
+
+## Automation (cron)
+
+An example `run_daily_job.sh` is provided. Update `BASE_DIR` and make it executable:
+
+```bash
+chmod +x run_daily_job.sh
+```
+
+Add a cron entry (example 22:00 daily):
+
+```
+0 22 * * * /absolute/path/to/reddit_stock_analyzer/run_daily_job.sh >> /absolute/path/to/reddit_stock_analyzer/cron.log 2>&1
+```
+
+## Docker
+
+Builds a Tailwind CSS layer, then a Python runtime with gunicorn. The compose files include optional nginx and varnish.
+
+Quick start for the dashboard only (uses your host `reddit_stocks.db`):
+
+```bash
+docker compose up -d rstat-dashboard
+```
+
+Notes:
+
+- The `rstat-dashboard` container mounts `./reddit_stocks.db` read-only. Populate it by running `rstat` on the host (or add a separate CLI container).
+- Prod compose includes nginx (and optional certbot/varnish) configs under `config/`.
+
+## Data model (SQLite)
+
+- `tickers(id, symbol UNIQUE, market_cap, closing_price, last_updated)`
+- `subreddits(id, name UNIQUE)`
+- `mentions(id, ticker_id, subreddit_id, post_id, comment_id NULLABLE, mention_type, mention_sentiment, mention_timestamp, UNIQUE(ticker_id, post_id, comment_id))`
+- `posts(id, post_id UNIQUE, title, post_url, subreddit_id, post_timestamp, comment_count, avg_comment_sentiment)`
+
+Uniqueness prevents duplicates across post/comment granularity. Cleanup helpers remove blacklisted “tickers” and stale subreddits.
+
+## UI and Tailwind
+
+The CSS (`static/css/style.css`) is generated from `static/css/input.css` using Tailwind 4 during Docker build. If you want to tweak UI locally:
+
+```bash
+npm install
+npx tailwindcss -i ./static/css/input.css -o ./static/css/style.css --minify
+```
+
+## Troubleshooting
+
+- Missing VADER: Run `python rstat_tool/setup_nltk.py` once (in your venv).
+- Playwright errors: Run `playwright install` once; ensure lib dependencies are present on your OS.
+- yfinance returns None: Retry later; some tickers or regions can be spotty. The app tolerates missing financials.
+- Flair required: If posting fails with flair errors, fetch a valid flair ID and pass `--flair-id`.
+- Empty dashboards: Make sure `rstat` ran recently and `.env` is set; check `rstat.log`.
+- DB locked: If you edit while the dashboard is reading, wait or stop the server; SQLite locks are short-lived.
+
+## Safety and notes
+
+- Do not commit `.env` or your database if it contains sensitive data.
+- This project is for research/entertainment. Not investment advice.
 
 ---
 
-## Usage
-
-The tool is split into two commands: one for gathering data and one for viewing it.
-
-### 1. The Scraper (`rstat`)
-
-This is the command-line tool you will use to populate the database. It is highly flexible.
-
-**Common Commands:**
-
-*   **Run a daily scan (for cron jobs):** Scans subreddits from `subreddits.json` for posts in the last 24 hours.
-    ```bash
-    rstat --config subreddits.json --days 1
-    ```
-
-*   **Scan a single subreddit:** Ignores the config file and scans just one subreddit.
-    ```bash
-    rstat --subreddit wallstreetbets --days 1
-    ```
-
-*   **Back-fill data for last week:** Scans a specific subreddit for all new posts in the last 7 days.
-    ```bash
-    rstat --subreddit Tollbugatabets --days 7
-    ```
-
-*   **Get help and see all options:**
-    ```bash
-    rstat --help
-    ```
-
-### 2. The Web Dashboard (`rstat-dashboard`)
-
-This command starts a local web server to let you explore the data you've collected.
-
-**How to Run:**
-1.  Make sure you have run the `rstat` scraper at least once to populate the database.
-2.  Start the web server:
-    ```bash
-    rstat-dashboard
-    ```
-3.  Open your web browser and navigate to **http://127.0.0.1:5000**.
-
-**Dashboard Features:**
-*   **Main Page:** Shows the Top 10 most mentioned tickers across all scanned subreddits.
-*   **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.
+Made with Python, Flask, NLTK, Playwright, and Tailwind.

config/nginx/dev/localhost.conf

@@ -0,0 +1,17 @@
+server {
+  listen 80 default_server;
+  listen [::]:80 default_server;
+
+  server_name _;
+  server_tokens off;
+
+  location / {
+    proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+    proxy_set_header X-Forwarded-Proto $scheme;
+    proxy_set_header X-Real-IP $remote_addr;
+    proxy_set_header Host $http_host;
+
+    proxy_pass http://varnish:80;
+    proxy_redirect off;
+  }
+}

config/nginx/rstat.net-NOSSL.conf

@@ -0,0 +1,15 @@
+server {
+  listen 80 default_server;
+  listen [::]:80 default_server;
+
+  server_name www.rstat.net rstat.net;
+  server_tokens off;
+
+  location /.well-known/acme-challenge/ {
+    root /usr/share/nginx/certbot;
+  }
+
+  location / {
+    return 301 https://rstat.net$request_uri;
+  }
+}

config/nginx/rstat.net-SSL.conf

@@ -0,0 +1,67 @@
+server {
+  listen 443 ssl;
+  listen [::]:443 ssl;
+
+  server_name www.rstat.net;
+  server_tokens off;
+
+  http2 on;
+
+  ssl_certificate /etc/nginx/ssl/live/www.rstat.net/fullchain.pem;
+  ssl_certificate_key /etc/nginx/ssl/live/www.rstat.net/privkey.pem;
+
+  # HSTS (ngx_http_headers_module is required) (63072000 seconds)
+  add_header Strict-Transport-Security "max-age=63072000" always;
+
+  return 301 https://rstat.net$request_uri;
+}
+
+server {
+  listen 443 ssl;
+  listen [::]:443 ssl;
+
+  server_name rstat.net;
+  server_tokens off;
+
+  http2 on;
+
+  ssl_certificate /etc/nginx/ssl/live/www.rstat.net/fullchain.pem;
+  ssl_certificate_key /etc/nginx/ssl/live/www.rstat.net/privkey.pem;
+
+  # HSTS (ngx_http_headers_module is required) (63072000 seconds)
+  add_header Strict-Transport-Security "max-age=63072000" always;
+
+  location / {
+    proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+    proxy_set_header X-Forwarded-Proto $scheme;
+    proxy_set_header X-Real-IP $remote_addr;
+    proxy_set_header Host $http_host;
+
+    proxy_pass http://varnish:80;
+    proxy_redirect off;
+  }
+}
+
+# intermediate configuration
+ssl_protocols TLSv1.2 TLSv1.3;
+ssl_ecdh_curve X25519:prime256v1:secp384r1;
+ssl_ciphers ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:DHE-RSA-AES128-GCM-SHA256:DHE-RSA-AES256-GCM-SHA384:DHE-RSA-CHACHA20-POLY1305;
+ssl_prefer_server_ciphers off;
+
+# see also ssl_session_ticket_key alternative to stateful session cache
+ssl_session_timeout 1d;
+ssl_session_cache shared:MozSSL:10m;  # about 40000 sessions
+
+# curl https://ssl-config.mozilla.org/ffdhe2048.txt > /path/to/dhparam
+ssl_dhparam /etc/nginx/ssl/dhparam.pem;
+
+# OCSP stapling
+ssl_stapling on;
+ssl_stapling_verify on;
+
+# verify chain of trust of OCSP response using Root CA and Intermediate certs
+ssl_trusted_certificate /etc/nginx/ssl/live/www.rstat.net/chain.pem;
+
+# replace with the IP address of your resolver;
+# async 'resolver' is important for proper operation of OCSP stapling
+resolver 67.207.67.3;

config/varnish/default.vcl

@@ -0,0 +1,105 @@
+vcl 4.1;
+
+# https://github.com/varnish/toolbox/tree/master/vcls/hit-miss
+include "hit-miss.vcl";
+import std;
+
+backend default {
+  .host = "rstat-dashboard";
+  .port = "5000";
+}
+
+sub vcl_recv {
+  if (req.method != "GET" &&
+      req.method != "HEAD" &&
+      req.method != "PUT" &&
+      req.method != "POST" &&
+      req.method != "TRACE" &&
+      req.method != "OPTIONS" &&
+      req.method != "DELETE") {
+        /* Non-RFC2616 or CONNECT which is weird. */
+        return (pipe);
+  }
+
+  # We only deal with GET and HEAD by default
+  if (req.method != "GET" && req.method != "HEAD") {
+      return (pass);
+  }
+
+  set req.url = regsub(req.url, "^http[s]?://", "");
+
+  # static files are always cacheable. remove SSL flag and cookie
+  if (req.url ~ "^/(pub/)?(media|static)/.*\.(ico|jpg|jpeg|png|gif|tiff|bmp|mp3|ogg|svg|swf|woff|woff2|eot|ttf|otf)$") {
+    unset req.http.Https;
+    unset req.http.X-Forwarded-Proto;
+    unset req.http.Cookie;
+    unset req.http.css;
+    unset req.http.js;
+  }
+
+  return (hash);
+}
+
+sub vcl_hash {
+  if (req.http.host) {
+    hash_data(req.http.host);
+  } else {
+    hash_data(server.ip);
+  }
+
+  # To make sure http users don't see ssl warning
+  if (req.http.X-Forwarded-Proto) {
+    hash_data(req.http.X-Forwarded-Proto);
+  }
+}
+
+sub vcl_backend_response {
+  set beresp.http.X-Host = bereq.http.host;
+
+  set beresp.ttl = 1m;
+  # Enable stale content serving
+  set beresp.grace = 24h;
+  # Preserve the origin's Cache-Control header for client-side caching
+  if (beresp.http.Cache-Control) {
+    set beresp.http.X-Orig-Cache-Control = beresp.http.Cache-Control;
+  }
+
+  # validate if we need to cache it and prevent from setting cookie
+  # images, css and js are cacheable by default so we have to remove cookie also
+  if (beresp.ttl > 0s && (bereq.method == "GET" || bereq.method == "HEAD")) {
+    unset beresp.http.set-cookie;
+    unset beresp.http.set-css;
+    unset beresp.http.set-js;
+    if (bereq.url !~ "\.(ico|jpg|jpeg|png|gif|tiff|bmp|gz|tgz|bz2|tbz|mp3|ogg|svg|swf|woff|woff2|eot|ttf|otf)(\?|$)") {
+      set beresp.http.Pragma = "no-cache";
+      set beresp.http.Expires = "-1";
+      set beresp.http.Cache-Control = "no-store, no-cache, must-revalidate, max-age=0";
+      set beresp.grace = 1m;
+    }
+  }
+
+  # If page is not cacheable then bypass varnish for 2 minutes as Hit-For-Pass
+  if (beresp.ttl <= 0s ||
+      beresp.http.Surrogate-control ~ "no-store" ||
+      (!beresp.http.Surrogate-Control && beresp.http.Vary == "*")) {
+    # Mark as Hit-For-Pass for the next 2 minutes
+    set beresp.ttl = 120s;
+    set beresp.uncacheable = true;
+  }
+  return (deliver);
+}
+
+sub vcl_deliver {
+  # Restore the origin's Cache-Control header for the browser
+  if (resp.http.X-Orig-Cache-Control) {
+    set resp.http.Cache-Control = resp.http.X-Orig-Cache-Control;
+    unset resp.http.X-Orig-Cache-Control;
+  } else {
+    # If no Cache-Control was set by the origin, we'll set a default
+    set resp.http.Cache-Control = "no-cache, must-revalidate";
+  }
+
+  unset resp.http.Server;
+  unset resp.http.Via;
+  unset resp.http.Link;
+}

config/varnish/dev.vcl

@@ -0,0 +1,105 @@
+vcl 4.1;
+
+# https://github.com/varnish/toolbox/tree/master/vcls/hit-miss
+include "hit-miss.vcl";
+import std;
+
+backend default {
+  .host = "rstat-dashboard";
+  .port = "5000";
+}
+
+sub vcl_recv {
+  if (req.method != "GET" &&
+      req.method != "HEAD" &&
+      req.method != "PUT" &&
+      req.method != "POST" &&
+      req.method != "TRACE" &&
+      req.method != "OPTIONS" &&
+      req.method != "DELETE") {
+        /* Non-RFC2616 or CONNECT which is weird. */
+        return (pipe);
+  }
+
+  # We only deal with GET and HEAD by default
+  if (req.method != "GET" && req.method != "HEAD") {
+      return (pass);
+  }
+
+  set req.url = regsub(req.url, "^http[s]?://", "");
+
+  # static files are always cacheable. remove SSL flag and cookie
+  if (req.url ~ "^/(pub/)?(media|static)/.*\.(ico|jpg|jpeg|png|gif|tiff|bmp|mp3|ogg|svg|swf|woff|woff2|eot|ttf|otf)$") {
+    unset req.http.Https;
+    unset req.http.X-Forwarded-Proto;
+    unset req.http.Cookie;
+    unset req.http.css;
+    unset req.http.js;
+  }
+
+  return (hash);
+}
+
+sub vcl_hash {
+  if (req.http.host) {
+    hash_data(req.http.host);
+  } else {
+    hash_data(server.ip);
+  }
+
+  # To make sure http users don't see ssl warning
+  if (req.http.X-Forwarded-Proto) {
+    hash_data(req.http.X-Forwarded-Proto);
+  }
+}
+
+sub vcl_backend_response {
+  set beresp.http.X-Host = bereq.http.host;
+
+  set beresp.ttl = 1m;
+  # Enable stale content serving
+  set beresp.grace = 24h;
+  # Preserve the origin's Cache-Control header for client-side caching
+  if (beresp.http.Cache-Control) {
+    set beresp.http.X-Orig-Cache-Control = beresp.http.Cache-Control;
+  }
+
+  # validate if we need to cache it and prevent from setting cookie
+  # images, css and js are cacheable by default so we have to remove cookie also
+  if (beresp.ttl > 0s && (bereq.method == "GET" || bereq.method == "HEAD")) {
+    unset beresp.http.set-cookie;
+    unset beresp.http.set-css;
+    unset beresp.http.set-js;
+    if (bereq.url !~ "\.(ico|jpg|jpeg|png|gif|tiff|bmp|gz|tgz|bz2|tbz|mp3|ogg|svg|swf|woff|woff2|eot|ttf|otf)(\?|$)") {
+      set beresp.http.Pragma = "no-cache";
+      set beresp.http.Expires = "-1";
+      set beresp.http.Cache-Control = "no-store, no-cache, must-revalidate, max-age=0";
+      set beresp.grace = 1m;
+    }
+  }
+
+  # If page is not cacheable then bypass varnish for 2 minutes as Hit-For-Pass
+  if (beresp.ttl <= 0s ||
+      beresp.http.Surrogate-control ~ "no-store" ||
+      (!beresp.http.Surrogate-Control && beresp.http.Vary == "*")) {
+    # Mark as Hit-For-Pass for the next 2 minutes
+    set beresp.ttl = 120s;
+    set beresp.uncacheable = true;
+  }
+  return (deliver);
+}
+
+sub vcl_deliver {
+  # Restore the origin's Cache-Control header for the browser
+  if (resp.http.X-Orig-Cache-Control) {
+    set resp.http.Cache-Control = resp.http.X-Orig-Cache-Control;
+    unset resp.http.X-Orig-Cache-Control;
+  } else {
+    # If no Cache-Control was set by the origin, we'll set a default
+    set resp.http.Cache-Control = "no-cache, must-revalidate";
+  }
+
+  unset resp.http.Server;
+  unset resp.http.Via;
+  unset resp.http.Link;
+}

config/varnish/hit-miss.vcl

@@ -0,0 +1,39 @@
+sub vcl_recv {
+	unset req.http.x-cache;
+}
+
+sub vcl_hit {
+	set req.http.x-cache = "hit";
+	if (obj.ttl <= 0s && obj.grace > 0s) {
+		set req.http.x-cache = "hit graced";
+	}
+}
+
+sub vcl_miss {
+	set req.http.x-cache = "miss";
+}
+
+sub vcl_pass {
+	set req.http.x-cache = "pass";
+}
+
+sub vcl_pipe {
+	set req.http.x-cache = "pipe uncacheable";
+}
+
+sub vcl_synth {
+	set req.http.x-cache = "synth synth";
+	# comment the following line to omit the x-cache header in the response
+	set resp.http.x-cache = req.http.x-cache;
+}
+
+sub vcl_deliver {
+	if (obj.uncacheable) {
+		set req.http.x-cache = req.http.x-cache + " uncacheable" ;
+	} else {
+		set req.http.x-cache = req.http.x-cache + " cached" ;
+	}
+
+	# comment the following line to omit the x-cache header in the response
+	set resp.http.x-cache = req.http.x-cache;
+}

docker-compose-dev.yml

@@ -0,0 +1,31 @@
+name: rstat
+
+services:
+
+  rstat-dashboard:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    restart: always
+    volumes:
+      - ./reddit_stocks.db:/usr/src/app/reddit_stocks.db:ro
+    ports:
+      - "5000:5000"
+
+  nginx:
+    image: nginx:1.29.0
+    restart: always
+    volumes:
+      - ./config/nginx/dev:/etc/nginx/conf.d:ro
+      - ./public:/usr/share/nginx:ro
+    ports:
+      - "80:80"
+
+  varnish:
+    image: varnish:7.7.1
+    restart: always
+    volumes:
+      - ./config/varnish/dev.vcl:/etc/varnish/default.vcl:ro"
+      - ./config/varnish/hit-miss.vcl:/etc/varnish/hit-miss.vcl:ro"
+    tmpfs:
+      - /var/lib/varnish/varnishd:exec

docker-compose.yml

@@ -0,0 +1,39 @@
+name: rstat
+
+services:
+
+  rstat-dashboard:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    restart: always
+    volumes:
+      - ./reddit_stocks.db:/usr/src/app/reddit_stocks.db:ro
+    ports:
+      - "5000:5000"
+
+  nginx:
+    image: nginx:1.29.0
+    restart: always
+    volumes:
+      - ./config/nginx:/etc/nginx/conf.d:ro
+      - ./config/certbot:/etc/nginx/ssl:ro
+      - ./public:/usr/share/nginx:ro
+    ports:
+      - "80:80"
+      - "443:443"
+
+  varnish:
+    image: varnish:7.7.1
+    restart: always
+    volumes:
+      - ./config/varnish/default.vcl:/etc/varnish/default.vcl:ro"
+      - ./config/varnish/hit-miss.vcl:/etc/varnish/hit-miss.vcl:ro"
+    tmpfs:
+      - /var/lib/varnish/varnishd:exec
+
+  certbot:
+    image: certbot/certbot:v4.1.1
+    volumes:
+      - ./config/certbot:/etc/letsencrypt:rw
+      - ./public/certbot:/usr/share/nginx/certbot:rw

export_image.py

@@ -0,0 +1,86 @@
+# export_image.py
+
+import argparse
+import os
+import time
+from playwright.sync_api import sync_playwright
+from pathlib import Path
+
+# Define the output directory as a constant
+OUTPUT_DIR = "images"
+
+
+def export_image(url_path, filename_prefix):
+    """
+    Launches a headless browser, navigates to a URL path, and screenshots
+    the main content element, saving it to the OUTPUT_DIR.
+    """
+    print(f"-> Preparing to export image for: {filename_prefix}")
+
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+    base_url = "https://rstat.net"
+    # Ensure the URL path starts correctly
+    url_path = url_path.lstrip("/")
+    url = f"{base_url}/{url_path}"
+
+    output_file = os.path.join(OUTPUT_DIR, f"{filename_prefix}_{int(time.time())}.png")
+
+    with sync_playwright() as p:
+        try:
+            browser = p.chromium.launch()
+            page = browser.new_page()
+
+            page.set_viewport_size({"width": 1920, "height": 1080})
+
+            print(f"  Navigating to {url}...")
+            # Use 'domcontentloaded' for faster navigation when possible
+            page.goto(url, wait_until="domcontentloaded")
+
+            # Give fonts and styles a moment to render after the DOM is ready
+            page.wait_for_timeout(500)
+
+            # --- THIS IS THE CORRECTED LINE ---
+            # Target the new, correct class for our main content card
+            element = page.locator(".max-w-3xl")
+
+            print(f"  Saving screenshot to {output_file}...")
+            element.screenshot(path=output_file)
+
+            browser.close()
+            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."
+            )
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Export subreddit sentiment images.")
+    group = parser.add_mutually_exclusive_group(required=True)
+    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.",
+    )
+    args = parser.parse_args()
+
+    view_type = "weekly" if args.weekly else "daily"
+
+    if args.subreddit:
+        url_path_to_render = f"subreddit/{args.subreddit}?view={view_type}&image=true"
+        filename_prefix_to_save = f"{args.subreddit}_{view_type}"
+        export_image(url_path_to_render, filename_prefix_to_save)
+
+    elif args.overall:
+        url_path_to_render = f"/?view={view_type}&image=true"
+        filename_prefix_to_save = f"overall_summary_{view_type}"
+        export_image(url_path_to_render, filename_prefix_to_save)

extract-words-from-log.sh

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+grep possibly rstat.log | grep -v 'YFPricesMissingError' | awk '{print $6 }' | tr -d : | tr -d \$ | sort -u | awk '{printf "%s\"%s\"", sep, $0; sep=", "} END {print ""}'

fetch_close_price.py

@@ -0,0 +1,37 @@
+# fetch_close_price.py
+# This script does ONLY ONE THING: gets the closing price using the stable Ticker.history() method.
+import sys
+import json
+import yfinance as yf
+import pandas as pd
+import logging
+
+# Suppress verbose yfinance logging in this isolated process
+logging.getLogger("yfinance").setLevel(logging.CRITICAL)
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        # Exit with an error code if no ticker is provided
+        sys.exit(1)
+
+    ticker_symbol = sys.argv[1]
+
+    try:
+        # Instead of the global yf.download(), we use the Ticker object's .history() method.
+        # This uses a different internal code path that we have proven is stable.
+        ticker = yf.Ticker(ticker_symbol)
+        data = ticker.history(period="2d", auto_adjust=False)
+
+        closing_price = None
+        if not data.empty:
+            last_close_raw = data["Close"].iloc[-1]
+            if pd.notna(last_close_raw):
+                closing_price = float(last_close_raw)
+
+        # On success, print JSON to stdout and exit cleanly
+        print(json.dumps({"closing_price": closing_price}))
+        sys.exit(0)
+    except Exception:
+        # If any error occurs, print an empty JSON and exit with an error code
+        print(json.dumps({"closing_price": None}))
+        sys.exit(1)

fetch_market_cap.py

@@ -0,0 +1,28 @@
+# fetch_market_cap.py
+# This script does ONLY ONE THING: gets the market cap.
+import sys
+import json
+import yfinance as yf
+import logging
+
+# Suppress verbose yfinance logging in this isolated process
+logging.getLogger("yfinance").setLevel(logging.CRITICAL)
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        # Exit with an error code if no ticker is provided
+        sys.exit(1)
+
+    ticker_symbol = sys.argv[1]
+
+    try:
+        # Directly get the market cap
+        market_cap = yf.Ticker(ticker_symbol).info.get("marketCap")
+
+        # On success, print JSON to stdout and exit cleanly
+        print(json.dumps({"market_cap": market_cap}))
+        sys.exit(0)
+    except Exception:
+        # If any error occurs, print an empty JSON and exit with an error code
+        print(json.dumps({"market_cap": None}))
+        sys.exit(1)

get_refresh_token.py

@@ -0,0 +1,82 @@
+# get_refresh_token.py
+# A temporary, one-time-use script to get your OAuth2 refresh token.
+
+import praw
+from dotenv import load_dotenv
+import os
+import random
+import socket
+
+# --- IMPORTANT: Ensure this matches the "redirect uri" in your Reddit App settings ---
+REDIRECT_URI = "http://localhost:5000"
+
+
+def main():
+    print("--- RSTAT Refresh Token Generator ---")
+    load_dotenv()
+    client_id = os.getenv("REDDIT_CLIENT_ID")
+    client_secret = os.getenv("REDDIT_CLIENT_SECRET")
+
+    if not all([client_id, client_secret]):
+        print(
+            "Error: REDDIT_CLIENT_ID and REDDIT_CLIENT_SECRET must be set in your .env file."
+        )
+        return
+
+    # 1. Initialize PRAW
+    reddit = praw.Reddit(
+        client_id=client_id,
+        client_secret=client_secret,
+        redirect_uri=REDIRECT_URI,
+        user_agent="rstat_token_fetcher (by u/YourUsername)",  # Can be anything
+    )
+
+    # 2. Generate the authorization URL
+    # Scopes define what our script is allowed to do. 'identity' and 'submit' are needed.
+    scopes = ["identity", "submit", "read"]
+    state = str(random.randint(0, 65536))
+    auth_url = reddit.auth.url(scopes, state, "permanent")
+
+    print("\nStep 1: Open this URL in your browser:\n")
+    print(auth_url)
+
+    print(
+        "\nStep 2: Log in to Reddit, click 'Allow', and you'll be redirected to a 'page not found'."
+    )
+    print(
+        "Step 3: Copy the ENTIRE URL from your browser's address bar after the redirect."
+    )
+
+    # 3. Get the redirected URL from the user
+    redirected_url = input(
+        "\nStep 4: Paste the full redirected URL here and press Enter:\n> "
+    )
+
+    # 4. Exchange the authorization code for a refresh token
+    try:
+        # The state is used to prevent CSRF attacks, we're just checking it matches
+        assert state == redirected_url.split("state=")[1].split("&")[0]
+        code = redirected_url.split("code=")[1].split("#_")[0]
+
+        print("\nAuthorization code received. Fetching refresh token...")
+
+        # This is the line that gets the key!
+        refresh_token = reddit.auth.authorize(code)
+
+        print("\n--- SUCCESS! ---")
+        print("Your Refresh Token is:\n")
+        print(refresh_token)
+        print(
+            "\nStep 5: Copy this token and add it to your .env file as REDDIT_REFRESH_TOKEN."
+        )
+        print(
+            "Step 6: You can now delete your REDDIT_USERNAME and REDDIT_PASSWORD from the .env file."
+        )
+
+    except Exception as e:
+        print(f"\nAn error occurred: {e}")
+        print("Please make sure you copied the full URL.")
+
+
+if __name__ == "__main__":
+    main()

package.json

@@ -0,0 +1,25 @@
+{
+  "name": "reddit_stock_analyzer",
+  "version": "1.0.0",
+  "description": "A powerful, installable command-line tool and web dashboard to scan Reddit for stock ticker mentions, perform sentiment analysis, generate insightful reports, and create shareable summary images.",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "repository": {
+    "type": "git",
+    "url": "ssh://git@git.pkhamre.com:43721/pkhamre/reddit_stock_analyzer.git"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC",
+  "type": "commonjs",
+  "devDependencies": {
+    "@tailwindcss/cli": "^4.1.11",
+    "@tailwindcss/typography": "^0.5.16",
+    "tailwindcss": "^4.1.11"
+  },
+  "dependencies": {
+    "@tailwindplus/elements": "^1.0.3"
+  }
+}

post_to_reddit.py

@@ -0,0 +1,145 @@
+# post_to_reddit.py
+
+import argparse
+import os
+import glob
+from datetime import datetime, timezone
+import praw
+from dotenv import load_dotenv
+from pathlib import Path
+
+IMAGE_DIR = "images"
+
+
+def get_reddit_instance():
+    """Initializes and returns a PRAW Reddit instance using OAuth2 refresh token."""
+
+    env_path = Path(__file__).parent / ".env"
+    load_dotenv(dotenv_path=env_path)
+
+    client_id = os.getenv("REDDIT_CLIENT_ID")
+    client_secret = os.getenv("REDDIT_CLIENT_SECRET")
+    user_agent = os.getenv("REDDIT_USER_AGENT")
+    refresh_token = os.getenv("REDDIT_REFRESH_TOKEN")
+
+    if not all([client_id, client_secret, user_agent, refresh_token]):
+        print(
+            "Error: Reddit API credentials (including REDDIT_REFRESH_TOKEN) must be set in .env file."
+        )
+        return None
+
+    return praw.Reddit(
+        client_id=client_id,
+        client_secret=client_secret,
+        user_agent=user_agent,
+        refresh_token=refresh_token,
+    )
+
+
+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)",
+    )
+    parser.add_argument(
+        "--flair-id",
+        help="The specific Flair ID to use for the post (required for some subreddits).",
+    )
+
+    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}...")
+
+        # --- Simplified submission logic ---
+        submission = target_sub.submit_image(
+            title=post_title,
+            image_path=image_to_post,
+            flair_id=args.flair_id,  # Directly use the provided ID. This will be None if not provided.
+        )
+
+        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 "FLAIR_REQUIRED" in str(e).upper():
+            print(
+                "\nHINT: This subreddit requires a flair. You MUST provide a valid Flair ID using the --flair-id argument."
+            )
+            print(
+                "Please follow the manual steps to find the Flair ID using your browser's developer tools."
+            )
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -1,5 +1,8 @@
-yfinance
-praw
-python-dotenv
-nltk
-Flask
+Flask==3.1.1
+gunicorn==23.0.0
+nltk==3.9.1
+playwright==1.54.0
+praw==7.8.1
+python-dotenv==1.1.1
+uvicorn==0.35.0
+yfinance==0.2.65

rstat_tool/cleanup.py

@@ -0,0 +1,88 @@
+# rstat_tool/cleanup.py
+
+import argparse
+from . import database
+from .logger_setup import setup_logging, logger as log
+
+# 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
+
+
+def load_subreddits(filepath):
+    """Loads a list of subreddits from a JSON file."""
+    try:
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            return data.get("subreddits", [])
+    except (FileNotFoundError, json.JSONDecodeError) as e:
+        log.error(f"Error loading config file '{filepath}': {e}")
+        return None
+
+
+def run_cleanup():
+    """Main function for the cleanup tool."""
+    parser = argparse.ArgumentParser(
+        description="A tool to clean stale data from the RSTAT database.",
+        formatter_class=argparse.RawTextHelpFormatter,
+    )
+    parser.add_argument(
+        "--tickers",
+        action="store_true",
+        help="Clean tickers that are in the blacklist.",
+    )
+
+    # --- UPDATED ARGUMENT DEFINITION ---
+    # nargs='?': Makes the argument optional.
+    # const='subreddits.json': The value used if the flag is present with no argument.
+    # default=None: The value if the flag is not present at all.
+    parser.add_argument(
+        "--subreddits",
+        nargs="?",
+        const="subreddits.json",
+        default=None,
+        help="Clean data from subreddits NOT in the specified config file.\n(Defaults to 'subreddits.json' if flag is used without a value).",
+    )
+
+    parser.add_argument(
+        "--all", action="store_true", help="Run all available cleanup tasks."
+    )
+    parser.add_argument(
+        "--stdout", action="store_true", help="Print all log messages to the console."
+    )
+
+    args = parser.parse_args()
+
+    setup_logging(console_verbose=args.stdout)
+
+    run_any_task = False
+
+    log.critical("\n--- Starting Cleanup ---")
+
+    # --- UPDATED LOGIC TO HANDLE THE NEW ARGUMENT ---
+    if args.all or args.tickers:
+        run_any_task = True
+        database.clean_stale_tickers()
+
+    # The --subreddits argument will be None if not provided, or a filename string if it is.
+    if args.all or args.subreddits is not None:
+        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"
+        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()
+        log.error(
+            "\nError: Please provide at least one cleanup option (e.g., --tickers, --subreddits, --all)."
+        )
+        return
+
+    log.critical("\nCleanup finished.")
+
+
+if __name__ == "__main__":
+    run_cleanup()

rstat_tool/dashboard.py

@@ -1,19 +1,20 @@
 # rstat_tool/dashboard.py
 
-from flask import Flask, render_template
-from datetime import datetime, timedelta 
+from flask import Flask, render_template, request
+from datetime import datetime, timedelta, timezone
+from .logger_setup import logger as log
 from .database import (
-    get_overall_summary,
-    get_subreddit_summary,
     get_all_scanned_subreddits,
     get_deep_dive_details,
-    get_image_view_summary,
-    get_weekly_summary_for_subreddit
+    get_daily_summary_for_subreddit,
+    get_weekly_summary_for_subreddit,
+    get_overall_daily_summary,
+    get_overall_weekly_summary,
 )
 
-app = Flask(__name__, template_folder='../templates')
+app = Flask(__name__, template_folder='../templates', static_folder='../static')
 
-@app.template_filter('format_mc')
+@app.template_filter("format_mc")
 def format_market_cap(mc):
     """Formats a large number into a readable market cap string."""
     if mc is None or mc == 0:
@@ -27,23 +28,81 @@ def format_market_cap(mc):
     else:
         return f"${mc:,}"
 
+
 @app.context_processor
 def inject_subreddits():
-    """Makes the list of all scanned subreddits available to every template."""
-    subreddits = get_all_scanned_subreddits()
-    return dict(subreddits=subreddits)
+    """Makes the list of all subreddits available to every template for the navbar."""
+    return dict(all_subreddits=get_all_scanned_subreddits())
+
 
 @app.route("/")
-def index():
-    """The handler for the main dashboard page."""
-    tickers = get_overall_summary(limit=10)
-    return render_template("index.html", tickers=tickers)
+def overall_dashboard():
+    """Handler for the main, overall dashboard."""
+    view_type = request.args.get("view", "daily")
+    is_image_mode = request.args.get("image") == "true"
+
+    try:
+        # Get the 'top' parameter, default to 10, and ensure it's an integer
+        top_n = int(request.args.get('top', 10))
+    except (ValueError, TypeError):
+        top_n = 10 # Fallback to 10 if the value is invalid
+
+    if view_type == "weekly":
+        tickers, start, end = get_overall_weekly_summary(limit=top_n)
+        date_string = f"{start.strftime('%b %d')} - {end.strftime('%b %d, %Y')}"
+        subtitle = f"All Subreddits - Top {top_n} Weekly"
+    else:  # Default to daily
+        tickers = get_overall_daily_summary(limit=top_n)
+        date_string = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+        subtitle = f"All Subreddits - Top {top_n} Daily"
+
+    return render_template(
+        "dashboard_view.html",
+        title="Overall Dashboard",
+        subtitle=subtitle,
+        date_string=date_string,
+        tickers=tickers,
+        view_type=view_type,
+        subreddit_name=None,
+        is_image_mode=is_image_mode,
+        base_url="/",
+    )
+
 
 @app.route("/subreddit/<name>")
 def subreddit_dashboard(name):
-    """A dynamic route for per-subreddit dashboards."""
-    tickers = get_subreddit_summary(name, limit=10)
-    return render_template("subreddit.html", tickers=tickers, subreddit_name=name)
+    """Handler for per-subreddit dashboards."""
+    view_type = request.args.get("view", "daily")
+    is_image_mode = request.args.get("image") == "true"
+
+    try:
+        top_n = int(request.args.get('top', 10))
+    except (ValueError, TypeError):
+        top_n = 10
+
+    if view_type == "weekly":
+        today = datetime.now(timezone.utc)
+        target_date = today - timedelta(days=7)
+        tickers, start, end = get_weekly_summary_for_subreddit(name, target_date, limit=top_n)
+        date_string = f"{start.strftime('%b %d')} - {end.strftime('%b %d, %Y')}"
+        subtitle = f"r/{name} - Top {top_n} Weekly"
+    else:  # Default to daily
+        tickers = get_daily_summary_for_subreddit(name, limit=top_n)
+        date_string = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+        subtitle = f"r/{name} - Top {top_n} Daily"
+
+    return render_template(
+        "dashboard_view.html",
+        title=f"r/{name} Dashboard",
+        subtitle=subtitle,
+        date_string=date_string,
+        tickers=tickers,
+        view_type=view_type,
+        subreddit_name=name,
+        is_image_mode=is_image_mode,
+        base_url=f"/subreddit/{name}",
+    )
+
 
 @app.route("/deep-dive/<symbol>")
 def deep_dive(symbol):
@@ -52,41 +111,21 @@ 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):
-    """The handler for the image-style dashboard."""
-    tickers = get_image_view_summary(name)
-    current_date = datetime.utcnow().strftime("%Y-%m-%d")
-    return render_template(
-        "image_view.html",
-        tickers=tickers,
-        subreddit_name=name,
-        current_date=current_date
-    )
 
-@app.route("/image/weekly/<name>")
-def weekly_image_view(name):
-    """The handler for the WEEKLY image-style dashboard."""
-    tickers = get_weekly_summary_for_subreddit(name)
-    
-    # Create the date range string for the title
-    end_date = datetime.utcnow()
-    start_date = end_date - timedelta(days=7)
-    date_range_str = f"{start_date.strftime('%b %d')} - {end_date.strftime('%b %d, %Y')}"
+@app.route("/about")
+def about_page():
+    """Handler for the static About page."""
+    # We need to pass these so the navbar knows which items to highlight
+    return render_template("about.html", subreddit_name=None, view_type='daily')
 
-    return render_template(
-        "weekly_image_view.html",
-        tickers=tickers,
-        subreddit_name=name,
-        date_range=date_range_str
-    )
 
 def start_dashboard():
     """The main function called by the 'rstat-dashboard' command."""
-    print("Starting Flask server...")
-    print("Open http://127.0.0.1:5000 in your browser.")
-    print("Press CTRL+C to stop the server.")
+    log.info("Starting Flask server...")
+    log.info("Open http://127.0.0.1:5000 in your browser.")
+    log.info("Press CTRL+C to stop the server.")
     app.run(debug=True)
 
+
 if __name__ == "__main__":
-    start_dashboard()
+    start_dashboard()

rstat_tool/database.py

@@ -2,26 +2,95 @@
 
 import sqlite3
 import time
-from .ticker_extractor import COMMON_WORDS_BLACKLIST
-from datetime import datetime, timedelta
+from .ticker_extractor import (
+    COMMON_WORDS_BLACKLIST,
+    extract_golden_tickers,
+    extract_potential_tickers,
+)
+from .logger_setup import logger as log
+from datetime import datetime, timedelta, timezone
 
 DB_FILE = "reddit_stocks.db"
+MARKET_CAP_REFRESH_INTERVAL = 86400
+
+
+def clean_stale_tickers():
+    """
+    Removes tickers and their associated mentions from the database
+    if the ticker symbol exists in the COMMON_WORDS_BLACKLIST.
+    """
+    log.info("\n--- Cleaning Stale Tickers from Database ---")
+    conn = get_db_connection()
+    cursor = conn.cursor()
+
+    placeholders = ",".join("?" for _ in COMMON_WORDS_BLACKLIST)
+    query = f"SELECT id, symbol FROM tickers WHERE symbol IN ({placeholders})"
+
+    cursor.execute(query, tuple(COMMON_WORDS_BLACKLIST))
+    stale_tickers = cursor.fetchall()
+
+    if not stale_tickers:
+        log.info("No stale tickers to clean.")
+        conn.close()
+        return
+
+    for ticker in stale_tickers:
+        ticker_id = ticker["id"]
+        ticker_symbol = ticker["symbol"]
+        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()
+    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.
+    """
+    log.info("\n--- Cleaning Stale Subreddits from Database ---")
+    conn = get_db_connection()
+    cursor = conn.cursor()
+
+    # Convert the list of active subreddits from the config file to a lowercase set for fast,
+    # case-insensitive lookups.
+    active_subreddits_lower = {sub.lower() for sub in active_subreddits}
+
+    cursor.execute("SELECT id, name FROM subreddits")
+    db_subreddits = cursor.fetchall()
+    stale_sub_ids = []
+    for sub in db_subreddits:
+        if sub["name"] not in active_subreddits_lower:
+            log.info(f"Found stale subreddit to remove: r/{sub['name']}")
+            stale_sub_ids.append(sub["id"])
+    if not stale_sub_ids:
+        log.info("No stale subreddits to clean.")
+        conn.close()
+        return
+    for sub_id in stale_sub_ids:
+        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()
+    log.info("Stale subreddit cleanup complete.")
+
 
 def get_db_connection():
-    """Establishes a connection to the SQLite database."""
     conn = sqlite3.connect(DB_FILE)
     conn.row_factory = sqlite3.Row
     return conn
 
+
 def initialize_db():
-    """
-    Initializes the database and creates the necessary tables if they don't exist.
-    """
     conn = get_db_connection()
     cursor = conn.cursor()
-
-    # --- Create tickers table ---
-    cursor.execute("""
+    cursor.execute(
+        """
         CREATE TABLE IF NOT EXISTS tickers (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
             symbol TEXT NOT NULL UNIQUE,
@@ -29,33 +98,36 @@ def initialize_db():
             closing_price REAL,
             last_updated INTEGER
         )
-    """)
-
-    # --- Create subreddits table ---
-    cursor.execute("""
+    """
+    )
+    cursor.execute(
+        """
         CREATE TABLE IF NOT EXISTS subreddits (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
             name TEXT NOT NULL UNIQUE
         )
-    """)
-
-    # --- Create mentions table ---
-    cursor.execute("""
+    """
+    )
+    cursor.execute(
+        """
         CREATE TABLE IF NOT EXISTS mentions (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
             ticker_id INTEGER,
             subreddit_id INTEGER,
             post_id TEXT NOT NULL,
-            mention_type TEXT NOT NULL, -- Can be 'post' or 'comment'
+            comment_id TEXT, -- NEW: Will be NULL for post mentions
+            mention_type TEXT NOT NULL,
+            mention_sentiment REAL,
             mention_timestamp INTEGER NOT NULL,
-            sentiment_score REAL,
             FOREIGN KEY (ticker_id) REFERENCES tickers (id),
             FOREIGN KEY (subreddit_id) REFERENCES subreddits (id),
-            UNIQUE(ticker_id, post_id, mention_type, sentiment_score)
+            -- The new, perfect uniqueness rule:
+            UNIQUE(ticker_id, post_id, comment_id)
         )
-    """)
-
-    cursor.execute("""
+    """
+    )
+    cursor.execute(
+        """
         CREATE TABLE IF NOT EXISTS posts (
             id INTEGER PRIMARY KEY AUTOINCREMENT,
             post_id TEXT NOT NULL UNIQUE,
@@ -67,155 +139,75 @@ def initialize_db():
             avg_comment_sentiment REAL,
             FOREIGN KEY (subreddit_id) REFERENCES subreddits (id)
         )
-    """)
-
+    """
+    )
     conn.commit()
     conn.close()
-    print("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 ---")
-    conn = get_db_connection()
-    cursor = conn.cursor()
-
-    placeholders = ','.join('?' for _ in COMMON_WORDS_BLACKLIST)
-    query = f"SELECT id, symbol FROM tickers WHERE symbol IN ({placeholders})"
-    
-    cursor.execute(query, tuple(COMMON_WORDS_BLACKLIST))
-    stale_tickers = cursor.fetchall()
-
-    if not stale_tickers:
-        print("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})...")
-        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("Database initialized successfully.")
 
 
-def add_mention(conn, ticker_id, subreddit_id, post_id, mention_type, timestamp, sentiment):
+def add_mention(
+    conn,
+    ticker_id,
+    subreddit_id,
+    post_id,
+    mention_type,
+    timestamp,
+    mention_sentiment,
+    comment_id=None,
+):
     cursor = conn.cursor()
     try:
         cursor.execute(
-            "INSERT INTO mentions (ticker_id, subreddit_id, post_id, mention_type, mention_timestamp, sentiment_score) VALUES (?, ?, ?, ?, ?, ?)",
-            (ticker_id, subreddit_id, post_id, mention_type, timestamp, sentiment)
+            """
+            INSERT INTO mentions (ticker_id, subreddit_id, post_id, comment_id, mention_type, mention_timestamp, mention_sentiment)
+            VALUES (?, ?, ?, ?, ?, ?, ?)
+            """,
+            (
+                ticker_id,
+                subreddit_id,
+                post_id,
+                comment_id,
+                mention_type,
+                timestamp,
+                mention_sentiment,
+            ),
         )
-        conn.commit()
     except sqlite3.IntegrityError:
+        # This will now correctly catch and ignore any true duplicates.
         pass
 
+
 def get_or_create_entity(conn, table_name, column_name, value):
     """Generic function to get or create an entity and return its ID."""
     cursor = conn.cursor()
     cursor.execute(f"SELECT id FROM {table_name} WHERE {column_name} = ?", (value,))
     result = cursor.fetchone()
     if result:
-        return result['id']
+        return result["id"]
     else:
         cursor.execute(f"INSERT INTO {table_name} ({column_name}) VALUES (?)", (value,))
         conn.commit()
         return cursor.lastrowid
 
+
 def update_ticker_financials(conn, ticker_id, market_cap, closing_price):
     """Updates the financials and timestamp for a specific ticker."""
     cursor = conn.cursor()
     current_timestamp = int(time.time())
     cursor.execute(
         "UPDATE tickers SET market_cap = ?, closing_price = ?, last_updated = ? WHERE id = ?",
-        (market_cap, closing_price, current_timestamp, ticker_id)
+        (market_cap, closing_price, current_timestamp, ticker_id),
     )
     conn.commit()
 
+
 def get_ticker_info(conn, ticker_id):
     """Retrieves all info for a specific ticker by its ID."""
     cursor = conn.cursor()
     cursor.execute("SELECT * FROM tickers WHERE id = ?", (ticker_id,))
     return cursor.fetchone()
 
-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 ---")
-    conn = get_db_connection()
-    cursor = conn.cursor()
-    query = """
-        SELECT
-            t.symbol, t.market_cap, COUNT(m.id) as mention_count,
-            SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
-            SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
-            SUM(CASE WHEN m.sentiment_score 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 ORDER BY mention_count DESC LIMIT ?;
-    """
-    results = cursor.execute(query, (limit,)).fetchall()
-    header = f"{'Ticker':<8} | {'Mentions':<8} | {'Bullish':<8} | {'Bearish':<8} | {'Neutral':<8} | {'Market Cap':<15}"
-    print(header)
-    print("-" * len(header))
-    for row in results:
-        market_cap_str = "N/A"
-        if row['market_cap'] and row['market_cap'] > 0:
-            mc = row['market_cap']
-            if mc >= 1e12: market_cap_str = f"${mc/1e12:.2f}T"
-            elif mc >= 1e9: market_cap_str = f"${mc/1e9:.2f}B"
-            else: market_cap_str = f"${mc/1e6:.2f}M"
-        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}")
-    conn.close()
-
-def get_overall_summary(limit=50):
-    conn = get_db_connection()
-    query = """
-        SELECT
-            t.symbol, t.market_cap, t.closing_price, -- Added closing_price
-            COUNT(m.id) as mention_count,
-            SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
-            SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
-            SUM(CASE WHEN m.sentiment_score 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 -- Added closing_price
-        ORDER BY mention_count DESC LIMIT ?;
-    """
-    results = conn.execute(query, (limit,)).fetchall()
-    conn.close()
-    return results
-
-def get_subreddit_summary(subreddit_name, limit=50):
-    conn = get_db_connection()
-    query = """
-        SELECT
-            t.symbol, t.market_cap, t.closing_price, -- Added closing_price
-            COUNT(m.id) as mention_count,
-            SUM(CASE WHEN m.sentiment_score > 0.1 THEN 1 ELSE 0 END) as bullish_mentions,
-            SUM(CASE WHEN m.sentiment_score < -0.1 THEN 1 ELSE 0 END) as bearish_mentions,
-            SUM(CASE WHEN m.sentiment_score 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 s.name = ?
-        GROUP BY t.symbol, t.market_cap, t.closing_price -- Added closing_price
-        ORDER BY mention_count DESC LIMIT ?;
-    """
-    results = conn.execute(query, (subreddit_name, limit)).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]
 
 def add_or_update_post_analysis(conn, post_data):
     """
@@ -232,79 +224,218 @@ def add_or_update_post_analysis(conn, post_data):
             comment_count = excluded.comment_count,
             avg_comment_sentiment = excluded.avg_comment_sentiment;
         """,
-        post_data
+        post_data,
     )
     conn.commit()
 
+
+def get_week_start_end(for_date):
+    """Calculates the start (Monday) and end (Sunday) of the week."""
+    start_of_week = for_date - timedelta(days=for_date.weekday())
+    end_of_week = start_of_week + timedelta(days=6)
+    start_of_week = start_of_week.replace(hour=0, minute=0, second=0, microsecond=0)
+    end_of_week = end_of_week.replace(hour=23, minute=59, second=59, microsecond=999999)
+    return start_of_week, end_of_week
+
+
+def get_overall_daily_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 total_mentions,
+            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
+        WHERE m.mention_timestamp >= ?
+        GROUP BY t.symbol, t.market_cap, t.closing_price
+        ORDER BY total_mentions DESC LIMIT ?;
+    """
+    results = conn.execute(query, (one_day_ago_timestamp, limit)).fetchall() 
+    conn.close()
+    return results
+
+
+def get_overall_weekly_summary(limit=10):
+    """Gets the top tickers across all subreddits for LAST WEEK (Mon-Sun)."""
+    conn = get_db_connection()
+    today = datetime.now(timezone.utc)
+    target_date_for_last_week = today - timedelta(days=7)
+    start_of_week, end_of_week = get_week_start_end(target_date_for_last_week)
+    start_timestamp = int(start_of_week.timestamp())
+    end_timestamp = int(end_of_week.timestamp())
+    query = """
+        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as total_mentions,
+            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
+        FROM mentions m JOIN tickers t ON m.ticker_id = t.id
+        WHERE m.mention_timestamp BETWEEN ? AND ?
+        GROUP BY t.symbol, t.market_cap, t.closing_price
+        ORDER BY total_mentions DESC LIMIT ?;
+    """
+    results = conn.execute(query, (start_timestamp, end_timestamp, limit)).fetchall()
+    conn.close()
+    return results, start_of_week, end_of_week
+
+
+def get_daily_summary_for_subreddit(subreddit_name, limit=10):
+    """Gets a summary for a subreddit's DAILY 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, COUNT(m.id) as total_mentions,
+            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
+        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, t.market_cap, t.closing_price
+        ORDER BY total_mentions DESC LIMIT ?;
+    """
+    results = conn.execute(query, (subreddit_name, one_day_ago_timestamp, limit)).fetchall()
+    conn.close()
+    return results
+
+
+def get_weekly_summary_for_subreddit(subreddit_name, for_date, limit=10):
+    """Gets a summary for a subreddit's WEEKLY view (for a specific week)."""
+    conn = get_db_connection()
+    start_of_week, end_of_week = get_week_start_end(for_date)
+    start_timestamp = int(start_of_week.timestamp())
+    end_timestamp = int(end_of_week.timestamp())
+    query = """
+        SELECT t.symbol, t.market_cap, t.closing_price, COUNT(m.id) as total_mentions,
+            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
+        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 BETWEEN ? AND ?
+        GROUP BY t.symbol, t.market_cap, t.closing_price
+        ORDER BY total_mentions DESC LIMIT ?;
+    """
+    results = conn.execute(
+        query, (subreddit_name, start_timestamp, end_timestamp, limit)
+    ).fetchall()
+    conn.close()
+    return results, start_of_week, end_of_week
+
+
 def get_deep_dive_details(ticker_symbol):
-    """
-    Gets all analyzed posts that mention a specific ticker.
-    """
+    """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 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 t.symbol = ?
-        ORDER BY p.post_timestamp DESC;
+        WHERE LOWER(t.symbol) = LOWER(?) ORDER BY p.post_timestamp DESC;
     """
     results = conn.execute(query, (ticker_symbol,)).fetchall()
     conn.close()
     return results
 
-def get_image_view_summary(subreddit_name):
-    """
-    Gets a summary of tickers for the image view, including post, comment,
-    and sentiment counts.
-    """
+
+def get_all_scanned_subreddits():
+    """Gets a unique list of all subreddits we have data for."""
     conn = get_db_connection()
-    # This query now also counts sentiment types
-    query = """
-        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.sentiment_score > 0.1 THEN 1 END) as bullish_mentions,
-            COUNT(CASE WHEN m.sentiment_score < -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 s.name = ?
-        GROUP BY t.symbol
-        ORDER BY (post_mentions + comment_mentions) DESC
-        LIMIT 10;
-    """
-    results = conn.execute(query, (subreddit_name,)).fetchall()
+    results = conn.execute(
+        "SELECT DISTINCT name FROM subreddits ORDER BY name ASC;"
+    ).fetchall()
+    conn.close()
+    return [row["name"] for row in results]
+
+
+def get_all_tickers():
+    """Retrieves the ID and symbol of every ticker in the database."""
+    conn = get_db_connection()
+    results = conn.execute("SELECT id, symbol FROM tickers;").fetchall()
     conn.close()
     return results
 
-def get_weekly_summary_for_subreddit(subreddit_name):
+
+def get_ticker_by_symbol(symbol):
     """
-    Gets a weekly summary for a specific subreddit for the image view.
+    Retrieves a single ticker's ID and symbol from the database.
+    The search is case-insensitive. Returns a Row object or None if not found.
     """
     conn = get_db_connection()
-    
-    # Calculate the timestamp for 7 days ago
-    seven_days_ago = datetime.utcnow() - timedelta(days=7)
-    seven_days_ago_timestamp = int(seven_days_ago.timestamp())
-
-    # The query is the same as before, but with an added WHERE clause for the timestamp
-    query = """
-        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.sentiment_score > 0.1 THEN 1 END) as bullish_mentions,
-            COUNT(CASE WHEN m.sentiment_score < -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 s.name = ? AND m.mention_timestamp >= ?
-        GROUP BY t.symbol
-        ORDER BY (post_mentions + comment_mentions) DESC
-        LIMIT 10;
-    """
-    results = conn.execute(query, (subreddit_name, seven_days_ago_timestamp)).fetchall()
+    cursor = conn.cursor()
+    cursor.execute(
+        "SELECT id, symbol FROM tickers WHERE LOWER(symbol) = LOWER(?)", (symbol,)
+    )
+    result = cursor.fetchone()
     conn.close()
-    return results
+    return result
+
+
+def get_top_daily_ticker_symbols():
+    """Gets a simple list of the Top 10 ticker symbols 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 FROM mentions m JOIN tickers t ON m.ticker_id = t.id
+        WHERE m.mention_timestamp >= ?
+        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
+    """
+    results = conn.execute(query, (one_day_ago_timestamp,)).fetchall()
+    conn.close()
+    return [row["symbol"] for row in results]  # Return a simple list of strings
+
+
+def get_top_weekly_ticker_symbols():
+    """Gets a simple list of the Top 10 ticker symbols from the last 7 days."""
+    conn = get_db_connection()
+    seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
+    seven_days_ago_timestamp = int(seven_days_ago.timestamp())
+    query = """
+        SELECT t.symbol FROM mentions m JOIN tickers t ON m.ticker_id = t.id
+        WHERE m.mention_timestamp >= ?
+        GROUP BY t.symbol ORDER BY COUNT(m.id) DESC LIMIT 10;
+    """
+    results = conn.execute(query, (seven_days_ago_timestamp,)).fetchall()
+    conn.close()
+    return [row["symbol"] for row in results]  # Return a simple list of strings
+
+
+def get_top_daily_ticker_symbols_for_subreddit(subreddit_name):
+    """Gets a list of the Top 10 daily ticker symbols for a specific subreddit."""
+    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 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 COUNT(m.id) DESC LIMIT 10;
+    """
+    results = conn.execute(
+        query,
+        (
+            subreddit_name,
+            one_day_ago_timestamp,
+        ),
+    ).fetchall()
+    conn.close()
+    return [row["symbol"] for row in results]
+
+
+def get_top_weekly_ticker_symbols_for_subreddit(subreddit_name):
+    """Gets a list of the Top 10 weekly ticker symbols for a specific subreddit."""
+    conn = get_db_connection()
+    seven_days_ago = datetime.now(timezone.utc) - timedelta(days=7)
+    seven_days_ago_timestamp = int(seven_days_ago.timestamp())
+    query = """
+        SELECT t.symbol 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 COUNT(m.id) DESC LIMIT 10;
+    """
+    results = conn.execute(
+        query,
+        (
+            subreddit_name,
+            seven_days_ago_timestamp,
+        ),
+    ).fetchall()
+    conn.close()
+    return [row["symbol"] for row in results]

rstat_tool/flair_finder.py

@@ -0,0 +1,76 @@
+# rstat_tool/flair_finder.py
+# A dedicated tool to find available link flairs for a subreddit.
+
+import argparse
+import sys
+import os
+import praw
+from dotenv import load_dotenv
+from pathlib import Path
+
+def get_reddit_instance_for_flairs():
+    """
+    Initializes and returns an authenticated PRAW instance using the refresh token.
+    This is a copy of the robust authentication from the posting script.
+    """
+    # Find the .env file relative to the project root
+    env_path = Path(__file__).parent.parent / '.env'
+    load_dotenv(dotenv_path=env_path)
+    
+    client_id = os.getenv("REDDIT_CLIENT_ID")
+    client_secret = os.getenv("REDDIT_CLIENT_SECRET")
+    user_agent = os.getenv("REDDIT_USER_AGENT")
+    refresh_token = os.getenv("REDDIT_REFRESH_TOKEN")
+
+    if not all([client_id, client_secret, user_agent, refresh_token]):
+        print("Error: Reddit API credentials (including REDDIT_REFRESH_TOKEN) must be set in .env file.", file=sys.stderr)
+        return None
+    
+    return praw.Reddit(
+        client_id=client_id,
+        client_secret=client_secret,
+        user_agent=user_agent,
+        refresh_token=refresh_token
+    )
+
+def main():
+    """Main function to fetch and display flairs."""
+    parser = argparse.ArgumentParser(description="Fetch and display available post flairs for a subreddit.")
+    parser.add_argument("subreddit", help="The name of the subreddit to check.")
+    args = parser.parse_args()
+
+    reddit = get_reddit_instance_for_flairs()
+    if not reddit:
+        sys.exit(1)
+
+    print(f"\n--- Attempting to Fetch Post Flairs for r/{args.subreddit} ---")
+    
+    try:
+        # This uses PRAW's generic GET request method to hit the specific API endpoint.
+        api_path = f"/r/{args.subreddit}/api/link_flair_v2.json"
+        flairs = reddit.get(api_path, params={"raw_json": 1})
+        
+        if not flairs:
+            print("No flairs found or flair list is empty for this subreddit.")
+            return
+
+        print("\n--- Available Post Flairs ---")
+        found_count = 0
+        for flair in flairs:
+            flair_text = flair.get('text')
+            flair_id = flair.get('id')
+            if flair_text and flair_id:
+                print(f"  Flair Text: '{flair_text}'")
+                print(f"  Flair ID:   {flair_id}\n")
+                found_count += 1
+        
+        if found_count == 0:
+            print("No flairs with both text and ID were found.")
+
+    except Exception as e:
+        print(f"\nAn error occurred: {e}", file=sys.stderr)
+        print("Hint: Please ensure the subreddit exists and that your authenticated user has permission to view it.", file=sys.stderr)
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()

rstat_tool/format_blacklist.py

@@ -1,58 +1,126 @@
 # The initial unsorted set of words.
 # Note: In Python, a 'set' is inherently unordered, but we define it here for clarity.
 COMMON_WORDS_BLACKLIST = {
-    "401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
-    "AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
-    "ARE", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL", "ATM",
-    "AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA", "BIG",
-    "BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS", "BRB",
-    "BRL", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST", "BUT", "BUY",
-    "BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO", "CEST", "CET",
-    "CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC", "CNY", "COKE",
-    "COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB", "CTO", "CYCLE",
-    "CZK", "DAO", "DATE", "DAX", "DAY", "DCA", "DD", "DEBT", "DEX", "DIA",
-    "DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE", "DOJ", "DONT", "DR",
-    "EACH", "EARLY", "EARN", "ECB", "EDGAR", "EDIT", "EDT", "EMA", "END", "EOD",
-    "EOW", "EOY", "EPA", "EPS", "ER", "ESG", "EST", "ETF", "ETFS", "ETH",
-    "EU", "EUR", "EV", "EVEN", "EVERY", "FAQ", "FAR", "FAST", "FBI", "FD",
-    "FDA", "FIHTX", "FINRA", "FINT", "FINTX", "FINTY", "FIRST", "FOMC", "FOMO", "FOR",
-    "FOREX", "FRAUD", "FRG", "FROM", "FSPSX", "FTSE", "FUCK", "FUD", "FULL", "FUND",
-    "FXAIX", "FXIAX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET",
-    "GL", "GLHF", "GMT", "GO", "GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB",
-    "GTG", "HALF", "HAS", "HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT",
-    "HKD", "HODL", "HOLD", "HOUR", "HSA", "HUF", "IF", "II", "IKZ", "IMHO",
-    "IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISM",
-    "IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY", "JST",
-    "JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST", "LATE",
-    "LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC", "LLM",
-    "LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A", "MA",
-    "MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID", "MIGHT",
-    "MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST", "MXN",
-    "MY", "NATO", "NEAR", "NEED", "NEVER", "NEW", "NEXT", "NFA", "NFC", "NFT",
-    "NGMI", "NIGHT", "NO", "NOK", "NONE", "NOT", "NOW", "NSA", "NULL", "NUT",
-    "NYSE", "NZD", "OBV", "OEM", "OF", "OG", "OK", "OLD", "ON", "ONE",
-    "ONLY", "OP", "OPEX", "OR", "OS", "OSCE", "OTC", "OTM", "OUGHT", "OUT",
-    "OVER", "OWN", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG", "PEW", "PLAN",
-    "PLN", "PM", "PMI", "POC", "POS", "PPI", "PR", "PRICE", "PROFIT", "PSA",
-    "PST", "PT", "PUT", "Q1", "Q2", "Q3", "Q4", "QQQ", "QR", "RBA",
-    "RBNZ", "RE", "REAL", "REIT", "REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK",
-    "ROE", "ROFL", "ROI", "ROTH", "RSD", "RSI", "RUB", "RULE", "SAME", "SAVE",
-    "SCALP", "SCAM", "SCHB", "SEC", "SEE", "SEK", "SELL", "SEP", "SGD", "SHALL",
-    "SHARE", "SHORT", "SL", "SMA", "SMALL", "SO", "SOLIS", "SOME", "SOON", "SP",
-    "SPAC", "SPEND", "SPLG", "SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR",
-    "SWING", "TA", "TAG", "TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS",
-    "TIME", "TITS", "TL", "TL;DR", "TLDR", "TO", "TODAY", "TOTAL", "TRADE", "TREND",
-    "TRUE", "TRY", "TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA",
-    "USD", "UTC", "VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH",
-    "WAY", "WE", "WEB3", "WEEK", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WORDS",
-    "WORTH", "WOULD", "WSB", "WTF", "XRP", "YES", "YET", "YIELD", "YOLO", "YOU",
-    "YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
+    "401K", "403B", "457B", "AAVE", "ABC", "ABOUT", "ABOVE", "ACAT", "ADAM", "ADHD",
+    "ADR", "ADS", "ADX", "AEDT", "AEST", "AF", "AFAIK", "AFTER", "AGENT", "AH",
+    "AI", "AINT", "AK", "AKSJE", "ALD", "ALGOS", "ALIVE", "ALL", "ALPHA", "ALSO",
+    "AM", "AMA", "AMEX", "AMK", "AMY", "AND", "ANSS", "ANY", "APES", "APL",
+    "APPL", "APPLE", "APR", "APUS", "APY", "AR", "ARBK", "ARE", "AREA", "ARH",
+    "ARK", "AROUND", "ART", "AS", "ASAP", "ASEAN", "ASK", "ASS", "ASSET", "AST",
+    "AT", "ATH", "ATL", "ATM", "AUD", "AUG", "AUM", "AV", "AVG", "AWS",
+    "BABY", "BAD", "BAG", "BAGS", "BALLS", "BAN", "BANG", "BASIC", "BBB", "BBBY",
+    "BE", "BEAR", "BEARS", "BECN", "BEER", "BELL", "BELOW", "BETA", "BETS", "BF",
+    "BID", "BIG", "BIS", "BITCH", "BKEY", "BLEND", "BLOW", "BMW", "BNP", "BNPL",
+    "BOARD", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BONED", "BORN", "BOTH", "BOTS",
+    "BOY", "BOYS", "BRB", "BRICS", "BRK", "BRKA", "BRKB", "BRL", "BROKE", "BRRRR",
+    "BS", "BSE", "BST", "BSU", "BT", "BTC", "BTS", "BTW", "BUDDY", "BULL",
+    "BULLS", "BUST", "BUT", "BUY", "BUZZ", "CAD", "CAFE", "CAGR", "CALL", "CALLS",
+    "CAN", "CAP", "CARB", "CARES", "CASE", "CATL", "CBD", "CBGM", "CBS", "CCI",
+    "CCP", "CD", "CDN", "CEO", "CEST", "CET", "CEX", "CFD", "CFO", "CFPB",
+    "CHART", "CHASE", "CHATS", "CHECK", "CHF", "CHICK", "CHIP", "CHIPS", "CIA", "CIC",
+    "CLAIM", "CLEAN", "CLICK", "CLOSE", "CMON", "CN", "CNBC", "CNN", "CNY", "COBRA",
+    "COCK", "COGS", "COIL", "COKE", "COME", "COST", "COULD", "COVID", "CPAP", "CPI",
+    "CRA", "CRE", "CRO", "CRV", "CSE", "CSP", "CSS", "CST", "CTB", "CTEP",
+    "CTO", "CUCKS", "CULT", "CUM", "CUSMA", "CUTS", "CUV", "CYCLE", "CZK", "DA",
+    "DAILY", "DAO", "DART", "DATA", "DATE", "DAX", "DAY", "DAYS", "DCA", "DCF",
+    "DD", "DEAL", "DEBT", "DEEZ", "DEMO", "DET", "DEX", "DGAF", "DIA", "DID",
+    "DIDNT", "DIP", "DITM", "DIV", "DIY", "DJI", "DJIA", "DJTJ", "DKK", "DL",
+    "DM", "DMV", "DNI", "DNUTZ", "DO", "DOD", "DOE", "DOES", "DOGE", "DOING",
+    "DOJ", "DOM", "DONNY", "DONT", "DONUT", "DOOR", "DOWN", "DOZEN", "DPI", "DR",
+    "DUDE", "DUMP", "DUNT", "DUT", "DUTY", "DXY", "DXYXBT", "DYI", "DYNK", "DYODD",
+    "DYOR", "EACH", "EARLY", "EARN", "EAST", "EASY", "EBIT", "ECB", "EDGAR", "EDIT",
+    "EDT", "EJ", "EMA", "EMJ", "EMT", "END", "ENRON", "ENSI", "ENV", "EO",
+    "EOD", "EOM", "EOW", "EOY", "EPA", "EPK", "EPS", "ER", "ESG", "ESPP",
+    "EST", "ETA", "ETF", "ETFS", "ETH", "ETHT", "ETL", "EU", "EUR", "EV",
+    "EVEN", "EVERY", "EVTOL", "EXTRA", "EYES", "EZ", "FAANG", "FAFO", "FAQ", "FAR",
+    "FAST", "FBI", "FCC", "FCFF", "FD", "FDA", "FED", "FEE", "FFH", "FFS",
+    "FGMA", "FIG", "FIGMA", "FIHTX", "FILES", "FINAL", "FIND", "FING", "FINRA", "FINT",
+    "FINTX", "FINTY", "FIRE", "FIRST", "FKIN", "FLOAT", "FLRAA", "FLT", "FLY", "FML",
+    "FOLO", "FOMC", "FOMO", "FOR", "FOREX", "FRAUD", "FREAK", "FRED", "FRG", "FROM",
+    "FRP", "FRS", "FSBO", "FSD", "FSE", "FSELK", "FSPSX", "FTD", "FTSE", "FUCK",
+    "FUCKS", "FUD", "FULL", "FUND", "FUNNY", "FVG", "FWIW", "FX", "FXAIX", "FXIAX",
+    "FXROX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GAV", "GAVE", "GBP", "GC",
+    "GDP", "GET", "GFC", "GG", "GGTM", "GIVES", "GJ", "GL", "GLHF", "GMAT",
+    "GMI", "GMT", "GO", "GOAL", "GOAT", "GOD", "GOING", "GOLD", "GONE", "GONNA",
+    "GOODS", "GOPRO", "GPT", "GPU", "GRAB", "GREAT", "GREEN", "GSOV", "GST", "GTA",
+    "GTC", "GTFO", "GTG", "GUH", "GUNS", "GUY", "GUYS", "HAD", "HAHA", "HALF",
+    "HAM", "HANDS", "HAS", "HATE", "HAVE", "HBAR", "HCOL", "HEAR", "HEDGE", "HEGE",
+    "HELD", "HELE", "HELL", "HELP", "HERE", "HEY", "HFCS", "HFT", "HGTV", "HIGH",
+    "HIGHS", "HINT", "HIS", "HITID", "HK", "HKD", "HKEX", "HODL", "HODOR", "HOF",
+    "HOLD", "HOLY", "HOME", "HOT", "HOUR", "HOURS", "HOW", "HS", "HSA", "HSI",
+    "HT", "HTCI", "HTF", "HTML", "HUF", "HUGE", "HV", "HYPE", "IANAL", "IATF",
+    "IB", "IBS", "ICSID", "ICT", "ID", "IDF", "IDK", "IF", "II", "IIRC",
+    "IKKE", "IKZ", "IM", "IMHO", "IMI", "IMO", "IN", "INC", "INR", "INTEL",
+    "INTO", "IP", "IPO", "IQVIA", "IRA", "IRAS", "IRC", "IRISH", "IRL", "IRMAA",
+    "IRS", "IS", "ISA", "ISIN", "ISM", "ISN", "IST", "IT", "ITC", "ITM",
+    "ITS", "ITWN", "IUIT", "IV", "IVV", "IWM", "IXL", "IXLH", "IYKYK", "JAVA",
+    "JD", "JDG", "JDM", "JE", "JFC", "JK", "JLR", "JMO", "JOBS", "JOIN",
+    "JOKE", "JP", "JPOW", "JPY", "JS", "JST", "JULY", "JUN", "JUST", "KARMA",
+    "KEEP", "KILL", "KING", "KK", "KLA", "KLP", "KNEW", "KNOW", "KO", "KOHLS",
+    "KPMG", "KRW", "LA", "LANGT", "LARGE", "LAST", "LATE", "LATER", "LBO", "LBTC",
+    "LCS", "LDL", "LEADS", "LEAP", "LEAPS", "LEARN", "LEGS", "LEI", "LET", "LETF",
+    "LETS", "LFA", "LFG", "LFP", "LG", "LGEN", "LID", "LIFE", "LIG", "LIGMA",
+    "LIKE", "LIMIT", "LIST", "LLC", "LLM", "LM", "LMAO", "LMAOO", "LMM", "LMN",
+    "LOANS", "LOKO", "LOL", "LOLOL", "LONG", "LONGS", "LOOK", "LOSE", "LOSS", "LOST",
+    "LOVE", "LOVES", "LOW", "LOWER", "LOWS", "LP", "LSS", "LTCG", "LUCID", "LUPD",
+    "LYC", "LYING", "M&A", "MA", "MACD", "MAIL", "MAKE", "MAKES", "MANGE", "MANY",
+    "MASON", "MAX", "MAY", "MAYBE", "MBA", "MC", "MCAP", "MCNA", "MCP", "ME",
+    "MEAN", "MEME", "MER", "MERGE", "MERK", "MES", "MEXC", "MF", "MFER", "MID",
+    "MIGHT", "MIN", "MIND", "MINS", "ML", "MLB", "MLS", "MM", "MMF", "MNQ",
+    "MOASS", "MODEL", "MODTX", "MOM", "MONEY", "MONGO", "MONTH", "MONY", "MOON", "MORE",
+    "MOST", "MOU", "MSK", "MTVGA", "MUCH", "MUSIC", "MUST", "MVA", "MXN", "MY",
+    "MYMD", "NASA", "NASDA", "NATO", "NAV", "NBA", "NBC", "NCAN", "NCR", "NEAR",
+    "NEAT", "NEED", "NEVER", "NEW", "NEWS", "NEXT", "NFA", "NFC", "NFL", "NFT",
+    "NGAD", "NGMI", "NIGHT", "NIQ", "NK", "NO", "NOK", "NON", "NONE", "NOOO",
+    "NOPE", "NORTH", "NOT", "NOVA", "NOW", "NQ", "NRI", "NSA", "NSCLC", "NSLC",
+    "NTG", "NTVS", "NULL", "NUT", "NUTS", "NUTZ", "NVIDIA", "NVM", "NW", "NY",
+    "NYSE", "NZ", "NZD", "OBBB", "OBI", "OBS", "OBV", "OCD", "OCF", "OCO",
+    "ODAT", "ODTE", "OEM", "OF", "OFA", "OFF", "OG", "OH", "OK", "OKAY",
+    "OL", "OLD", "OMFG", "OMG", "ON", "ONDAS", "ONE", "ONLY", "OP", "OPEC",
+    "OPENQ", "OPEX", "OPRN", "OR", "ORB", "ORDER", "ORTEX", "OS", "OSCE", "OSE",
+    "OSEBX", "OT", "OTC", "OTM", "OTOH", "OUCH", "OUGHT", "OUR", "OUT", "OVER",
+    "OWN", "OZZY", "PA", "PAID", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG",
+    "PETA", "PEW", "PFC", "PGHL", "PIMCO", "PITA", "PLAN", "PLAYS", "PLC", "PLN",
+    "PM", "PMCC", "PMI", "PNL", "POC", "POMO", "POP", "POS", "POSCO", "POTUS",
+    "POV", "POW", "PPI", "PR", "PRICE", "PRIME", "PROFIT", "PROXY", "PS", "PSA",
+    "PST", "PT", "PTD", "PUSSY", "PUT", "PUTS", "PWC", "Q1", "Q2", "Q3",
+    "Q4", "QE", "QED", "QIMC", "QQQ", "QR", "RAM", "RATM", "RBA", "RBNZ",
+    "RE", "REACH", "READY", "REAL", "RED", "REIT", "REITS", "REKT", "REPE", "RFK",
+    "RH", "RICO", "RIDE", "RIGHT", "RIP", "RISK", "RISKY", "RNDC", "ROCE", "ROCK",
+    "ROE", "ROFL", "ROI", "ROIC", "ROTH", "RPO", "RRSP", "RSD", "RSI", "RT",
+    "RTD", "RUB", "RUG", "RULE", "RUST", "RVOL", "SAGA", "SALES", "SAME", "SAVE",
+    "SAYS", "SBF", "SBLOC", "SC", "SCALP", "SCAM", "SCHB", "SCIF", "SEC", "SEE",
+    "SEK", "SELL", "SELLL", "SEP", "SESG", "SET", "SFOR", "SGD", "SHALL", "SHARE",
+    "SHEIN", "SHELL", "SHIT", "SHORT", "SHOW", "SHS", "SHTF", "SI", "SICK", "SIGN",
+    "SL", "SLIM", "SLOW", "SMA", "SMALL", "SMFH", "SNZ", "SO", "SOLD", "SOLIS",
+    "SOME", "SOON", "SOOO", "SOUTH", "SP", "SPAC", "SPDR", "SPEND", "SPLG", "SPX",
+    "SPY", "SQUAD", "SS", "SSA", "SSDI", "START", "STAY", "STEEL", "STFU", "STILL",
+    "STO", "STOCK", "STOOQ", "STOP", "STOR", "STQQQ", "STUCK", "STUDY", "SUS", "SUSHI",
+    "SUV", "SWIFT", "SWING", "TA", "TAG", "TAKE", "TAM", "TBTH", "TEAMS", "TED",
+    "TEMU", "TERM", "TESLA", "TEXT", "TF", "TFNA", "TFSA", "THAN", "THANK", "THAT",
+    "THATS", "THE", "THEIR", "THEM", "THEN", "THERE", "THESE", "THEY", "THING", "THINK",
+    "THIS", "THROW", "TI", "TIA", "TIKR", "TIME", "TIMES", "TINA", "TITS", "TJR",
+    "TL", "TL;DR", "TLDR", "TNT", "TO", "TODAY", "TOLD", "TONS", "TOO", "TOS",
+    "TOT", "TOTAL", "TP", "TPU", "TRADE", "TREND", "TRUE", "TRUMP", "TRUST", "TRY",
+    "TSA", "TSMC", "TSP", "TSX", "TSXV", "TTIP", "TTM", "TTYL", "TURNS", "TWO",
+    "UAW", "UCITS", "UGH", "UI", "UK", "UNDER", "UNITS", "UNO", "UNTIL", "UP",
+    "US", "USA", "USD", "USMCA", "USSA", "USSR", "UTC", "VALID", "VALUE", "VAMOS",
+    "VAT", "VEIEN", "VEO", "VERY", "VFMXX", "VFV", "VI", "VISA", "VIX", "VLI",
+    "VOO", "VP", "VPAY", "VR", "VRVP", "VSUS", "VTI", "VUAG", "VW", "VWAP",
+    "VWCE", "VXN", "VXUX", "WAGER", "WAGMI", "WAIT", "WALL", "WANT", "WAS", "WATCH",
+    "WAY", "WBTC", "WE", "WEB", "WEB3", "WEEK", "WENT", "WERO", "WEST", "WHALE",
+    "WHAT", "WHEN", "WHERE", "WHICH", "WHILE", "WHO", "WHOS", "WHY", "WIDE", "WILL",
+    "WIRE", "WIRED", "WITH", "WL", "WON", "WOOPS", "WORDS", "WORTH", "WOULD", "WP",
+    "WRONG", "WSB", "WSJ", "WTF", "WV", "WWII", "WWIII", "X", "XAU", "XCUSE",
+    "XD", "XEQT", "XI", "XIV", "XMR", "XO", "XRP", "XX", "YEAH", "YEET",
+    "YES", "YET", "YIELD", "YM", "YMMV", "YOIR", "YOLO", "YOU", "YOUR", "YOY",
+    "YT", "YTD", "YUGE", "YUP", "YUPPP", "ZAR", "ZEN", "ZERO", "ZEV"
 }
 
 def format_and_print_list(word_set, words_per_line=10):
     """
     Sorts a set of words and prints it in a specific format.
-    
+
     Args:
         word_set (set): The set of words to process.
         words_per_line (int): The number of words to print on each line.
@@ -60,32 +128,33 @@ def format_and_print_list(word_set, words_per_line=10):
     # 1. Convert the set to a list to ensure order, and sort it alphabetically.
     #    The set is also used to remove any duplicates from the initial list.
     sorted_words = sorted(list(word_set))
-    
+
     # 2. Start printing the output
     print("COMMON_WORDS_BLACKLIST = {")
-    
+
     # 3. Iterate through the sorted list and print words, respecting the line limit
     for i in range(0, len(sorted_words), words_per_line):
         # Get a chunk of words for the current line
-        line_chunk = sorted_words[i:i + words_per_line]
-        
+        line_chunk = sorted_words[i : i + words_per_line]
+
         # Format each word with double quotes
         formatted_words = [f'"{word}"' for word in line_chunk]
-        
+
         # Join the words with a comma and a space
         line_content = ", ".join(formatted_words)
-        
+
         # Add a trailing comma if it's not the last line
         is_last_line = (i + words_per_line) >= len(sorted_words)
         if not is_last_line:
             line_content += ","
-            
+
         # Print the indented line
         print(f"    {line_content}")
 
     # 4. Print the closing brace
     print("}")
 
+
 # --- Main execution ---
 if __name__ == "__main__":
-    format_and_print_list(COMMON_WORDS_BLACKLIST)
+    format_and_print_list(COMMON_WORDS_BLACKLIST)

rstat_tool/gunicorn-cfg.py

@@ -0,0 +1,9 @@
+# -*- encoding: utf-8 -*-
+
+bind = '0.0.0.0:5000'
+workers = 4
+worker_class = 'uvicorn.workers.UvicornWorker'
+accesslog = '-'
+loglevel = 'debug'
+capture_output = True
+enable_stdio_inheritance = True

rstat_tool/logger_setup.py

@@ -0,0 +1,51 @@
+# rstat_tool/logger_setup.py
+
+import logging
+import sys
+
+logger = logging.getLogger("rstat_app")
+
+
+def setup_logging(console_verbose=False, debug_mode=False):
+    """
+    Configures the application's logger with a new DEBUG level.
+    """
+    # The logger itself must be set to the lowest possible level (DEBUG).
+    log_level = logging.DEBUG if debug_mode else logging.INFO
+    logger.setLevel(log_level)
+
+    logger.propagate = False
+    if logger.hasHandlers():
+        logger.handlers.clear()
+
+    # File Handler (Always verbose at INFO level or higher)
+    file_handler = logging.FileHandler("rstat.log", mode="a")
+    file_handler.setLevel(logging.INFO)  # We don't need debug spam in the file usually
+    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)
+
+    # Console Handler (Verbosity is controlled)
+    console_handler = logging.StreamHandler(sys.stdout)
+    console_formatter = logging.Formatter("%(message)s")
+    console_handler.setFormatter(console_formatter)
+
+    if debug_mode:
+        console_handler.setLevel(logging.DEBUG)
+    elif console_verbose:
+        console_handler.setLevel(logging.INFO)
+    else:
+        console_handler.setLevel(logging.CRITICAL)
+
+    logger.addHandler(console_handler)
+
+    # YFINANCE LOGGER CAPTURE
+    yfinance_logger = logging.getLogger("yfinance")
+    yfinance_logger.propagate = False
+    if yfinance_logger.hasHandlers():
+        yfinance_logger.handlers.clear()
+    yfinance_logger.setLevel(logging.WARNING)
+    yfinance_logger.addHandler(console_handler)
+    yfinance_logger.addHandler(file_handler)

rstat_tool/main.py

@@ -4,148 +4,487 @@ import argparse
 import json
 import os
 import time
+import sys
+from dotenv import load_dotenv
+from pathlib import Path
+from concurrent.futures import ThreadPoolExecutor
 
 import praw
 import yfinance as yf
-from dotenv import load_dotenv
+import pandas as pd
 
 from . import database
-from .ticker_extractor import extract_tickers
+from .ticker_extractor import extract_golden_tickers, extract_potential_tickers
 from .sentiment_analyzer import get_sentiment_score
+from .logger_setup import setup_logging, logger as log
 
-load_dotenv()
-MARKET_CAP_REFRESH_INTERVAL = 86400
-POST_AGE_LIMIT = 86400 
 
 def load_subreddits(filepath):
+    """Loads a list of subreddits from a JSON file."""
     try:
-        with open(filepath, 'r') as f:
+        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):
-    try:
-        ticker = yf.Ticker(ticker_symbol)
-        data = { "market_cap": ticker.fast_info.get('marketCap'), "closing_price": ticker.fast_info.get('previousClose') }
-        return data
-    except Exception:
-        return {"market_cap": None, "closing_price": None}
 
 def get_reddit_instance():
+    """Initializes and returns a PRAW Reddit instance."""
+    env_path = Path(__file__).parent.parent / ".env"
+    load_dotenv(dotenv_path=env_path)
     client_id = os.getenv("REDDIT_CLIENT_ID")
     client_secret = os.getenv("REDDIT_CLIENT_SECRET")
     user_agent = os.getenv("REDDIT_USER_AGENT")
     if not all([client_id, client_secret, user_agent]):
-        print("Error: Reddit API credentials not found in .env file.")
+        log.error("Error: Reddit API credentials not found in .env file.")
         return None
-    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 fetch_financial_data(ticker_symbol):
+    """
+    Fetches market cap and the most recent closing price for a single ticker.
+    This function is designed to be thread-safe and robust.
+    """
+    try:
+        ticker = yf.Ticker(ticker_symbol)
+        market_cap = ticker.info.get("marketCap")
+        data = ticker.history(period="2d", auto_adjust=False)
+        closing_price = None
+        if not data.empty:
+            last_close_raw = data["Close"].iloc[-1]
+            if pd.notna(last_close_raw):
+                closing_price = float(last_close_raw)
+        return ticker_symbol, {"market_cap": market_cap, "closing_price": closing_price}
+    except Exception:
+        return ticker_symbol, None
+
+
+def _process_submission(submission, subreddit_id, conn, comment_limit):
+    """
+    Processes a single Reddit submission with a more precise "Golden Ticker" logic.
+    - If a '$' ticker exists anywhere, the entire submission is in "Golden Only" mode.
+    - Falls back to potential tickers only if no '$' tickers are found anywhere.
+    """
+    # 1. --- Establish Mode: Golden or Potential ---
+    # Scan the entire submission (title + selftext) to determine the mode.
+    post_text_for_discovery = submission.title + " " + submission.selftext
+    golden_tickers_in_post = extract_golden_tickers(post_text_for_discovery)
+
+    is_golden_mode = bool(golden_tickers_in_post)
+
+    if is_golden_mode:
+        log.info(
+            f"  -> Golden Ticker(s) Found: {', '.join(golden_tickers_in_post)}. Engaging Golden-Only Mode."
+        )
+        # In Golden Mode, we ONLY care about tickers with a '$'.
+        tickers_in_title = extract_golden_tickers(submission.title)
+    else:
+        log.info("  -> No Golden Tickers. Falling back to potential ticker search.")
+        # In Potential Mode, we look for any valid-looking capitalized word.
+        tickers_in_title = extract_potential_tickers(submission.title)
+
+    all_tickers_found_in_post = set(tickers_in_title)
+    ticker_id_cache = {}
+
+    # 2. --- Process Title Mentions ---
+    if tickers_in_title:
+        log.info(
+            f"  -> Title Mention(s): {', '.join(tickers_in_title)}. Attributing all comments."
+        )
+        post_sentiment = get_sentiment_score(submission.title)
+        for ticker_symbol in tickers_in_title:
+            # All title tickers are saved as 'post' type mentions
+            ticker_id = database.get_or_create_entity(
+                conn, "tickers", "symbol", ticker_symbol
+            )
+            ticker_id_cache[ticker_symbol] = ticker_id
+            database.add_mention(
+                conn,
+                ticker_id,
+                subreddit_id,
+                submission.id,
+                "post",
+                int(submission.created_utc),
+                post_sentiment,
+                comment_id=None,
+            )
+
+    # 3. --- Process Comments (Single, Efficient Loop) ---
+    submission.comments.replace_more(limit=0)
+    all_comments = submission.comments.list()[:comment_limit]
+
+    for comment in all_comments:
+        comment_sentiment = get_sentiment_score(comment.body)
+
+        if tickers_in_title:
+            # If the title had tickers, every comment is a mention for them.
+            # We don't need to scan the comment text for tickers here.
+            for ticker_symbol in tickers_in_title:
+                ticker_id = ticker_id_cache[ticker_symbol]  # Guaranteed to be in cache
+                database.add_mention(
+                    conn,
+                    ticker_id,
+                    subreddit_id,
+                    submission.id,
+                    "comment",
+                    int(comment.created_utc),
+                    comment_sentiment,
+                    comment_id=comment.id,
+                )
+        else:
+            # If no title tickers, we must scan the comment for direct mentions.
+            # The type of ticker we look for depends on the mode.
+            if is_golden_mode:
+                # This case is rare (no golden in title, but some in comments) but important.
+                tickers_in_comment = extract_golden_tickers(comment.body)
+            else:
+                tickers_in_comment = extract_potential_tickers(comment.body)
+
+            if tickers_in_comment:
+                all_tickers_found_in_post.update(tickers_in_comment)
+                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,
+                        comment_id=comment.id,
+                    )
+
+    # 4. --- Save Deep Dive Analysis ---
+    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
+    )
+    post_analysis_data = {
+        "post_id": submission.id,
+        "title": submission.title,
+        "post_url": f"https://reddit.com{submission.permalink}",
+        "subreddit_id": subreddit_id,
+        "post_timestamp": int(submission.created_utc),
+        "comment_count": len(all_comments),
+        "avg_comment_sentiment": avg_sentiment,
+    }
+    database.add_or_update_post_analysis(conn, post_analysis_data)
+
+    return all_tickers_found_in_post
+
+
+def scan_subreddits(
+    reddit,
+    subreddits_list,
+    post_limit=100,
+    comment_limit=100,
+    days_to_scan=1,
+    fetch_financials=True,
+):
+    """
+    Scans subreddits to discover mentions, then performs a single batch update for financials if enabled.
+    """
     conn = database.get_db_connection()
     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)...")
+    all_tickers_to_update = set()
+
+    log.info(f"Scanning {len(subreddits_list)} subreddit(s) for NEW posts...")
+    if not fetch_financials:
+        log.warning("NOTE: Financial data fetching is disabled for this run.")
+
     for subreddit_name in subreddits_list:
         try:
-            subreddit_id = database.get_or_create_entity(conn, 'subreddits', 'name', subreddit_name)
-            subreddit = reddit.subreddit(subreddit_name)
-            print(f"Scanning r/{subreddit_name}...")
-            
+            normalized_sub_name = subreddit_name.lower()
+            subreddit_id = database.get_or_create_entity(
+                conn, "subreddits", "name", normalized_sub_name
+            )
+            subreddit = reddit.subreddit(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. Moving to next subreddit.")
+                    log.info(
+                        f"  -> Reached posts older than the {days_to_scan}-day limit."
+                    )
                     break
 
-                post_text = submission.title + " " + submission.selftext
-                tickers_in_post = extract_tickers(post_text)
-                if tickers_in_post:
-                    post_sentiment = get_sentiment_score(submission.title)
-                    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)
-                all_comment_sentiments = []
-                for comment in submission.comments.list()[:comment_limit]:
-                    all_comment_sentiments.append(get_sentiment_score(comment.body))
-                    tickers_in_comment = extract_tickers(comment.body)
-                    if tickers_in_comment:
-                        comment_sentiment = get_sentiment_score(comment.body)
-                        for ticker_symbol in set(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)
-                
-                avg_sentiment = sum(all_comment_sentiments) / len(all_comment_sentiments) if all_comment_sentiments else 0
-                post_analysis_data = {
-                    "post_id": submission.id, "title": submission.title,
-                    "post_url": f"https://reddit.com{submission.permalink}",
-                    "subreddit_id": subreddit_id, "post_timestamp": int(submission.created_utc),
-                    "comment_count": len(all_comment_sentiments), "avg_comment_sentiment": avg_sentiment
-                }
-                database.add_or_update_post_analysis(conn, post_analysis_data)
+                tickers_found = _process_submission(
+                    submission, subreddit_id, conn, comment_limit
+                )
+                if tickers_found:
+                    all_tickers_to_update.update(tickers_found)
 
         except Exception as e:
-            print(f"Could not scan r/{subreddit_name}. Error: {e}")
-            
+            log.error(
+                f"Could not scan r/{normalized_sub_name}. Error: {e}", exc_info=True
+            )
+
     conn.close()
-    print("\n--- Scan Complete ---")
+    log.critical("\n--- Reddit Scan Complete ---")
+
+    if fetch_financials and all_tickers_to_update:
+        log.critical(
+            f"\n--- Starting Batch Financial Update for {len(all_tickers_to_update)} Discovered Tickers ---"
+        )
+
+        tickers_from_db = {t["symbol"]: t["id"] for t in database.get_all_tickers()}
+        tickers_needing_update_symbols = [
+            symbol for symbol in all_tickers_to_update if symbol in tickers_from_db
+        ]
+
+        financial_data_batch = {}
+        with ThreadPoolExecutor(max_workers=10) as executor:
+            results = executor.map(fetch_financial_data, tickers_needing_update_symbols)
+            for symbol, data in results:
+                if data:
+                    financial_data_batch[symbol] = data
+
+        if financial_data_batch:
+            conn = database.get_db_connection()
+            for symbol, financials in financial_data_batch.items():
+                database.update_ticker_financials(
+                    conn,
+                    tickers_from_db[symbol],
+                    financials.get("market_cap"),
+                    financials.get("closing_price"),
+                )
+            conn.close()
+        log.critical("--- Batch Financial Update Complete ---")
+
 
 def main():
     """Main function to run the Reddit stock analysis tool."""
-    parser = argparse.ArgumentParser(description="Analyze stock ticker mentions on Reddit.", formatter_class=argparse.RawTextHelpFormatter)
-    
-    parser.add_argument("--config", default="subreddits.json", help="Path to the JSON file containing subreddits.\n(Default: subreddits.json)")
-    parser.add_argument("--subreddit", help="Scan a single subreddit, ignoring the config file.")
-    parser.add_argument("--days", type=int, default=1, help="Number of past days to scan for new posts.\n(Default: 1 for last 24 hours)")
-    
-    parser.add_argument("-p", "--posts", type=int, default=200, help="Max posts to check per subreddit.\n(Default: 200)")
-    parser.add_argument("-c", "--comments", type=int, default=100, help="Number of comments to scan per post.\n(Default: 100)")
-    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}")
-    else:
-        # Otherwise, load from the config file.
-        print(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.")
-        return
-
-    # --- Initialize and Run ---
-    database.initialize_db()
-    database.clean_stale_tickers()
-    
-    reddit = get_reddit_instance()
-    if not reddit: return
-
-    scan_subreddits(
-        reddit,
-        subreddits_to_scan,
-        post_limit=args.posts,
-        comment_limit=args.comments,
-        days_to_scan=args.days
+    parser = argparse.ArgumentParser(
+        description="Analyze stock ticker mentions on Reddit.",
+        formatter_class=argparse.RawTextHelpFormatter,
     )
-    database.generate_summary_report(limit=args.limit)
+
+    parser.add_argument(
+        "-f",
+        "--config",
+        default="subreddits.json",
+        help="Path to the JSON file for scanning. (Default: subreddits.json)",
+    )
+    parser.add_argument(
+        "-s", "--subreddit", help="Scan a single subreddit, ignoring the config file."
+    )
+    parser.add_argument(
+        "-d",
+        "--days",
+        type=int,
+        default=1,
+        help="Number of past days to scan for new posts. (Default: 1)",
+    )
+    parser.add_argument(
+        "-p",
+        "--posts",
+        type=int,
+        default=200,
+        help="Max posts to check per subreddit. (Default: 200)",
+    )
+    parser.add_argument(
+        "-c",
+        "--comments",
+        type=int,
+        default=100,
+        help="Number of comments to scan per post. (Default: 100)",
+    )
+    parser.add_argument(
+        "-n",
+        "--no-financials",
+        action="store_true",
+        help="Disable fetching of financial data during the Reddit scan.",
+    )
+    parser.add_argument(
+        "--update-top-tickers",
+        action="store_true",
+        help="Update financial data only for tickers currently in the Top 10 daily/weekly dashboards.",
+    )
+    parser.add_argument(
+        "-u",
+        "--update-financials-only",
+        nargs="?",
+        const="ALL_TICKERS",  # A special value to signify "update all"
+        default=None,
+        metavar="TICKER",
+        help="Update financials. Provide a ticker symbol to update just one,\nor use the flag alone to update all tickers in the database.",
+    )
+    parser.add_argument(
+        "--debug",
+        action="store_true",
+        help="Enable detailed debug logging to the console.",
+    )
+    parser.add_argument(
+        "--stdout", action="store_true", help="Print all log messages to the console."
+    )
+
+    args = parser.parse_args()
+    setup_logging(console_verbose=args.stdout, debug_mode=args.debug)
+
+    database.initialize_db()
+
+    if args.update_top_tickers:
+        # --- Mode 1: Update Top Tickers ---
+        log.critical("--- Starting Financial Data Update for Top Tickers ---")
+        top_daily = database.get_top_daily_ticker_symbols()
+        top_weekly = database.get_top_weekly_ticker_symbols()
+        all_sub_names = database.get_all_scanned_subreddits()
+        for sub_name in all_sub_names:
+            top_daily.extend(
+                database.get_top_daily_ticker_symbols_for_subreddit(sub_name)
+            )
+            top_weekly.extend(
+                database.get_top_weekly_ticker_symbols_for_subreddit(sub_name)
+            )
+        tickers_to_update = sorted(list(set(top_daily + top_weekly)))
+
+        if not tickers_to_update:
+            log.info("No top tickers found in the last week. Nothing to update.")
+        else:
+            log.info(
+                f"Found {len(tickers_to_update)} unique top tickers to update. Fetching in parallel..."
+            )
+
+            financial_data_batch = {}
+            successful_updates = 0
+            failed_updates = 0
+
+            with ThreadPoolExecutor(max_workers=10) as executor:
+                results = executor.map(fetch_financial_data, tickers_to_update)
+                for symbol, data in results:
+                    # A successful fetch is one where data is returned and has a closing price
+                    if data and data.get("closing_price") is not None:
+                        log.info(f"  -> SUCCESS: Fetched data for {symbol}")
+                        financial_data_batch[symbol] = data
+                        successful_updates += 1
+                    else:
+                        log.warning(
+                            f"  -> FAILED: Could not fetch valid financial data for {symbol}"
+                        )
+                        failed_updates += 1
+
+            if not financial_data_batch:
+                log.error("Failed to fetch any batch financial data. Aborting update.")
+            else:
+                conn = database.get_db_connection()
+                all_tickers_from_db = database.get_all_tickers()
+                ticker_map = {t["symbol"]: t["id"] for t in all_tickers_from_db}
+
+                for symbol, financials in financial_data_batch.items():
+                    if symbol in ticker_map:
+                        database.update_ticker_financials(
+                            conn,
+                            ticker_map[symbol],
+                            financials.get("market_cap"),
+                            financials.get("closing_price"),
+                        )
+                conn.close()
+
+        log.critical("--- Top Ticker Financial Data Update Complete ---")
+        log.critical(f"    Successful updates: {successful_updates}")
+        log.critical(f"    Failed updates: {failed_updates}")
+
+    elif args.update_financials_only:
+        # --- Mode 2: Update All or a Single Ticker ---
+        update_mode = args.update_financials_only
+        tickers_to_update = []
+        if update_mode == "ALL_TICKERS":
+            log.critical("--- Starting Financial Data Update for ALL tickers ---")
+            all_tickers_from_db = database.get_all_tickers()
+            tickers_to_update = [t["symbol"] for t in all_tickers_from_db]
+        else:
+            ticker_symbol_to_update = update_mode
+            log.critical(
+                f"--- Starting Financial Data Update for single ticker: {ticker_symbol_to_update} ---"
+            )
+            if database.get_ticker_by_symbol(ticker_symbol_to_update):
+                tickers_to_update = [ticker_symbol_to_update]
+            else:
+                log.error(
+                    f"Ticker '{ticker_symbol_to_update}' not found in the database."
+                )
+
+        if tickers_to_update:
+            log.info(
+                f"Found {len(tickers_to_update)} unique tickers to update. Fetching in parallel..."
+            )
+
+            financial_data_batch = {}
+            successful_updates = 0
+            failed_updates = 0
+
+            with ThreadPoolExecutor(max_workers=10) as executor:
+                results = executor.map(fetch_financial_data, tickers_to_update)
+                for symbol, data in results:
+                    # A successful fetch is one where data is returned and has a closing price
+                    if data and data.get("closing_price") is not None:
+                        log.info(f"  -> SUCCESS: Fetched data for {symbol}")
+                        financial_data_batch[symbol] = data
+                        successful_updates += 1
+                    else:
+                        log.warning(
+                            f"  -> FAILED: Could not fetch valid financial data for {symbol}"
+                        )
+                        failed_updates += 1
+
+            if not financial_data_batch:
+                log.error("Failed to fetch any batch financial data. Aborting update.")
+            else:
+                conn = database.get_db_connection()
+                all_tickers_from_db = database.get_all_tickers()
+                ticker_map = {t["symbol"]: t["id"] for t in all_tickers_from_db}
+
+                for symbol, financials in financial_data_batch.items():
+                    if symbol in ticker_map:
+                        database.update_ticker_financials(
+                            conn,
+                            ticker_map[symbol],
+                            financials.get("market_cap"),
+                            financials.get("closing_price"),
+                        )
+                conn.close()
+
+        log.critical("--- Financial Data Update Complete ---")
+        log.critical(f"    Successful updates: {successful_updates}")
+        log.critical(f"    Failed updates: {failed_updates}")
+
+    else:
+        # --- Mode 3: Default Reddit Scan ---
+        log.critical("--- Starting Reddit Scan Mode ---")
+        if args.subreddit:
+            subreddits_to_scan = [args.subreddit]
+            log.info(f"Targeted Scan Mode: Focusing on r/{args.subreddit}")
+        else:
+            log.info(f"Config Scan Mode: Loading subreddits from {args.config}")
+            subreddits_to_scan = load_subreddits(args.config)
+
+        if not subreddits_to_scan:
+            log.error("Error: No subreddits to scan.")
+            return
+
+        reddit = get_reddit_instance()
+        if not reddit:
+            return
+
+        scan_subreddits(
+            reddit,
+            subreddits_to_scan,
+            post_limit=args.posts,
+            comment_limit=args.comments,
+            days_to_scan=args.days,
+            fetch_financials=(not args.no_financials),
+        )
+
 
 if __name__ == "__main__":
-    main()
+    main()

rstat_tool/sentiment_analyzer.py

@@ -9,11 +9,11 @@ _analyzer = SentimentIntensityAnalyzer()
 def get_sentiment_score(text):
     """
     Analyzes a piece of text and returns its sentiment score.
-    
+
     The 'compound' score is a single metric that summarizes the sentiment.
     It ranges from -1 (most negative) to +1 (most positive).
     """
     # The polarity_scores() method returns a dictionary with 'neg', 'neu', 'pos', and 'compound' scores.
     # We are most interested in the 'compound' score.
     scores = _analyzer.polarity_scores(text)
-    return scores['compound']
+    return scores["compound"]

rstat_tool/setup_nltk.py

@@ -3,9 +3,9 @@ import nltk
 # This will download the 'vader_lexicon' dataset
 # It only needs to be run once
 try:
-    nltk.data.find('sentiment/vader_lexicon.zip')
+    nltk.data.find("sentiment/vader_lexicon.zip")
     print("VADER lexicon is already downloaded.")
 except LookupError:
     print("Downloading VADER lexicon...")
-    nltk.download('vader_lexicon')
-    print("Download complete.")
+    nltk.download("vader_lexicon")
+    print("Download complete.")

rstat_tool/ticker_extractor.py

@@ -5,71 +5,142 @@ import re
 # A set of common English words and acronyms that look like stock tickers.
 # This helps reduce false positives.
 COMMON_WORDS_BLACKLIST = {
-    "401K", "403B", "457B", "ABOUT", "ABOVE", "ADAM", "ADX", "AEDT", "AEST", "AH",
-    "AI", "ALL", "ALPHA", "ALSO", "AM", "AMA", "AMEX", "AND", "ANY", "AR",
-    "ARE", "ARK", "AROUND", "ASAP", "ASS", "ASSET", "AT", "ATH", "ATL", "ATM",
-    "AUD", "AWS", "BABY", "BAG", "BAGS", "BE", "BEAR", "BELOW", "BETA", "BIG",
-    "BIS", "BLEND", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BOTH", "BOTS", "BRB",
-    "BRL", "BS", "BST", "BSU", "BTC", "BTW", "BULL", "BUST", "BUT", "BUY",
-    "BUZZ", "CAD", "CALL", "CAN", "CAP", "CBS", "CCI", "CEO", "CEST", "CET",
-    "CEX", "CFD", "CFO", "CHF", "CHIPS", "CIA", "CLOSE", "CNBC", "CNY", "COKE",
-    "COME", "COST", "COULD", "CPAP", "CPI", "CSE", "CST", "CTB", "CTO", "CYCLE",
-    "CZK", "DAO", "DATE", "DAX", "DAY", "DCA", "DD", "DEBT", "DEX", "DIA",
-    "DIV", "DJIA", "DKK", "DM", "DO", "DOE", "DOGE", "DOJ", "DONT", "DR",
-    "EACH", "EARLY", "EARN", "ECB", "EDGAR", "EDIT", "EDT", "EMA", "END", "EOD",
-    "EOW", "EOY", "EPA", "EPS", "ER", "ESG", "EST", "ETF", "ETFS", "ETH",
-    "EU", "EUR", "EV", "EVEN", "EVERY", "FAQ", "FAR", "FAST", "FBI", "FD",
-    "FDA", "FIHTX", "FINRA", "FINT", "FINTX", "FINTY", "FIRST", "FOMC", "FOMO", "FOR",
-    "FOREX", "FRAUD", "FRG", "FROM", "FSPSX", "FTSE", "FUCK", "FUD", "FULL", "FUND",
-    "FXAIX", "FXIAX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GBP", "GDP", "GET",
-    "GL", "GLHF", "GMT", "GO", "GOAL", "GOAT", "GOING", "GPT", "GPU", "GRAB",
-    "GTG", "HALF", "HAS", "HATE", "HAVE", "HEAR", "HEDGE", "HELP", "HIGH", "HINT",
-    "HKD", "HODL", "HOLD", "HOUR", "HSA", "HUF", "IF", "II", "IKZ", "IMHO",
-    "IMO", "IN", "INR", "IP", "IPO", "IRA", "IRS", "IS", "ISA", "ISM",
-    "IST", "IT", "ITM", "IV", "IVV", "IWM", "JD", "JPOW", "JPY", "JST",
-    "JUST", "KARMA", "KEEP", "KNOW", "KO", "KRW", "LANGT", "LARGE", "LAST", "LATE",
-    "LATER", "LBO", "LEAP", "LEAPS", "LETS", "LFG", "LIKE", "LIMIT", "LLC", "LLM",
-    "LMAO", "LOKO", "LOL", "LONG", "LOOK", "LOSS", "LOVE", "LOW", "M&A", "MA",
-    "MACD", "MAKE", "MAX", "MC", "ME", "MEME", "MERK", "MEXC", "MID", "MIGHT",
-    "MIN", "MIND", "ML", "MOASS", "MONTH", "MORE", "MSK", "MUSIC", "MUST", "MXN",
-    "MY", "NATO", "NEAR", "NEED", "NEVER", "NEW", "NEXT", "NFA", "NFC", "NFT",
-    "NGMI", "NIGHT", "NO", "NOK", "NONE", "NOT", "NOW", "NSA", "NULL", "NUT",
-    "NYSE", "NZD", "OBV", "OEM", "OF", "OG", "OK", "OLD", "ON", "ONE",
-    "ONLY", "OP", "OPEX", "OR", "OS", "OSCE", "OTC", "OTM", "OUGHT", "OUT",
-    "OVER", "OWN", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG", "PEW", "PLAN",
-    "PLN", "PM", "PMI", "POC", "POS", "PPI", "PR", "PRICE", "PROFIT", "PSA",
-    "PST", "PT", "PUT", "Q1", "Q2", "Q3", "Q4", "QQQ", "QR", "RBA",
-    "RBNZ", "RE", "REAL", "REIT", "REKT", "RH", "RIGHT", "RIP", "RISK", "ROCK",
-    "ROE", "ROFL", "ROI", "ROTH", "RSD", "RSI", "RUB", "RULE", "SAME", "SAVE",
-    "SCALP", "SCAM", "SCHB", "SEC", "SEE", "SEK", "SELL", "SEP", "SGD", "SHALL",
-    "SHARE", "SHORT", "SL", "SMA", "SMALL", "SO", "SOLIS", "SOME", "SOON", "SP",
-    "SPAC", "SPEND", "SPLG", "SPX", "SPY", "START", "STILL", "STOCK", "STOP", "STOR",
-    "SWING", "TA", "TAG", "TAKE", "TERM", "THANK", "THAT", "THE", "THINK", "THIS",
-    "TIME", "TITS", "TL", "TL;DR", "TLDR", "TO", "TODAY", "TOTAL", "TRADE", "TREND",
-    "TRUE", "TRY", "TTYL", "TWO", "UI", "UK", "UNDER", "UP", "US", "USA",
-    "USD", "UTC", "VALUE", "VOO", "VP", "VR", "VTI", "WAGMI", "WANT", "WATCH",
-    "WAY", "WE", "WEB3", "WEEK", "WHALE", "WHO", "WHY", "WIDE", "WILL", "WORDS",
-    "WORTH", "WOULD", "WSB", "WTF", "XRP", "YES", "YET", "YIELD", "YOLO", "YOU",
-    "YOUR", "YOY", "YT", "YTD", "ZAR", "ZEN", "ZERO"
+    "401K", "403B", "457B", "AAVE", "ABC", "ABOUT", "ABOVE", "ACAT", "ADAM", "ADHD",
+    "ADR", "ADS", "ADX", "AEDT", "AEST", "AF", "AFAIK", "AFTER", "AGENT", "AH",
+    "AI", "AINT", "AK", "AKSJE", "ALD", "ALGOS", "ALIVE", "ALL", "ALPHA", "ALSO",
+    "AM", "AMA", "AMEX", "AMK", "AMY", "AND", "ANSS", "ANY", "APES", "APL",
+    "APPL", "APPLE", "APR", "APUS", "APY", "AR", "ARBK", "ARE", "AREA", "ARH",
+    "ARK", "AROUND", "ART", "AS", "ASAP", "ASEAN", "ASK", "ASS", "ASSET", "AST",
+    "AT", "ATH", "ATL", "ATM", "AUD", "AUG", "AUM", "AV", "AVG", "AWS",
+    "BABY", "BAD", "BAG", "BAGS", "BALLS", "BAN", "BANG", "BASIC", "BBB", "BBBY",
+    "BE", "BEAR", "BEARS", "BECN", "BEER", "BELL", "BELOW", "BETA", "BETS", "BF",
+    "BID", "BIG", "BIS", "BITCH", "BKEY", "BLEND", "BLOW", "BMW", "BNP", "BNPL",
+    "BOARD", "BOE", "BOJ", "BOLL", "BOMB", "BOND", "BONED", "BORN", "BOTH", "BOTS",
+    "BOY", "BOYS", "BRB", "BRICS", "BRK", "BRKA", "BRKB", "BRL", "BROKE", "BRRRR",
+    "BS", "BSE", "BST", "BSU", "BT", "BTC", "BTS", "BTW", "BUDDY", "BULL",
+    "BULLS", "BUST", "BUT", "BUY", "BUZZ", "CAD", "CAFE", "CAGR", "CALL", "CALLS",
+    "CAN", "CAP", "CARB", "CARES", "CASE", "CATL", "CBD", "CBGM", "CBS", "CCI",
+    "CCP", "CD", "CDN", "CEO", "CEST", "CET", "CEX", "CFD", "CFO", "CFPB",
+    "CHART", "CHASE", "CHATS", "CHECK", "CHF", "CHICK", "CHIP", "CHIPS", "CIA", "CIC",
+    "CLAIM", "CLEAN", "CLICK", "CLOSE", "CMON", "CN", "CNBC", "CNN", "CNY", "COBRA",
+    "COCK", "COGS", "COIL", "COKE", "COME", "COST", "COULD", "COVID", "CPAP", "CPI",
+    "CRA", "CRE", "CRO", "CRV", "CSE", "CSP", "CSS", "CST", "CTB", "CTEP",
+    "CTO", "CUCKS", "CULT", "CUM", "CUSMA", "CUTS", "CUV", "CYCLE", "CZK", "DA",
+    "DAILY", "DAO", "DART", "DATA", "DATE", "DAX", "DAY", "DAYS", "DCA", "DCF",
+    "DD", "DEAL", "DEBT", "DEEZ", "DEMO", "DET", "DEX", "DGAF", "DIA", "DID",
+    "DIDNT", "DIP", "DITM", "DIV", "DIY", "DJI", "DJIA", "DJTJ", "DKK", "DL",
+    "DM", "DMV", "DNI", "DNUTZ", "DO", "DOD", "DOE", "DOES", "DOGE", "DOING",
+    "DOJ", "DOM", "DONNY", "DONT", "DONUT", "DOOR", "DOWN", "DOZEN", "DPI", "DR",
+    "DUDE", "DUMP", "DUNT", "DUT", "DUTY", "DXY", "DXYXBT", "DYI", "DYNK", "DYODD",
+    "DYOR", "EACH", "EARLY", "EARN", "EAST", "EASY", "EBIT", "ECB", "EDGAR", "EDIT",
+    "EDT", "EJ", "EMA", "EMJ", "EMT", "END", "ENRON", "ENSI", "ENV", "EO",
+    "EOD", "EOM", "EOW", "EOY", "EPA", "EPK", "EPS", "ER", "ESG", "ESPP",
+    "EST", "ETA", "ETF", "ETFS", "ETH", "ETHT", "ETL", "EU", "EUR", "EV",
+    "EVEN", "EVERY", "EVTOL", "EXTRA", "EYES", "EZ", "FAANG", "FAFO", "FAQ", "FAR",
+    "FAST", "FBI", "FCC", "FCFF", "FD", "FDA", "FED", "FEE", "FFH", "FFS",
+    "FGMA", "FIG", "FIGMA", "FIHTX", "FILES", "FINAL", "FIND", "FING", "FINRA", "FINT",
+    "FINTX", "FINTY", "FIRE", "FIRST", "FKIN", "FLOAT", "FLRAA", "FLT", "FLY", "FML",
+    "FOLO", "FOMC", "FOMO", "FOR", "FOREX", "FRAUD", "FREAK", "FRED", "FRG", "FROM",
+    "FRP", "FRS", "FSBO", "FSD", "FSE", "FSELK", "FSPSX", "FTD", "FTSE", "FUCK",
+    "FUCKS", "FUD", "FULL", "FUND", "FUNNY", "FVG", "FWIW", "FX", "FXAIX", "FXIAX",
+    "FXROX", "FY", "FYI", "FZROX", "GAAP", "GAIN", "GAV", "GAVE", "GBP", "GC",
+    "GDP", "GET", "GFC", "GG", "GGTM", "GIVES", "GJ", "GL", "GLHF", "GMAT",
+    "GMI", "GMT", "GO", "GOAL", "GOAT", "GOD", "GOING", "GOLD", "GONE", "GONNA",
+    "GOODS", "GOPRO", "GPT", "GPU", "GRAB", "GREAT", "GREEN", "GSOV", "GST", "GTA",
+    "GTC", "GTFO", "GTG", "GUH", "GUNS", "GUY", "GUYS", "HAD", "HAHA", "HALF",
+    "HAM", "HANDS", "HAS", "HATE", "HAVE", "HBAR", "HCOL", "HEAR", "HEDGE", "HEGE",
+    "HELD", "HELE", "HELL", "HELP", "HERE", "HEY", "HFCS", "HFT", "HGTV", "HIGH",
+    "HIGHS", "HINT", "HIS", "HITID", "HK", "HKD", "HKEX", "HODL", "HODOR", "HOF",
+    "HOLD", "HOLY", "HOME", "HOT", "HOUR", "HOURS", "HOW", "HS", "HSA", "HSI",
+    "HT", "HTCI", "HTF", "HTML", "HUF", "HUGE", "HV", "HYPE", "IANAL", "IATF",
+    "IB", "IBS", "ICSID", "ICT", "ID", "IDF", "IDK", "IF", "II", "IIRC",
+    "IKKE", "IKZ", "IM", "IMHO", "IMI", "IMO", "IN", "INC", "INR", "INTEL",
+    "INTO", "IP", "IPO", "IQVIA", "IRA", "IRAS", "IRC", "IRISH", "IRL", "IRMAA",
+    "IRS", "IS", "ISA", "ISIN", "ISM", "ISN", "IST", "IT", "ITC", "ITM",
+    "ITS", "ITWN", "IUIT", "IV", "IVV", "IWM", "IXL", "IXLH", "IYKYK", "JAVA",
+    "JD", "JDG", "JDM", "JE", "JFC", "JK", "JLR", "JMO", "JOBS", "JOIN",
+    "JOKE", "JP", "JPOW", "JPY", "JS", "JST", "JULY", "JUN", "JUST", "KARMA",
+    "KEEP", "KILL", "KING", "KK", "KLA", "KLP", "KNEW", "KNOW", "KO", "KOHLS",
+    "KPMG", "KRW", "LA", "LANGT", "LARGE", "LAST", "LATE", "LATER", "LBO", "LBTC",
+    "LCS", "LDL", "LEADS", "LEAP", "LEAPS", "LEARN", "LEGS", "LEI", "LET", "LETF",
+    "LETS", "LFA", "LFG", "LFP", "LG", "LGEN", "LID", "LIFE", "LIG", "LIGMA",
+    "LIKE", "LIMIT", "LIST", "LLC", "LLM", "LM", "LMAO", "LMAOO", "LMM", "LMN",
+    "LOANS", "LOKO", "LOL", "LOLOL", "LONG", "LONGS", "LOOK", "LOSE", "LOSS", "LOST",
+    "LOVE", "LOVES", "LOW", "LOWER", "LOWS", "LP", "LSS", "LTCG", "LUCID", "LUPD",
+    "LYC", "LYING", "M&A", "MA", "MACD", "MAIL", "MAKE", "MAKES", "MANGE", "MANY",
+    "MASON", "MAX", "MAY", "MAYBE", "MBA", "MC", "MCAP", "MCNA", "MCP", "ME",
+    "MEAN", "MEME", "MER", "MERGE", "MERK", "MES", "MEXC", "MF", "MFER", "MID",
+    "MIGHT", "MIN", "MIND", "MINS", "ML", "MLB", "MLS", "MM", "MMF", "MNQ",
+    "MOASS", "MODEL", "MODTX", "MOM", "MONEY", "MONGO", "MONTH", "MONY", "MOON", "MORE",
+    "MOST", "MOU", "MSK", "MTVGA", "MUCH", "MUSIC", "MUST", "MVA", "MXN", "MY",
+    "MYMD", "NASA", "NASDA", "NATO", "NAV", "NBA", "NBC", "NCAN", "NCR", "NEAR",
+    "NEAT", "NEED", "NEVER", "NEW", "NEWS", "NEXT", "NFA", "NFC", "NFL", "NFT",
+    "NGAD", "NGMI", "NIGHT", "NIQ", "NK", "NO", "NOK", "NON", "NONE", "NOOO",
+    "NOPE", "NORTH", "NOT", "NOVA", "NOW", "NQ", "NRI", "NSA", "NSCLC", "NSLC",
+    "NTG", "NTVS", "NULL", "NUT", "NUTS", "NUTZ", "NVIDIA", "NVM", "NW", "NY",
+    "NYSE", "NZ", "NZD", "OBBB", "OBI", "OBS", "OBV", "OCD", "OCF", "OCO",
+    "ODAT", "ODTE", "OEM", "OF", "OFA", "OFF", "OG", "OH", "OK", "OKAY",
+    "OL", "OLD", "OMFG", "OMG", "ON", "ONDAS", "ONE", "ONLY", "OP", "OPEC",
+    "OPENQ", "OPEX", "OPRN", "OR", "ORB", "ORDER", "ORTEX", "OS", "OSCE", "OSE",
+    "OSEBX", "OT", "OTC", "OTM", "OTOH", "OUCH", "OUGHT", "OUR", "OUT", "OVER",
+    "OWN", "OZZY", "PA", "PAID", "PANIC", "PC", "PDT", "PE", "PEAK", "PEG",
+    "PETA", "PEW", "PFC", "PGHL", "PIMCO", "PITA", "PLAN", "PLAYS", "PLC", "PLN",
+    "PM", "PMCC", "PMI", "PNL", "POC", "POMO", "POP", "POS", "POSCO", "POTUS",
+    "POV", "POW", "PPI", "PR", "PRICE", "PRIME", "PROFIT", "PROXY", "PS", "PSA",
+    "PST", "PT", "PTD", "PUSSY", "PUT", "PUTS", "PWC", "Q1", "Q2", "Q3",
+    "Q4", "QE", "QED", "QIMC", "QQQ", "QR", "RAM", "RATM", "RBA", "RBNZ",
+    "RE", "REACH", "READY", "REAL", "RED", "REIT", "REITS", "REKT", "REPE", "RFK",
+    "RH", "RICO", "RIDE", "RIGHT", "RIP", "RISK", "RISKY", "RNDC", "ROCE", "ROCK",
+    "ROE", "ROFL", "ROI", "ROIC", "ROTH", "RPO", "RRSP", "RSD", "RSI", "RT",
+    "RTD", "RUB", "RUG", "RULE", "RUST", "RVOL", "SAGA", "SALES", "SAME", "SAVE",
+    "SAYS", "SBF", "SBLOC", "SC", "SCALP", "SCAM", "SCHB", "SCIF", "SEC", "SEE",
+    "SEK", "SELL", "SELLL", "SEP", "SESG", "SET", "SFOR", "SGD", "SHALL", "SHARE",
+    "SHEIN", "SHELL", "SHIT", "SHORT", "SHOW", "SHS", "SHTF", "SI", "SICK", "SIGN",
+    "SL", "SLIM", "SLOW", "SMA", "SMALL", "SMFH", "SNZ", "SO", "SOLD", "SOLIS",
+    "SOME", "SOON", "SOOO", "SOUTH", "SP", "SPAC", "SPDR", "SPEND", "SPLG", "SPX",
+    "SPY", "SQUAD", "SS", "SSA", "SSDI", "START", "STAY", "STEEL", "STFU", "STILL",
+    "STO", "STOCK", "STOOQ", "STOP", "STOR", "STQQQ", "STUCK", "STUDY", "SUS", "SUSHI",
+    "SUV", "SWIFT", "SWING", "TA", "TAG", "TAKE", "TAM", "TBTH", "TEAMS", "TED",
+    "TEMU", "TERM", "TESLA", "TEXT", "TF", "TFNA", "TFSA", "THAN", "THANK", "THAT",
+    "THATS", "THE", "THEIR", "THEM", "THEN", "THERE", "THESE", "THEY", "THING", "THINK",
+    "THIS", "THROW", "TI", "TIA", "TIKR", "TIME", "TIMES", "TINA", "TITS", "TJR",
+    "TL", "TL;DR", "TLDR", "TNT", "TO", "TODAY", "TOLD", "TONS", "TOO", "TOS",
+    "TOT", "TOTAL", "TP", "TPU", "TRADE", "TREND", "TRUE", "TRUMP", "TRUST", "TRY",
+    "TSA", "TSMC", "TSP", "TSX", "TSXV", "TTIP", "TTM", "TTYL", "TURNS", "TWO",
+    "UAW", "UCITS", "UGH", "UI", "UK", "UNDER", "UNITS", "UNO", "UNTIL", "UP",
+    "US", "USA", "USD", "USMCA", "USSA", "USSR", "UTC", "VALID", "VALUE", "VAMOS",
+    "VAT", "VEIEN", "VEO", "VERY", "VFMXX", "VFV", "VI", "VISA", "VIX", "VLI",
+    "VOO", "VP", "VPAY", "VR", "VRVP", "VSUS", "VTI", "VUAG", "VW", "VWAP",
+    "VWCE", "VXN", "VXUX", "WAGER", "WAGMI", "WAIT", "WALL", "WANT", "WAS", "WATCH",
+    "WAY", "WBTC", "WE", "WEB", "WEB3", "WEEK", "WENT", "WERO", "WEST", "WHALE",
+    "WHAT", "WHEN", "WHERE", "WHICH", "WHILE", "WHO", "WHOS", "WHY", "WIDE", "WILL",
+    "WIRE", "WIRED", "WITH", "WL", "WON", "WOOPS", "WORDS", "WORTH", "WOULD", "WP",
+    "WRONG", "WSB", "WSJ", "WTF", "WV", "WWII", "WWIII", "X", "XAU", "XCUSE",
+    "XD", "XEQT", "XI", "XIV", "XMR", "XO", "XRP", "XX", "YEAH", "YEET",
+    "YES", "YET", "YIELD", "YM", "YMMV", "YOIR", "YOLO", "YOU", "YOUR", "YOY",
+    "YT", "YTD", "YUGE", "YUP", "YUPPP", "ZAR", "ZEN", "ZERO", "ZEV"
 }
 
-def extract_tickers(text):
+def extract_golden_tickers(text):
     """
-    Extracts potential stock tickers from a given piece of text.
-    A ticker is identified as a 1-5 character uppercase word, or a word prefixed with $.
+    Extracts ONLY tickers with a '$' prefix. This is the highest-confidence signal.
+    Returns a set of cleaned ticker symbols (e.g., {'TSLA', 'GME'}).
     """
-    # Regex to find potential tickers:
-    # 1. Words prefixed with $: $AAPL, $TSLA
-    # 2. All-caps words between 1 and 5 characters: GME, AMC
-    ticker_regex = r"\$[A-Z]{1,5}\b|\b[A-Z]{2,5}\b"
+    # Regex to find words prefixed with $: $AAPL, $TSLA
+    ticker_regex = r"\$[A-Z]{1,5}\b"
+    tickers = re.findall(ticker_regex, text)
+    # Clean the tickers by removing the '$' and return as a set
+    return {ticker.replace("$", "").upper() for ticker in tickers}
 
+def extract_potential_tickers(text):
+    """
+    Extracts potential tickers (all-caps words). This is a lower-confidence signal
+    used as a fallback when no golden tickers are present.
+    Returns a set of cleaned ticker symbols.
+    """
+    # Regex to find all-caps words between 2 and 5 characters: GME, AMC
+    ticker_regex = r"\b[A-Z]{2,5}\b"
     potential_tickers = re.findall(ticker_regex, text)
-
-    # Filter out common words and remove the '$' prefix
-    tickers = []
-    for ticker in potential_tickers:
-        cleaned_ticker = ticker.replace("$", "").upper()
-        if cleaned_ticker not in COMMON_WORDS_BLACKLIST:
-            tickers.append(cleaned_ticker)
-
-    return tickers
+    
+    # Filter out common blacklisted words
+    return {ticker for ticker in potential_tickers if ticker not in COMMON_WORDS_BLACKLIST}

run_daily_job.sh

@@ -0,0 +1,36 @@
+#!/bin/bash
+
+BASE_DIR="/home/rstat/reddit_stock_analyzer"
+
+# CRITICAL: Navigate to the project directory using an absolute path.
+cd ${BASE_DIR}
+
+# CRITICAL: Activate the virtual environment using an absolute path.
+source ${BASE_DIR}/.venv/bin/activate
+
+echo "--- Starting RSTAT Daily Job on $(date +%F) ---"
+
+# 1. Scrape data from the last 24 hours and update price for top tickers.
+echo "Step 1: Scraping new data..."
+rstat --no-financials --comments 256
+rstat --update-top-tickers
+
+# 2. Start the dashboard in the background.
+echo "Step 2: Starting dashboard in background..."
+rstat-dashboard &
+DASHBOARD_PID=$!
+sleep 10
+
+# 3. Export the overall summary image.
+echo "Step 3: Exporting overall summary image..."
+python export_image.py --overall
+
+# 4. Post the 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 dashboard server.
+echo "Step 5: Stopping dashboard server..."
+kill ${DASHBOARD_PID}
+
+echo "--- RSTAT Daily Job Complete ---"

setup.py

@@ -2,23 +2,25 @@
 
 from setuptools import setup, find_packages
 
-with open('requirements.txt') as f:
+with open("requirements.txt") as f:
     requirements = f.read().splitlines()
 
 setup(
-    name='reddit-stock-analyzer',
-    version='0.0.1',
-    author='Pål-Kristian Hamre',
-    author_email='its@pkhamre.com',
-    description='A command-line tool to analyze stock ticker mentions on Reddit.',
+    name="reddit-stock-analyzer",
+    version="0.0.2",
+    author="Pål-Kristian Hamre",
+    author_email="its@pkhamre.com",
+    description="A command-line tool to analyze stock ticker mentions on Reddit.",
     # This now correctly finds your 'rstat_tool' package
-    packages=find_packages(), 
+    packages=find_packages(),
     install_requires=requirements,
     entry_points={
-        'console_scripts': [
+        "console_scripts": [
             # The path is now 'package_name.module_name:function_name'
-            'rstat=rstat_tool.main:main',
-            'rstat-dashboard=rstat_tool.dashboard:start_dashboard',
+            "rstat=rstat_tool.main:main",
+            "rstat-dashboard=rstat_tool.dashboard:start_dashboard",
+            "rstat-cleanup=rstat_tool.cleanup:run_cleanup",
+            "rstat-flairs=rstat_tool.flair_finder:main",
         ],
     },
-)
+)

static/css/input.css

@@ -0,0 +1,2 @@
+@import "tailwindcss";
+@plugin "@tailwindcss/typography";

static/favicon.svg

@@ -0,0 +1,3 @@
+<svg xmlns="http://www.w3.org/2000/svg" version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" width="200" height="200"><svg xmlns="http://www.w3.org/2000/svg" version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 200 200"><rect width="200" height="200" fill="url('#gradient')"></rect><defs><linearGradient id="SvgjsLinearGradient1001" gradientTransform="rotate(45 0.5 0.5)"><stop offset="0%" stop-color="#697f83"></stop><stop offset="100%" stop-color="#161f2f"></stop></linearGradient></defs><g><g fill="#b1d6bb" transform="matrix(12.518681318681319,0,0,12.518681318681319,14.808730859284879,189.00720071373405)" stroke="#498990" stroke-width="0.7"><path d="M8.87 0L6.36-5.02L4.50-5.02L4.50 0L1.07 0L1.07-14.22L6.67-14.22Q9.20-14.22 10.63-13.10Q12.05-11.97 12.05-9.92L12.05-9.92Q12.05-8.44 11.45-7.46Q10.85-6.48 9.57-5.88L9.57-5.88L12.54-0.15L12.54 0L8.87 0ZM4.50-11.57L4.50-7.67L6.67-7.67Q7.65-7.67 8.14-8.18Q8.63-8.69 8.63-9.61Q8.63-10.53 8.13-11.05Q7.64-11.57 6.67-11.57L6.67-11.57L4.50-11.57Z"></path></g></g></svg><style>@media (prefers-color-scheme: light) { :root { filter: none; } }
+@media (prefers-color-scheme: dark) { :root { filter: none; } }
+</style></svg>

static/site.webmanifest

@@ -0,0 +1,21 @@
+{
+  "name": "MyWebSite",
+  "short_name": "MySite",
+  "icons": [
+    {
+      "src": "/web-app-manifest-192x192.png",
+      "sizes": "192x192",
+      "type": "image/png",
+      "purpose": "maskable"
+    },
+    {
+      "src": "/web-app-manifest-512x512.png",
+      "sizes": "512x512",
+      "type": "image/png",
+      "purpose": "maskable"
+    }
+  ],
+  "theme_color": "#ffffff",
+  "background_color": "#ffffff",
+  "display": "standalone"
+}

subreddits.json

@@ -1,18 +1,18 @@
 {
   "subreddits": [
+    "dividends",
+    "investing",
+    "options",
     "pennystocks",
+    "SecurityAnalysis",
     "Shortsqueeze",
     "smallstreetbets",
-    "wallstreetbets",
-    "Wallstreetbetsnew",
-    "wallstreetbets2",
+    "stockmarket",
     "stocks",
-    "RobinHoodPennyStocks",
-    "StocksAndTrading",
-    "investing",
-    "WallStreetBetsELITE",
+    "thetagang",
+    "Tollbugatabets",
     "ValueInvesting",
-    "Daytrading",
-    "Tollbugatabets"
+    "wallstreetbets",
+    "WallStreetBetsELITE"
   ]
-}
+}

tailwind.config.js

@@ -0,0 +1,27 @@
+/** @type {import('tailwindcss').Config} */
+module.exports = {
+  content: [
+    './templates/**/*.html',
+  ],
+  safelist: [
+    'text-violet-400',
+    'text-lime-400',
+    'text-cyan-400',
+    'text-yellow-400',
+    'text-red-400',
+    'text-orange-400',
+    'text-emerald-400',
+    'text-blue-400',
+    'text-gray-300',
+    'text-pink-400'
+  ],
+  theme: {
+    extend: {
+      fontFamily: {
+        sans: ['Inter', 'sans-serif'],
+      },
+    },
+  },
+  plugins: [
+  ],
+}

templates/about.html

@@ -0,0 +1,51 @@
+{% extends "dashboard_base.html" %}
+
+{% block title %}About RSTAT{% endblock %}
+
+{% block content %}
+<!-- This outer div now handles the centering -->
+<div class="flex flex-col items-center">
+  <div class="w-full max-w-3xl bg-slate-800/50 ring-1 ring-slate-700 rounded-2xl p-6 sm:p-10 shadow-2xl">
+    <div class="text-center mb-10">
+      <h1 class="text-3xl sm:text-4xl font-extrabold tracking-tight text-white">About RSTAT (beta)</h1>
+    </div>
+
+    <!-- The 'prose' class will now work correctly inside this standard block flow -->
+    <article class="prose prose-slate prose-invert max-w-none">
+      <h2>What is this?</h2>
+      <p>RSTAT (Reddit Stock Analysis Tool) is an automated data pipeline that scans popular financial communities on
+        Reddit to identify and analyze trending stock tickers. It provides a daily and weekly snapshot of the most
+        discussed stocks, their social sentiment, and key financial data.</p>
+
+      <h2>How does it work?</h2>
+      <ul>
+        <li>A <strong>scraper</strong> runs on a schedule to read new posts and comments from a predefined list of
+          subreddits.</li>
+        <li>A <strong>sentiment analyzer</strong> scores each mention as Bullish, Bearish, or Neutral using a natural
+          language processing model.</li>
+        <li>A <strong>data fetcher</strong> enriches the ticker data with the latest closing price and market
+          capitalization from Yahoo Finance.</li>
+        <li>All data is stored in a local <strong>SQLite database</strong>.</li>
+        <li>This <strong>web dashboard</strong> reads from the database to provide a clean, interactive visualization of
+          the results.</li>
+      </ul>
+
+      <h2>Supporting the Project</h2>
+      <p>RSTAT is a <b>soon-to-be</b>free and open-source project. To ensure the dashboard remains fast and reliable, it is hosted on a
+        small virtual server with running costs of approximately $6 per month. And about $30 per year for he domain.
+        If you find this tool useful, donations are gratefully accepted via Dogecoin (DOGE).</p>
+      <div class="not-prose bg-slate-900/50 ring-1 ring-slate-700 rounded-lg p-3 text-center">
+        <code class="text-sm text-slate-200 break-all">DRTLo2BsBijY4MrLmNNHzmjZ5tVvpTebFE</code>
+      </div>
+    </article>
+
+    <footer class="mt-12 text-center">
+      <div class="text-xl font-extrabold tracking-tight text-white">r/rstat</div>
+      <div class="text-sm text-slate-400">
+        <a href="https://www.reddit.com/r/rstat/" target="_blank" class="hover:text-white transition-colors">visit us
+          for more.</a>
+      </div>
+    </footer>
+  </div>
+</div>
+{% endblock %}

templates/base.html

@@ -1,109 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>{% block title %}Reddit Stock Dashboard{% endblock %}</title>
-    <style>
-        body {
-            font-family: 'Inter', -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
-            background-color: #f4f7f6;
-            color: #333;
-            margin: 0;
-            line-height: 1.6;
-        }
-        .navbar {
-            background-color: #ffffff;
-            padding: 1rem 2rem;
-            border-bottom: 1px solid #e0e0e0;
-            display: flex;
-            flex-wrap: wrap;
-            gap: 1rem;
-        }
-        .navbar a {
-            color: #555;
-            text-decoration: none;
-            font-weight: 600;
-            padding: 0.5rem 1rem;
-            border-radius: 6px;
-            transition: background-color 0.2s ease-in-out, color 0.2s ease-in-out;
-        }
-        .navbar a:hover {
-            background-color: #e9ecef;
-            color: #000;
-        }
-        .container {
-            max-width: 1000px;
-            margin: 2rem auto;
-            padding: 2rem;
-            background-color: #ffffff;
-            border-radius: 8px;
-            box-shadow: 0 4px 12px rgba(0,0,0,0.05);
-        }
-        h1 {
-            font-size: 1.75rem;
-            font-weight: 700;
-            margin-top: 0;
-            border-bottom: 1px solid #eee;
-            padding-bottom: 0.5rem;
-        }
-        table {
-            width: 100%;
-            border-collapse: collapse;
-            margin-top: 2rem;
-            font-size: 0.95rem;
-        }
-        th, td {
-            padding: 1rem;
-            text-align: left;
-            border-bottom: 1px solid #e0e0e0;
-        }
-        th {
-            font-weight: 600;
-            text-transform: uppercase;
-            font-size: 0.8rem;
-            letter-spacing: 0.05em;
-            color: #666;
-        }
-        tr:last-child td {
-            border-bottom: none;
-        }
-        .sentiment-bullish { color: #28a745; font-weight: 600; }
-        .sentiment-bearish { color: #dc3545; font-weight: 600; }
-        .sentiment-neutral { color: #6c757d; }
-
-        .post-card {
-            border: 1px solid #e0e0e0;
-            border-radius: 8px;
-            padding: 1.5rem;
-            margin-bottom: 1.5rem;
-        }
-        .post-card h3 {
-            margin-top: 0;
-            font-size: 1.2rem;
-        }
-        .post-card h3 a {
-            color: #0056b3;
-            text-decoration: none;
-        }
-        .post-card h3 a:hover {
-            text-decoration: underline;
-        }
-        .post-meta {
-            font-size: 0.9rem;
-            color: #666;
-        }
-    </style>
-</head>
-<body>
-    <header class="navbar">
-        <a href="/">Overall</a>
-        {% for sub in subreddits %}
-            <a href="/subreddit/{{ sub }}">r/{{ sub }}</a>
-        {% endfor %}
-    </header>
-    <main class="container">
-        {% block content %}{% endblock %}
-    </main>
-</body>
-</html>

templates/dashboard_base.html

@@ -0,0 +1,119 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>{% block title %}RSTAT Dashboard{% endblock %}</title>
+
+    <link rel="icon" type="image/png" href="{{ url_for('static', filename='favicon-96x96.png') }}" sizes="96x96" />
+    <link rel="icon" href="{{ url_for('static', filename='favicon.ico') }}">
+    <link rel="shortcut icon" type="image/svg+xml" href="{{ url_for('static', filename='favicon.svg') }}">
+    <link rel="apple-touch-icon" sizes="180x180" href="{{ url_for('static', filename='apple-touch-icon.png') }}" />
+    <link rel="manifest" href="{{ url_for('static', filename='site.webmanifest') }}" />
+
+    <link rel="preconnect" href="https://fonts.googleapis.com">
+    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700;800&display=swap" rel="stylesheet">
+    <link rel="stylesheet" href="{{ url_for('static', filename='css/style.css') }}">
+    <script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"></script>
+    <style>
+        /* This sets the custom font as the default for the page */
+        body {
+            font-family: 'Inter', sans-serif;
+        }
+
+        [class*="text-"]>a {
+            color: inherit;
+            text-decoration: none;
+            transition: color 0.2s ease-in-out;
+        }
+
+
+        [class*="text-"]>a:hover {
+            color: #ffffff;
+        }
+    </style>
+</head>
+
+<body class="bg-slate-900 text-slate-200 min-h-screen">
+
+    {% if not is_image_mode %}
+    <header class="p-4 sm:p-6 w-full">
+        <nav
+            class="w-full max-w-7xl mx-auto bg-slate-800/50 ring-1 ring-slate-700 rounded-xl p-4 flex flex-col sm:flex-row items-center gap-4">
+            <div class="flex items-center gap-4">
+                <!-- Home Link -->
+                <a href="/"
+                    class="font-bold {% if not subreddit_name %}text-white{% else %}text-slate-400 hover:text-white{% endif %} transition-colors">Home</a>
+
+                <!-- Alpine.js Dropdown Component -->
+                <div x-data="{ isOpen: false }" class="relative">
+                    <!-- The Button that toggles the 'isOpen' state -->
+                    <button @click="isOpen = !isOpen"
+                        class="font-bold flex items-center gap-1 cursor-pointer {% if subreddit_name %}text-white{% else %}text-slate-400 hover:text-white{% endif %} transition-colors">
+                        <span>Subreddits</span>
+                        <svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none"
+                            stroke="currentColor" stroke-width="3" stroke-linecap="round" stroke-linejoin="round"
+                            class="transition-transform duration-200" :class="{'rotate-180': isOpen}">
+                            <polyline points="6 9 12 15 18 9"></polyline>
+                        </svg>
+                    </button>
+
+                    <!-- The Dropdown Menu, controlled by Alpine.js -->
+                    <div x-show="isOpen" @click.outside="isOpen = false"
+                        x-transition:enter="transition ease-out duration-100"
+                        x-transition:enter-start="opacity-0 scale-95" x-transition:enter-end="opacity-100 scale-100"
+                        x-transition:leave="transition ease-in duration-75"
+                        x-transition:leave-start="opacity-100 scale-100" x-transition:leave-end="opacity-0 scale-95"
+                        class="absolute left-0 mt-2 bg-slate-800 ring-1 ring-slate-700 shadow-lg rounded-lg py-1 w-48 z-10"
+                        style="display: none;">
+                        {% for sub in all_subreddits %}
+                        <a href="/subreddit/{{ sub }}"
+                            class="block px-4 py-2 text-sm text-slate-300 hover:bg-slate-700 hover:text-white">{{ sub
+                            }}</a>
+                        {% endfor %}
+                    </div>
+                </div>
+            </div>
+
+            <div class="flex items-center gap-2 sm:ml-auto">
+                <a href="?view=daily"
+                    class="px-3 py-1 rounded-md text-sm font-semibold {% if view_type == 'daily' %}bg-sky-500 text-white{% else %}bg-slate-700/50 text-slate-300 hover:bg-slate-700 hover:text-white{% endif %} transition-all">Daily</a>
+                <a href="?view=weekly"
+                    class="px-3 py-1 rounded-md text-sm font-semibold {% if view_type == 'weekly' %}bg-sky-500 text-white{% else %}bg-slate-700/50 text-slate-300 hover:bg-slate-700 hover:text-white{% endif %} transition-all">Weekly</a>
+                <a href="/about" title="About this Project"
+                    class="p-2 rounded-md text-slate-400 hover:bg-slate-700 hover:text-white transition-colors">
+                    <svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none"
+                        stroke="currentColor" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round">
+                        <circle cx="12" cy="12" r="10"></circle>
+                        <line x1="12" y1="16" x2="12" y2="12"></line>
+                        <line x1="12" y1="8" x2="12.01" y2="8"></line>
+                    </svg>
+                </a>
+            </div>
+        </nav>
+        {% endif %}
+
+        <main class="w-full p-4 sm:p-6">
+            {% block content %}{% endblock %}
+        </main>
+
+        {% if not is_image_mode %}
+        <footer class="mt-8 text-center">
+            <div class="flex items-center justify-center gap-2">
+                <img src="{{ url_for('static', filename='dogecoin_logo.png') }}" alt="Doge" class="w-6 h-6">
+
+                <!-- text-base makes the text larger -->
+                <span class="text-base text-slate-400">
+                    Support this service:
+                    <!-- text-sm and p-2 make the code block larger -->
+                    <code
+                        class="text-sm bg-slate-800 p-2 rounded-lg text-slate-300">DRTLo2BsBijY4MrLmNNHzmjZ5tVvpTebFE</code>
+                </span>
+            </div>
+        </footer>
+        {% endif %}
+</body>
+
+</html>

templates/dashboard_view.html

@@ -0,0 +1,126 @@
+{% extends "dashboard_base.html" %}
+
+{% block title %}{{ title }}{% endblock %}
+
+{% block content %}
+<div class="flex flex-col items-center">
+    <div
+        class="w-full max-w-3xl bg-gradient-to-br from-slate-800 to-slate-900 ring-1 ring-slate-700 rounded-2xl p-6 sm:p-8 shadow-2xl">
+        <header class="flex flex-col sm:flex-row justify-between sm:items-start mb-8">
+            <div class="text-left">
+                <h1 class="text-2xl sm:text-4xl font-extrabold tracking-tight text-white">Reddit Ticker Mentions</h1>
+                <h2 class="text-lg sm:text-xl font-semibold mt-1 text-slate-400">{{ subtitle }}</h2>
+            </div>
+            <div class="text-left sm:text-right mt-2 sm:mt-0 flex-shrink-0">
+                <div class="text-md font-semibold text-slate-400 whitespace-nowrap">{{ date_string }}</div>
+                {% if not is_image_mode %}
+                <a href="{{ base_url }}?view={{ view_type }}&image=true" class="inline-block mt-2 sm:float-right"
+                    title="View as Shareable Image">
+                    <svg class="text-slate-400 hover:text-white transition-colors" xmlns="http://www.w3.org/2000/svg"
+                        width="22" height="22" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2.5"
+                        stroke-linecap="round" stroke-linejoin="round">
+                        <path d="M23 19a2 2 0 0 1-2 2H3a2 2 0 0 1-2-2V8a2 2 0 0 1 2-2h4l2-3h6l2 3h4a2 2 0 0 1 2 2z">
+                        </path>
+                        <circle cx="12" cy="13" r="4"></circle>
+                    </svg>
+                </a>
+                {% endif %}
+            </div>
+        </header>
+
+        {% set ticker_colors = {
+        1: 'text-violet-400', 2: 'text-lime-400', 3: 'text-cyan-400',
+        4: 'text-yellow-400', 5: 'text-red-400', 6: 'text-orange-400',
+        7: 'text-emerald-400', 8: 'text-blue-400', 9: 'text-gray-300',
+        10: 'text-pink-400'
+        } %}
+
+        <!-- Ticker List -->
+        <div class="flex flex-col">
+
+            <!-- 1. The Desktop Header Row (hidden on mobile) -->
+            <div
+                class="hidden sm:flex items-center text-xs font-bold text-slate-500 uppercase tracking-wider px-4 py-3 border-b border-slate-700">
+                <div class="w-1/4 flex items-center gap-4 text-left">
+                    <span class="w-6 text-center">#</span>
+                    <span>Ticker</span>
+                </div>
+                <div class="w-3/4 grid grid-cols-4 gap-4 text-right">
+                    <div class="text-center">Mentions</div>
+                    <div class="text-center">Sentiment</div>
+                    <div>Mkt Cap</div>
+                    <div>Last Price</div>
+                </div>
+            </div>
+
+            <!-- 2. Ticker Rows -->
+            <div class="divide-y divide-slate-800">
+                {% for ticker in tickers %}
+                <!-- THIS IS THE UPDATED LINE -->
+                <div
+                    class="p-4 flex flex-col sm:flex-row sm:items-center sm:gap-4 hover:bg-slate-800/50 transition-colors duration-150">
+                    <!-- Rank & Ticker Symbol -->
+                    <div class="flex items-center gap-4 w-full sm:w-1/4 text-left mb-4 sm:mb-0">
+                        <span class="text-lg font-bold text-slate-500 w-6 text-center">{{ loop.index }}</span>
+                        <div class="text-xl font-bold">
+                            <span class="{{ ticker_colors.get(loop.index, 'text-slate-200') }}">
+                                {% if is_image_mode %}
+                                {{ ticker.symbol }}
+                                {% else %}
+                                <a href="/deep-dive/{{ ticker.symbol }}">{{ ticker.symbol }}</a>
+                                {% endif %}
+                            </span>
+                        </div>
+                    </div>
+                    <!-- Financial Data Points -->
+                    <div class="w-full grid grid-cols-2 sm:grid-cols-4 gap-4 text-right">
+                        <div class="text-center sm:text-center">
+                            <div class="sm:hidden text-xs font-bold text-slate-500 uppercase tracking-wider mb-1">
+                                Mentions</div>
+                            <div class="text-lg font-semibold text-white">{{ ticker.total_mentions }}</div>
+                        </div>
+                        <div class="text-center sm:text-center">
+                            <div class="sm:hidden text-xs font-bold text-slate-500 uppercase tracking-wider mb-1">
+                                Sentiment</div>
+                            <div class="text-lg font-semibold">
+                                {% if ticker.bullish_mentions > ticker.bearish_mentions %}<span
+                                    class="text-green-400">Bullish</span>
+                                {% elif ticker.bearish_mentions > ticker.bullish_mentions %}<span
+                                    class="text-red-400">Bearish</span>
+                                {% else %}<span class="text-slate-400">Neutral</span>{% endif %}
+                            </div>
+                        </div>
+                        <div>
+                            <div class="sm:hidden text-xs font-bold text-slate-500 uppercase tracking-wider mb-1">Mkt
+                                Cap</div>
+                            <div class="text-lg font-semibold text-white">{{ ticker.market_cap | format_mc }}</div>
+                        </div>
+                        <div>
+                            <div class="sm:hidden text-xs font-bold text-slate-500 uppercase tracking-wider mb-1">Last Price</div>
+                            <div class="text-lg font-semibold text-white">
+                                {% if ticker.closing_price %}<a
+                                    href="https://www.marketwatch.com/investing/stock/{{ ticker.symbol }}" target="_blank"
+                                    class="hover:text-blue-400 transition-colors">${{
+                                    "%.2f"|format(ticker.closing_price) }}</a>
+                                {% else %}N/A{% endif %}
+                            </div>
+                        </div>
+                    </div>
+                </div>
+                {% else %}
+                <div class="text-center text-slate-500 p-8">No ticker data found for this period.</div>
+                {% endfor %}
+            </div>
+        </div>
+
+        <footer class="mt-8 text-center">
+            <div class="text-xl font-extrabold tracking-tight text-white">r/rstat</div>
+            <div class="text-sm text-slate-400">
+                <a href="https://www.reddit.com/r/rstat/" target="_blank"
+                    class="hover:text-white transition-colors">visit us for more.</a>
+            </div>
+        </footer>
+    </div>
+</div>
+
+{% endblock %}

templates/deep_dive.html

@@ -1,29 +1,54 @@
-{% extends "base.html" %}
+{% extends "dashboard_base.html" %}
 
 {% block title %}Deep Dive: {{ symbol }}{% endblock %}
 
 {% block content %}
-    <h1>Deep Dive Analysis for: <strong>{{ symbol }}</strong></h1>
-    <p>Showing posts that mention {{ symbol }}, sorted by most recent.</p>
+<!-- This outer div handles the centering -->
+<div class="flex flex-col items-center">
+    <div class="w-full max-w-3xl bg-slate-800/50 ring-1 ring-slate-700 rounded-2xl p-6 sm:p-10 shadow-2xl">
 
-    {% for post in posts %}
-        <div class="post-card">
-            <h3><a href="{{ post.post_url }}" target="_blank">{{ post.title }}</a></h3>
-            <div class="post-meta">
-                <span>r/{{ post.subreddit_name }}</span> |
-                <span>{{ post.comment_count }} comments analyzed</span> |
-                <span>Avg. Sentiment: 
-                    {% if post.avg_comment_sentiment > 0.1 %}
-                        <span class="sentiment-bullish">{{ "%.2f"|format(post.avg_comment_sentiment) }}</span>
-                    {% elif post.avg_comment_sentiment < -0.1 %}
-                        <span class="sentiment-bearish">{{ "%.2f"|format(post.avg_comment_sentiment) }}</span>
-                    {% else %}
-                        <span class="sentiment-neutral">{{ "%.2f"|format(post.avg_comment_sentiment) }}</span>
-                    {% endif %}
-                </span>
+        <!-- --- THIS IS THE KEY CHANGE --- -->
+        <!-- We wrap all the content in an <article> tag with the 'prose' classes -->
+        <article class="prose prose-slate prose-invert max-w-none">
+
+            <header class="text-center mb-8">
+                <!-- The h1 and p tags will now be beautifully styled by 'prose' -->
+                <h1>Deep Dive Analysis: <span class="text-sky-400">{{ symbol }}</span></h1>
+                <p>Showing posts that mention {{ symbol }}, sorted by most recent.</p>
+            </header>
+
+            <div class="space-y-4 not-prose">
+                {% for post in posts %}
+                <!-- 'not-prose' is used on the container so we can control styling precisely -->
+                <div class="bg-slate-800/50 ring-1 ring-slate-700/50 rounded-lg p-4 text-left not-prose">
+                    <h3 class="text-lg font-bold text-slate-200 mb-2">
+                        <!-- This link WILL be styled by the parent 'prose' class -->
+                        <a href="{{ post.post_url }}" target="_blank">{{ post.title }}</a>
+                    </h3>
+                    <div class="text-sm text-slate-400 flex flex-col sm:flex-row sm:items-center gap-x-4 gap-y-1">
+                        <span class="font-semibold">r/{{ post.subreddit_name }}</span>
+                        <span class="hidden sm:inline">|</span>
+                        <span>{{ post.comment_count }} comments analyzed</span>
+                        <span class="hidden sm:inline">|</span>
+                        <span>Avg. Sentiment:
+                            {% if post.avg_comment_sentiment > 0.1 %}
+                            <span class="font-bold text-green-400">{{ "%.2f"|format(post.avg_comment_sentiment) }}
+                                (Bullish)</span>
+                            {% elif post.avg_comment_sentiment < -0.1 %} <span class="font-bold text-red-400">{{
+                                "%.2f"|format(post.avg_comment_sentiment) }} (Bearish)</span>
+                        {% else %}
+                        <span class="font-bold text-slate-500">{{ "%.2f"|format(post.avg_comment_sentiment) }}
+                            (Neutral)</span>
+                        {% endif %}
+                        </span>
+                    </div>
+                </div>
+                {% else %}
+                <div class="text-center text-slate-500 p-8 not-prose">No analyzed posts found for this ticker.</div>
+                {% endfor %}
             </div>
-        </div>
-    {% else %}
-        <p>No analyzed posts found for this ticker. Run the 'rstat' scraper to gather data.</p>
-    {% endfor %}
+
+        </article>
+    </div>
+</div>
 {% endblock %}

templates/image_view.html

@@ -1,116 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>r/{{ subreddit_name }} Mentions</title>
-    <link rel="preconnect" href="https://fonts.googleapis.com">
-    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700;800&display=swap" rel="stylesheet">
-    <style>
-        body {
-            margin: 0;
-            padding: 2rem;
-            font-family: 'Inter', sans-serif;
-            background: #1a1a1a;
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            min-height: 100vh;
-        }
-        .image-container {
-            width: 650px; /* Increased width to accommodate new column */
-            background: linear-gradient(145deg, #4d302d, #1f2128);
-            color: #ffffff;
-            border-radius: 16px;
-            padding: 2.5rem;
-            box-shadow: 0 10px B30px rgba(0,0,0,0.5);
-            text-align: center;
-        }
-        header {
-            display: flex;
-            justify-content: space-between;
-            align-items: flex-start;
-            margin-bottom: 2rem;
-        }
-        .title-block { text-align: left; }
-        .title-block h1 { font-size: 2.5rem; font-weight: 800; margin: 0; line-height: 1; }
-        .title-block h2 { font-size: 1.25rem; font-weight: 600; margin: 0.5rem 0 0; color: #b0b0b0; }
-        .date { font-size: 1.1rem; font-weight: 600; color: #c0c0c0; letter-spacing: 0.02em; }
-        table { width: 100%; border-collapse: collapse; text-align: left; }
-        th, td { padding: 1rem 0.5rem; border-bottom: 1px solid rgba(255, 255, 255, 0.1); }
-        th { font-weight: 700; text-transform: uppercase; font-size: 0.8rem; color: #a0a0a0; }
-        td { font-size: 1.1rem; font-weight: 600; }
-        tr:last-child td { border-bottom: none; }
-        td.rank { font-weight: 700; color: #d0d0d0; width: 8%; }
-        td.ticker { width: 30%; }
-        td.mentions { text-align: center; width: 18%; }
-        td.sentiment { text-align: center; width: 26%; } /* New width */
-        
-        /* Sentiment Colors */
-        .sentiment-bullish { color: #28a745; font-weight: 700; }
-        .sentiment-bearish { color: #dc3545; font-weight: 700; }
-        .sentiment-neutral { color: #9e9e9e; font-weight: 600; }
-
-        /* Row colors */
-        tr:nth-child(1) td.ticker { color: #d8b4fe; } tr:nth-child(6) td.ticker { color: #fca5a5; }
-        tr:nth-child(2) td.ticker { color: #a3e635; } tr:nth-child(7) td.ticker { color: #fdba74; }
-        tr:nth-child(3) td.ticker { color: #67e8f9; } tr:nth-child(8) td.ticker { color: #6ee7b7; }
-        tr:nth-child(4) td.ticker { color: #fde047; } tr:nth-child(9) td.ticker { color: #93c5fd; }
-        tr:nth-child(5) td.ticker { color: #fcd34d; } tr:nth-child(10) td.ticker { color: #d1d5db; }
-        
-        footer { margin-top: 2.5rem; }
-        .brand-name { font-size: 1.75rem; font-weight: 800; letter-spacing: -1px; }
-        .brand-subtitle { font-size: 1rem; color: #b0b0b0; }
-    </style>
-</head>
-<body>
-    <div class="image-container">
-        <header>
-            <div class="title-block">
-                <h1>Reddit Mentions</h1>
-                <h2>r/{{ subreddit_name }}</h2>
-            </div>
-            <div class="date">{{ current_date }}</div>
-        </header>
-
-        <table>
-            <thead>
-                <tr>
-                    <th class="rank">Rank</th>
-                    <th class="ticker">Ticker</th>
-                    <th class="mentions">Posts</th>
-                    <th class="mentions">Comments</th>
-                    <!-- UPDATED: Added Sentiment column header -->
-                    <th class="sentiment">Sentiment</th>
-                </tr>
-            </thead>
-            <tbody>
-                {% for ticker in tickers %}
-                <tr>
-                    <td class="rank">{{ loop.index }}</td>
-                    <td class="ticker">{{ ticker.symbol }}</td>
-                    <td class="mentions">{{ ticker.post_mentions }}</td>
-                    <td class="mentions">{{ ticker.comment_mentions }}</td>
-                    <!-- UPDATED: Added Sentiment data cell -->
-                    <td class="sentiment">
-                        {% if ticker.bullish_mentions > ticker.bearish_mentions %}
-                            <span class="sentiment-bullish">Bullish</span>
-                        {% elif ticker.bearish_mentions > ticker.bullish_mentions %}
-                            <span class="sentiment-bearish">Bearish</span>
-                        {% else %}
-                            <span class="sentiment-neutral">Neutral</span>
-                        {% endif %}
-                    </td>
-                </tr>
-                {% endfor %}
-            </tbody>
-        </table>
-
-        <footer>
-            <div class="brand-name">RSTAT</div>
-            <div class="brand-subtitle">Reddit Stock Analysis Tool</div>
-        </footer>
-    </div>
-</body>
-</html>

templates/index.html

@@ -1,44 +0,0 @@
-{% extends "base.html" %}
-
-{% block title %}Overall Dashboard{% endblock %}
-
-{% block content %}
-    <h1>Top 10 Tickers (All Subreddits)</h1>
-    <table>
-        <thead>
-            <tr>
-                <th>Ticker</th>
-                <th>Mentions</th>
-                <th>Market Cap</th>
-                <th>Closing Price</th>
-                <th>Sentiment</th>
-            </tr>
-        </thead>
-        <tbody>
-            {% for ticker in tickers %}
-            <tr>
-                <td><strong><a href="/deep-dive/{{ ticker.symbol }}">{{ ticker.symbol }}</a></strong></td>
-                <td>{{ ticker.mention_count }}</td>
-                <td>{{ ticker.market_cap | format_mc }}</td>
-                <!-- NEW COLUMN FOR CLOSING PRICE -->
-                <td>
-                    {% if ticker.closing_price %}
-                        ${{ "%.2f"|format(ticker.closing_price) }}
-                    {% else %}
-                        N/A
-                    {% endif %}
-                </td>
-                <td>
-                    {% if ticker.bullish_mentions > ticker.bearish_mentions %}
-                        <span class="sentiment-bullish">Bullish</span>
-                    {% elif ticker.bearish_mentions > ticker.bullish_mentions %}
-                        <span class="sentiment-bearish">Bearish</span>
-                    {% else %}
-                        <span class="sentiment-neutral">Neutral</span>
-                    {% endif %}
-                </td>
-            </tr>
-            {% endfor %}
-        </tbody>
-    </table>
-{% endblock %}

templates/subreddit.html

@@ -1,49 +0,0 @@
-{% extends "base.html" %}
-
-{% block title %}r/{{ subreddit_name }} Dashboard{% endblock %}
-
-{% 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>
-        <!-- 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>
-    <table>
-        <thead>
-            <tr>
-                <th>Ticker</th>
-                <th>Mentions</th>
-                <th>Market Cap</th>
-                <th>Closing Price</th>
-                <th>Sentiment</th>
-            </tr>
-        </thead>
-        <tbody>
-            {% for ticker in tickers %}
-            <tr>
-                <td><strong><a href="/deep-dive/{{ ticker.symbol }}">{{ ticker.symbol }}</a></strong></td>
-                <td>{{ ticker.mention_count }}</td>
-                <td>{{ ticker.market_cap | format_mc }}</td>
-                <!-- NEW COLUMN FOR CLOSING PRICE -->
-                <td>
-                    {% if ticker.closing_price %}
-                        ${{ "%.2f"|format(ticker.closing_price) }}
-                    {% else %}
-                        N/A
-                    {% endif %}
-                </td>
-                <td>
-                    {% if ticker.bullish_mentions > ticker.bearish_mentions %}
-                        <span class="sentiment-bullish">Bullish</span>
-                    {% elif ticker.bearish_mentions > ticker.bullish_mentions %}
-                        <span class="sentiment-bearish">Bearish</span>
-                    {% else %}
-                        <span class="sentiment-neutral">Neutral</span>
-                    {% endif %}
-                </td>
-            </tr>
-            {% endfor %}
-        </tbody>
-    </table>
-{% endblock %}

templates/weekly_image_view.html

@@ -1,93 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>Weekly Sentiment: r/{{ subreddit_name }}</title>
-    <!-- All the <style> and <link> tags from image_view.html go here -->
-    <!-- You can just copy the entire <head> section from image_view.html -->
-    <link rel="preconnect" href="https://fonts.googleapis.com">
-    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
-    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700;800&display=swap" rel="stylesheet">
-    <style>
-        /* This entire style block is IDENTICAL to image_view.html */
-        body { margin: 0; padding: 2rem; font-family: 'Inter', sans-serif; background: #1a1a1a; display: flex; justify-content: center; align-items: center; min-height: 100vh; }
-        .image-container { width: 650px; background: linear-gradient(145deg, #4d302d, #1f2128); color: #ffffff; border-radius: 16px; padding: 2.5rem; box-shadow: 0 10px 30px rgba(0,0,0,0.5); text-align: center; }
-        header { display: flex; justify-content: space-between; align-items: flex-start; margin-bottom: 2rem; }
-        .title-block { text-align: left; }
-        .title-block h1 { font-size: 2.5rem; font-weight: 800; margin: 0; line-height: 1; }
-        .title-block h2 { font-size: 1.25rem; font-weight: 600; margin: 0.5rem 0 0; color: #b0b0b0; }
-        .date { font-size: 1rem; font-weight: 600; color: #c0c0c0; letter-spacing: 0.02em; }
-        table { width: 100%; border-collapse: collapse; text-align: left; }
-        th, td { padding: 1rem 0.5rem; border-bottom: 1px solid rgba(255, 255, 255, 0.1); }
-        th { font-weight: 700; text-transform: uppercase; font-size: 0.8rem; color: #a0a0a0; }
-        td { font-size: 1.1rem; font-weight: 600; }
-        tr:last-child td { border-bottom: none; }
-        td.rank { font-weight: 700; color: #d0d0d0; width: 8%; }
-        td.ticker { width: 30%; }
-        td.mentions { text-align: center; width: 18%; }
-        td.sentiment { text-align: center; width: 26%; }
-        .sentiment-bullish { color: #28a745; font-weight: 700; }
-        .sentiment-bearish { color: #dc3545; font-weight: 700; }
-        .sentiment-neutral { color: #9e9e9e; font-weight: 600; }
-        tr:nth-child(1) td.ticker { color: #d8b4fe; } tr:nth-child(6) td.ticker { color: #fca5a5; }
-        tr:nth-child(2) td.ticker { color: #a3e635; } tr:nth-child(7) td.ticker { color: #fdba74; }
-        tr:nth-child(3) td.ticker { color: #67e8f9; } tr:nth-child(8) td.ticker { color: #6ee7b7; }
-        tr:nth-child(4) td.ticker { color: #fde047; } tr:nth-child(9) td.ticker { color: #93c5fd; }
-        tr:nth-child(5) td.ticker { color: #fcd34d; } tr:nth-child(10) td.ticker { color: #d1d5db; }
-        footer { margin-top: 2.5rem; }
-        .brand-name { font-size: 1.75rem; font-weight: 800; letter-spacing: -1px; }
-        .brand-subtitle { font-size: 1rem; color: #b0b0b0; }
-    </style>
-</head>
-<body>
-    <div class="image-container">
-        <header>
-            <div class="title-block">
-                <!-- UPDATED: Title shows it's a weekly report -->
-                <h1>Weekly Sentiment</h1>
-                <h2>r/{{ subreddit_name }} - Top 10</h2>
-            </div>
-            <!-- UPDATED: Date now shows the range -->
-            <div class="date">{{ date_range }}</div>
-        </header>
-
-        <!-- The entire table structure is IDENTICAL to image_view.html -->
-        <table>
-            <thead>
-                <tr>
-                    <th class="rank">Rank</th>
-                    <th class="ticker">Ticker</th>
-                    <th class="mentions">Posts</th>
-                    <th class="mentions">Comments</th>
-                    <th class="sentiment">Sentiment</th>
-                </tr>
-            </thead>
-            <tbody>
-                {% for ticker in tickers %}
-                <tr>
-                    <td class="rank">{{ loop.index }}</td>
-                    <td class="ticker">{{ ticker.symbol }}</td>
-                    <td class="mentions">{{ ticker.post_mentions }}</td>
-                    <td class="mentions">{{ ticker.comment_mentions }}</td>
-                    <td class="sentiment">
-                        {% if ticker.bullish_mentions > ticker.bearish_mentions %}
-                            <span class="sentiment-bullish">Bullish</span>
-                        {% elif ticker.bearish_mentions > ticker.bullish_mentions %}
-                            <span class="sentiment-bearish">Bearish</span>
-                        {% else %}
-                            <span class="sentiment-neutral">Neutral</span>
-                        {% endif %}
-                    </td>
-                </tr>
-                {% endfor %}
-            </tbody>
-        </table>
-
-        <footer>
-            <div class="brand-name">RSTAT</div>
-            <div class="brand-subtitle">Reddit Stock Analysis Tool</div>
-        </footer>
-    </div>
-</body>
-</html>

yfinance_test.py

@@ -0,0 +1,59 @@
+# yfinance_test.py
+# A standalone script to diagnose the persistent yfinance issue.
+
+import yfinance as yf
+import logging
+
+# Set up a simple logger to see detailed error tracebacks
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
+
+# A list of tickers to test. One very common one, and two from your logs.
+TICKERS_TO_TEST = ["MSFT", "AEBI", "AEHR"]
+
+print("--- Starting YFINANCE Diagnostic Test ---")
+
+for ticker_symbol in TICKERS_TO_TEST:
+    print(f"\n--- Testing Ticker: {ticker_symbol} ---")
+
+    # --- Test 1: The Ticker().info method ---
+    try:
+        logging.info(
+            f"Attempting to create Ticker object and get .info for {ticker_symbol}..."
+        )
+        ticker_obj = yf.Ticker(ticker_symbol)
+        market_cap = ticker_obj.info.get("marketCap")
+        if market_cap is not None:
+            logging.info(f"SUCCESS: Got market cap for {ticker_symbol}: {market_cap}")
+        else:
+            logging.warning(
+                f"PARTIAL SUCCESS: .info call for {ticker_symbol} worked, but no market cap was found."
+            )
+    except Exception:
+        logging.error(
+            f"FAILURE: An error occurred during the Ticker().info call for {ticker_symbol}.",
+            exc_info=True,
+        )
+
+    # --- Test 2: The yf.download() method ---
+    try:
+        logging.info(f"Attempting yf.download() for {ticker_symbol}...")
+        data = yf.download(
+            ticker_symbol, period="2d", progress=False, auto_adjust=False
+        )
+        if not data.empty:
+            logging.info(
+                f"SUCCESS: yf.download() for {ticker_symbol} returned {len(data)} rows of data."
+            )
+        else:
+            logging.warning(
+                f"PARTIAL SUCCESS: yf.download() for {ticker_symbol} worked, but returned no data (likely delisted)."
+            )
+    except Exception:
+        logging.error(
+            f"FAILURE: An error occurred during the yf.download() call for {ticker_symbol}.",
+            exc_info=True,
+        )
+
+print("\n--- YFINANCE Diagnostic Test Complete ---")