Feature/analytics: Implementation for mempool-based fee statistics + API stats endpoint

[mercie-ux]

Description:

This pr implements the backend foundation for the mempool-based fee statistics feature
and exposes a clean, API-driven interface for the frontend to consume.

What's implemented

• added a new /stats endpoint that:
  • accepts a start_height query parameter
  • automatically derives the internal [start_height, start_height + 1000]
  • caps the range using the latest known blockheight
  • fetches fee-ratedata using the external source

https://bitcoincorefeerate.com/fees/2/economical/2

• computes block-level statistics: p25, p75, average fee rate
• classifies each block as:
  • overpaid
  • underpaid
  • within_range
• Returns a fully structured JSON response ready for frontend intergration
• The backend defines block range, summary and plotting inputs.
• The frontend is expected to consume latest_block_height, request data using start_height render charts and summaries without local assumptions.

Current limitation

Analytics summary and charts do not render for any block height due to frontend rendering/state issue. However the API responses are successful.

[b-l-u-e]

Should we migrate from Flask to FastAPI? Current implementation ismaelsadeeq#1 uses Flask with synchronous RPC calls. FastAPI would provide: Built-in async support for concurrent RPC requests
However, the current Flask setup is working well for our use case. What are your thoughts on the trade-offs? @ismaelsadeeq @mercie-ux

[ismaelsadeeq]

Superseded by https://github.com/ismaelsadeeq/bitcoin-core-fees/pull/4, thanks.