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🩺 NCIC Live A&E Monitor # 🩺 NCIC Live A&E Monitor
This is a Python application that allows you to view live data of the amount of patients in A&E and the latest waiting times, at NCIC facilities. The data is scraped from the ncic.nhs.uk waiting times page and displayed in a user-friendly GUI. This is a Python application that allows you to view live data of the amount of patients in A&E and the latest waiting times, at North Cumbria Integrated Care (NCIC) facilities. The data is scraped from the ncic.nhs.uk waiting times page and displayed in a user-friendly GUI.
## Features ## Features
Real-time Data: Displays the latest A&E and UTC waiting times for NCIC hospitals - Real-time Data: Displays the latest A&E and UTC waiting times for NCIC hospitals
Auto-refresh: The app automatically refreshes data every 5 minutes with a countdown timer. - Auto-refresh: The app automatically refreshes data every 5 minutes with a countdown timer.
Customizable UI: The interface is split into two sections for A&E and UTC departments, with hospital names highlighted for clarity. - Customizable UI: The interface is split into two sections for A&E and UTC departments, with hospital names highlighted for clarity.
Data Fetching: Uses BeautifulSoup to scrape HTML tables from the NHS website, parsing the relevant data on patients, wait times, and arrivals. - Data Fetching: Uses BeautifulSoup to scrape HTML tables from the NHS website, parsing the relevant data on patients, wait times, and arrivals.
Requirements ## Requirements
To run this application, you need to have the following Python libraries installed: To run this application, you need to have the following Python libraries installed:
requests - requests
- beautifulsoup4
beautifulsoup4 - tkinter (usually comes pre-installed with Python)
tkinter (usually comes pre-installed with Python)
You can install the required libraries using pip: You can install the required libraries using pip:
pip install requests beautifulsoup4 `pip install requests beautifulsoup4`
Python Version ## Python Version
This script is compatible with Python 3.x. This script is compatible with Python 3.x.
How to Run ## How to Run
Clone this repository to your local machine. ### Linux
- Clone this repository to your local machine.
- Navigate to the directory:
- Run the script linux.py
### Windows
- Download and run the windows.exe file
### iOS / iPadOS
- Download the ios.py script and run it in Pythonista
Navigate to the directory: ## Troubleshooting
- App doesn't load: Ensure that all required libraries are installed. Run pip install requests beautifulsoup4.
Run the script linux.py - No data appears: The data is fetched from the live NHS website, so ensure you have an internet connection and the website is accessible.
## License
This project uses data sourced from the NHS website and is made available under the <a href="https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government License</a>
The app should now open and display the current NHS waiting times for A&E and UTC departments in North Cumbria.
How It Works
GUI Components
Title and Countdown: Displays the app title and a countdown timer showing the time remaining until the next data refresh.
Two Panels: One panel shows A&E departments, and the other shows Urgent Treatment Centres (UTC).
Hospital Information: Each hospital entry includes:
Hospital name (with an icon)
Number of patients currently in the department
Average wait time
Number of arrivals in the last hour
Data Fetching
The fetch_data() method scrapes the NHS page and extracts data from HTML tables using BeautifulSoup. This data is then formatted and displayed in the GUI.
Auto Refresh
The app refreshes the data every 5 minutes using a background thread, with a countdown timer indicating the time remaining until the next refresh.
Simplifying Hospital Names
The simplify_name() method is used to standardize and clean up hospital names, ensuring that any extra details (such as "24hrs") are removed for consistency.
Example Screenshot
Troubleshooting
App doesn't load: Ensure that all required libraries are installed. Run pip install requests beautifulsoup4.
No data appears: The data is fetched from the live NHS website, so ensure you have an internet connection and the website is accessible.

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