📺 New Season Soon for Kometa

Inspired by PATTRMM this simplifed script checks your Sonarr for TV Shows for which a new season is airing within a chosen amount of days and creates .yml files which can be used by Kometa to create a collection and overlays.

✨ Features

• 🔍 Detects upcoming Season: Searches Sonarr for Shows with upcoming seasons
• ▼ Filters out unmonitored: Skips show if season/episode is unmonitored. (optional)
• 🪄 Customizable: Change date format, collection name, overlay positioning, text, ..
• ℹ️ Informs: Lists matched and skipped(unmonitored) TV shows.
• 📝 Creates .yml: Creates a collection and overlay file which can be used with Kometa.

---

🛠️ Installation

1️⃣ Download the script

Clone the repository:

git clone https://github.com/netplexflix/New-Season-Soon-for-Kometa.git
cd New-Season-Soon-for-Kometa

Or simply download by pressing the green 'Code' button above and then 'Download Zip'.

2️⃣ Extract or move the files to a 'NSSK' subfolder in your Kometa config folder

• Go to your Kometa install folder, then config.
• Create a subfolder named NSSK.
• Put the files in this subfolder. (config.yml, NSSK.py and requirements.txt)

3️⃣ Install Dependencies

• Ensure you have Python installed (>=3.8 recommended).
  
• Open a Terminal in the script's directory

Tip

Windows Users:
Go to the NSSK folder (where NSSK.py is). Right mouse click on an empty space in the folder and click Open in Windows Terminal

• Install the required dependencies by pasting the following code:

pip install -r requirements.txt

4️⃣ Edit your Kometa config

• Open your Kometa config.yml (config/config.yml, NOT config/NSSK/config.yml)
• Under your TV Show library settings, add the paths to NSSK_TV_COLLECTION.yml and NSSK_TV_OVERLAYS.yml (These files will be created in your NSSK folder when you run the script).
  Example:

  TV Shows:
    collection_files:
    - file: P:/Kometa/config/NSSK/NSSK_TV_COLLECTION.yml
    overlay_files:
    - file: P:/Kometa/config/NSSK/NSSK_TV_OVERLAYS.yml
  

Note

If you don't want to create a collection and only overlays you can ofcourse skip adding the collection file to your Kometa config.
Or the other way around..

---

⚙️ Configuration

Edit the config.yml file in your NSSK folder and edit the settings:

• sonarr_url: Change if needed.
• sonarr_api_key: Can be found in Sonarr under settings => General => Security.
• future_days: How many days into the future the script should look for season premieres.
• skip_unmonitored: Default true will skip a show if the upcoming season/episode is unmonitored.
• collection_name: The name of the collection.
• sort_title: Collection sort title.
• backdrop: Change backdrop (the colored banner behind the text) size, color and positioning. More info here
• text: Change text color and positioning. More info here
  • date_format: The date format to be used on the overlays. e.g.: "yyyy-mm-dd", "mm/dd", "dd/mm", etc.
  • use_text: Text to be used on the overlays before the date. e.h.: "NEW SEASON"

---

🚀 Usage - Running the Script

Open a Terminal in your script directory and launch the script with:

python NSSK.py

The script will list matched and/or skipped shows and create the .yml files.
The previous configuration will be erased so Kometa will automatically remove overlays for shows that no longer match the criteria.

Tip

Windows users can create a batch file to quickly launch the script.
Type "[path to your python.exe]" "[path to the script]" -r pause" into a text editor

For example:

"C:\Users\User1\AppData\Local\Programs\Python\Python311\python.exe" "P:\Kometa\config\NSSK\NSSK.py" -r
pause

Save as a .bat file. You can now double click this batch file to directly launch the script.
You can also use this batch file to schedule the script to run.

---

⚠️ Do you Need Help or have Feedback?

• Join the Discord.
• Open an Issue on GitHub.

---

？ FAQ

Is there a docker container?
I made this for my personal use. I don't use docker myself and have no plans atm to learn how to make dockerfiles.
If anyone wants to help make one, please feel free to create a pull request!

---

❤️ Support the Project

If you like this project, please ⭐ star the repository and share it with the community!