commit a1072dcb977fcc06f3da5a2dfc741c8186427c13
Author: Florian <flo@meergans.org>
Date:   Mon Nov 2 19:55:04 2026 +0100

    First version

diff --git a/1.getting-started.md b/1.getting-started.md
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+# Getting Started
+
+
+## 1. Create a Git repository
+
+Start by creating a repository on GitHub or another Git hosting platform.
+
+- Give it a descriptive name.
+- Add a `README.md` explaining what the project does.
+- Add a `.gitignore` to prevent unnecessary files from being committed. Github has a Python template you should use, which prevents cache or build data to be commited
+- Commit changes regularly with descriptive commit messages.
+
+## 2. Recommended project structure
+
+```text
+my-project/
+├── src/
+│   ├── main.py
+│   ├── utils.py
+│   └── ...
+├── .venv/
+├── .gitignore
+├── requirements.txt
+└── README.md
+```
+## 3. requirements.txt
+
+Use `requirements.txt` to keep track of external Python packages your project depends on.
+
+Example:
+
+```text
+requests==2.32.5
+beautifulsoup4==4.14.2
+```
+
+- One package per line.
+- Pin versions to make installations reproducible.
+- Update the file whenever you add or remove dependencies.
+
+Install all dependencies with:
+
+```bash
+pip install -r requirements.txt
+```
+# Next step: Set up a virtual environment
+
+A virtual environment (`venv`) creates an isolated Python environment for your project.
+
+This means:
+- Each project can have its own dependencies.
+- Installing packages won't affect your system Python installation.
+- Different projects can use different package versions.
+
+## 1. Check your Python installation
+
+```bash
+python3 --version
+```
+
+
+## 2. Create the virtual environment
+
+Navigate to your project directory:
+
+```bash
+cd my-project
+```
+
+Create the environment:
+
+```bash
+python3 -m venv .venv
+```
+This creates a `.venv/` directory containing the isolated Python environment.
+
+## 3. Activate the virtual environment
+
+
+```bash
+source .venv/bin/activate
+```
+Once activated, your terminal should show something similar to:
+
+```text
+(.venv) user@computer:~/my-project$
+```
+
+## 4. Install dependencies
+
+With the virtual environment activated:
+
+```bash
+pip install -r requirements.txt
+```
+
+You can now install additional packages:
+
+```bash
+pip install requests
+```
+
+If you add a new dependency, update `requirements.txt` by running `pip freeze` which lists all installed packages.:
+
+```bash
+pip freeze > requirements.txt
+```
+## 5. Deactivate the environment
+
+When you're finished working or want to change to a different virtual environment:
+
+```bash
+deactivate
+```
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diff --git a/2.backend-api.md b/2.backend-api.md
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+
+# Backend API – Getting Started
+
+## 1. Project overview
+
+The `backend-api` is a small REST API responsible for receiving, storing and delivering notifications.
+
+It uses:
+- **FastAPI:** Python web framework for building REST APIs.
+- **Uvicorn:** Server used to run the FastAPI application.
+- **SQLite:** Lightweight database for storing notifications.
+- **Pydantic:** Data validation for incoming API requests (included with FastAPI).
+
+## 2. API endpoints
+
+The application requires two POST endpoints. POST is used when the application call changes something, GET when it just retrieves information.
+
+| Method | Endpoint | Description |
+|---|---|---|
+| POST | `/notifications` | Receive and store a notification. |
+| POST | `/notifications/deliver` | Retrieve pending notifications and mark them as delivered. |
+
+### Receiving notifications
+
+`POST /notifications`
+
+Accepts a JSON payload containing the notification information.
+
+Example request:
+
+```json
+{
+	"title": "New notification",
+	"body": "Something happened!",
+	"link": "https://example.com",
+	"timestamp": 1791626400
+}
+```
+
+The API validates the payload and saves it into the `notifications` database.
+
+Each notification should have a `delivered` flag, initially set to `false`.
+
+### Getting notifications
+
+`POST /notifications/deliver`
+
+This endpoint retrieves all notifications where `delivered = false`.
+
+The application should:
+1. Query the database for undelivered notifications.
+2. Set their `delivered` flag to `true`.
+3. Commit the database transaction.
+4. Return the retrieved notifications as JSON.
+
+Example response:
+
+```json
+[
+	{
+		"id": 1,
+		"title": "New notification",
+		"body": "Something happened!",
+		"link": "https://example.com",
+		"timestamp": 1791626400,
+		"delivered": true
+	}
+]
+```
+
+If there are no pending notifications, return an empty array.
+
+**Important:** The database update should happen before returning the notifications. This prevents the same notifications from being delivered again on subsequent requests.
+
+## 3. Database structure
+
+For the initial implementation, use SQLite.
+
+The database will be stored in a local file called `notifications.db`.
+
+The `notifications` table should contain:
+
+| Column | Type | Description |
+|---|---|---|
+| `id` | INTEGER | Unique notification identifier (primary key). |
+| `title` | TEXT | Notification title. |
+| `body` | TEXT | Notification content. |
+| `link` | TEXT | Optional URL associated with the notification. |
+| `timestamp` | INTEGER | Unix timestamp of the notification. |
+| `delivered` | BOOLEAN | Indicates whether the notification was delivered. |
+
+---
+
+# 4. Minimal working implementation
+
+The following implementation gives you a baseline for starting the server
+
+## requirements.txt
+
+```text
+fastapi
+uvicorn
+```
+
+## src/main.py
+
+```python
+from contextlib import asynccontextmanager
+from fastapi import FastAPI
+from pydantic import BaseModel #use this to create the Notification class
+from db_module import initialize_database, get_database #Implement these yourself with SqLite3
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+	initialize_database()
+	yield
+
+
+app = FastAPI(lifespan=lifespan)
+
+@app.post("/notifications")
+def receive_notification(notification: Notification):
+
+
+
+@app.post("/notifications/deliver")
+def deliver_notifications():
+
+```
+
+## 6. Run the application
+
+Make sure the virtual environment is activated and the dependencies are installed.
+
+Start the application from the project root:
+
+```bash
+uvicorn src.main:app --host 0.0.0.0 --port 8100 --reload
+```
+
+Explanation:
+
+| Argument | Description |
+|---|---|
+| `src.main:app` | Imports the FastAPI instance called `app` from `src/main.py`. |
+| `--host 0.0.0.0` | Makes the server accessible outside localhost. |
+| `--port 8100` | Port on which the API listens. |
+| `--reload` | Automatically restarts the server when source files change. |
+
+The `--reload` option should only be used during development.
+
+## 7. Test the application
+
+FastAPI automatically generates interactive API documentation.
+
+Open:
+
+http://localhost:8100/docs
+
+You can use the Swagger UI to execute both POST endpoints without installing additional tools.
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diff --git a/3.youtube-service.md b/3.youtube-service.md
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+
+# YouTube Notification Service – Overview
+
+You need to use an [external Website like this one](https://channelsurfer.tv/tools/youtube-rss-feed/) to get the RSS feed ID for a channel.
+## 1. Order of events
+
+1. **Connect to the database:** Establish a connection to the database containing the subscribed YouTube channels.
+2. **Retrieve subscriptions:** Fetch all subscribed YouTube RSS feed URLs from the database.
+3. **Fetch RSS feeds:** Use `feedparser` to query each subscribed feed.
+4. **Check for updates:** Compare the latest feed entries against the last known entry stored in the database.
+5. **Send notifications:** If a new video is found, send its information (`title`, `body`, `link`, `timestamp`) to the `backend-api` using a POST request.
+6. **Update database:** After successfully sending the notification, update the stored latest video information to prevent duplicate notifications.
+7. **Close database connection:** Close the database connection once all subscriptions have been processed.
+
+## 2. Dependencies
+
+- **feedparser:** Parse YouTube RSS feeds and extract video information.
+- **requests:** Send HTTP POST requests to the `backend-api`.
+- **Database driver:** Connect to and query the database.
+
+## 3. Things to improve once it works
+
+- Handle unavailable RSS feeds without stopping the entire service.
+- Handle failed API requests so notifications aren't accidentally marked as processed.
+- Log errors and processing information using Python's `logging` module. Use a LOG_LEVEL to set it to either debugging or production(info)
diff --git a/4.asura-scans-monitoring.md b/4.asura-scans-monitoring.md
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+
+# AsuraScans Monitoring – Overview
+
+## 1. Order of events
+
+1. **Fetch comic URL:** Use `requests.get(baseurl)` to retrieve the current comic page URL. The URL may change frequently, so avoid hardcoding the chapter page URL.
+2. **Parse website:** Use `BeautifulSoup` to parse the HTML and extract the chapter information.
+3. **Extract chapter data:** The chapter information is stored inside the HTML element's `props` attribute as JSON.
+
+   ```python
+   soup = BeautifulSoup(response.text, "html.parser")
+
+   element = soup.select_one("[props*='chapters']")
+   props = json.loads(element.get("props"))
+   ```
+
+4. **Check for updates:** Compare the latest chapter against the last known chapter stored in the database.
+5. **Create notification:** If a new chapter is found, extract its title, URL and timestamp.
+6. **Send notification:** Convert the chapter information into the notification payload (`title`, `body`, `link`, `timestamp`) and send it to the `backend-api` using a POST request.
+7. **Update database:** After successfully sending the notification, update the stored latest chapter information to prevent duplicate notifications.
+
+## 2. Dependencies
+
+- **requests:** Fetch the comic website and send HTTP POST requests to the `backend-api`.
+- **beautifulsoup4:** Parse the website HTML and extract chapter information.
+- **Database driver:** Connect to and query the database.
+- **json:** Parse the chapter data stored in the HTML `props` attribute (included in Python's standard library).
+- **datetime:** Convert chapter timestamps if necessary (included in Python's standard library).
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diff --git a/5.Improvements.md b/5.Improvements.md
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+# 8. Future improvements
+
+Once the basic setup is working, consider implementing the following:
+
+- **MySQL:** Replace SQLite with MySQL for persistent production database storage.
+- **Authentication:** Protect endpoints using API keys or token-based authentication. The [backend-api](https://git.gansejunge.com/notifier/backend-api/src/branch/main/src/main.py) has an example
+- **Logging:** Replace `print()` statements with Python's `logging` module.
+- **Error handling:** Handle database connection failures and invalid requests.
+- **Configuration:** Move database paths, ports and other settings into environment variables.
+- **Deployment** - Use Docker with docker-compose to run self hosted images from
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diff --git a/README.md b/README.md
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+# Guide for Kaash
+
+- [1.  Getting started](1.getting-started.md)
+
+- [2. The backbone: Backend-API](2.backend-api.md)
+
+- [3. First Service: Get Youtube updates](3.youtube-service.md)
+
+- [4. AsuraScans monitoring](4.asura-scans-monitoring.md)
+- [5. Improvements for the future](5.Improvements.md)
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