On-Chain

Real-time Ethereum blockchain insights at your fingertips. Visualize transaction volumes, gas usage, and price trends with an intuitive, interactive dashboard

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Inspiration

I wanted to do a project to learn more about on-chain analytics and gain hands-on experience with blockchain data. The increasing importance of decentralized finance and the wealth of data available on the Ethereum blockchain inspired me to create a tool that could provide valuable insights to both novice and experienced crypto enthusiasts.

What it does

Our On-Chain Analytics Dashboard is a Streamlit-based web application that provides real-time insights into Ethereum blockchain data. It offers:

  • Visualization of recent block data, including transaction counts and gas usage
  • Current ETH price display
  • Interactive charts for easy data interpretation
  • Customizable analysis range (number of blocks to analyze)

How we built it

  • Python as the core programming language
  • Streamlit for creating the interactive web application
  • Web3.py for interacting with the Ethereum blockchain
  • Pandas for data manipulation and analysis
  • Plotly for creating interactive visualizations
  • Requests library for fetching ETH price data from CoinGecko API
  • Infura as our Ethereum node provider

Challenges we ran into

  • Putting this website together in a very short amount of time.
  • Debugging errors

Accomplishments that we're proud of

  • Created a functional, real-time Ethereum analytics dashboard from scratch
  • Successfully integrated multiple technologies (Streamlit, Web3.py, Plotly) into a cohesive application
  • Developed a user-friendly interface that makes blockchain data accessible to non-technical users
  • Implemented dynamic data fetching and visualization updating

What we learned

Gained more experience with the technologies used and increased understanding of how cryptocurrencies work.

What's next for On-Chain

  • Expand analytics to include more metrics (e.g., average transaction fees, popular smart contracts)
  • Implement predictive models for gas prices and transaction volume
  • Add support for multiple blockchain networks beyond Ethereum
  • Develop custom alerts for significant on-chain events or anomalies
  • Integrate with DeFi protocols to provide liquidity and yield farming analytics

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