I want to update and modify my trading setup to use Lightweight Charts Library from TradingView to display market data in a Next.js frontend to get a chart with real-time updates, historical data, switchable timeframes, and switchable symbols.

The market data for that should be retrieved from MT5.

On the technical side, I want to use the following setup for this approach:

Tools/Libraries/Frameworks:


1. MetaTrader 5 (MT5)
2. MetaTrader5 Python package
3. Python
4. FastAPI (Backend)
5. TradingView Lightweight Charts (Frontend)
6. Next.js or React (Frontend framework)
7. Redux for State Management
8. Supabase (Database)

Textual Diagram:

```other
MT5 <---> Python (MetaTrader5 package)
              |
              v
         FastAPI Backend <---> Supabase
              |
              v
      Next.js/React Frontend
              |
              v
   TradingView Lightweight Charts
```


Relationships:


1. MT5 communicates directly with Python using the MetaTrader5 package.
2. FastAPI serves as the backend, processing data from Python and managing communication with the frontend.
3. Supabase is used for storing historical data and user information.
4. Next.js or React forms the frontend framework.
5. Redux for State Management: Use state management in the frontend (Redux) to keep track of the currently selected symbol.
6. TradingView Lightweight Charts is integrated into the frontend for chart rendering.

Implementation Considerations:


1. Data Flow:
	- MT5 sends real-time and historical data via the MetaTrader5 Python package.
	- Python processes this data.
	- FastAPI manages the data and serves it to the frontend.
2. Real-time Updates:
	- Implement WebSocket connections between FastAPI and the frontend for real-time data streaming.
3. Historical Data:
	- Store historical data in Supabase for efficient retrieval when changing timeframes.
4. Chart Rendering:
	- Use TradingView Lightweight Charts to display both real-time and historical data.
5. Timeframe / Symbol Switching:
	- Implement logic in the backend to aggregate data for different timeframes and symbols.
	- Cache commonly used timeframes for faster switching.
6. Redux for State Management:
	- Use state management in the frontend (Redux) to keep track of the currently selected symbol.
7. Performance Optimization:
	- Implement efficient data transfer protocols between all components.
	- Use data compression where appropriate.
8. Error Handling:
	- Implement robust error handling throughout the system, especially for network issues and data inconsistencies.

Additionally, to implement the ability to select different symbols within the TradingView Lightweight Charts window in the frontend. Here are the key points:


- Symbol Selection:
	- The Lightweight Charts library itself doesn't have built-in functionality for symbol selection, but you can implement this feature in your frontend application.
- Implementation Approach:
	- You would need to create a custom UI element (e.g., a dropdown or search box) for symbol selection.
	- When a new symbol is selected, you would fetch the corresponding data for that symbol from your backend (MT5 via MetaTrader5 Python package).
	- Then, you would update the chart with the new data using the Lightweight Charts API
- Backend Handling:
	- In your FastAPI backend, implement an endpoint to handle symbol change requests.
	- When a request is received, use the MetaTrader5 Python package to request data for the new symbol from MT5.
- MT5 and Python:
	- Modify your Python script to handle requests for different symbols.
	- When a new symbol request is received, switch to that symbol and start streaming its data.
- Data Flow:
	- MT5 sends the new symbol's data through the MetaTrader5 Python package to the Python backend.
	- The FastAPI backend processes this data and sends it to the frontend.
	- The frontend updates the TradingView Lightweight Charts with the new symbol's data.
- Redux for State Management:
	- Use state management in the frontend (Redux) to keep track of the currently selected symbol.
- Historical Data:
	- Store historical data for different symbols in Supabase for quick retrieval when switching symbols.
- Real-time Updates:
	- Ensure your WebSocket connection can handle switching between symbols for real-time data streaming.
- Chart Update:
	- You can use the `setData()` method of the series object to update the chart with new data when a different symbol is selected.
	- Alternatively, you might create a new chart instance for each symbol change, depending on your specific requirements.
- Multiple Charts:
	- If you need to display multiple symbols simultaneously, you can create multiple chart instances, each with its own symbol [3][5].
- Synchronization:
	- If you want to synchronize multiple charts (e.g., for different timeframes of the same symbol), you can use the `setCrosshairPosition` API along with `visibleRange` subscribers and setters [3].
- Performance Considerations:
	- Be mindful of performance when implementing symbol switching, especially if you're dealing with large datasets or frequent updates.
- Data Fetching:
	- Ensure your backend (MT5 with MetaTrader5 Python package) can efficiently handle requests for different symbols and return the data in a format compatible with Lightweight Charts.
- User Experience:
	- Consider implementing smooth transitions or loading indicators when switching between symbols to enhance the user experience.

While the Lightweight Charts library doesn't provide built-in symbol switching functionality, I want to implement this feature by combining the library's API with your own frontend logic and backend data fetching. This approach allows for a flexible and customizable solution for displaying different symbols within your trading application.

Implementation Considerations:


1. Performance: Optimize data transfer and processing to ensure smooth symbol switching.
2. Error Handling: Implement robust error handling for cases where a symbol might not be available or data retrieval fails.
3. User Experience: Provide visual feedback during symbol switching (e.g., loading indicators).
4. Caching: Consider caching recent symbol data on the frontend for faster switching between frequently used symbols.
5. MT5 Capabilities: Leverage MT5's ability to handle multiple symbols simultaneously for efficient data retrieval and processing.


----

I already have installed:


1. MetaTrader 5 (MT5)
2. Python
3. Supabase (Database)

please help with installing rest of all 
----

First of all: do you understand my approach and all the steps, features and logic or do you have any questions for clarification? If so, feel free to ask.

If everything is clear, please give a step-by-step instruction for implementing the approach described above. Provide as much full and production-ready code as possible.

Provide instructions on what to install, in which environment. Where to put the code, in which environment and specifically in which directory/path, so all dependencies are satisfied.

Additionally provide a textual diagram for an oversight over structure of the whole setup and its relational tools/frameworks/Libraries as you going to code it.

Important: While coding, please consider: I'm a huge fan of a modular coding style, in every framework and language, because I want to add new features now and then. As well, I like input parameters and/or config files for quick customization.